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science teacher 2011 Featuring: Model IT Problem-based learning Modelling Eocene climate Forecasting the weather Optimising solar radiation collection Junior CafĂŠ Scientifique Reading to learn in science Magic of quantum mechanics Modelling in science education Modelling fluid splashes Southern Ocean carbon cycle And more...

Number 127

ISSN 0110-7801


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Editorial Advisory Group: Rosemary Hipkins, Chris Joyce, Suzanne Boniface, Beverley Cooper, Miles Barker and Anne Hume Editorial Address: lyn.nikoloff@xtra.co.nz

Editorial 2 From the President’s desk 3

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NZST PublicationTeam: Editor: Lyn Nikoloff, Bijoux Publishing Ltd, Palmerston North Sub editor: Teresa Connor Typesetting and Cover Design: Pip’s Pre-Press Services, Palmerston North Printing: K&M Print, Palmerston North Distribution: NZ Association of Science Educators

Feature: Model IT Modelling Eocene climate 4 Magic of quantum mechanics 7 Modelling fluid splashes 12

NZASE National Executive: President: Lindsey Conner Senior Vice-President: Jenny Pollock Treasurer/Web Manager: Robert Shaw Primary Science: Chris Astall Auckland Science Teachers: Carolyn Haslam Publications: Matt Balm

Detecting changes in the Southern Ocean carbon cycle 15

Mailing Address and Subscription Inquiries: NZASE 29 Nicholls Road Halswell Christchurch 8025. email: nzase@xtra.co.nz NZASE Subscriptions (2011) School description Secondary school

Roll numbers Subscription > 500 $240.00 < 500 $185.00 Area School - to be determined TBA Intermediate, middle and > 600 $240.00 composite schools 150-599 $90.00 < 150 $65.00 Primary/contributing schools > 150 $90.00 < 150 $70.00 Tertiary Education Organisations $240.00 Libraries $110.00 Individuals $50.00 Student teachers $45.00 Special Interest Group (includes access to secure sites): BEANZ, NZIC, STANZ, SCIPED $10 per group Note: SIG fees are included all subscriptions except for individual members. Additional copies of the NZ Science Teacher Journal $32.06 per year for three issues Subscription includes membership and one copy of NZST per issue (i.e. three copies a year). All prices are inclusive of GST. Advertising: Advertising rates are available on request from nzst@nzase.org.nz Deadlines for articles and advertising: Issue 128 - (Bio) Diversity August 20 (publication date: 1 October) Issue 129 - December 20 (publication date: 1 March 2012) NZST welcomes contributions for each journal but the Editor reserves the right to publish articles it receives. Please contact the Editor before submitting unsolicited articles: nzst@nzase.org.nz Disclaimer: The New Zealand Science Teacher is the journal of the NZASE and aims to promote the teaching of science, and foster communication between teachers, scientists, consultants and other science educators. Opinions expressed in this publication are those of the various authors, and do not necessarily represent those of the Editor, Editorial Advisory Group or the NZASE. Websites referred to in this publication are not necessarily endorsed.

Modelling horticultural produce storage and packaging design 18 Optimising solar energy collection 20 Forecasting the weather 23 Science Education Problem-based learning in science 28 Reading to learn about birds and their conservation 31 Junior Café Scientifique 34 Coastal adaptation to climate change 37 Science/Science Education Interface Conversation: Modelling in science education 11 Conversation about polymaths and data deluge 45 Primary science iPod Touch and science teaching 40 Nature of science activity 41 Mr Science – Part 2 43 Subject associations Chemistry 44 Physics 46 Women in science conference 46 ESSE 47 Technicians 48

Front cover: A section of the NZLAM forecast system domain for 12 noon on 15 Feb 2004 (during the severe weather event over the lower North Island), visualized in 3 dimensions, showing a) specific humidity at the surface (red indicates high, and violet low values) and an iso surface aloft, b) regions of updraft and down draft coloured according to the potential temperature, and c) isobar contours of pressure (Pa) at 6.1 km altitude. Courtesy of NIWA. For more read: Forecasting the weather (p.23). New Zealand Association of Science Educators

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modelling creative thinking In the April issue of QNewZ (NZ Organisation for Quality), of which I am also the editor, Jenni Scanlon from Strategies Direct wrote about the importance of being creative in business. This can be achieved, she wrote, by reaching beyond our usual sources of information and ideas. For example, Jenni challenged herself to read a magazine she would never normally read – so she read a snowboarding magazine, where she found a creative way to innovate her consultancy business. So to be creative in our thinking we must step outside our comfort zone, allowing ourselves to be challenged by new ways of thinking and doing. This issue of the NZST has the theme Model IT – the idea came to me from a horticultural conference I attended in 2001. The issue begins with the President of the NZASE, Lindsey Conner encouraging members to dialogue about the future of science education to ensure that the future model is one that serves all students (p.4). In the education section I commend to you some exciting new models for teaching science which may have merit in your classroom: problem-based learning (p.28); reading to learn about NZ birds (p.31); Junior Café Scientifique (p.34); and a teacher-student-scientist collaboration on climate change (p.37). There are also some excellent ideas for bringing science into the primary classroom: iPod Touch apps (p.40); science entrepreneurs (p.41); and using colour (p.43). The NZASE standing committees have some inspirational ideas: Chemistry Olympiad and knitting the periodic table (p.44); using bathroom scales in physics (p.46); and proving Earth’s age (p.47). Also read thoughts from a school science technician about the proposed changes to science education (p.48). If we are to think creatively we must first put aside our preconceived ideas about articles in this issue and allow our precepts and practices to be further honed by reading beyond our usual stereotypical interests. In so doing, I am certain that you will all find creative ways of using many articles in this issue. For example, introduce more reading into your primary or secondary school classroom (p.31), and make better use of free iPod Touch apps (p.42). Thanks to supercomputers, such as NIWA’s FitzRoy, computer modelling is a vital part of scientific endeavour. In this issue we bring to your attention contemporary examples of modelling in science: • by better understanding the Eocene climate scientists can develop better models to understand global warming (p.4) • quantum mechanics is a model that helps scientists and non-scientists to understand the world around us, and this includes science students (p.7) • have you ever tried to paint an external curve but found that the paint gets thinner over the curve? (p.12) • modelling indicates that the Southern Ocean carbon sink may be slower in the future due to climate change, and atmospheric radiocarbon may be a valuable tool for looking at changes in this vital cycle (p.15)

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Did you know that packaging design impacts on shelflife of horticultural produce? (p.18) • maximising the collection of solar radiation depends on the location and angle of the solar panels (p.21) • forecasting the weather accurately is vital if its impacts are to be, in part, mitigated. Modelling, data collection and management, and computing are improving scientists’ ability to accurately forecast the weather (p.24). If you are prepared to think creatively then you will find every one of these articles useful to your science programmes, such as additional student reading material, background reading or a conceptual idea. And to help you gain even more benefit from our science based articles Rosemary Hipkins and Miles Barker have been engaging some of our contributors in a conversation. In this issue, Miles speaks with Cather Simpson about quantum mechanics, and in so doing illuminates aspects of Nature of Science (p.11). Miles also spoke with Vic Arcus (Issue 126 – Data deluge and polymaths) and the conversation raised the important issue of public scientific literacy (p.45). I commend both conversations to you. Back to thinking creatively, which by the way is important for thinking strategically, and so it was that Jenni became more strategically savvy thanks to an idea in a snowboarding magazine. Teachers are constantly being asked to be creative and innovative in their programmes, and there is pressure from BOT for schools to be more strategic. I challenge you all to read at least a part of this issue of the NZST that you would not normally read, and let’s see if it raises a creative (strategic) thought or three! Remember there is no preconceived notion of how that creativity will manifest – maybe it will be a career goal, a unit context, a management strategy or a new way of thinking…but only you can choose to move outside your comfort zone and think creatively. Yet by modelling creative thinking, by thinking outside the box, by being open and receptive to new ideas and information, by breaking down preconceived barriers between primary and secondary science, our models of teaching science can be fundamentally revised and reinvigorated, and in so doing impact positively on our students. And that’s a win-win. Finally, my sincerest thanks to contributors to this issue of the NZST; your generosity of spirit, time and expertise, and support for the NZST and science education is greatly appreciated. Thank you. Enjoy thinking creatively everyone!

Lyn Nikoloff Editor, NZST


As a science education community we are very interested in what the Government sees as the priorities for science education. Recently, Sir Peter Gluckman, the Prime Minister’s advisor on Science, released a paper Looking Ahead: Science Education for the Twenty-First Century. His paper discusses ideas from two previous papers; one developed by NZCER and the other from the Prime Minister’s Science Advisory Committee: Engaging Young New Zealanders with Science. Priorities for Action in School Science Education. NZASE had representation on this advisory committee and contributed to this. However, it is very important that many more science teachers also have opportunities to contribute to a wider discussion and take a proactive approach to implementing support for future directions. For example, on p.48 Ian de Stigter provides his opinion, as a science technician, on Sir Peter’s document and makes suggestions about the priorities for science education resources. There are many approaches we could discuss and suggest to the Government as ways forward. One approach that we support is the development of teachers’ knowledge through networks. NZASE already has existing networks through regional associations and our special interest groups. These groups may like to host meetings to discuss priorities for their region and how they can contribute to national initiatives. SCICON, the technicians’ conference, the Primary Science week and the subject association conferences this year, all provide focused events for such engagement. NZASE is well placed as a national body to network and inform members about professional development initiatives. I would like to encourage you to visit our website and contribute to the notices on the website to support this role. Also PD experiences could focus on the importance of science as part of the implementation of the new curriculum, incorporating the nature of science components and inquiry approaches to science.

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There is a strong recognition that science leads to new knowledge and innovation. While the use of ICT and other technologies enables us to enhance our understanding of the scientific world, experiencing, exploring and thinking are also fundamental. There is a need to place a strong emphasis on how the knowledge and use of science can improve the quality of life. Given the recent earthquakes in Christchurch, the resultant constraints to everyday life mean that the people of Christchurch are refocusing on their quality of life and what is required to improve it. Young New Zealanders need to know how extremely important it is to be able to use scientific knowledge and scientific thinking processes to determine the quality of their lives. This can support – or indeed promote – economic development through a higher level of participation and application to innovations. The global implications of the recent nuclear disaster in Japan are also becoming more and more apparent. The people in Japan are being faced with power shortages and the consequent ‘shifts’ for electricity usage during part of the day. The effects and consequences of decisions (i.e. to use nuclear power, where they are built etc.) not only affect the local people and environment, but also the ‘global village’. All these recent events are useful contemporary contexts for emphasising the importance of science knowledge and the evaluative thinking associated with applying that knowledge. Let’s use the summary document to provide impetus for a much wider discussion about how to develop more effective and appropriate science education. We welcome further discussion of this topic on our website forum at: www.nzase.org.nz . Noho ora mai Lindsey Conner President NZASE

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New!!! NZASE Members’ Forum Starting this month: An online forum about the future of science education!

We want to hear what you think about the future of science education, so post your views online today. The NZASE website features: • a dynamic forum for members • latest news, information and happenings • subject association pages • forthcoming conferences • useful links and resources. So...it all happens online at nzase.org.nz. See you there!! If you would like to become a member of NZASE please email: nzase@xtra.co.nz

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modelling Eocene climate Models indicate that New Zealand may have been warmer and drier in the Eocene as Duncan Ackerley, Climate Scientist at NIWA, James Renwick, Principal Scientist, Climate Variability and Change at NIWA, Matthew Huber, Associate Professor at Purdue University, Indiana, USA and Chris Hollis, Senior Scientist at GNS Science, explain: The Earth’s climate is not a fixed system and varies greatly on seasonal (summer to winter) to millennial (ice ages to inter-glacial periods) timescales. Methods of estimating the past surface temperature of the Earth are important to show us to what extent the climate may have varied in the deep past. These temperature estimates can then be used to test computer model simulations of past climate. If there is agreement between the observations and models, it gives us confidence in the capability of the model to represent the climate of the given period. If there is disagreement, then we can re-evaluate both the science behind the temperature estimates and the model processes and attempt to improve them. With the threat of global warming to the human society, methods of evaluating and improving our model simulations during past episodes of climate change are important so that we can have greater confidence in our projections for the future. The last time the planet experienced a period of considerably higher global temperatures was in the Eocene 55 to 34 million years ago1. During this period the Earth’s surface temperature was approximately 10°C higher than at present. Given that we cannot rule out a 10°C increase in temperature (above present day) as a result of greenhouse gas emissions from fossil fuel combustion, the Eocene presents a useful period to study. In this article, we will discuss what data are used for estimating past climate, discuss the climate models used to represent past climate, describe and show how we set up the very first attempt of a high-resolution simulation of New Zealand climate for the Eocene, show some key results from the model study and discuss them in context of what we know about New Zealand’s climate during the Eocene.

Proxy data Unfortunately we don’t have time machines that would allow us to travel back in time 50 million years and measure the Earth’s surface temperature. Therefore, to understand past climates, geologists have developed a variety of methods to indirectly measure climate variables such as temperature and precipitation. Because these are not direct measurements of climate variables, but measurements of features of the geological record that are believed to represent these variables, they are termed ‘proxy’ data. Examples of proxy data sources (used in this study) that are available for the Eocene in New Zealand include: 1. Oxygen isotopes: In the natural world, the oxygen molecule comes in two primary forms, or isotopes: O18 and O16. In seawater, the ratio between these two isotopes is closely related to water temperature. When marine organisms incorporate oxygen in their shells, this ratio is maintained. Consequently, the O18/O16 ratio in fossil shells has become the most commonly used proxy for past temperature1. 2. Biomarkers: These are complex organic molecules that are specific to certain forms of life. In recent years these have been increasingly used to estimate past 4

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temperatures, and are especially useful in sedimentary rocks that lack the shells of marine fossils. One set of biomarkers provides a sea temperature proxy called TEX-862 that is based on the relationship between modern sea temperature and the distribution of a group of marine microbes: the Crenarchaeota.

Climate models The processes that lead to weather and climate on Earth can be represented using complex mathematical equations. These equations are used in General Circulation Models (GCMs), which are run on supercomputers to represent the past, current and future climate. These GCMs include many atmospheric processes including the passage of solar and terrestrial radiation through the atmosphere, cloud and precipitation formation processes, exchanges of energy from the surface (land and ocean) to and from the atmosphere, atmospheric and oceanic flow, and the freezing and melting of ice sheets and sea ice. The models also include the radiative properties of greenhouse gases (GHGs) such as carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4), which act by trapping thermal, inf rared radiation and in doing so warm the climate. By representing all of these different aspects of the climate system, we can attempt to understand the possible response of the climate system to increased GHG concentrations. The model represents the surface of the planet and the atmosphere as a series of finite ‘grid points’ at which the physical equations of the atmosphere are solved. However, while full global GCMs are useful for understanding the effects of changing variables such as GHGs, they cannot capture the intricacies of New Zealand climate due to their low spatial resolution (typically more than 1° latitude or longitude, which is more than 100km between grid points). Therefore, to understand how changes to the model impact on local-scale climate, we employ a higher resolution Regional Climate Model (RCM, typically less than 0.5° latitude or longitude and therefore less than 50km between grid points), which is driven by output from the GCM. As the RCM represents only a small region of the globe, it can be run at a much higher resolution and can represent the varied topography of New Zealand (for example) with greater accuracy. The RCM can then be used to understand the effects of local-scale processes (such as the interaction of the westerly winds with the Southern Alps) due to changes in the larger-scale atmospheric flow. Therefore, by running the RCM we can identify regional scale influences on climate.

Past warmer climate: The Eocene The Eocene was a period in geological history spanning approximately 55 to 34 million years ago3. The Eocene is an important period as it is considered a ‘greenhouse’ period4, where surface temperatures and GHG concentrations were considerably higher than at present (up to 10°C for the global mean temperature at the start of the Eocene). With the uncertainty over the likely climatological impacts of future global warming, the representation of periods such as these provides an important validation method for the climate models, which are subsequently used to make future projections. If the models agree with the proxy data then we can increase our confidence in future projections of climate change. However, if they (models and proxy data) do not agree, then we can address the possible shortcomings of the model or the derivation of the proxy data and improve them.


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Figure 1: (a) the location and morphology of the New Zealand landmass and surrounding marine basins 55 million years ago2 and (b) the representation of the surface topography (m) used in the RCM. Apart from the lack of instrument data during the Eocene, there are also other important considerations when modelling periods in the distant past. The Earth’s geography was quite different. The Atlantic Ocean was considerably smaller than at present, whereas the Pacific Ocean was much larger. The Indian sub-continent had not collided with southern Asia (no Himalayas), which would result in a completely different global circulation to the present day. The location of gateways between ocean basins, deep sea trenches and mid-ocean ridges would also have been different and their locations would impact greatly on oceanic circulation. The location of land (and high topography) and deep sea bed features are therefore a source of uncertainty in model representations of the Eocene. However, by attempting to reproduce these features, running simulations, comparing the model output to the proxy data and then refining the model setup, a greater understanding of past climates can be achieved.

New Zealand in the Eocene

Figure 2: (a) the seasonal (by month) mean surface air temperature (°C) averaged over the New Zealand landmass for the present day average (1980-1999, blue bars) and the Eocene (red extensions). Also plotted is the spatial distribution of annual mean surface air temperature (°C) over New Zealand for (b) present day and (c) the Eocene. (d) is the seasonal (by month), daily mean precipitation (mm/day) averaged over the New Zealand landmass for the present day average (19801999, blue extensions) and the Eocene (red bars). Also plotted is the spatial distribution of annual, daily mean precipitation (mm/day) over New Zealand for (e) present day and (f) the Eocene.

The New Zealand landmass at approximately 55 million years ago can be seen in Figure 1(a). New Zealand currently lies between approximately 34°S – 48°S and is entirely to the west of the date line (180°E), whereas 55 million years ago5, New Zealand was located further south (between approximately 50°S – 60°S) and almost entirely to the east of 180°E. The landmass probably consisted of one main island (shaded grey) and several smaller peripheral islands (unlike the two major islands today) with a likely ‘non-marine’ link from the main landmass to the land near the Great South Basin (all other areas are marine)6. The location of the east and west coasts of the present islands are marked by the thick black lines to indicate how the landmass has changed in the last 55 million years (to see how the New Zealand landmass has changed over the last 65 million years see ref. 6). An estimate of the land surface and topography (as used in the model) can be seen in Figure 1(b). The land is considered to be low lying with the highest land orientated north-south (in this case the maximum height is 100m above sea level) within the main landmass. It is considered unlikely that there were large mountains during this period (as there currently are in New Zealand) meaning that the New Zealand land surface 55 million years ago would have interacted less with the prevailing westerly wind flow. New Zealand Association of Science Educators

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Model simulations and setup To represent the climate of New Zealand during the Eocene we make use of both a GCM and a RCM. To run the GCM we need to set up the appropriate conditions (boundary conditions) such as land surface characteristics and sea surface temperatures (SSTs) that were appropriate for the Eocene period. To do this, we used data from a GCM that was capable of representing the oceanic circulation as well as the atmospheric circulation (as our GCM does not represent the ocean circulation). We took the SST data from that model and used it as one of the boundary conditions in our model, along with setting CO2 concentrations to 1200 parts per million (about three times the present-day levels), which will cause a strong increase in global temperatures (approximately 10°C higher globally on average, than present day). We also reproduced the land surface characteristics (topography, vegetation, soils, etc.), based on data from the model used to derive the SSTs, to make both simulations compatible. The grid spacing in our GCM is 1.875° longitude by 1.25° latitude (more than 100km between grid points), which means New Zealand climate is represented by very few grid points. Therefore, we configure the GCM simulation to produce ‘lateral boundary conditions’ for our RCM with much higher resolution (0.27° longitude and 0.27° latitude, approximately 30km spacing). These lateral boundary conditions consist of wind speed, sea level pressure, temperature and moisture data from the GCM to transfer weather systems from the low-resolution GCM to the boundaries of the higher resolution RCM. These systems then track through the RCM and give us high-resolution data for variables such as precipitation and surface temperature. Subsequently, the increased resolution in the RCM allows us to understand the regional climate in New Zealand much better than in a GCM. Such a high-resolution simulation of New Zealand climate has not been attempted before for this time period and so these simulations provide a first attempt at recreating some aspect of the Eocene climate in New Zealand. The simulations were run for 21 model years on the National Institute of Water and Atmospheric Research (NIWA) supercomputing facility with data from the last 16 (model) years used in the following analysis.

Temperature and precipitation Temperature and precipitation output for the present day (1980 – 1999 average) observational data and the Eocene RCM simulation can be seen in Figure 2. The monthly mean New Zealand temperatures can be seen in Figure 2(a) with the present day observations colder (blue bar) in each month than the Eocene simulation (red extensions). The largest difference occurs in January where the mean land surface temperature is approximately 6.5°C warmer in the Eocene than at present despite the landmass being located 15° further south. Despite the difference in the actual temperature values, the seasonal cycle of temperature is very similar with the warmest months in JanuaryFebruary and the coldest in July. The overall annual mean temperature over the present-day New Zealand landmass is 10.4°C and is 14.5°C in the Eocene simulation. When we consider the geographical distribution of annual mean temperatures across New Zealand at present and in the Eocene (Figures 2(b) and (c)), there are some interesting differences. There are large regions of cold temperatures in upland areas such as the Southern Alps and the Central Plateau for the present day New Zealand, which are not apparent in the Eocene simulation due to the much lower topography (nothing above 100m). Therefore, the higher topography may also be contributing to the colder surface 6

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air temperatures in Figure 2(b) compared with Figure 2(c) and not just the reduced levels of CO2. However, in lowland areas of the North Island, such as Northland, the annual mean temperature today is between 14 – 16°C, which is comparable with the temperatures in the middle of the New Zealand landmass during the Eocene. The precipitation output is very different, however. The precipitation is lower in every month during the Eocene (Figure 2(d), red bars) with the present day precipitation much higher (blue extensions). Also, the seasonal cycle of precipitation is very different with peak rainfall in October and the lowest rainfall in February for the present day observations. The Eocene simulation, however, has peak rainfall occurring in April and the lowest rainfall in September and December (almost the opposite of the present day seasonal rainfall cycle). The annual mean precipitation from observational data and the Eocene simulation can be seen in Figures 2(e) and (f ). The effect of the Southern Alps on the annual mean precipitation becomes apparent for the present day. Very high precipitation values to the west of the Southern Alps (some values are >10mm/day) are the driving factor behind the higher precipitation values for the present day. In the Eocene simulation, the surface topography is never above 100m and does not produce the same west-east gradient in the precipitation. The precipitation is actually higher in the north of New Zealand during the Eocene than the south, which is likely to be caused by a greater availability of warmer, more humid air from the tropics and subtropics in the north and drier, cooler air from the Pole in the south. Overall, the models indicate that New Zealand may have been warmer and drier in the Eocene. The Southern Alps, which were not present during the Eocene, have a large impact on the current values of temperature and precipitation. However, the difference in the seasonal cycle of precipitation during the Eocene with the wetter season in the late summer and the drier season in the late winter (almost the opposite of the present day) slightly resembles a more tropical or subtropical climate, despite New Zealand’s location 15° further south.

Comparisons to the proxy data and implications While there are interesting differences between the model simulation and the present day conditions, how does the model do in comparison to the available proxy data? Estimates of the annual mean SSTs around New Zealand for the early Eocene2 (55 - 50 million years ago) suggest that the temperatures were as high as 30°C (with annual mean land temperatures >20°C), which is much higher than the values produced by the models. Studies of Eocene sediments also indicate that precipitation was very high in the early Eocene7. However, while the model simulations do not compare well with the proxy data 55 million years ago, they do agree well with proxy data for the later Eocene (about 40 million years ago) that indicate SSTs were around 25°C and air temperatures over land were about 14°C. This tells us that the models are capable of representing the atmospheric processes of the mid- to late-Eocene period, but they may be missing an important process that caused the extreme high temperatures in the early Eocene4. These simulations have therefore provided useful information on the capabilities of our model and allow us to start addressing the issues that have been raised. This will allow us to develop the models further from this first attempt. For further information contact: d.ackerley@niwa.co.nz

Acknowledgment The authors would like to thank Richard Nottage (NIWA) for helpful and insightful comments in reviewing this work,

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Quantum mechanics is a model that helps scientists and non-scientists to understand the world around us, and quantum mechanical software can have a very positive impact on student learning and engagement as Cather Simpson, Director of the Photon Factory, University of Auckland explains: Introduction The development of quantum mechanics (QM) near the beginning of the 20th century was a tremendously exciting time, in which our model of the construction and behaviour of matter and light evolved dramatically. In the hundred and ten or so years since Max Planck first proposed the idea of quantization1 – that atoms and molecules can emit or absorb energy only in little "packets" or quanta – this now very sophisticated model about the microscopic behaviour of atoms, molecules and light has become integral to our understanding and appreciation of the macroscopic world. It underpins much of our technology as well. In a 2001 Scientific American article celebrating 100 years of quantum physics, it was noted that "an estimated 30 percent of the U.S. gross national product is based upon inventions made possible by quantum mechanics, from semiconductors in computer chips to lasers in compact-disc players, magnetic resonance imaging in hospitals and much, much more”.2 It has also become an indispensible scientific tool, used in classrooms and laboratories around the world to inform, reinforce understanding, and to create new knowledge. Specialist research journals focus upon quantum mechanical studies of physical and chemical systems, and major research institutions provide their scientists with access to quantum mechanical software as a necessary tool for performing first-rate science. In university classrooms and teaching laboratories, quantum mechanics does double duty. First, it provides a framework upon which students can build deeper understanding. Second, its implementation is an important part of the curriculum in virtually every major science faculty, with instruction tailored to help students learn this valuable tool. Finally, quantum mechanics is now moving into the school curriculum, starting naturally with high school science. High schools around the world, including those in New Zealand, increasingly use the models of quantum mechanics to enhance learning3. Indeed, some pioneers in high school education go much further and include quantum mechanical models in a very hands-on way, with laboratories and projects that use quantum mechanical ideas and solutions explicitly. The extent to which quantum mechanics has become so widely practical is rather surprising. The execution of quantum mechanics requires what to some is a frighteningly high degree of mathematical prowess. Quantum mechanical particles obey wave equations and act with probabilities rather than with the deterministic certainty conferred by classical mechanics. The solutions to the fundamental quantum mechanical equation of motion, the Schrödinger equation HY = EY, are complex – in both the mathematical sense and in the common one. Fortunately, the development of fast computers, sophisticated computational programming languages and algorithms, and graphical user interfaces have been both timely and adventitious4. Hence we see a new form of scientific endeavour: computational science5.

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Quantum Mechanical Model The most important feature of the quantum mechanical model is that it describes the behaviour of microscopic particles, such as electrons, as waves that tell us about probabilities6. We are all familiar with the one-dimensional standing wave of a string (e.g. a violin string) and the two-dimensional standing wave in a pool. In quantum mechanics, the electrons are described by three-dimensional standing waves (Figure 1). These shapes, familiar to chemists as the atomic orbitals, come from solving the Schrödinger equation above to find the wavefunctions {Y} for the one-electron hydrogen atom. The wavefunctions themselves are based upon the spherical harmonics, and are beautiful to the mathematically inclined. For example, the wavefunction that describes one of the 3d orbitals is7 z5 1/2 2 1 Y3,2,0 = r (3cos2 f – 1)e–Zr/3 6p 81

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This orbital is shown in Figure 2, and is one of the types of orbitals used by transition metals. Because of their energies, excitations among the d-orbitals give many metal compounds their colours. Because of its shape, this orbital on the iron atom of haem is the one that forms the bond with O2 to carry it from our lungs to our tissues. Even for the experienced research scientist, though, this information would be largely inaccessible if it were expressed only as equations like (1). Fortunately, these orbitals can be completely represented with a simple triplet of integers {n, l, ml}called quantum numbers8. Thus this orbital in (1) is identified by {3, 2, 0} and one need recall only the shape associated with those numbers, and not the equation itself. This simplified referencing is why so many high school graduates can talk knowledgably about s-orbitals, p-orbitals and such. Further, no information is lost in the triplet notation – give a theoretical chemist or physicist any set of {n, l, ml} quantum numbers and she can write down the wavefunction in full. It is important to understand that these wave functions describe the electron. That is, an electron acts like a three-dimensional standing wave with the atom's nucleus at its centre. One common student misconception is that the electrons travel inside the orbital shapes. This interpretation is incorrect. No single point on the violin string is the standing wave that generates the sound; the one-dimensional standing wave extends over the length of the string. By extension, the electron as a three-dimensional standing wave extends over the three dimensions of Cartesian space; it is not a tiny particle of matter, whizzing around in those orbital shapes9. The model of the electron as a wave has extraordinary consequences. It accounts for the existence of bonds between atoms. The constructive interference between the two 1s orbitals of adjacent hydrogen atoms gives the extra bit of electron density between them needed to form a bonding molecular orbital. When the two electrons 'occupy' that bonding orbital, a stable H2 molecule results. Without the constructive interference between the two 1s wavefunctions no bond would exist. That is, the two electrons would overlap but not interfere with one another, and they would not form a chemical bond. New Zealand Association of Science Educators

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Figure 1: Standing waves in 1-, 2- and 3-dimensions. A violin string provides a good example of a 1-D standing wave. The top diagram is the fundamental and the others are higher order harmonics. 2-D standing waves are well approximated by a circular drum head. The top, left 2-D standing wave has the lowest energy. The others are higher energy vibrations, with more nodes (places where the wave is mathematically zero) . In the right-hand panel, the first few 3-D standing waves corresponding to the 1s, 2s, 3s, 2pz and 3pz orbitals are shown . Notice that the nodes for 1-D, 2-D and 3-D standing waves are points, lines, and surfaces, respectively.

Figure 3: The stilbene and azobenzene structures were calculated using the quantum mechanical software Gaussian17. Both of these molecules undergo torsional motion about the central double bond when they convert light energy to mechanical motion; azobenzene can also rotate a phenyl group in the molecular plane to achieve the same end. The molecule at the bottom is the diphosphene (P=P) described in the text. While the simpler azobenzene and stilbene compounds are stable at room temperature, the reactive P=P bond requires the protection of bulky groups.

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Figure 2: The 3dz2 orbital represented by equation (1) is shown on the left. Slightly different settings were used on OrbitalViewer to allow visualization of the internal features of this orbital. The haem group, embedded in the protein, on the right contains an iron atom. The 3dz2 orbital of the iron constructively interferes with orbitals from the nearby O2 molecule to form a bond. The green curve indicates where this interaction will take place3.

Figure 4: The potential mechanisms for the transition (isomerization) of diphosphene from the reactant to the product structure are shown, as are some typical experimental data. The quantum mechanical computations indicate that low-energy excitations are generally followed by torsional rotation of the molecule about the P=P bond. For the molecule discussed here, that rotation is frustrated by the extraordinary bulk of the ligands. The mechanism that involves P=P bond breaking is not observed in C=C or N=N analogues, however, some experimental and computational evidence suggests that this process may occur during high-energy excitations. Further experimental and computational studies will help us to better understand these promising molecules.


Using QM in research labs One project in the Photon Factory at the University of Auckland provides an example of how computational modelling aids interpreting experimental results. The project seeks to understand – and control – how molecules convert light energy into mechanical motion. The light-induced rotation about a carbon-carbon double bond (C=C) or a nitrogen-nitrogen double bond (N=N) is an incredibly useful reaction (Figure 3). It is the vital component in hundreds of patents for devices ranging from liquid crystal displays and optical memory storage to nanopumps and organic solar cells12, and is the first reaction in our visual response to light. Our project expands the ‘toolbox’ to similar, but heavier, elements in the periodic table, starting with phosphorus (P=P). This research also provides new tests of prevailing chemical models. Our intuition about chemical structures and reactivity are based largely upon molecules with atoms like C, N, and O. It is increasingly apparent, however, that such elements should be seen as outliers rather than trend-setters in the periodic table13, 14. For instance, the hybrid orbital model, upon which scientists rely heavily for insight into structure, bonding and reactivity, breaks down for molecules containing P, As, Se and other main group elements. The P=P project opens the door to establishing new trends for the reactions of molecules to light. Light-induced structure changes involving the P=P bond have not been thoroughly examined, though the same process in C=C and N=N molecules has been studied for over 100 years15. Our results are thus exciting and new, but interpreting them correctly is very challenging. Currently, we are exploring three possible pathways the molecule might take to get from the reactant to the product structure (Figure 4). We use very short-pulsed lasers to excite the molecule and then probe its evolution using spectroscopy16. Typical data is shown at the bottom of Figure 4 – bumps and valleys that change with time. This is where computational modelling proves indispensable. We use high-level quantum mechanics software17, 18 to predict our molecule's energy levels and geometries. Then, by comparing those results to our data,

we evaluate whether our ideas about how the molecule transforms are reasonable. In this case, the molecule never makes it to the product structure. It starts along pathway A (Figure 4), but the ligands bound to the phosphorus atoms are so large that they prevent rotation about the P=P bond; the molecule returns to the ground state unchanged by the laser19. The next P=P molecule we will study has smaller ligands. It forms the product shape in Figure 4, but also forms a product that involves breaking the P=P bond. Neither the C=C nor N=N molecules undergo this light-induced reaction, so the computational software again will be critical for understanding the experimental results.

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Using QM in the school curriculum Virtually every successful scientific advance evolves in two equally important directions. Research scientists find new levels of sophistication and detail as they refine the model and search for limitations. Concomitantly, new conceptual understanding allows the model to push into science curricula for increasingly younger students. In the first half of the 20th century, quantum mechanics was the art of a handful of chemists, physicists and mathematicians. Within just a few generations, however, it has penetrated the school curriculum, from grade school to college. In the NZ Curriculum3, this can clearly be seen in the Physical World and Material World achievement objectives. At levels one and two, students learn about waves and light. By level four, they are exploring the particle nature of matter as a core, foundational principle. This is astonishing, given that the existence of atoms was still controversial ~100 years ago! The famous physicist and proponent of the atomic theory, Ludwig Boltzmann, committed suicide in 1906 in part, it is believed, because he thought he was losing a long, bitter battle with other prominent scientists who firmly held that matter was not made up of atoms and molecules20-22. Now, school students all over the world are steeped in quantum mechanical models of how matter is constructed and how it behaves. Unfortunately, many of these students leave school with a serious misconception about the atom: the Bohr model. The Bohr atom is incorrect, not because it is incomplete but because it is founded upon principles that do not work. A student with the Bohr atom as their working picture of the structure of atoms must unlearn that model before they can move forward in science. And because of its similarity to the solar system, the Bohr atom model is compelling, memorable, and very challenging for students to unlearn. As world-renowned science educator Professor Peter Atkins says: The Bohr atom is an important step in the historical development of quantum theory, but no more than that, and only appropriate, like phlogiston, when teaching science from an historical perspective. As well as being wholly wrong (in the sense of ascribing orbits to electrons, supposing that the electron has orbital angular momentum in the ground state, and asserting that the electron will never be found at the nucleus), it is such a powerful icon that students who have once encountered it cannot shed its image when they are introduced to the quantum mechanical version of the atom. It is unsafe to teach a model that must later be untaught.23 The most common reason given for teaching the Bohr atom in school is that it is simple and quantum mechanics is too difficult. But the ideas of three-dimensional standing waves, coupled with computational science offers an equally compelling alternative. Computational science – including quantum mechanical software – can have a very positive impact on student learning and engagement at this level24-27. The challenging New Zealand Association of Science Educators

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The same principles that make a stable H-H bond can be applied to much more complex systems. One of the founders of quantum mechanics, Paul A.M. Dirac, famously said in 1929 that, with quantum mechanics, the underlying laws of chemistry and much of physics were known, but the mathematics of these laws too complex to be soluble10. This is still true today, in the sense that exact solutions to the Schrödinger equation still elude us for all but the simplest systems. However, theoretical assumptions and powerful computational software have largely enabled us to overcome this limitation. The software packages available today11 use a variety of quantum mechanical models to calculate structures, energies and other properties of small to moderately sized (a few hundred atoms) molecules. The results can be used to predict what the structure of a new compound will be and how chemical species will react with one another. Thermodynamic variables such as DH, DS and DG can be calculated for real and imaginary reactant/ product systems. The structures and energies of transition state complexes can be computed to obtain insight into reaction mechanisms and kinetics. Calculated UV/Vis absorption spectra, vibrational spectra and NMR spectra provide confirmation of products. These software tools have become so useful that running 'experiments' on the computer with software that uses quantum mechanics is an essential complement to experimental research.

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mathematics are hidden behind easy-to-use graphical interfaces, so that their description of the structures of atoms, how atoms form bonds, how molecules adopt characteristic shapes, how compounds react with each other to form products, and how molecules interact with external sources of energy like heat and light can now be encapsulated and displayed in powerful images and ideas that are accessible to students. These computational science approaches are already entering the high school science curriculum with great success. One pioneering programme is the North Carolina High School Computational Chemistry Server in the USA26. Here, quantum mechanical computational resources are available to all high school students in the state. Students do classroom exercises and independent projects, and even report their findings in The Journal of Student Computational Chemistry. Another groundbreaking initiative, The Institute for Chemistry Literacy through Computational Science27, 24, is run by the University of Illinois. This initiative focuses upon teachers and students to increase student performance and enjoyment of chemistry, and better prepare students for 21st century jobs. This transformative programme has shown statistically significant improvement in chemistry knowledge on the part of both teachers and students, and heightened enthusiasm for the subject as well.

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A Final Word It is important to remember that, for all of its sophisticated concepts and mathematics, quantum mechanics is just a model – it is a mental construction devised by humans to explain the macroscopic, observable behaviour of the world by imagining how microscopic particles that we cannot see must behave. As with all models, experiments and observations are absolutely required to keep quantum mechanics grounded in reality, to distinguish the science from science fiction. Max Planck once said, "Experiments are the only means of knowledge at our disposal. The rest is poetry, imagination." The ideas and images that derive from quantum mechanics are intrinsically compelling to scientists and non-scientists alike because they explain so much about how the world works – even without resorting to computers or mathematics. Hence, quantum mechanics is seen by many as wondrous. Its ideas lend themselves to the philosopher, the poet, the science fiction writer, and the artist, as well as to the scientist and science student. For further information contact: c.simpson@auckland.ac.nz

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Planck, M. (1900). On the Theory of the Law of Energy Distribution in the Normal Spectrum, in German Physical Society. Berlin. Tegmark, M. & Wheeler, J.A. (2001). Celebrating 100 Years of Quantum Mysteries. Scientific American, 284(2): 68-75. The New Zealand Curriculum, the Ministry of Education. (2007). Learning Media Ltd., Wellington, NZ. Kauffman, G.B. & Kauffman, L.M. (1999). Quantum Chemistry Comes of Age. The Chemical Educator, 4, 259-267. Computational science should be distinguished from computer science. The former is the use of computers as tools to study scientific phenomena; the latter is the application of scientific study to the operation and development of computers.

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This essay will not address several important features of quantum mechanics. For example, spin and the wavefunctions of nuclei will be omitted. I focus upon the quantum mechanical model of the atom and molecule from the perspective of a molecular scientist. This perspective necessitates treating the electrons first and foremost, and is of most relevance to chemistry and large portions of physics and biology. Z = atomic number, r = radial distance from the nucleus, j = azimuthal angle. For more information, see university-level chemistry textbooks such as Principles of Modern Chemistry (7th Edition, 2011) by D.W. Oxtoby, H.P. Gilles and A. Campion). n is the principal quantum number; it denotes the shell of the orbital and can only adopt positive integer values. l is the angular momentum quantum number; it identifies the subshell and can adopt values of 0, 1, 2, up to (n-1). The orbital names come from this quantum number: l = 0 is an s-orbital, l = 1 is a p-orbital, l = 2 is a d-orbital and so on. ml is the azimuthal quantum number. It can take on integer values between negative and positive l, and identifies the specific orbital (i.e. pz or dxy) described by the wavefunction. Unfortunately, this misconception is reinforced by the now settled language used to discuss electrons and orbitals. For example, we say that an electron occupies a particular orbital when we mean that the electron adopts the shape of that particular three-dimensional standing wave. The wave-particle duality is one of the most difficult concepts to grasp in quantum mechanics. Only when we measure the location of the electron does it "collapse" into a point of matter. Images of orbitals should be interpreted as locations of high and low probability of finding an electron, should one look. Usually the images represent 90% or 95% probability boundaries. Dirac, P.A.M. (1929). Quantum Mechanics of Many-Electron Systems. Proceedings of the Royal Society London A, 123, 714-733. A list of computational chemistry resources for high school and university levels, some of which is freeware, is given at www.redbrick.dcu.ie/~noel/ linux4chemistry (last accessed April 24, 2011). The U.S. National Institutes of Health Center for Molecular Modeling also maintains a comprehensive list of modelling programs and the applications for which they are suited at http:// cmm.cit.nih.gov/software.html (last accessed April 24, 2011). Those that utilize quantum mechanics are indicated by a QM. Other models are used in computational science software as well. Classical mechanics is widely used for biopolymers such as proteins and DNA. Programs such as SimChemistry for Windows www.simchemistry.co.uk (last accessed April 19, 2011) run simulations that use the kinetic molecular theory of gases. Google patent search http://www.google.com/patents performed May 19, 2010 with keywords "photoisomerization", "photoisomerization + azobenzene" and "photoisomerization + stilbene" Kutzelnigg, W. (1984). Chemical Bonding in Higher Main Group Elements. Angew. Chem. Int. Ed. Engl., 23, 272-295. Power, P.P. (1999). p-Bonding and the Lone Pair Effect in Multiple Bonds between Heavier Main Group Elements. Chem. Rev., 99, 3463-3503. Albini, A. & Dichairante V. (2009). The 'belle epoque' of photochemistry. Photochemical and Photobiological Sciences, 8, 248-254. Simpson, M.C., & Rhode, C. (2009). When is shorter better? NZ Science Teachers, 122, 24-26. Frisch, M.J., et al. (2003). Gaussian 03 (Revision D.01). Gaussian, Inc.: Pittsburgh PA. Werner, H.-J., et al. (2006). MolPro. Package of ab initio computational chemistry programs. Peng, H.-L., et al. (2011). Frustrated Rotation and Fast Intersystem Crossing in a Diphosphene. Photophysics of the P=P Bond. J. Am. Chem. Soc. (submitted). Schwarzschild, B. (1992). A German Professor's Trip to El Dorado. Physics Today, 45, 44-51. Stiller, W. (1986). Ludwig Boltzmann - Pioneer of Atomistics and Evolution. Isotopenpraxis, 22(8), 257-262. Cercignani, C. (2006). Ludwig Boltzmann: Atomic Genius. Physics World, 2006. 34-37. Professor Peter Atkins is a British scientist and writer, formerly a Professor of Chemistry at Oxford University and a Fellow of Lincoln College. He is the author of best-selling textbooks in chemistry, as well as several science books for the general public. Personal communication. 15 April, 2011. Sendlinger, S.C., et al. (2008). Transforming Chemistry Education through Comptutational Science. Computing in Science and Engineering, 34-39. Pallant, A. & Tinker, R.F. (2004). Reasoning with Atomic-Scale Molecular Dynamics Models. J. Science Education and Technology, 13(1), 51-66. See http://chemistry.ncssm.edu (last accessed April 24, 2011). Information about the programme, including links to articles, answers to frequently asked questions, and case studies can be found there. Information about the ICLCS can be found at http://www.iclcs.illinois.edu/ (last accessed April 24, 2011).

continued from page 6 which greatly improved the structure of the text and helped to clarify some of our arguments.

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Zachos, J.C., Dickens, G.R., & Zeebe, R.E. (2008). An early Cenozoic perspective on greenhouse warming and carbon-cycle dynamics. Nature, 451, 279-283. Hollis, C.J., Handley, L., Crouch, E.M., Morgans, H.E.G., Baker, J.A., Creech, J., Collins, K.S., Gibbs, S.J., Huber, M., Schouten, S., Zachos, J.C. & Pancost, R.D. (2009).Tropical sea temperatures in the high-latitude South Pacific during the Eocene. Geology, 37(2), 99-102. http://en.wikipedia.org/wiki/Eocene Huber, M. (2008). A hotter greenhouse? Science, 321, 353-354.

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Cande, S.C. & Stock, J.M. (2004). Cenozoic reconstructions of the Australia-New Zealand-South Pacific sector of Antarctica. In N. Exon, J.P. Kennett, M. Malone (Eds.), The Cenozoic Southern Ocean (pp. 5-18). AGU Geophysical Monograph, 151.Washington DC, USA. King, P.R., Naish, T.R., Browne, G.H., Field, B.D., & Edbrooke, S.W. (1999). Cretaceous to Recent sedimentary patterns in New Zealand. Institute of Geological and Nuclear Sciences folio series 1. [See: http://www.gns.cri.nz/ Home/Our-Science/Energy-Resources/Oil-and-Gas/NZs-Sedimentary-Basins/ Paleogeographic-maps] Nicolo, M.J., Dickens, G.R., Hollis, C.J., & Zachos, J.C. (2007). Multiple early Eocene hyperthermals: Their sedimentary expression on the New Zealand continental margin and in the deep sea. Geology, 35(8): 699-702; doi:610.1130/ G23648A.23641.


“Maybe it’s like this”... the following article explores the science/science education interface and is based on Cather Simpson’s article “Magic of quantum mechanics” (p. 7), as Miles Barker, University of Waikato, explains: My conversation with Cather Simpson turned out to be a heady experience. Her two previous articles1 had led me to expect someone whose life in science at the University of Auckland challenges the sometimes outmoded divisions2 of school science into ‘physics’, ‘chemistry’ and ‘biology’. What I was unprepared for was the extent to which Cather, in the amalgam of her professional and private lives, already routinely inhabits the space between science and science education.3 As director of the Department of Chemistry and Physics’ ‘Photon Factory’, dedicated to bringing “short laser pulses to New Zealand scientists, engineers and educators”,4 she has become a supporter of, and contributor to, the Royal Society’s CREST Awards. Numerous secondary school students have been inspired by visits to her lab. Collecting her two boys from primary school each day has evolved into constant contacts with a group of primary school teachers of science whom she mentors and learns from. And the rich diversity of assessment techniques she employs in on-campus undergraduate group project work would bring a sparkle into the eyes of many teachers of school science. As Cather elaborated the notion (dealt with in her article here) on computer-generated representation of a chemical system as one form of mental model, our talk broadened into the place of models generally in professional science and in school science learning. We talked of the relationship between a model (be it the four-boxes-and-arrows representation of the mammalian heart; or the proton-andorbiting-electron of a hydrogen atom) and the system itself (the heart to be dissected, the gas jar of hydrogen). In short, we talked about the challenge of representing our thinking about what we are observing – what happens when we begin to theorize, to say, “Maybe it’s like this”.5 Cather offered a number of helpful propositions for school science: 1. It is crucial to discuss with learners the question “What is this model saying, and not saying?” i.e. the importance of critiquing a model. To this end, we agreed that Mary Hesse’s idea6 about identifying the positive, negative and neutral features of any model is helpful. The classic model of the London Underground7 is a wonderful example: the positive features where an analogy between the model and the system is intended (e.g. the sequence of the stations), the negative features where an analogy should not be drawn (e.g. the distances between stations), and the neutral features (e.g. the model itself is, as yet, silent on the question of train frequency).8 2. School science investigations should, wherever possible, access both a system and a model; both what we see and how we represent our thinking. Just as a passively observed vinegar/bicarbonate papier-mache volcano demonstration can be unproductive of conceptual learning, conversely so is a computer simulated representation of a redox or

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acid-base titration remote from the laboratory materials equally ‘worth-sucking’ (to use Cather’s colourful term). 3. Even at a very young age, science learners can be consciously familiar with models and model-building. Cather applauded the comprehensive treatment of models in the Science Learning Area of ‘The New Zealand Curriculum’9: L1/2: “… discussing simple models” L3/4: … explore simple models” L5/6: “… complex investigations including using models” L7/8: “Understanding the relationship between investigations and scientific theories and models”. We traded misconceptions that learners may be prone to: a model in science is not, in fact, a miniature version (like a model car); nor is it an idealized form (a model army, a model country school); nor is it a display (a model on a catwalk). 4. It is essential for students to understand that there are frequently rival models,10 that a progression of increasingly sophisticated models may be suggested,11 and that sometimes there may be wholesale replacement of the theory which underpins a cluster of models.12 In summary, my conversation with Cather illuminated both a general aspect of the Nature of Science (NoS), namely, what a life in science may be like, and a specific aspect of NoS: the centrality of model-building – “Maybe it’s like this” – in science education. For further information contact: mbarker@waikato.ac.nz

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New Zealand Science Teacher, 122, 24-26 and 124, 15-17. Aikenhead (2000), p.257. Rosemary Hipkins (2011) has pursued the same purpose. NZST, 122, p.25. Bill MacIntyre (2008) has discussed young learners’ representations of a burning candle. Refer Hesse (1966) or: http://en.wikipedia.org/wiki/Mary_Hesse Judson (1980). I am grateful to Ian Taylor for teaching me about this. For example, Cather would applaud teachers and students together applying this approach to the heart model and the hydrogen model mentioned above. Ministry of Education (2007). It is not well known that Watson and Crick’s iconic wire-and-steel-plates model of DNA replaced rival models based on a longstanding alternative theory that nucleoproteins were the basis for the genetic material (Barker, 2003). Carr et al. (1994) explains this in terms of the frequently taught primary school topic of ‘floating and sinking’. French (2007), pp.80-84, 95-96. Famous historical examples of science theories that have been replaced include phlogisten, catastrophic geography, caloric, the humours (in medieval medicine), vital force (in physiology), the ether (in electromagnetism) and spontaneous generation.

References Aikenhead, G. (2000). Renegotiating the culture of school science education. In R. Millar, J. Leech & J. Osborne (Eds.), Improving science education – the contribution of research. Buckingham: Open University Press, pp.245-264. Barker, M.A. (2003). Watson and Crick (1953): Brave new conceptual world, or business as usual? New Zealand Science Teacher, 103, 27-28. Carr, M., Barker, M., Bell, B., Biddulph, F., Jones, A., Kirkwood, V., Pearson, J. & Symington, D. (1994). The constructivist paradigm and some implications for science content and pedagogy. In P. Fensham, R. Gunstone, & R. White (Eds.), The content of science: A constructivist approach to its teaching and learning (pp.147-160). London: The Falmer Press. French, S. (2007). Science – key concepts on philosophy. New York: Continuum. Hesse, M. (1966). Models and analogies in science. Indiana: University of Notre Dame Press. Hipkins, R. (2011). A conversation about nanotechnology at the science/science education interface. New Zealand Science Teacher, 126, 12. Judson, H. F. (1980). The search for solutions. New York: Holt, Rinehart and Winston. MacIntyre, W. R. (2008). The burning candle. New Zealand Science Teacher, 117, 31-32. Ministry of Education (2007). The New Zealand Curriculum. Wellington: Learning Media.

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modelling fluid splashes Capillary and wetting phenomena are essential for painting walls, and printing processes, as Mathieu Sellier and Mark Jermy, Department of Mechanical Engineering, University of Canterbury, explain: Introduction and background What happens to a cement block thrown into a bath? Obviously, it sinks. Now, what happens if the block is broken into a myriad of very fine pieces which are thrown in the same bath? The answer is then less obvious: some will float, some won't. People with basic physics training know that surface tension, sometimes referred to as capillarity, is responsible for the flotation of the cement pieces. This example illustrates an important point: capillary phenomena only play an important role at smaller length scales, though they may have large observable effects in nature. For example, they allow water striders to crawl at the surface of ponds1 or palm beetles to produce adhesion forces exceeding 100 times their body weight, a very effective defence mechanism against predators which simply cannot “peel” the beetle off surfaces2 (see Figure 1). If we now consider a glass being slowly filled up with water, the water level will rise to a height which is slightly greater than the rim of the glass. Again, it is common knowledge that the excess water is held by surface tension. The exact quantity of water which can be held by surface tension is dependent on the shape of the rim and its wetting properties, which determine its tendency to ‘attract’ or ‘repel’ the water. Wetting phenomena are also apparent in nature, the most prominent example being the lotus leaf which is a very strongly water repellent surface thanks to its convoluted microstructure (see Figure 1). Such surfaces have been coined “superhydrophobic” (extremely water-fearing) surfaces and have inspired the development of self-cleaning glass window panes for example3. Capillary phenomena only occur when an interface between two different fluids exists such as the water/ air interface, also known as free surface, which exists around a rain drop. This interface can be thought of as a stretched membrane characterised by a surface tension that opposes its distortion. Surface tension is related to the energy required to stretch an interface, and a good way to understand its effect it to think about blowing bubbles. The air blown exerts pressure on the soap film and provides a)

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the required energy to stretch it to produce a bubble. If the liquid surface tension is increased, the air must be blown harder, i.e. more work must be done to produce the bubbles. In other words, it takes work to create surface area and this is the very reason why drops adopt a spherical shape which is the shape with the least amount of surface area for a given volume. Wetting phenomena arise when one fluid displaces another on a solid surface. For example, when a water droplet spreads on a solid surface, water molecules displace previously present air molecules at the wetting front, also known as the contact line, where the water, air, and solid surface meet. The property which characterises the wettability, i.e. the potential of the liquid to spread and cover a solid surface, is the contact angle. For a water droplet in air on a horizontal solid surface, the contact angle is simply the angle of the water/air interface to the horizontal. A highly wetting fluid tends to spread indefinitely such that the contact angle is very small, whereas a poorly wetting fluid does not ‘like’ to spread and cover the solid surface. In this case, the contact angle is large and in the case of superhydrophobic surfaces such as a lotus leaf, it can be as large as 160˚. The value of the contact angle is determined by the energy required to make new liquid-gas surface, against the energy required to make new liquid-solid surface. It takes a lot of energy to make an area of water-leaf contact on a lotus leaf, so the contact area is minimised. Capillary and wetting phenomena arise in nature as already mentioned, but much of the research effort has been motivated by the wide range of applications where they play an important role4: the application of surface coatings such as paint on walls, anti-reflective coatings on TV screens, the deposition of ink on paper in printing, or pesticides on leaves, the penetration of liquid in porous rocks, anti-stain or anti-frost treatment of glass, treatment of tyres to promote adhesion even on wet or icy roads. The list is seemingly endless. Young and Laplace laid the foundation of our understanding of capillary and wetting phenomena in the early 19th century, but many of the breakthroughs in this field have been facilitated by the use of IT and more specifically computer-aided modelling. Computational fluid dynamics, known to engineers as CFD, is nowadays a standard tool to analyse fluid flows. c)

Figure 1: (a) Water strider resting on a water surface. The weight of the water strider is supported by a combination of buoyancy and surface tension forces. (b) Palm beetle on a palm leaf. Palm beetles harvest oil from palm trees and use its surface tension to stick to the leaves. They do it by forming over 100,000 tiny droplets of palm oil on their ‘feet’. Each droplet adheres to the leaf with only the tiniest force, but multiplied by all the droplets produces a significant force. (c) The lotus leaf is highly hydrophobic, i.e. extremely water repellent, because of its complex micro- and nanoscopic architecture which minimises adhesion. Dirt particles are picked up and drained by water droplets. 12

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Flow modelling Much of our understanding of fluid mechanics, and our methods of getting answers to fluid mechanic problems, is based on the idea of conservation laws. The thing we can really be sure of in fluid flows is that mass, momentum and energy are conserved. Mass is easy; unless there are nuclear reactions or motion at near light speed, the total mass of a given quantity fluid stays the same. It might spread out, or flow into and out of different chambers, but the total mass doesn’t change. The same is true of momentum: it is not created or destroyed, though it can be transferred according to Newton’s laws. A kayak paddle transfers momentum to the water, and an equal amount of momentum in the opposite direction is transferred to the kayak, pushing it forward. Energy also is conserved, though it is often converted from one form to another. Viscous friction converts the kinetic energy of otherwise free-flowing fluid into turbulent kinetic energy (eddies and vortices) and heat. Kinetic energy can be converted into pressure, a form of internal energy, as described by Bernoulli’s principle. If the fluid flows uphill, some kind of energy is converted to gravitational potential energy. These conservation laws allow us to deduce a set of equations which govern fluid flow, called the governing equations. By including different forces acting on the fluid, and different assumptions about what is unimportant and can be left out of the equations, they can take many forms. These equations can be solved with pencil and paper, but only for a few very simple cases. In most practical problems, they must be solved by computer. For flows, the most common method of solving these equations is the finite volume method. The space in which the fluid flows is divided up into small cells. The fluid entering and leaving each cell is tracked, as are the forces acting on the fluid in each cell and the principles of conservation applied to determine the mass (density), momentum (velocity) and energy (pressure, temperature) of the fluid in each cell. Boundary conditions are applied, the known conditions at the inlets and outlets and at the walls, and the computer works inwards into the fluid from these boundaries to determine the state of the flow in each cell. The computer then works forward in time to see how the flow evolves. Encompassing capillary and wetting effects into simulations is particularly challenging because the position of the interface between the fluids is not known a priori. The position of the free surface must therefore be inferred as part of the solution process. A number of techniques have been developed to resolve this issue such as the front tracking method, the level set method, the marker particle method, or the volume of fluid method5. The essence of these methods is to identify the fluid phases as topological entities which can be achieved by either introducing markers on the interface or introducing a binary variable which takes on a value of 1 when the cell is filled with one fluid phase and 0 otherwise. The interface can then be numerically advected, i.e. transported, by the flow. Another difficulty which is a much disputed point in the fluid mechanics community is: what happens at the contact line? It is commonly assumed that because of their

viscosity, fluids adhere to solid surfaces. Consequently, the fluid velocity at the solid surface should be zero if the solid surface is at rest. This condition is known as the “no-slip” condition and is in contradiction with the fact that the wetting front (aka the contact line) is moving. This ‘contact line paradox’ is a singularity, a point where the classical description of fluid mechanics fails and some form of regularisation is required to overcome this issue. One possibility is to introduce a small amount of ‘numerical’ slip in the neighbourhood of the wetting front. Simulating the flow like this allows us to know and understand the flow much better than we can do by doing laboratory experiments. We can know, from a simulation, the pressure, temperature, position of the free surface, velocity and the concentration of chemical species at every place in the flow, at any time. It is impossible to measure to this level of detail (resolution) in an experiment, especially when you have to put physical probes like thermometers into the fluid, which redirect and alter the flow. Doing a simulation is usually quicker and cheaper than doing a properly controlled experiment. Of course there are disadvantages to simulation. If we are too rash in making assumptions, important physics can be left out of the simulation, and the computer’s solution may not represent the real flow. If the flow is divided into cells too large (coarse), as often happens in an effort to save computer memory or reduce the running time of the program, errors appear in the solution. The most common is an additional diffusion of mass and momentum, which gives rise to effects as though the fluid is more viscous than it really is. If the wrong values are applied at the boundaries, the solution may resemble a completely different flow. These errors may exist without being noticed, until the results are compared to reality. Sometimes the simulation diverges, and produces an unphysical result or no result at all. The best work comes when the results of simulation, with the detailed understanding it creates, are made certain by careful comparison to experiment and observation.

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Computer modelling complements (and sometimes replaces) laboratory experiments on scaled physical models reducing the cost and time of testing. The presence of an interface and contact lines in the flows of interest here presents some challenges in modelling. This article describes how this modelling is performed. Two examples drawn from the authors’ research at the University of Canterbury are presented.

Applications This section highlights through a couple of recent projects at the University of Canterbury the benefits of being able to model capillary and wetting phenomena. Modelling blood droplet impacts Bloodstain pattern analysis is the examination of the shape and distribution of bloodstains which can sometimes provide valuable information for crime scene investigators. One of the important pieces of information which may be inferred from impact spatter patterns is the area of origin of the spatter, i.e. exactly where the victim was when injured. It is deduced from the knowledge of the position of bloodstains in the pattern, their directionality, their impact angles, and elementary trigonometry. Forensic scientists use a lot of empirical laws to make deduction from bloodstains, but the range of validity of these laws is not always well known because of an incomplete understanding of the underlying fluid mechanics. This has motivated a series of projects in collaboration between the Department of Mechanical Engineering at the University of Canterbury and Environmental Science and Research, the Crown Research Institute in charge of forensic science in New Zealand, to explore experimentally and numerically the formation of bloodstains. A commercially available Computational Fluid Dynamics (CFD) package called Fluent was used to model the impact of blood droplets. Figure 2a shows the mesh which is generated to simulate the flow field. It encompasses all the cells (approximately 400,000 of them) in the computational New Zealand Association of Science Educators

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Figure 2: (a) Mesh with approximately 400,000 cells used to model the blood droplet impact. The mesh shows two levels of refinements: a very fine mesh in the expected droplet path and a coarser one in the surrounding atmosphere. (b) Sequence of droplet profiles obtained from the simulation showing the collapse of the initially spherical droplet into a flat pancake. domain, i.e. the volume in the three-dimensional space through which the blood droplet travels and collides with the solid surface. Because of the large number of cells, the time required to complete the computation is long, on the order of 24 hours on a high-performance computer. Figure 2b shows a sequence of images of the droplet profiles computed at various times. For this particular simulation, the blood droplets impact perpendicular to the glass solid surface. The stain formation results from an energy conversion; most of the droplet energy is initially in the form of kinetic energy. During the impact the kinetic energy is converted into surface energy as the droplet stretches radially outwards at the base. Kinetic energy is also dissipated by viscous friction as the liquid film deforms and flows over the surface. It takes between 3 and 4 ms for the droplet to reach its maximum spread radius. At that stage the droplet assumes a flat pancake shape. The maximum spread radius corresponds to the shape of the final bloodstain. The results of the simulation have been compared with high speed camera images from experiments and a good agreement was found between the two giving us confidence that CFD can help shed light on bloodstain formation.

Modelling coating flows Many manufactured products are coated with a protective, decorative, or functional layer. Examples include the production of CDs, displays, or cars on which a paint layer is applied. Typically, the aim is to apply a thin liquid layer and to let it dry ensuring that it maintains a defect-free, uniform thickness. The presence at the solid surface of defects such as microscopic asperities or chemical variations often interact with the coated layer and can compromise the quality of the coating finish. We have developed simulation tools relying on a special simplifying approximation of the conservation equations mentioned above to understand how a thin liquid layer or a droplet interacts with surface defects. Figure 3a illustrates, for example, the spreading of a droplet over a cross of poorly wettable material. The figure sequence shows that the droplet does not want to spread over the cross and finds it more energetically favorable to split into four smaller satellite droplets located in the four quadrants of more wettable material. Figure 3b also shows the evolution of the thickness of a liquid layer coated around a corner. Anyone who has ever tried to paint a convex corner knows how difficult it is because the paint layer tends to thin sometimes exposing the underlying wall. This phenomenon is a consequence of surface tension which aims to flatten the fluid free surface to reduce its curvature. The figure shows the results of a numerical simulation tracking the evolution of an initially uniform fluid layer around a convex corner. The expected thinning, and thinning rate, are well captured by the numerical simulation. By deepening our

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Figure 3: (a) Sequence showing the evolution of a droplet spreading over a cross of poorly wetting material. The sequence reads from the top-left to the bottom-right figures. The lines represent the contours of fluid elevation just like those on a topographical map. (b) Evolution of a thin liquid layer around a convex corner. The black solid line indicates the corner contour and the dashed line the final liquid coating free surface. 14

New Zealand Association of Science Educators


Atmospheric radiocarbon may be a valuable tool for looking at changes in the Southern Ocean carbon cycle, as Dr Sara E. Mikaloff Fletcher, from NIWA, explains: Atmospheric carbon dioxide (CO2) is the dominant contributor to human-induced climate change. Between 2000 and 2009, human beings emitted an average of 8.8 billion tonnes of carbon to the atmosphere each year from fossil fuel burning, cement production, and deforestation.1 However, measurements from a global network of atmospheric CO2 monitoring stations indicate that slightly less than half of these emissions stayed in the atmosphere, which means that the remainder must be taken up by the terrestrial biosphere and the oceans (Figure 1). These natural sinks of atmospheric CO2 have been the subject of vigorous research over the last few decades due to their crucial role in slowing climate change.

Figure 1: The partitioning of human emissions of CO2 into different reservoirs in the environment, where negative values indicate a carbon sink. Fossil fuel and land use change emissions are the sum of fossil fuel emissions from the Carbon Dioxide Information Analysis Center at Oak Ridge National Laboratory (Marland et al., 2005) and land use change emissions estimated from United Nations Food and Agriculture Organization statistics (Houghton, 1999). Atmospheric accumulation is based on atmospheric observations from the National Oceanic and Atmospheric Administration Earth Systems Research Laboratory. The oceanic uptake is based on an average of five different ocean models, and the terrestrial uptake is calculated as the net emissions minus the atmospheric and oceanic components (Le Quéré et al., 2009). These values are publicly available courtesy of the Global Carbon Project (www.globalcarbonproject.org). 1

Friedlingstein et al. (2010). Update on CO2 emissions. Nature Geoscience, doi: 10.1038/ngeo_1022.

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The amount of CO2 taken up by the oceans – also called the ocean sink – can be determined in three ways: by combining computer models of ocean circulation with other computer models that help us understand chemical cycling in the ocean; using shipboard measurements of carbon in the surface ocean and atmosphere from around the world; or estimating it from ocean interior measurements and models. While there has been considerable debate about the magnitude of this sink in the scientific community in the past, over the recent decade independent estimates from all three of these approaches have converged on a mean global uptake of about 2 billion tonnes of carbon per year (2000-2009 mean). This is about half of the global carbon sink over this period, with uptake from the terrestrial biosphere accounting for the rest.

Why do the oceans take up atmospheric CO2? The amount of CO2 exchanged between the air and the ocean, called the CO2 flux, is proportional to the difference between the partial pressure of CO2 in the water near the ocn , and the partial pressure of CO2 in surface of the ocean, PCO2 atm : the atmosphere, PCO2 ocn atm FCO2 = kw(PCO2 –PCO2 ) = kwDpCO2 Where kw is the gas exchange parameter, which is a function of wind speed and other environmental factors, and negative fluxes indicate CO2 uptake by the ocean. Therefore, as human beings increase atmospheric CO2 through fossil fuel emissions, the ocean uptake of CO2 also increases. If there were no ocean circulation, the atmosphere and the surface ocean would be in near equilibrium, and the oceanic uptake of atmospheric CO2 would be relatively modest. However, upwelling of deep waters that have not seen the atmosphere since pre-industrial times and sinking of waters that have taken up atmospheric CO2 also increases ocn at the surface. This ocean the ocean sink by decreasing PCO2 sink is not large enough to absorb all anthropogenic emissions to the atmosphere, but it plays a major role in slowing climate change. The Southern Ocean is particularly important to the global carbon cycle, because it is responsible for nearly a quarter of the global ocean uptake of anthropogenic carbon, more than any other ocean region (Figure 2). This is because the Southern Ocean is one of the greatest regions of upwelling of deep waters, which are able to absorb a great deal of anthropogenic CO2 from the atmosphere.

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How does ocean CO2 uptake change with time? Recent modelling studies have suggested that the Southern Ocean carbon sink may slow in the future in response to climate change. Increases in atmospheric greenhouse gasses don’t just increase the global mean temperature, they also have a major impact on atmospheric winds. In particular, model simulations suggest that climate change increases the westerly winds over the Southern Ocean. Atmospheric winds can in turn influence ocean carbon uptake in two ways: through their role in driving ocean circulation, and through their role in air-sea gas exchange. Ocean model simulations suggest that observed changes in the winds over the last few decades may have slowed the New Zealand Association of Science Educators

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Southern Ocean carbon sink by influencing upwelling in this region. If this is correct, then this carbon sink would be expected to continue to slow in the future as a result of human-induced climate change, creating a positive feedback between climate and the ocean carbon sink. However, this hypothesis is still the subject of debate in the scientific community, since this result may be sensitive to processes that are poorly represented in the current generation of ocean models, such as ocean eddies. Environmental measurements are needed to determine whether, and to what extent, the Southern Ocean carbon sink is slowing.

of carbon, 14C, to the dominant isotope, 12C, can provide tremendous insight into ocean circulation. Radiocarbon is generated in the atmosphere through natural cosmogenic radiation, nuclear bomb testing (primarily prior to the Partial Nuclear Test Ban treaty, which banned above ground nuclear testing in 1963), and nuclear power. Some of this radiocarbon is then absorbed into the ocean, and slowly decays radioactively into 14N in the interior ocean. Therefore, radiocarbon in the ocean can give scientists an idea about the age of the water, or the amount of time that has passed since that water was last in contact with the surface, in much the same way that radiocarbon dating can be used to determine the age of other carbon containing materials. In order to separate very small changes in radiocarbon due to these aging effects from much larger changes due to variations in the total amount of carbon in a sample, radiocarbon is typically expressed as the ratio of 14C/12C in a sample relative to a standard ratio, scaled up by a factor of 1000. The resulting quantity is known as D14C and has units of per mil (due to the scaling by a factor of 1000).

Figure 2: Oceanic uptake of atmospheric CO2 from fossil fuel burning and land use change, broken down by geographic region, where negative values reflect a carbon sink. These fluxes were estimated using ocean interior observations of dissolved inorganic carbon and nutrient data as well as ocean models (Mikaloff Fletcher et al., 2006). The mean and error bars reflect a weighted mean and standard deviation of ten different contributing ocean models.

How can we detect changes in the Southern Ocean carbon sink from atmospheric observations? In principle, it should be possible to use high precision atmospheric CO2 measurements from observing stations across the high latitude Southern Hemisphere to detect changes in the ocean carbon sink. The National Institute for Water and Atmospheric Research (NIWA) maintains the longest running continuous CO2 record in the Southern Hemisphere at the Baring Head Clean Air Monitoring Station in Wellington, which has been in operation for over 30 years. In addition, international laboratories such as Australia’s Commonwealth Scientific and Industrial Research Organisation, the U.S. National Oceanic and Atmospheric Administration and others operate a global network of sites that include stations in Australia, Antarctica, South America, and on remote islands in the Southern Ocean. Some studies using atmospheric CO2 measurements and atmospheric models to infer Southern Ocean carbon uptake have suggested that there may be a trend towards a slowing Southern Ocean sink. However, subsequent modelling and data analysis work have cast doubt onto this result. This is in part due to the fact that atmospheric CO2 is also strongly influenced by trends and variability in uptake by plants on land, which is the least well-known part of the carbon budget. In addition, the differences in the trends of atmospheric CO2 that one would expect due to a slowing of the ocean carbon sink over the last two decades are only slightly larger than the measurement accuracy as determined by comparisons between laboratories. Therefore, analysis of atmospheric CO2 alone isn’t an effective way to detect changes in the Southern Ocean carbon cycle.

Radiocarbon as a tracer for ocean circulation Subtle changes in the ratio of the radioactive isotope 16

New Zealand Association of Science Educators

Figure 3: Annual mean air-sea fluxes from the Modular Ocean Model 3 (MOM3). For simplicity, only the natural fluxes are shown here, and changes in ocean uptake due to fossil fuel emissions and atmospheric bomb testing are not included. Top: Air-Sea CO2 flux (mol C m-2y-1). Centre: 14CO2 flux scaled using the pre-industrial ratio of 12 CO2/14CO2 (mol C m-2y-1). Bottom panel: middle panel minus the top panel. Negative values represent ocean uptake, and positive values represent ocean outgassing. The greatest difference between the top and middle panels is in the Southern Ocean.


Sensitivity of atmospheric CO2 to perturbations in winds over the Southern Ocean

Figure 4: Response of the atmospheric radiocarbon to scaling winds over the Southern Ocean as a function of latitude. Winds are scaled between 50% of their current value (0.5) and 150% of their current value (1.5) in a model to evaluate the impact of winds on atmospheric radiocarbon.

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Atmospheric radiocarbon measurements NIWA maintains the longest running atmospheric radiocarbon timeseries in the world, which runs from 1955 to the present. This unique atmospheric record combined with other atmospheric radiocarbon records in the Northern Hemisphere has the potential to provide a new window onto changes in winds in the high latitude Southern Hemisphere and allow early detection of changes in the Southern Ocean carbon sink. Knowing how the natural sinks are changing over time will help us to predict how much anthropogenic emissions need to be reduced or captured and sequestered in order to stabilise atmospheric CO2. For further information contact: s.mikalofffletcher@niwa.co.nz

References and further reading

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The Southern Ocean is characterised by vigorous upwelling of very old waters that are strongly depleted in radiocarbon compared with surface waters over the rest of the ocean. Figure 3 shows modelled air-sea fluxes of 12CO2 (top panel), 14CO2 (middle panel, scaled by the pre-industrial ratio between 12C and 12C so that the magnitudes will be comparable), and the difference between them (bottom panel). Over most of the ocean, the 12CO2 and 14CO2 air-sea fluxes behave very similarly. When the air-sea flux of 12CO2 is subtracted from the air-sea flux of 14CO2, which has been scaled up by a standard ratio (bottom panel), the difference is near zero outside the Southern Ocean. However, since the waters on the surface of the Southern Ocean are much more depleted of radiocarbon than the waters in other areas, the ratio of 14C uptake to 12C uptake is much higher in this region. This suggests that atmospheric radiocarbon is likely to be highly sensitive to changes in winds over the Southern Ocean because the winds affect both upwelling of waters low in 14C and air-sea gas exchange. Therefore, this species could serve as an early indicator of changes in the Southern Ocean carbon cycle. In order to test this hypothesis, a series of simple, idealised model experiments were done. The winds over the Southern Ocean were reduced by 50% in an ocean model, then subsequent model simulations were run in which the winds were increased each time until they were 150% of their usual value. These modelled fluxes were then used in an atmospheric transport model to determine how they might influence atmospheric radiocarbon as we move from the Southern Hemisphere to the Northern Hemisphere.

For this illustrative example, the simulations shown here reflect only the natural radiocarbon and CO2 and do not include fluxes due to fossil fuel burning, nuclear testing, and other human-induced factors. However, the results are qualitatively similar to what would be expected from using the full radiocarbon budget. Since the Southern Ocean is the primary sink region for atmospheric radiocarbon, the atmospheric radiocarbon generally increases as you move from south to north (Figure 4). However, the north-south gradient is highly sensitive to these wind perturbations. This confirms our hypothesis that atmospheric radiocarbon may be a valuable tool for looking at changes in the Southern Ocean carbon cycle.

Houghton, R.A. (1999). The annual net flux of carbon to the atmosphere from land use 1850-1990. Tellus, 51B, 298-313. Le Quéré, C., Raupach, M.R., Canadell, J.G., Marland, G., Bopp, L., Ciais, P., Conway, T.J.,Doney, S.C., Feely, R., Foster, P., Friedlingstein, P., Gurney, K., Houghton, R.A., House, J.I., Huntingford, C., Levy, P.E., Lomas, M.R., Majkut, J., Metzl, N., Ometto, J.P., Peters, G.P., Prentice, I.C., Randerson, J.T., Running, S.W., Sarmiento, J.L., Schuster, U., Sitch, S., Takahashi, T., Viovy, N., van der Werf, G.R., Woodward, F.I. (2009). Trends in the sources and sinks of carbon dioxide. Nature Geoscience, 2, 831-836. Le Quéré, C., Rödenbeck, C., Buitenhuis, E.T., Conway, T.J., Langenfelds, R., Gomez, A., Labuschagne, C., Ramonet, M., Nakazawa, T., Metzl, N., Gillett, N., & Heimann, M. (2007). Saturation of the Southern Ocean CO2 Sink Due to Recent Climate Change. Science, 22, doi: 10.1126/science.1136188. Lovenduski, N., Gruber, N., & Doney, S.C. (2008). Toward a mechanistic understanding of the decadal trends in the Southern Ocean carbon sink, Global Biogeochem. Cycles, 22, GB3016, doi:10.1029/2007GB003139. Marland, G., Boden, T.A., Andres, R.J. (2005). Global, Regional, and National fossil fuel CO2 emissions. In Trends: A Compendium of data on global change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, TN, U.S.A. Mikaloff Fletcher, S.E., Gruber, N., Jacobson, A.R., Doney, S.C., Dutkiewicz, S., Gerber, M., Follows, M., Joos, F., Lindsay, K., Menemenlis, D., Mouchet, A., Muller, S.A., & Sarmiento, J.L. (2006). Inverse estimates of anthropogenic CO2 uptake, transport, and storage by the ocean. Global Biogeochemical Cycles, 20. Rodgers, K.B., Mikaloff Fletcher, S.E., Bianchi, D., Beaulie, C., Galbraith, E.D., Gnanadesikan, A., Hogg, A.G., Iudicone, D., Lintner, B., Naegler, T., Reimer, P.J., Sarmiento, J.L., & Slater, R.D. Interhemispheric gradient of atmospheric radiocarbon reveals natural variability of Southern Ocean winds, Clim. Past Discuss., 7, 347–379, 2011, www.clim-past-discuss.net/7/347/2011/, doi:10.5194/cpd-7-347-201.

continued from page 14 understanding, the ability to model such flows opens up the possibility to develop new coatings and application tools which mitigate the appearance of coating defects.

Closing remarks The equations governing fluid flow are too complex for analytical solution in all but the simplest cases. Information technology allows us to solve these equations numerically, and in doing so gain a deep understanding of the flow phenomena, with a detail not possible in experiments, though comparison with observations is important to check the results are correct. The size and complexity of the problems which can be tackled by this type of modelling

simulated have grown rapidly with the speed and memory capacity of computers. For further information contact: mathieu.sellier@canterbury.ac.nz

References 1

2

3

4

5

Bush, J.W.M. & Hu, D.L. (2006). Walking on water: biolocomotion at the interface. Annual Review of Fluid Mechanics, 38, 339-369. Vogel, M.J., & Steen, P.H. (2010). Capillary-based switchable adhesion. Proceedings of the National Academy of Sciences of the USA, Vol. 107, 3377-3381. Forbes, P. (2008). Self-cleaning materials: Lotus Leaf-Inspired Nanotechnology. Scientific American, August issue. de Gennes, P.-G., Brochard-Wyart, F., & Quéré, D. Capillary and wetting phenomena – drops, bubbles, pearls, waves. Springer. Scardovelli, R., & Zaleski, S. (1999). Direct numerical simulation of free surface and interfacial flow. Annual Review of Fluid Mechanics, 31,567-603.

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modelling horticultural produce storage and packaging design organoleptic and toxicological measures, and a maximum tolerable loss of quality (Qmax) may be established. The package is assumed to be free of leaks, so permeation characteristics depend on the packaging material alone.

NZ is a key exporter of horticultural produce, but ensuring the food reaches the consumer in prime condition requires the use of mathematical modelling, as Tom Robertson (pictured) and Jon Bronlund, School of Engineering and Advanced Technology, Massey University, explain:

Modelling studies

New Zealand-grown horticultural produce is extensively exported, often over long distances to key markets in Europe, Japan, North America and Australia (Figure 1). As a consequence horticultural produce is stored for long periods whereby potential quality deterioration is controlled by appropriate grading, storage, packaging and distribution systems. The shelf life of horticultural produce is a complex function of: initial quality of the produce; exposure to variations in temperature and surrounding gas composition; relative humidity during storage. All of which influence the produce physiology, extent of water loss and microbial spoilage. As such, full-scale shelf life trials are complex, expensive and time-consuming. These factors have led to the use of mathematical modelling approaches to predict produce quality, and to design packaging and distribution systems for fresh horticultural produce.

Modelling of horticultural produce storage and distribution Modelling of packaged food shelf life is a quantitative description of a system of the food, the package and the environment. For the modelling to be successful quantitative data on each system is required. Some assumptions that are widely used to simplify the mathematical formulation of shelf life models are (Gnanasekharan & Floros, 1993): (1) The deteriorative mechanisms that limit shelf life depend primarily on environmental factors (oxygen partial pressure, relative humidity and temperature) and compositional factors (pH, concentration, water activity, etc.). The rate of quality loss (dQ/dt) may then be expressed as: dQ (1) = f (P02,RH,T,F) dt (2) The rate of quality loss can be characterised by relating some objective measure(s) of deterioration to

Initially, modelling was used to predict the heat load during chilling and storage of horticultural produce to optimise the design of the refrigerated storage (e.g. Cleland and Cleland, 1989). This modelling was then extended to include the contribution of the fruit and the packaging to the heat loads used in design of refrigerated storage (e.g. Tanner et al., 2002a). Other studies have investigated prediction of air flows in cool stores, shipping holds and containers (e.g. Smale, 2004) and air flow within cartons (Zou et al., 2006a,b). Models have been used to characterise heat (Bronlund and Robertson, 2006) and moisture transfer through corrugated paperboard used to pack the produce. It is through the integrated understanding of product and package heat and moisture transfer achieved in this work that led to the design of packaging that meets the requirements of both pre-cooling and long-term storage. To complement the understanding of heat and moisture flow in bulk produce, research on predicting produce quality from environmental conditions has been carried out (Hertog and Nicholson, 2003; Hertog et al., 2004, Johnston et al., 2005, 2006 and East et al., 2009). By combining these models for weight loss, firmness loss, chilling injury and rot, with heat and mass transfer models, insights have been gained into packaging and distribution system design (Tanner et al., 2002b). The search for technologies to increase the storage life of high quality produce has led to the development of controlled volatile release systems. To avoid trial and error, models have been developed to predict the impact of antimicrobial component (single and multiple) release such as hexanal from packaging material into the package atmosphere (Utto et al., 2008). This models the rates of release required to maintain the produce quality over the required shelf life. These design tools provide clear targets for new research on manufacture of polymer films to release active compounds at the required rates.

Produce

Export produce Amount (tonnes)

Apples

421,000

342.3

288,000 (80 million trays)

765.1

108,787

88.8

Onions

210,000

120.5

Squash

123,000

66.0

Kiwifruit Other fresh fruit

Other fresh vegetables Figure 1: Fruit and vegetables exported from New Zealand in 2007. 18

Value (NZ $ million, fob)

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Table 1: Some factors that should be considered during modelling of packaged food shelf life Deteriorative effect on foods

Type of packaging protection/ function

Oxygen

Lipid oxidation, Vitamin destruction, Protein loss, Pigment oxidation

Oxygen barrier

Moisture

Nutritional quality loss, Organoleptic changes, Browning reactions, Lipid oxidation

Moisture barrier

Light

Oxidation, Rancidity, Protein and amino acid changes, Vitamin destruction, Pigment changes

Light barrier

Microorganisms/ Macroorganisms

Food spoilage, Nutritional and quality loss, Potential health hazard

Hermetic containment

Mechanical abuse (drop, compression, vibration, abrasion and rough handling)

Organoleptic changes, Spoilage and other quality changes due to failure of seals, pinhole formation, etc.

Material and sealing properties

Odorous substances Toxic chemicals

Off-flavour formation, Taste deterioration, Chemical changes, Toxic hazards

Barrier properties Chemical resistance

Tampering

Product loss, Quality changes, Potential health hazard

Tamper proof/evident/resistant

Consumer handling, Abuse, Misuse

Product loss, Quality changes, Nutritional changes, Organoleptic changes

Mechanical properties, Clear information (labelling)

The approach of model-based design of packaging and distribution systems has been widely used in the New Zealand horticultural export industry. It is clear that to gain significant improvements in product quality in the marketplace, design of these systems must integrate produce quality models, packaging design and cold-chain systems. Through the use of modelling and extending it into developing areas such as active packaging and nanotechnology, future improvements of quality and potential export of other horticultural products is possible. This type of mathematical modelling can be extended to packaged food, but the range of factors (see Table 1) that have to be taken into account can be greater depending on the type of food and packaging system used.

In summary Mathematical modelling of packaged food and produce shelf life is used to predict produce shelf life, but often obtaining the required information and data can be complex. It is also recommended that once a product is on the market that full shelf life trials should still be conducted. For further information contact T.R.Robertson@massey.ac.nz

References Bronlund, J., & Robertson T.R. (2006). Modelling of heat transfer through corrugated cardboard packaging. Proceedings of the International Institute of Refrigeration (IIR) Institute of Refrigeration, Heating and Air Conditioning Engineers of New Zealand (IRHACE) International Conference. Cleland, D.J., & Cleland, A.C. (1989). Appropriate level of model complexity in dynamic simulation of refrigeration systems. Refrigeration Science and Technology, 1, 261-268.

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East A.R., Araya X.I.T., Hertog M.L.A.T.M., Nicholson, S.E., & Mawson, A.J. (2009). The effect of controlled atmospheres on respiration and rate of quality change in 'Unique' feijoa fruit. Postharvest Biology and Technology, 53(1-2), 66-71. Hertog M.L.A.T.M., & Nicholson S.E. (2003). Modelling product quality in MA systems: the missing link. Acta Horticulturae, 600, 639-646. Hertog M.L.A.T.M., Nicholson S.E., & Jeffery P.B. (2004). The effect of modified atmospheres on the rate of firmness change of 'Hayward' kiwifruit. Postharvest Biology and Technology, 31(3), 251-261. Gnanasekharan, V., & Floros, J.D. (1993). Shelf life Prediction of Packaged Foods from Charalambous, G. (Ed), Shelf Life Studies of Foods and Beverages. Elsevier Sc. Publishers, BV. Johnston J.W., Hewett E.W., & Hertog M.L.A.T.M. (2005). Apple (Malus domestica) softening in the postharvest coolchain: effects of delayed cooling and shelf life temperatures. New Zealand Journal of Crop and Horticultural Science, 33(3), 283-292. Johnston J.W., Hewett E.W., & Hertog M.L.A.T.M. (2006). Characterisation of 'Royal Gala' and 'Cox's Orange Pippin' apple (Malus domestica) softening during controlled atmosphere storage. New Zealand Journal of Crop and Horticultural Science, 34(1), 73-83. Tanner, D.J., Cleland, A.C., Opara, L.U., & Robertson T.R. (2002a). A generalised mathematical modelling methodology for design of horticultural food packaging exposed to refrigerated conditions : part 1, formulation. International Journal of Refrigeration, 25(1) 33-42. Tanner, D.J., Cleland, A.C., & Robertson T.R. (2002b). A generalised mathematical modelling methodology for design of horticultural food packaging exposed to refrigerated conditions : Part 3, mass transfer modelling and testing. International Journal of Refrigeration, 25(1): 54-65. Utto, W., Mawson A.J., & Bronlund J.E. (2008). Hexanal reduces infection of tomatoes by Botrytis cinerea whilst maintaining quality. Postharvest Biology and Technology, 47(3), 434-437. Zou Q., Opara L.U., & McKibbin R. (2006a). A CFD modeling system for airflow and heat transfer in ventilated packaging for fresh foods: I. Initial analysis and development of mathematical models. Journal of Food Engineering, 77(4), 1037-1047. Zou Q., Opara L.U., & McKibbin, R. (2006b). A CFD modeling system for airflow and heat transfer in ventilated packaging for fresh foods: II. Computational solution, software development, and model testing. Journal of Food Engineering, 77(4), 1048-1058.

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optimising solar energy collection Collection of solar radiation can be optimised by better understanding the impact of local cloud formations and applications of the model SolarView include students identifying the best tilt angle for their school’s solar panels, as Ben Liley, NIWA Lauder, explains: Solar energy over NZ The global need to replace dependence on fossil fuels with renewable energy sources has prompted an increased focus on understanding climate and modelling. Within NIWA research and consultancy, measurements and models of climate help to predict both energy demand – especially for heating or cooling – and the energy available from most renewable sources. Climate variability and change affects the energy supply of hydroelectricity, wind power, wave and tidal systems, biofuel production, and solar hot water, photoelectricity, and passive heating and lighting. Solar energy is the most widely available and plentiful renewable energy source. About 15 times New Zealand’s total annual energy consumption falls as sunlight on just the roof area of all of our buildings over the same period, but there are two main difficulties in using this resource. The first is that solar radiation varies widely; being absent at night and low in winter when demand is greatest, so some form of storage is required. Solar hot water systems meet this need directly, storing daytime heat as hot water, but it is still necessary to manage the solar heating and electrical backup to match demand. Modern systems are controlled to avoid, for example, having a cylinder full of hot water from electrical heating just as the sun strikes the solar collector. Storage of photoelectricity requires batteries, or reverse metering to put it into the electricity grid as widely implemented in Germany. One promising idea would integrate household photovoltaic generation with a move to electric cars, so that the car batteries would be part of the storage system. The other main issue concerns the relative intensity of solar energy. Direct sunlight is more than sufficient for passive solar heating and lighting of homes and buildings; indeed it is much more intense than most artificial sources. For electrical generation or transport, however, the intensity of solar energy, and indeed most renewable resources, is very low compared to the concentrated chemical energy of fossil fuels. The effect is that systems to capture and convert or store solar energy have significant cost, and it can take some time for solar systems to recover their cost relative to mains electricity. This problem is reduced by optimising the location and orientation of a solar system, and sizing it to match demand. For both of these issues, reliable information about solar energy is required. The situation for clear skies is fairly simple, as illustrated in Figure 1 with output from a radiative transfer model.

Model: Clear skies A horizontal solar panel in Northland would collect over 8.5 GJ m-2 in a hypothetical year of clear skies, whereas the same panel in Invercargill would collect only 7.0 GJ m-2 in a (more improbable) year of clear skies there. The main 20

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point of interest is that tilting the panel toward the north by the latitude angle somewhat reduces the range, and raises the Invercargill yield above the Northland horizontal value. Mounting the panel to track the sun increases the yield again, but tracking systems add greatly to the cost, and are generally only used for large concentrating systems. Importantly, these figures are applicable only to clear skies, and the true picture for the Land of the Long White Cloud is very different. Using satellite data, NIWA has derived statistics on the frequency of different cloud types and clear sky conditions for the New Zealand region, as illustrated in Figure 2 for clear sky frequency.

Correcting for cloud The other source of solar radiation data for New Zealand is the NIWA Climate Database, with hourly measurements at over 100 sites around the country. The cloud frequency has been used to interpolate between these data to map the average solar energy anywhere in New Zealand. The correction for global irradiance – the energy flux onto a horizontal surface – does not apply equally to the radiation on a tilted panel, except in the case of uniform cloud or fog. For the most common situation of scattered or broken cloud, the measured radiation is some mixture of the diffuse and direct components. This can be illustrated with data from the NIWA site at Lauder in Central Otago, where a solar tracking instrument that is part of the international Baseline Surface Radiation Network (BSRN) measures the separate components of direct (R) and diffuse (F) radiation that make up the global (G) radiation on a horizontal surface. Because R is measured with a detector perpendicular to the solar beam, whereas G and F (shaded from direct sun) are measured on a horizontal plane, they are related by the formula , G = F + R cos  where  is the angle to the sun from the zenith point of the sky. Figure 3 illustrates most of the features of solar radiation that are important for this discussion. The day shown starts clear, with the measured components R (red line) and F (blue line), and their combination G (green line), closely approximating the model clear sky values (Gc, Fc, Rc, dotted lines). Very little radiation comes from the sky on a clear day; for high sun in typically clean, deep blue skies over New Zealand, only about 6% of the global radiation is in the diffuse component. As the sun climbs in the sky, R rises steeply so that there is little difference in the direct intensity of sunlight over most of the day. Values of R above 120 W m-2 are classified as bright sunshine by the instruments that measure sunshine hours. As cloud appears, soon after 11:00 in the plot, the sky becomes brighter, so that when the sun is out the global irradiance is even greater than it would be for clear sky. When the sun is obscured by cloud, R is sharply reduced, and in the plot it drops to near zero between 13:15 and 17:15. Then all of the radiation is diffuse, so G = F. An alternative view of the Lauder BSRN data is shown in Figure 4, where the abscissa shows G as a fraction of its clear sky model value Gc for each minute over 12 years. This fraction is sometimes called the clear sky clearness index. The ordinate shows the separate components, also expressed


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EnergyScape project to quantify New Zealand’s recoverable energy resources. The results are shown in Figure 5, where the first two panel configurations are as considered previously for clear sky radiation. The third differs in that it considers only the direct component, as would be available to a solar concentrating system like those constructed or proposed for desert areas in the US, Australia, and North Africa. Figure 5 shows again that tilting the panel to latitude angle more than makes up for the reduction in G at more southern latitudes, but any benefit of solar tracking is lost in all but the sunniest areas. Whereas flat panels like solar water heaters or photovoltaic arrays still collect useful energy when the sun is obscured by cloud, solar concentrating systems capture almost nothing at these times.

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as fractions of Gc. The yellow and light blue contours of data frequency show that almost all individual measurements can be classified by whether the sun is obscured (R = 0, G = F) or not (R = Rc, F  Fc). Most importantly, the dark blue and dark red percentiles of the data for given G/Gc suggest that this quantity can be used to predict the other two with reasonable accuracy by a suitable function that approximates the curves of the 50th percentiles. Separate measurements of G, F, and R are only available at four sites in New Zealand (Kaitaia, Paraparaumu, Invercargill, and Lauder) from the Climate Database but, by using the first fraction to predict the other two, they can be estimated for the 100+ sites that measure G. These calculations, interpolated between climate stations with the satellite data, were undertaken by NIWA for the

Figure 3: Measured and modelled global, diffuse and direct radiation at Lauder, Central Otago.

Figure 1: Annual total energy in gigajoules per square metre (GJ m-2) under clear skies for different panel orientations.

Figure 4: Measured diffuse (F) and downward direct (Rcos) radiation versus global radiation (G), with all quantities expressed as fractions of the model clear sky global irradiance Gc for that minute. Yellow and light blue lines are contours of data frequency. Dark red and blue lines are percentiles of the two ordinates for intervals of the abscissa. Horizontal

Figure 2: Average annual frequency of clear skies derived from AVHRR satellite data retrievals.

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Figure 5: Annual average solar power in watts per square metre (W m-2 = J m-2 s-1) available to horizontal or latitudetilted collectors, or to a solar concentrating system that tracks the sun. New Zealand Association of Science Educators

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Figure 6: Average solar energy available in Featherston to a panel tilted 41° from horizontal toward the north. The orography of the Tararua Range is from a 100m digital elevation model. Solar positions are shown for each hour on five representative days.

SolarView: Personalised solar data Maps like those above, and the other work within the EnergyScape project, help to plan New Zealand’s efficient use of energy resources by showing where major developments might be best located. They are not as helpful for individuals considering solar systems, nor to engineers planning solar installations, or architects designing energy-efficient buildings. These purposes are addressed better by NIWA’s SolarView tool (see: http:// solarview.niwa.co.nz) Instead of looking down from above, SolarView shows a model of the view outward from a given location, with solar positions at representative times of year, as illustrated in Figure 6 for Featherston. Users of the system type their street address into an interface to Google Maps, and can optionally check their exact location from its satellite view. This link provides the exact latitude and longitude shown on the left above the plot. Using this location, translated to NZTM map co-ordinates, Solarview shows the landscape from a digital elevation model (DEM) of New Zealand on a 100m grid. To provide the wide-angle view shown here, the local region is interpolated onto a radial grid, and elevation angles are corrected for perspective and Earth’s curvature. The DEM provides a good approximation to the physical landscape for topography more than a few hundred metres distant, with the idea that this landscape can be used to orient the picture and sketch in local obstructions such as trees or neighbouring buildings. Overlaid on the landscape view are the solar track for the summer and winter solstices, autumn equinox, and two shoulder months in spring. The sun’s position is shown every minute, and labelled below the curves, on the hour, in New Zealand Standard Time. Shown above the curves is the result of the solar energy calculations described above. Hourly data from the nearest climate stations with at least 10 years of data, taken from the NIWA Climate Database, are processed to derive the diffuse and direct components for each hour of the record. The direct radiation onto the panel is weighted by the 22

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cosine of the angle between panel normal and the sun’s mean position for that hour, and the diffuse component is estimated from the fraction of sky ‘seen’ by the panel plus a component for light scattered from the ground. These hourly estimates are averaged over the years, and for 15 days either side of the given date, to give the figures shown. Here the panel is tilted 41° from horizontal, toward the north (bearing = 0°). The user can specify any angles, to allow for a roof that faces north-west or an easterly wall, for example, but the view is unchanged as it is determined by the need to plot the solar position. Incident energy is expressed as a cumulative value over the day to make it easier to see how much is lost to local obstructions. If you live in Featherston and the sun doesn’t clear your neighbour’s house until 09:00 in August then you will lose about 0.22 kW-hr m-2 from the 3.18 kW-hr m-2 available that day before the sun drops behind the Tararuas. SolarView provides site-specific solar energy information. Further developments will make the calculated figures available in tabular form for use in system design spreadsheets or other software, probably by subscription to commercial users, but the basic product is served free on NIWA’s Web pages. Many schools are participating in Genesis Energy’s Schoolgen programme, which provides schools across New Zealand the opportunity to generate their own electricity and can also show a log of the amount generated. Because of the delay in accumulating climate data and completing the required quality checks, SolarView does not currently run in this ‘real-time’ fashion, but it could be adapted to provide comparable data as a focus for statistical study. I encourage users to think of how they can apply the solar energy information in SolarView. For example, it is interesting to explore the effect of changing the bearing angle; in many places around the country the afternoons are clear more often than the mornings, so the optimal bearing is to the north-west. Tilt angle has a big effect on the available energy by season, with steeper tilt favourable in the winter months. For further information contact: b.liley@niwa.co.nz


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forecasting the weather It has been said that if we can fly a man to the Moon, why can’t we forecast tomorrow’s weather correctly? While this question is showing its age, the response is probably still correct…because it is a harder problem! While listening to a public weather forecast that predicts showers over some region and gale force winds over another, it is probably difficult to conceive of the scientific, mathematical and computational resources that lie behind such predictions. Nonetheless, forecasting the weather is a ‘grand challenge’ problem, one of a class of problems that present a fundamental challenge to science, and which require the application of the largest computational (i.e. supercomputer) resources available. The goal of weather prediction is to predict the future state of the atmosphere given observations of its current state and a set of numerical approximations to a closed set of equations that govern atmospheric motion – and to do this at increasingly smaller spatial and temporal scales. Four key components are required to accurately and reliably forecast the weather: a model that is able to simulate all relevant atmospheric processes (called a numerical weather prediction (NWP) model); measurements from observing systems that are able to characterise the state of the atmosphere with time; a method to incorporate these measurements into the NWP model (called data assimilation); and a computer with sufficient power to process the observations, assimilate those that are valid, and to then integrate the NWP model forward in time quickly enough that the results are available before the future events actually occur. Other attendant issues include the removal of local biases in the forecasts, meaningful dissemination of the forecasts, and verification of forecast system accuracy. Each of these four components is described in more detail below.

Numerical weather prediction model The underlying principal that makes it possible to predict the future state of the atmosphere is that it can be approximated as a fluid, and that its circulation is subject to the same physical laws as fluid motion. To fully describe the time-evolving nature of the atmosphere, all that is needed are numerical approximations that describe and obey the principals of: 1) conservation of momentum; 2) conservation of energy; 3) conservation of mass, and 4) conservation of water (in all its phases) – 6 equations in all. To deal with the principal of conservation of momentum, a set of equations that describe fluid motion is needed. The most all-inclusive set of equations that do so is the Navier-Stokes equations, which are essentially a re-telling of Newton’s Second Law, ‘mass times acceleration equals the sum of forces’, with density replacing mass and the equations being written per unit volume. On large spatial scales, such as those on which we would typically be interested in creating a weather forecast for, the effects of Earth’s rotation, via the Coriolis force, becomes important and must be included also. Finally, the equations are solved for motion on a sphere in the horizontal and vertical directions. Likewise, the principal of conservation of energy

becomes a re-telling of the first law of thermodynamics: ‘the internal energy of a system is equal to the heat it receives minus the mechanical work it performs on its surroundings’. The remaining equations that are used to close the system are the Continuity Equation and the Equation of State, which can be derived from the Ideal Gas Law. In reality, the process of developing a numerical model is far more complicated than just numerically integrating a set of equations forward in time. The spatial and temporal scales on which we wish to generate a weather forecast can lead to assumptions that alter the precise form of the momentum equations (which can mean solving either the Euler, Boussinesq or Shallow Water Equations), while the numerical methods and the horizontal and vertical grid design must ensure suitably accurate and stable results. Figure 1 shows how, for a given area, the horizontal and vertical model grid can be visualised. Two other important aspects of NWP model formulation also need to be considered: the impact of the lower boundary (the surface), and the parametrization of unresolved processes. Surface friction has large and direct impacts on near-surface winds. This effect is demonstrated in the 10 m wind forecast valid at midnight on the evening of the 27th April 2011 during the post-Easter severe weather event that impacted much of the North Island (Figure 2). The figure shows the impact of surface friction on the wind field as the southeasterly flow crosses the coast (e.g. in the Hawke’s Bay region). Winds are much stronger over the smooth ocean surface than over a topographically complex vegetated surface. To account for this effect, and more subtle indirect effects, the NWP model is coupled to a land surface model (LSM), that accounts for the effects of different surface types (sea, grass, shrubs, trees, ice, etc.) and soil properties. Additionally, the LSM is used to simulate the movement of water in the top few metres of soil as well as surface runoff and soil temperatures. The LSM is critical to improving the accuracy of forecasts of surface temperatures, winds and soil moisture. Figure 2 also shows the impact of local topography on near surface wind fields with a pronounced speedup in winds downstream from the Cook Strait region due to funnelling in the presence of the mountainous topography on both sides of the Strait.

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Modelling, data collection and management, and computing are the foundations to improving our ability to accurately forecast the weather as Michael Uddstrom, Stuart Moore, Phil Andrews and Trevor Carey-Smith, NIWA, Wellington explain:

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Figure 1: An example NWP model domain showing how it is divided into a horizontal (x,y) grid, vertical layers (z) – which near the surface are terrain following, but become smoother with height. Courtesy of the UCAR COMET Program. New Zealand Association of Science Educators

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12km, where convective parametrization is required, the maximum rainfall accumulation was 274mm, but with a 1km resolution grid, where convective parametrization is turned off and convective processes are modelled explicitly, the maximum rainfall accumulation was 499mm – close to the 545mm observed.

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Figure 2: NZLAM forecast of 10 m wind speed (colour & length of arrows) and direction, and mean sea level pressure (isobars) valid at midnight on 27th April 2011. Atmospheric processes occur over a range of horizontal and vertical scales – from the interactions of cloud condensation nuclei (CCN) in clouds at the microscale to large-scale weather systems covering hundreds of kilometres. No one NWP model can currently be run at a grid resolution that covers all of these scales at the same time. This means that the effects of unresolved (by the model) physical processes must be accounted for using a more statistical approach – called parametrization. That is, the physical effects of an atmospheric process are represented by a statistical model that describes the observations of that process. One case in point is convection. Responsible in part for the formation of clouds and therefore precipitation, convection is notoriously difficult to model directly at horizontal resolutions greater than 2km since many of the processes that make up the convective nature of the atmosphere occur at this or finer scales. Thus, in mesoscale models whose resolution is typically 12km or more, convection must be parametrized. At finer resolutions however, convection can be modelled directly, this often leads to much improved forecasts, particularly of severe rainfall events. Figure 3 shows the impact on accumulated rainfall over a 24-hour period in January 2004. At a grid resolution of

At NIWA, weather forecasts (and, with minor model configuration changes, climate change scenario simulations) are generated with the New Zealand Limited Area Model (NZLAM), a local implementation of the UK Met Office Unified Model (MetUM), one of the world’s leading NWP models. The MetUM is set apart from other NWP models by its original design ethos of having just one model capable of being used to produce forecasts for a wide variety of spatial and temporal scales; from global models used for climate simulations spanning centuries, to localised high resolution forecasts covering just a few hours. A good overview of the MetUM can be read at: http:// www.metoffice.gov.uk/research/modelling-systems/ unified-model while a complete description of the underlying mathematical assumptions and formulations used in the MetUM is available in Staniforth et al. (2004). The horizontal grid size of NZLAM is 324 ¥ 324 in the east-west (x) and north-south (y) directions with a grid spacing of 12km, and there are 70 levels in the vertical (z direction), with 5 levels concentrated in the lowest 100m. The model top is set at approximately 80km, which may seem very high (it is way above ‘the weather’) but it is essential if one is to make proper use of critically important satellite observations of radiance emitted to space. There are a further 4 sub-surface levels in the LSM. The area covered by the NZLAM domain is indicated in Figure 4, and it has purposefully been made this large to ensure that under normal conditions, the forecast weather over the New Zealand land mass has remained within the NZLAM domain throughout the period for which forecasts are made – 48 hours. A new cloud resolving model called NZCONV (for New Zealand CONVective scale model) is also under development. NZCONV will have 1.5km resolution and a 1222 ¥ 1370 ¥ 70 (level) grid – of which 9 of the vertical levels lie in the first 100m above the surface. This model is expected to resolve all key features of the New Zealand landscape and to provide even more accurate weather forecasts.

Observing networks The World Meteorological Organisation (WMO) operates the Global Observing System, a co-ordinated system of methods and facilities for making meteorological and

Figure 3: Contour maps of the 24-h modelled total accumulated rainfall (mm) for 8 January 2004. (a) The 12-km model, (b) the 4-km model, (c) the 2-km model, and (d) the 1-km model. The legend show rainfall accumulation in mm. Courtesy of Webster et al. 2008.

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Data assimilation

NZLAM has more than 44 million variables (i.e. 324 ¥ 324 ¥ 70 ¥ 6), and for NZCONV the number is greater than 700 million. To produce a useful forecast, a NWP model must be started from a set of initial conditions that specify the values of all of the state variables at all grid points. In a perfect world the 6 state variables would be able to be observed simultaneously and the results of these measurements provided to the NWP model, which could then be integrated on a supercomputer, and tomorrow’s (as well as today’s) forecasts generated. Of course, this is not possible; instead the initial conditions must be estimated from measurements derived from sparse surface and aircraft based observing networks and from much denser, but non-independent satellite measurements of black body radiation emitted at microwave and infrared wavelengths, and of cloud motions derived from time lapse satellite infrared and visible imagery. Despite the large

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Figure 4: A Geostationary Meteorological Satellite (GMS) visible image of a cut off low mapped onto the New Zealand Limited Area Model (NZLAM) domain. numbers of observations made by satellites, the number of degrees of freedom in a modern NWP model is far larger – and so the problem is indeterminate. The Data Assimilation system overcomes this difficulty by periodically combining a forecast (known as the background) which propagates information from observations at earlier times, with the latest observations. At NIWA we use a variational approach based on Bayes’ theorem to assimilate data (Lorenc, 1986). Essentially it estimates the initial conditions (also known as the ‘analysis’) for a model integration by performing a least squares fit between the observations and the background by directly minimising a cost function J(x) as shown in equation (1): 1 (1) J(x) = (x – xb)B–1(x – xb)T + 1 (Hx – yo)O–1 (Hx – yo)T 2 2

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other environmental observations on a global scale, in near real time. It is this system that provides the observations needed to initialise an NWP model (see next section), and it is comprised of operationally reliable surface, aircraft, and space-based subsystems (Figure 5). New Zealand’s location means that it has relatively poor coverage from surface (and aircraft) based observing systems, but excellent coverage from satellite systems, made even more useful as a result of our marine location. Figure 6 shows the same scene as Figure 4 when viewed at 6.5µm (infrared) near the centre of a water vapour absorption feature that reveals the distribution of water vapour in the upper troposphere, and at 3.3mm (89GHz) in the microwave region, which shows the water vapour distribution near the surface. Satellite instruments like the Advanced Microwave Sounding Unit (AMSU) and IASI (Infrared Atmospheric Sounding Interferometer) provide thousands of radiometric observations from the surface to the top of the atmosphere at intervals of 15km, for 2000km wide swaths below the satellite.

Figure 5: Components of the Global Observing System operated under the auspices of the World Meteorological Organisation (WMO). Courtesy of the WMO. New Zealand Association of Science Educators

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Figure 6: NOAA Advanced TIROS Operational Vertical Sounder (ATOVS) data for: a) the High-resolution InfraRed Sounder (HIRS) channel 12 (6.2µm) and b) the Advanced Microwave Sounding Unit (AMSU), channel 20. The surface resolution of each instrument is approximately 15km, and the instruments scan ‘across track’ as the satellite moves in its polar orbit. The grey bands indicate missing data. Where x is the analysis (i.e. ‘initial conditions’) to be determined; xb the background model state (usually a 6 h forecast); B the error covariance matrix of the background; yO the observed values; H are the observation operators used to determine the model estimates, y = Hx of the observed values; and O is the observation error covariance matrix, including both instrumental and representivity errors: the latter of which accounts for the uncertainty introduced by differences between the scale on which the observations are made and the scale the model value represents. There are two main types of variational analysis, both described by equation (1). In the first, simpler method, known as 3D-Var, the time dimension is largely ignored: and the observations within a time interval centred on the time of the background are used to calculate the analysis at that time. In the second method, known as 4D-Var, a forecast model (or rather a tangent linear or perturbation forecast model) is included in the observation operators H, with the result that 4D-Var is, unlike 3D-Var, able to extract information from the temporal distribution of the observations. A small fraction of all observations contain gross errors. These could be seriously detrimental to the analysis and subsequent forecasts, so quality control checks are made on the observations prior to their use. Track checks are applied to aircraft and ship observations to ensure that the position reported for the latest observation is consistent with earlier reports from the same source. A probability of gross error is determined for each observation via comparison with the model background and ‘buddy checks’ with nearby similar observations. Systematic errors, such as incorrectly reported altitudes for surface observation stations or the large biases effecting many satellite observations are detected and statistically corrected. To avoid the risk of correlated observation errors, many observation types are ‘thinned’. That is, a high quality subset with appropriate spatial and temporal separations to avoid this problem is selected from all the data available for each effected observation type.

Supercomputer It is perhaps clear now, why a supercomputer is needed to carry out the calculations required to forecast the weather. A vast number of computations and a vast amount of

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memory are needed to both estimate the initial conditions for each forecast cycle and to integrate the NWP model forward in time. NIWA has recently installed a large IBM p575/p6 supercomputer, called FitzRoy, to provide the resources needed to integrate such complex models. This system (http://www.niwa.co.nz/our-services/hpcf ) has 1,792 4.7GHz POWER 6 processors made up of 56 32 processor nodes, connected such that all of the nodes can communicate with each other at up to 16GB/s each way. Since the MetUM, data assimilation and observation quality control computer codes have all been parallelised, they can spread the numerical problems across multiple processors, and in this way make use of the processing power provided by FitzRoy. The result is that a 48-hour NZLAM forecast completes in just 10 minutes elapsed time on 256 processors (or 8 nodes). NZCONV completes a 24-hour forecast in 60 minutes on 1024 processors (or 32 nodes). To put the NZLAM forecast model into perspective, if one had the fastest home PC available, and it was possible to attach in excess of 128GB of memory to it, then it would take around 4 days to complete a 2-day forecast! For NZCONV, it would require in excess of 50 days computing time to complete a 2-day forecast!

Statistical downscaling – model output statistics An important part of any weather prediction system is the ability to provide and evaluate site specific forecasts of surface meteorological variables. To achieve this, statistical post processing methods are often used to ‘downscale’ the NWP output to forecast variables at particular locations. This is particularly important in regions where the topography is not adequately resolved by the NWP model, such as in New Zealand’s mountainous regions. The basic idea behind statistical downscaling is to develop a relationship between historical observations (at a point) and NWP forecasts (valid at a larger scale). At its simplest, this may amount to finding the mean difference between the historical forecasts and observations and subtracting this bias from the current forecast. More sophisticated approaches generally use some form of (non-)linear regression.


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Figure 7: For the complex Queenstown site, the upper panel shows the raw NZLAM wind speed and direction (top row), MOS corrected wind speed and direction (centre row), and observed wind speed and direction (bottom row); the wind blows in the direction indicated by the shaft, toward the head, and a ‘full’ barb is 10km/h, and a half barb, 5km/h. The lower panel shows raw NZLAM forecasts of temperature (red, solid) and relative humidity (solid, blue). The dashed lines are the MOS corrected values, and the dotted lines the observed values. At NIWA we have developed a Model Output Statistics (MOS) site-specific forecast correction system which allows for correction of surface temperature, mean sea level pressure, relative humidity and surface wind speed and direction (Glahn and Lowry, 1972). This involves building a multiple linear regression model with coefficients Bi, that relate observed values, y, to a set of archived NWP output fields, xi, y = b0 + b1x1 + b2x2 + ... + e (2) where e is the error term. The regression model can then be applied to the current NZLAM forecast and will remove any systematic biases. Using multiple linear regression allows for corrections to depend on a variety of meteorological fields; for example, the bias adjustment to a surface temperature forecast may depend on the wind direction and speed (as well as the forecast surface temperture!). For each field, location and forecast range, regression coefficients are calculated from the previous 16 weeks of observations and NWP forecasts. In other words, each hourly forecast for a particular site has a regression model specific to that location and time of day. The rolling 16-week learning period is long enough to provide enough data to ensure stable regression equations while minimising the effect of seasonal variations and incremental changes to the NWP model. The actual NZLAM predictors to be used are chosen from a set of NWP fields using a stepwise regression technique, favouring fields that are well correlated with observations (Sokol, 2003). Figure 7 demonstrates how MOS can be applied in complex terrain. In this case for Queenstown airport, the coarse horizontal resolution of NZLAM means the ‘surface’ of the model is close to 300m above the physical ground level, leading to ‘raw’ forecast temperatures that are colder than the verifying data, and wind fields that cannot resolve the diurnally driven valley flows in the region. Using MOS downscaling, the temperature and relative humidity biases are removed, and the wind fields corrected, both in terms of

wind speed and direction (as can be seen from the verifying observations).

Summary While weather forecasts may often be used to determine whether to put the washing out or not, or what to wear tomorrow, there is a much more serious side to their use. The weather is responsible for many of the hazards we face, from fog closing airports and interrupting travel, high winds and heavy snow to river flooding and inundation, and to coastal erosion and dangers to vessels at sea. All are ‘driven’ by the weather, so…being able to predict their occurrence and intensity is an important goal for science. Even when the weather is not having hazardous impacts, it is still important, since it is key for our agricultural and horticultural enterprises, and provides the fuel for our hydro and wind turbine renewable energy resources, as well as shaping much of the temporal variability in the demand for electricity, be it for heating, or cooling. To this end, modelling, data collection and management and computing are the foundations to improving our ability to accurately forecast the weather in the future, and all of the impacts resulting there from. For further information contact: m.uddstrom@niwa.co.nz

References Glahn, H.R. & Lowry, D.A. (1972). The use of model output statistics (MOS) in objective weather forecasting. J. Appl. Meteor, 11, 1203-1211. Lorenc, A.C. (1986). Analysis methods for numerical weather prediction. Quarterly Journal of the Royal Meteorological Society, 120, 1177-1194. Lorenc, A.C., Ballard, S.P., Bell, R.S, Ingleby, N.B., Andrews, P.L., Barker, D.M., Bray,J.R., Clayton, A.M., Dalby, T., Li, D., Payne, T.J.F., & Saunders, F.W. (2000). The Met. Office Global 3-Dimensional Variational Data Assimilation Scheme. Quarterly Journal of the Royal Meteorological Society, 125. Sokol, Z. (2003). MOS-based precipitation forecasts for river basins. Weather and Forecasting, 18(5), 769-781 Staniforth, A., et al.,(April 2004). Joy of U.M. 6.0. Model Formulation”. Unified Model Documentation Paper No. 15, Version 6.0. Webster, S., Uddstrom, M., Oliver, H. & Vosper, S. (2008). A High Resolution Modeling Case study of a severe weather event over New Zealand, Atmospheric Science Letters, 9, 119-128 (http://www3.interscience.wiley.com/ cgi-bin/fulltext/118677446/PDFSTART).

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problem-based learning in science Science programmes in a number of schools across the Waikato, Coromandel and Bay of Plenty have been radically restructured using a problem-based, co-operative approach to learning and assessment as Paul Lowe and Simon Taylor (pioneers of the initiatives) and Cathy Buntting, the University of Waikato, explain:

Dr Paul Lowe (right) after receiving the inaugural Prime Minister’s Science Teacher Prize in 2009 from Prime Minister John Key, (centre), and Simon Taylor.

Introduction Problem-based learning (PBL) integrates the development of content knowledge and critical thinking skills by having: “…students develop rich understandings of science concepts within the context of a contextualized real-world situation guided by a driving question,” (Rivet & Krajcik, 2008, p.80). Students work in groups with a teacher facilitating and helping to: “…guide the learning process through open-ended questioning designed to get students to make their thinking visible and to keep all the students involved in the group process,” (Hmelo-Silver, 2004, p.239). PBL requires not only a change in teachers’ content knowledge, but also a reconceptualisation of what it means to teach and learn (Park Rogers, Cross, Sommerfeld Gresalfi, Trauth-Nare & Buck, 2010). A range of PBL models exists, with varying levels of teacher input in framing the research question and providing the initial information about ‘the problem’. This article describes two initiatives (PROBLIT and PLUTO) highlighting key considerations in setting up problem-based learning programmes that include co-operative approaches to learning and assessment. These examples are significant in the New Zealand context in both their scope – now formally including 18 schools – and the student cohorts that are involved – gifted and talented Year 10 students in the case of PROBLIT, and mixed-ability Years 9, 10, and NCEA Level 1 classes in PLUTO.

1. PROBLIT (PROblem-Based Learning In Teams) In 2006 PROBLIT was introduced to schools within the CoroNet cluster by Paul Lowe, HOD of science at Morrinsville College. The aim was to develop a science programme for top Year 10 students that used authentic, relevant contexts to create powerful learning experiences. Paul was funded by an e-Learning Teacher Fellowship (Ministry of Education) and the project was funded by GATE. 28

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Three top Year 10 students from each of the seven CoroNet schools were selected to participate in the programme. As the participating schools were geographically disparate, communication between Paul and the student teams relied predominantly on emails and video conferencing, with the GATE co-ordinator at each school providing general support. Seven problems formed the basis of the year’s programme, and were based on each school’s Year 10 scheme of work (an eighth problem was added subsequently). Each problem had a student relevant ‘focus question’ with the potential to offer powerful learning experiences. They were: 1. Describe how the following features of the human body work together and change with training to allow for optimum possible performance: the cardiovascular system; respiration (including lungs, blood and the respiration equation); digestion and nutrition (including basic food tests); and muscles, joints and connective tissue. 2. How do glider pilots use the principles of the conservation of energy to enjoy long extended flights? 3. How can cave environments be effectively managed to ensure they remain available to future New Zealanders? 4. The protection of New Zealand’s many unique species is very important for the world’s biodiversity. Why is this, and how are we doing? 5. Is surrogate motherhood good for mankind? 6. How prepared are we for a tsunami? 7. Could we live in an energy independent house in New Zealand? 8. A group of students are going on a ski trip to Mount Ruapehu, which has been placed on Alert Level 1 for some time. What do the students need to know to prepare for this trip, and is there any risk to them? Weekend camps, associated with the first four of these problems, were held at Auckland University of Technology (a key player in sporting research), Piako Gliding Club, Waitomo Caves and Goat Island Marine Reserve north of Auckland. Project briefs for each topic included: the focus question, references for relevant resources, and a list of ‘key ideas’, or student learning objectives. For example, the unit on human potential coincided with the 2006 Commonwealth Games and students watched the television programme ‘Human potential’. School teams then created and presented a PowerPoint presentation outlining how the basic body systems operate. After the camp – which included presentations from a range of relevant experts and interactive demonstrations of equipment used to test fitness and strength – the students presented a response to the focus question about optimal performance highlighting what they had learned. 1.1. Assessment Whilst the knowledge the students developed was still closely aligned with traditional curriculum objectives and ‘knowing that’, it was also anchored to their actual experiences and embedded within a context relevant to them. The ability of students to transfer this knowledge to new contexts was not examined; however, emphasis was placed on integration of ideas, with judgements guided by the Structure of the Observed Learning Outcome (SOLO) taxonomy (Biggs & Collis, 1982). This empirically-derived taxonomy describes five levels of increasing complexity (see Table 1). For example, in the ‘human potential’ project (as above), students were expected to synthesise information


Table 1: SOLO taxonomy (Biggs & Collis, 1982) SOLO level

Descriptor

1. Prestructural

No evidence of anything learned, student may repeat the question or convey some irrelevancy.

2. Unistructural

The student shows at least one element of knowledge but does not apply or transfer this easily.

3. Multi-structural

Several relevant elements are present but these aspects are not interrelated and inconsistency results.

4. Relational

The relevant elements are integrated into a generalised structure; there is evidence of induction.

5. Extended-abstract

The structure of elements is related to other relevant domains of knowledge; answers are not bounded by the question allowing the student to suggest alternative outcomes.

1.2 PROBLIT vs. curriculum ‘coverage’ The problems forming the basis of the year’s work were deliberately aligned with participating schools’ schemes of work to enable students to participate in the school’s traditional testing activities. However, some tensions between the two approaches inevitably arose. For example, several parents expressed concern that the key competencies emphasised by PROBLIT, whilst inherently valuable, were not directly related to achieving well in traditional forms of assessment such as NCEA, recognised as the official gateway to future opportunities. This is perhaps particularly pertinent when our current assessment framework is not yet fully aligned with the intentions of the revised New Zealand Curriculum to foster skills and competencies desirable for the 21st century. As one parent put it: “Now I know that there is more to education than passing exams but exams are hurdles that need to be overcome. Most of the kids that I know on the program were borrowing books and notes from the rest of their class to catch up with the curriculum program”. Parental expectations can therefore form a significant barrier to substantive teacher change. Whilst some parents felt that their concerns were alleviated during the course, it is not clear whether this would have held weight had their sons or daughters been participating in ‘high stakes’ school assessment activities like NCEA: “I initially had some concerns about the lack of exams, which meant there appeared to be no easy way of ensuring she was keeping up with her peers, but having looked at the work she is doing and had a talk with one of the science teachers at school we were satisfied that she was well ahead.” Students, too, may struggle with the shift in emphasis and the self-directed approach to learning. Two students commented that: “Sometimes a teacher is good for getting an answer straight off but this way you have to find out for yourself ...” and “It takes so much longer because you can’t do as much”. Perhaps this was the underlying reason why three students

chose to leave the 2006 programme, reporting that it was easier to “…just do the stuff in class and get good marks in the exam”. As a result, greater emphasis has since been placed on outlining the nature of the learning within the PROBLIT programme to prospective participants. 1.3 Impact on learning and engagement Paul is a strong believer of using student voice to inform change, and so he interviewed students at the end of each camp (Lowe, 2006). He wanted to investigate their attitudes to the learning experiences and to ascertain which support structures were working effectively, as well as those that needed attention. From the interviews he hoped to glean suggestions to improve the programme. A review questionnaire was also sent to parents, support teachers and school principals. Not surprisingly, the camps were considered one of the highlights because of, in part, their hands-on nature of the learning and the perceived relevance of the topics:“The camps are cool; we get to do what we are actually learning” [student]; “The experiential learning camps have been a highlight and have given [my daughter] a real appreciation how textbook science fits into the real world. I don’t think this would have happened with just classroom science” [parent]. The camps were also critical for building a sense of community: “Coming to these camps reminds us there is [sic] more of you. Usually there are just the three of us in the VC room. Coming here and there is everyone who’s doing the same thing and we can learn off each other and we have fun” [student]. Both parents and students reflected positively on opportunities to interact with their peers from other schools, and there was a sense of academic freedom in learning alongside other GATE students: “We are not stereotyped with the rest of the class who can only learn about one thing. You can go in depth, like learning about things you are really interested (about), like the engine in the winch was really cool. If I was in a normal class camp we wouldn’t learn about that stuff – everyone would get bored” [student]; “The experiential trips have been both socially and intellectually stimulating for [my daughter]” [parent]. Parents also felt that the initiative had fostered a wider range of life skills within their children as well as supported a more integrated approach to learning: “PROBLIT has given [my daughter] a higher level of interest in science, leadership skills, computer skills, self-management skills and presentation skills. But more than that it has taught her to start going the extra mile...” [parent]; “It is interesting how she was relating some of her geography learning to the science projects, with some good lateral thinking, so I would say that the problem-based learning and keeping an eye on the big picture seems to work well” [parent]. 1.4 Practical issues The 2006 PROBLIT experience highlighted a range of practical issues likely to impact on the sustainability of the programme. Of significant concern was the space each small group had available for working, with many using the library or a computer room, but often with other classes present. The computing capability varied in each work space impacting on the students’ ability to complete certain tasks. In addition, the GATE co-ordinators (responsible for the day-to-day needs of the PROBLIT students), science teachers, and IT facilitators had to be kept informed and ensure their availability should students need their assistance. GATE students in the CoroNet cluster continue to participate in PROBLIT based on the 2006 initiative and Paul (currently in Abu Dhabi) is still the convenor. As Craig Lidgard, HOD of Mercury Bay Area School comments: “PROBLIT enables

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across the body systems in order to answer the focus question, as well as integrate contextual information about training and optimal performance. At the end of 2006 group assessment and analysis indicated that all groups had moved from the uni- or multi-structural level of thinking (at the start of the year), to thinking at the relational or extended abstract level. Reporting to parents included feedback on the relevant group’s skills in gathering knowledge (based on a report submitted by students in which they collate the different areas of knowledge required to address the problem), team work skills, and presentation in response to the focus question.

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students to spend time developing the skills to solve complex problems. This certainly helps with the excellence questions in NCEA which require the ability to discuss issues. The electronic communication used for PROBLIT has meant that little has changed with Paul now overseas. He runs the course and organises the camps as usual. The only difference is that he cannot attend the camps. I ran the first one at Goat Island which went very well”.

2. PLUTO (Please Let Us Take Off) In 2009, the PROBLIT philosophy of problem-based, co-operative learning and assessment was introduced to 16 mixed-ability Year 9 classes in 12 schools across the Waikato and Bay of Plenty. Sixteen Year 10 classes participated in 2010, and the first Year 11 classes are currently underway. As with PROBLIT, PLUTO is based on a series of problem-based projects targeting different aspects of the science curriculum. For example, in 2009 Year 9 students were asked to integrate a range of biological topics in response to the following scenario: A worldwide viral pandemic is threatening our community and survival. It has been decided to establish a large biodome near Morrinsville for some of us to live in. It is expected it will take at least 2 years before it could be considered safe to exit the dome. What do we need to put into the dome and why? Note: The dome needs to exclude all material from outside except sunlight, as the virus is thought to be able to survive on non-living material for a significant time. The dome will be 2km in diameter. In order to help guide students in their gathering of relevant knowledge, seven ‘key ideas’ and related questions were provided. For example, the first key idea focused on how plants and animals in the dome would get their food. The questions included: • How do plants use the sun to get their food? Explain using a simple diagram and word equation. (Photosynthesis.) • You will do some simple experiments with plants and photosynthesis. 1 • How could animals get their food in the dome? What sort of food could it be and can they get enough? • What different plants and animals would need to be in the dome? Students had three weeks to gather the knowledge they needed and make decisions about the construction of their dome, which they presented either as a model or as a PowerPoint slide show. As with PROBLIT, the assessment was based on the SOLO taxonomy and considered the following four areas: thinking skills (i.e. the response to the focus question); gathering knowledge (presented in the form of a report); team work; and the presentation. Students were also given opportunities for self-assessment and reflecting on their own contributions to team work and gathering knowledge. In addition, students individually complete an end of year examination. As with PROBLIT, PLUTO is based on a collaborative approach to learning and assessment, with students doing the bulk of their class work and assessment in co-operative groups with the common goals of increased enjoyment, improved understanding, greater confidence, and improved grades (Lowe, 2004). Paul’s suggestions for setting up effective teams include: • allow students to select their own group, no bigger than three • rotate tasks such as equipment manager, technician and recorder • use league tables to create a motivated, competitive 1

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atmosphere amongst groups; award points for various activities • encourage students to review their test answers by returning test scripts and allowing the groups to re-submit, then average the first and second marks • explain difficult aspects of a particular problem to students, at times giving ‘keystone lectures’ to the whole class. Peter Hampton, who has used Paul’s co-operative learning strategies for several years, also suggests waiting two to three weeks before setting up permanent groups and allowing groups to change at the start of each term. In addition, he recommends using a range of activities for awarding points for the league table, including academic activities (such as a quick quiz) as well as other important tasks such as packing up the fastest. In terms of shared assessment, he believes: “The shared assessments are great and provide early success for students. Giving them a second chance and averaging the marks is great too and helps them learn what they don’t know. I don’t worry too much about the overinflated initial results as at some stage later they will have to do assessments on their own – I just want them to have success and come to my class because they want to and because they are having fun”. Note: Paul and co-director Simon Taylor (science advisor, The University of Waikato’s School Support Services), write the majority of the materials for PLUTO. However, each teacher is responsible for the overall direction of their class and participates in quarterly meetings, which Simon notes are, “…really important learning retreats, and a key to the initiative’s success.”

3. Discussion PROBLIT and PLUTO represent a repackaging of the science curriculum into problems that engage students in learning for a purpose. Benefits include: increasing the perceived relevance of science conceptual knowledge; enhancing self-directed and collaborative approaches to learning; and supporting the development of key competencies as outlined in the 2007 New Zealand Curriculum. As with any new education initiative, challenges exist around resourcing, and alignment with the rest of the school programme. There is also the significant shift from a focus on content coverage towards a more context-driven, inquiry model of science learning. Teacher, student and parent responses to this are likely to reflect their views of the aims and purposes of science education. Furthermore, whilst all teachers want their students to be successful, different definitions of success lead to different approaches to teaching. This is also true of school leadership teams, and of parents’ views of what constitutes effective teaching and learning programmes. A shared goal is thus a critical aspect of any transformational change. National-level assessment also has the potential to both encourage and constrain the creativity of classroom programmes. The teachers, students and schools currently trialling PLUTO in Year 11 are to be commended for their willingness to embark on a slightly different road towards NCEA Level 1. For further information contact: problit@xtra.co.nz

Acknowledgements Paul and Simon acknowledge the significant support of Jane Barnett, Director of School Support Services at The University of Waikato; John Inger, Principal of Morrinsville College; principals at each of the other participating schools; and the many teachers and students who have joined with them on this journey. Professor Darrell Fisher from Curtin

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Reading about NZ birds is a useful activity in primary science programmes as Junjun Chen, Bronwen Cowie (both from University of Waikato), and Kim Oliver (Marian Catholic School) explain: Introduction Active reading is an important activity for making meaning during the process of science inquiry (Osborne, 2010). As Bulman (1985) explains, “if we wish to give our pupils a taste of being a real scientist then reading should play an important part in our science lessons” (p.19). This statement is even truer in today’s information age with rich and varied science texts available through a wide range of resources, in particular the news media and Internet (Hipkins, 2010). Research has shown that student subject-specific reading proficiency can become a gatekeeper to their further learning (Greenleaf et al., 2010; Pearson, Moje, & Greenleaf, 2010; Wallace & Hand, 2007). Students who will become future scientists need to be capable of reading actively, critically and evaluatively (Wellington & Osborne, 2001). If they are to participate in socio-scientific debates and decision-making processes as active and involved citizens (Ministry of Education (MOE), 2007), all students need to be able to gain information about science matters through reading. Opportunities to talk science and interact with a range of texts, when complemented by hands-on activities, can stimulate children’s interest in the world around them and in science itself (Bull, Gilbert, Barwick, Hipkins & Baker, 2010). The skills such as engaging with a range of science texts and using their growing science knowledge when considering issues of concern to them are endorsed in the communication aspect of the nature of science strand in the New Zealand Curriculum (NZC). Asking questions and finding evidence are part of investigating in science. The integration of science and literacy can enhance student learning in both areas (Greenleaf et al., 2010; Wallace & Hand, 2007). However, research has shown that for students to learn to read critically, teachers need to make explicit the tacit reasoning processes and strategies needed to become successful readers (Lemke, 1990). Teachers also need to consider the quality of the science reading materials they use in order for students to gain the most benefit from reading activities (Pearson, Moje, & Greenleaf, 2010). In this paper we describe the range of interactive and collaborative instructional reading approaches a teacher (Kim) used to engage her Year 7 students in learning about native birds.

Reading approaches to learn about birds and their conservation The science unit was aimed at helping students understand why certain birds in New Zealand have a threatened status or have become extinct, and to investigate various conservation methods to protect New Zealand native birds. Kim used a variety of reading approaches throughout the unit, including shared reading, reading to students, reading in small groups and guided reading. In the main, she sourced reading material from the Science Learning Hub (SLH): http://www.sciencelearn.org.nz/1. The Hub materials

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are based on current New Zealand research and aligned with the NZC. The researchers observed ten lessons through the unit, interviewed students after the first and the final lessons, and interviewed the teacher after the final lesson. The students completed a pre- and a post-test. Here we provide detail on these reading approaches.

Shared reading Shared reading is an approach in which the teacher, as a reader and facilitator, supports students as readers and listeners (Ross & Frey, 2002). It allows a high degree of teacher-student interaction to help students read and understand the text and come to see themselves as effective readers (MOE, 2006). During shared reading, both the teacher and the students can see the text even though students may not have an individual copy of it. Kim employed shared reading using handouts and online materials, sometimes in combination, to introduce new science ideas. For example, in Lesson 7, Kim wanted students to understand the methods used to protect native birds, along with the pros and cons of each method. Kim handed out a copy of the article Protecting Native Birds. Before she began reading the article, she instructed, “I would like you to highlight the key pieces of information with your partner as I read. Just the key bits of information.” While she was reading the article, Kim asked the students to explain the meaning of some technical terms such as ‘non-target species’. She did this to make sure students understood the science meaning of key terms within the context of the unit. Then she accessed the SLH website and projected the same article onto a screen and guided the students through the article, enlarging and explaining the images embedded in it. She said, “I’m just putting up the article that I read to you. Here is the image of a Predator-proof Fence, so if I click on it, [it will] come up a little bit bigger.” She asked questions like, “Why do you think the vegetation has been cleared away from the edge of the fence? Why are there big strips either side?” (Video data, November). In this example, Kim’s actions indicated that although the students were to read silently she expected them to be active readers as well as listeners. She encouraged the students to identify the main ideas in the text. More than just reading for literal meaning, Kim’s questions guided students towards inferential thinking as in the giving of reasons for clearing the vegetation from both sides of the fence. Kim thought that there were advantages to the handout and to the online article for shared reading. During the shared reading of the handout, she could stop reading and ask questions when she thought her students might need support or they looked confused. The students could highlight key ideas on the handouts and keep the handout for later review. When using the online-shared reading, the visual information played a greater role. Kim could enlarge 1

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The Science Learning Hub is an online portal funded by New Zealand’s Ministry of Science and Innovation, formally the Ministry of Research, Science, and Technology, and managed by Wilf Malcolm Institute of Educational Research, the University of Waikato since 2007.

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the images so that the students could see more detail, and online the images came with pop-up explanatory notes. Because of this the students were more able to take advantage of the information the images depicted. This approach links well with the intention of the communicating in science strand in NZC because it supported students to consider more critically the images and the writer’s purpose in using them. Many of the students appeared to find the online text very engaging and to find the images informative.

Reading in small groups Student reading gains can be linked to their opportunities to talk with others about a text (Guthrie, Schafer, Wang, & Afflerbach, 1995). In small group reading, the teacher can scaffold a group to help them make sense of the text and become actively engaged with it. Students themselves can work together to arrive at a deeper understanding of the text through discussion. Kim made considerable use of reading in pairs or in small groups using both handout reading materials and online reading materials. For example, in Lesson 1 students, in small groups, read the article Native Bird Adaptations on the SLH website. This lesson focused on biological adaptation and its effect on an organism. First, Kim used a deck of playing cards to randomly assign students to ‘home’ groups of four students (groups had to include each suit in the pack). She then regrouped the students into four ‘expert’ groups (one for each suit in the pack). Each ‘expert’ group read the article to answer the question that had been allocated to them. Once the group had agreed on the answer, the students went back to their ‘home’ groups and shared their answers with other group members. Kim made it clear that she expected the students to read, synthesize, and interpret the reading and then answer their assigned questions using their own words: “It will be great if you aren’t just copying what is on the website. If you could use your own words, I will be even more impressed.” (Video data, October) In this way, Kim ensured that students were able to ‘talk science’ using their own words (Lemke, 1990). Kim indicated she had two distinct purposes for using reading in small groups: to encourage students to work together, and to enhance their science learning. While the students were reading, Kim circulated around the groups and provided support to make sure students understood the article. She explained the technical vocabulary using straightforward language, and examples that linked to students’ prior knowledge and life experience. Kim emphasised, “It’s good to find an example from their own life.” For example, when students read that adaptation occurs over many, many generations, they could not understand the word ‘generation’. Kim explained: “What does it [generation] mean? Your grandparents to your parents, it is one generation, and then to you, it is another generation, when you grow up, and you have children, that’s another generation…so it takes hundreds of years for adaptation to occur.” When students’ prior knowledge is activated and they make connections between what they know and what they are reading this improves their reading comprehension and helps them to hypothesise, infer, and build their own interpretations (MOE, 2006), something that is also important in learning science.

Linking reading to hands-on activities It is important that students understand the reasoning that underpins the activities their teacher asks them to do. Teachers can use reading materials to help with this (Weiss et al., 2003). Kim’s students read and talked about the 32

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different types of predators and the impact of bird habitat loss prior to making tracking tunnels to check the presence of predators in the school gully. Understanding the kinds of threats birds face was important when they came to locate their tracking tunnels in the school gully. When the students checked the tunnels, not many of the tracking paper strips had footprints on them. The students realised that this was evidence that their area was probably safe for native birds. The students really valued this activity. It prompted some of them to think more widely about taking action to conserve native birds. Some students placed tracking tunnels in gullies near their homes and brought the evidence of predators to school. As Kim commented, “Obviously, they [students] were interested in it and enthusiastic about it.” This action provides a science-based example of participating and contributing in science as outlined in NZC.

Reading stories to students Reading to students is a time when the teacher is the reader, involving the students as active listeners as they jointly enter the world created by the story or other materials (Ross & Frey, 2002). For this, students do not need to have a copy of the text. Kim read a number of books and articles to her students. For example, in the final two lessons Kim read aloud the book Old Blue by Mary Taylor (1993). This is a story of how the Chatham Island Black Robins of New Zealand were brought back from the edge of extinction. During the reading Kim posed a number of questions. For example, when reading that, “The black robin had become the rarest bird in the world. Only a miracle could save it from extinction,” Kim asked, “Can anyone make a prediction about what they [the scientists] did?” Predicting is a strategy that can used to prompt students to anticipate what will come next. It involves using prior knowledge and information in the text and relates to inferring meaning rather than mere speculation (MOE, 2006, p.139). Throughout the reading, Kim also used questions like this to prompt students to recall and make connections with what they had learned in the previous lessons, such as adaptation, the impact of predation, and the role of birds in the ecosystem. The children really enjoyed the Old Blue story, as one student commented in the interview, “I was very interested in the story – how we create more robins and how we grow more of the plants they like.” It brought the ideas of the unit to life for the students and was used strategically by Kim to help her students to create a coherent, cohesive mental image of the focus of the unit. It also helped the students understand the nature of scientists’ work.

Student outcomes Student attitudes towards science were surveyed before and after the unit. Findings indicated that students’ attitudes towards science were more positive after the unit. Student and teacher post-unit interviews confirmed that their enjoyment and interest in learning science had been increased. As might be expected, comparison of the preand post-test results showed that students’ understanding about native birds had increased. However, both the teacher and students were of the view that students had learned much more than usual. One student said, “I learnt quite a lot more. When I heard that we were going to learn about kiwis, I thought I knew a lot about them, but then I realised that there was quite a lot that I didn’t know.” In their end-of-unit evaluations, 20 of the 23 students stated that they had learned facts relating to native birds, 5 stated that their understanding had increased, 6 stated that the unit had been interesting, and 12 stated that they felt more confident in their knowledge of native birds and the threats they face.


Concluding comments

References

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The NZC promotes a view of students as confident connected lifelong learners. With Miles Barker (2010), we agree that ideally students also need to become confident connected lifelong science learners. Reading can play a role in this. Various forms of communication and reading are important aspects of scientists’ work and in learning science. The birds’ unit described here included a combination of reading, writing, discussing and doing activities, although overall it could be claimed that reading was a dominant activity. While reading is often contrasted unfavourably with opportunities for students to build science knowledge through hands-on scientific exploration, we hope that we have illustrated that reading can be an interactive activity that builds students’ interest in and ability to engage with science ideas now and into the future. Teachers have a rich repertoire of reading approaches and strategies that can be used with multiple positive outcomes as part of science lessons. With careful teacher guidance, the reading of different texts can foster active student engagement with ideas that replicates the kinds of thinking needed to interrogate and make sense of data in science. For further information contact: j.chen@waikato.ac.nz Acknowledgement: We would like to thank the school and students for warmly welcoming us into the classroom, and Marilyn Blakeney-Williams for discussing effective reading strategies with us. This research was undertaken as part of a study on teacher use of the Science Learning Hub.

Bulman, L. (1985). Teaching Language and Study Skills in Secondary Science. London: Heinemann. Bull, A., Gilbert, J., Barwick, H., Hipkins, R., & Baker, R. (2010). Inspired by science. Retrieved from New Zealand Council for Educational Research website: http://www.nzcer.org.nz/default.php?products_id=2647 Greenleaf, C.L., Litman, C., Hanson, T.L., Rosen, R., Boscardin, C.K., Herman J., … Jones, B. (2010). Integrating Literacy Instruction into Secondary School Science Inquiry: The Challenges of Disciplinary Literacy Teaching and Professional Development. Retrieved from http://aer.sagepub.com/content/ early/2010/10/14/0002831210384839 Guthrie, J.T., Schafer, W.D., Wang, Y.Y., & Afflerbach, P. (1995). Relationships of instruction to amount of reading: An exploration of social, cognitive and instructional connection. Reading Research Quarterly, 30(1), 8-25. Hipkins, R (2010, June). Should students learn to “read” science writing from the media? New Zealand Science Teacher, 124, 4-6. Lemke, J.L. (1990). Talking science: Language, learning, and values. Norwood, NJ: Ablex. Ministry of Education. (2006). Effective Literacy Practice in Years 5 to 8. Wellington, New Zealand: Learning Media. Ministry of Education. (2007). The New Zealand Curriculum. Wellington, New Zealand: Learning Media. Osborne, J. (2010). Arguing to learn in science: The role of collaborative, critical discourse. Science, 328, 463-466. Pearson, P.D., Moje, E., & Greenleaf, C. (2010). Literacy and science: Each in the service of the other. Science, 328(5977), 459-463, doi: 10.1126/science.1182595 Ross, D., & Frey, N. (2002). In a spring garden: Literacy and science bloom in second grade. Reading Improvement, 39(4), 64-74. Taylor, M. (1993). Old blue: The rarest bird in the world. Auckland, New Zealand: Ashton Scholastic. Wallace, C.S., & Hand, B. (2007). Using a Science Writing Heuristic to promote learning from laboratory. In C. S. Wallace, B. Hand, & V. Prain (Eds.), Writing and Learning in the Science Classroom (pp.67-90). Dordrecht, The Netherlands: Kluwer. Weiss, I.R., Pasley, J.D., Smith, P.S., Banilower, E.R., & Heck, D.J. (2003). Looking inside the classroom: A study of K-12 mathematics and science education in the United States. Chapel Hill, NC: Horizon Research. Wellington, J., & Osborne, J. (2001). Language and literacy in science education. Philadelphia, PA: Open University Press.

Barker, M. (2010, February). Lifelong science learning. New Zealand Science Teacher, 123, 32-36.

continued from page 30 University of Technology has provided research support and is supervising Simon’s doctoral-level investigation into the impacts of PLUTO on student engagement and learning. Rose Hipkins provided valuable feedback on the writing of this article.

References Biggs, J. & Collis, K. (1982). Evaluating the quality of learning: The SOLO taxonomy. New York: Academic Press. Hmelo-Silver, C.E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235-266. Hipkins, R., Boyd, S., & Joyce, C. (2005). Documenting the learning of the key competencies: What are the issues? A discussion paper. Wellington: Ministry of Education. Retrieved from http://www.nzcer.org.nz/default.php?products_ id=2476

Lowe, J.P. (2004). The effect of cooperative group work and assessment on the attitudes of students towards science in New Zealand. Unpublished doctoral thesis, Curtin University of Technology, Perth, Australia. Retrieved from http:// adt.curtin.edu.au/theses/available/adt-WCU20041112.102310/ Lowe, P. (2006). PROBLIT 2006. Problem-based learning in teams for a cluster wide cyber science class. Retrieved from http://centre4.core-ed.net/viewfile. php/17876/kb/1/62765/68/PaulLoweFinalReport.pdf Park Rogers, M.A., Cross, D.I., Sommerfeld Gresalfi, M., Trauth-Nare, A.E., & Buck, G.A. (2010). First year implementation of a project-based learning approach: The need for addressing teachers’ orientations in the era of reform. International Journal of Science and Mathematics Education. Published online, October 2010. Rivet, A.E. & Krajcik, J.S. (2008). Contextualizing instruction: Leveraging students’ prior knowledge and experiences to foster understanding in middle school science. Journal of Research in Science Teaching, 45, 79-100.

New!!! NZASE Members’ Forum Starting this month: An online forum about the future of science education!

We want to hear what you think about the future of science education, so post your views online today. The NZASE website features: • a dynamic forum for members • latest news, information and happenings • subject association pages • forthcoming conferences • useful links and resources. So...it all happens online at nzase.org.nz. See you there!! If you would like to become a member of NZASE please email: nzase@xtra.co.nz

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junior café scientifique Junior Café Scientifique is a new initiative that is connecting scientists and students, as Kathrin Otrel-Cass, the University of Waikato, explains: The Junior Café Scientifique (JCS) is modelled on the highly successful Café Scientifique where its informality creates an atmosphere for young people to feel confident about discussing their ideas and positions on science topics of their choosing. A pilot project was conducted with two North Island decile 8 high schools. The JCS involved students selecting and inviting scientists to talk with them about science topics chosen by, and of interest to, the students. The results of the pilot project show that students enjoyed the experience; in particular, because they could choose the topics they were interested in, and were in charge of organising and running the events. Feedback included: "It was a great success and turn out; the students who came were interested and had questions." "We really enjoyed the fact that the talk was not strictly science, it meant that all sorts of people enjoyed it even those who don't do science." "Some of us went to the events with no expectations and were pleasantly surprised by the content".

Why Junior Café Scientifique? Educators and policy makers alike argue that all students should have some understanding of science to take part in decision making around socio-scientific issues, but also so they get to appreciate its relevance to their lives (Fensham, 2007; Ministry of Education, 2007). Because participation and engagement in science is shaped by students’ identity with, and their ideas about, science (Roth & Tobin, 2007), it is, therefore, not surprising that the experiences young people have with science, both at home and at school, shape these identities (Cowie, Jones & Otrel-Cass, 2010; Kolsto et al. 2006). When students experience science in school they don’t always perceive it to be what real scientists do. Osborne et al. (2003) highlight that often what is portrayed in school science is an oversimplification of real science and not representative of the true Nature of Science (NoS) and the way scientists conduct their research. In an effort to draw renewed attention to the NoS, the latest New Zealand curriculum (NZC) highlights that science is more than learning about how to conduct experiments, but involves an understanding and appreciation how scientists understand, investigate, participate and communicate science. The NZC emphasises that students be encouraged “to look into the future by exploring such significant future focused issues as sustainability, citizenship, enterprise, and globalisation” (Ministry of Education, 2007, p.9). The key competencies that students should acquire include: to think critically; use language, symbols and texts; be self-motivated; relate to others, and be actively involved in problem solving. An education that teaches students to become self-driven, engaged with current and future issues, and to have a voice, which implies a particular point of view that represents an informed and interested individual, is an expectation (Thomson, 2008). With this in mind the curriculum promotes the transformation of society, rather than reproduction of its current state. 34

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Students need opportunities where they can consider problems that require further elaborations, including uncertainties and social ambiguities, plus an opportunity to share and listen to ideas that are underpinned by current knowledge in science (Roth, 1995, p.xiii). Such environments allow students to critically exchange ideas and provide opportunities for students to use their own knowledge and experiences about science. In New Zealand there are a number of projects that aim to bring science contexts and scientists into classrooms. For example, the New Zealand Science Learning Hub website has videos and online stories from a range of NZ scientists that teachers can show and share with their students (Jones, Cowie & Buntting, 2009). Face-to-face meetings between the scientist and students have been introduced to put a face to science, and demystify who scientists are and what they do (Bay et al., 2009). Junior Café Scientifique is another initiative to demystify the role of scientists and to promote an authentic engagement with them.

What is the Junior Café Scientifique? During a JCS event a student usually introduces the speaker who then talks for only a short time (maximum of 10 minutes) about the topic or the research in which he or she is an expert and then students ask questions. To break with the traditional classroom or lecture style and emphasise a relaxed atmosphere food and drinks may be offered before or during intermission and after the discussion. In contrast to the adult café the emphasis is on student ownership of the cafés where students organise and run the events with some support from teachers and JCS organisers. The biggest difference between the ‘adult’ Café Scientifique is that in JCS students identify topics and specialist areas for discussion. This responsibility means that the selection of topics is not guided by curriculum or assessment needs, but by what the student organising committee identifies as being of interest. This strong emphasis on student ownership is crucial for creating an atmosphere where students are less constrained by the demands, norms and relationships of the science classroom and science curriculum. The informality of JCS allows students who do not choose science as a school subject to attend or even be part of the JCS organising committee.

The pilot study A small pilot study of a JCS based on a format developed in the UK was undertaken in 2009 at two urban, decile 8 high schools in the North Island. The study, funded by the Royal Society of New Zealand, explored: • the implementation of JCS in the two pilot schools, their similarities and differences • how the student organising team perceived their experiences, and how the teachers felt about this • the topics that students were interested in • future recommendations. One school was an urban, decile 8, Years 9-13, secondary school with 1500 students. The organising committee involved 15 students across all year levels who shared seven roles: chairperson, speaker liaison, co-ordinator, logistics (2), administration (2), head publicist and publicist (7). The other


The findings 1. Our review highlighted two stages of JCS events: the pre-organising and the organising stage (see Tables 1 and 2). Table 1 shows five steps from the initial contact made by the JCS co-ordinator, to a speaker being identified and contacted. Table 2 shows a further four steps around the organisation of the event and highlights the high degree of student involvement in JCS. 2. While some teacher and JCS co-ordinator support was necessary, the main onus of the organisation was on the students who were in control of topic selection, and the format of their event. Students were encouraged to identify a topic they were interested in and to think about questions they may have. This pre-planning was so they could contact the speaker beforehand and liaise around the focus of the discussion. However, students from both schools did not submit questions to their speakers, but they did liaise with the speakers about the possible direction of the discussion topic, and were often directed by the speaker’s suggestions. 3. At times students found it difficult to identify a topic, which was the case especially for the very first event. Students were given a list of possible topics by the JCS co-ordinator, which then provided a springboard for their own ideas. 4. For some topics there were no available speakers. For example, one student committee suggested discussing ‘paranormal activity’. No speaker could be located to discuss this topic, and this caused some delay until students re-negotiated a new topic. 5. Students had to be reminded to focus on science related topics. 6. Topics selected for the six events were: Science vs. Religion; Animal Cloning; Origin of New Zealand Humans; Robots; Parallel Universes; and Darwin’s Evolutionary Theory. Table 3 presents a selection of

questions asked by the students during the discussions. 7. The events attracted both junior and senior students, although senior students dominated the audiences. On two occasions the events were also advertised in neighbouring schools and attracted students from outside the host school. This was especially the case when the topics aligned strongly with the senior science curriculum and teachers suggested the JCS be promoted outside their own school. However, this caused an increase in audience numbers, impacting on the students’ interaction with the speaker. 8. Themes relating to the NoS were of most interest to the students. For example, during the Darwin vs. Religion discussion one of the students asked the speaker: “What percentage of scientists around the world do you think believe in Darwin’s theory?” In the scientist’s response, she drew attention to the fact that while she was unsure about a specific percentage, there were a number of famous scientists who responded critically to Darwin’s ideas. The speaker pointed out that while scientists don’t always agree they operate on universally agreed on principals and may challenge each other from time to time within those parameters. Students also asked questions relating to socio-scientific issues. For example, one student asked during the discussion about animal cloning: ‘How far is too far with the cloning technology?” Questions equally concentrated on pure scientific aspects, such as: “Is the DNA of a cow in milk?” 9. In some cases students who attended the discussions came with specific questions that related to interests or projects they were involved in. And so these discussions with the speakers often continued into tea break. For example, a student asked about specific techniques used in the animal cloning process. 10. Students were also interested to hear about the scientists’ backgrounds, what got them interested, and study or work experiences that influenced their career choices and pathways. All of the scientists responded very well to the students’ questions, and were overwhelmingly surprised and pleased about the interest and the knowledge and experiences the students brought into the discussion. 11. While it is not possible to ascertain whether the involvement in JCS would change students’ long-term choices in science, however, it was encouraging to hear that students wanted to continue with the cafes, seeing them as worthwhile. We found the positive interest in

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school was also an urban, decile 8, Years 9-13, secondary school but with 1870 students. The student committee in this school was smaller with two key organisers, senior students who usually took on the chairperson’s and speaker liaison’s roles as well as two to three students, who were responsible for other duties including publicity and event co-ordination. The team also included, at times, junior students and also senior students who were not studying science subjects. The pilot study involved participating students and their teachers in reflective group discussions to identify their views about and experiences at JCS. Below are the findings.

Table 1: Pre-organising stages for JCS event.

Table 2: Organising stages of JCS event. New Zealand Association of Science Educators

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Table 3: Sample questions. JCS was demonstrated by the number of students who stayed on after school had finished to participate in them.

Discussion In recognition that science and technology play a key role in economic prosperity and the development of a knowledge economy, participation in science and engaging in science discourse has become a matter of increased importance (Cowie, Jones & Otrel-Cass, 2010). Providing contextual opportunities for students to engage with science and scientists is important so that students learn about how scientists understand, investigate, participate and communicate science. When scientists share with JCS attendees their work and how their ideas have developed, and at times maybe even changed, they highlight that science is tentative in nature and a social practice that is, and should be, open to anyone to participate in. Such personalised science examples potentially increase the opportunity for students to experience scientists beyond stereotypes and may open up a range of new science identities students can aspire to. Opportunities that allow students to use their understanding in context draw attention to what it means to take a critical stance, particularly on socio-scientific issues (Kolsto, et al. 2004). By exploring emotional and ethical dimensions relating to science students can also explore that “individual positions on certain issues can change as a consequence of exposure to the arguments of others and/or information that was not previously available” (Du Plessis, 2003, p.2). The positive response by students to take ownership and responsibility for the choice of issues, topics and organisation of the event draws attention to the need to listen to students’ voices, their interests and concerns, and trusting students in their ability to be “confident, connected and actively involved” young people (MOE, 2007, p.8). For further information contact: kathrino@waikato. ac.nz, and for information about how to set up a JCS in your school visit: http://cster.waikato.ac.nz/research/ juniorcafesci.shtml.

Acknowledgement The JCS pilot project was kindly funded through the Royal Society of New Zealand. This article is based on the findings presented in the final report (Otrel-Cass & Bryan, 2009). The author would like to acknowledge the contributions made by Catherine Bryan who was part of the research team.

References Bay, J.L., Sloboda, D.M., Perry, J.K., Hamilton, R., Mora, H.A., Campbell, J., Lobie, P., et al. (2009). Scientists in High School Classrooms via Interactive Television. Paper presented to the annual conference of the Australasian Science Education Research Association, Geelong, July 1-4, 2009. Cooper, B., Cowie, B., & Jones, A. (2010). Connecting teachers and students with science and scientists: The science learning hub. Science Education International, 21(2), 92–101. Cowie, B., Jones, A., & Otrel-Cass, K. (2010). Re-engaging students in science: issues of assessment, funds of knowledge and sites for learning. International Journal of Science and Mathematics Education, 1–20. Du Plessis, R. (2003). Democracy, participation and “scientific citizenship’: New Zealand initiatives. Paper presented to the Policy and Politics International Conference on ‘Policy and Politics in a globalising world’ Bristol, 24-26 July 2003. Fensham, P. (2007). Policy issues for science education. Discussion paper prepared for World Conference on Science and Technology. Perth, Australia, 8-12 July. Jones, A., Cowie, B., & Buntting, C.M. (2009). Expanding the context for student learning of science: The conceptual development of the New Zealand Science Learning Hub. Paper presented at the 40th annual ASERA conference, Deakin University, Geelong. Kolsto, S.D., Bungum, B., Arnesen, E., Isnes, A., Kristensen, T., Mathiassen, K., et al. (2006). Science students' critical examination of scientific information related to socioscientific issues. Science Education, 90(4), 632-655. Ministry of Education (2007). The New Zealand Curriculum. Wellington, New Zealand: Learning Media. Osborne, J., Collins, S., Ratcliffe, M., Millar, R., & Duschl, R. (2003). What “ideas-aboutscience” should be taught in school science? A Delphi study of the expert community. Journal of research in science teaching, 40(7), 692-720. Otrel-Cass, K., & Bryan, C., (2009). Junior Café Scientifique. Report to Royal Society of New Zealand, p. 1-35. Roth, W.M. (1995). Authentic School Science: Knowing and Learning in Open-lnquiry Science Laboratories. London: Kluwer Academic Publishers. Roth, W.M., & Tobin, K. (2007). Science, learning, identity: Sociocultural and culturalhistorical perspectives. Sense Publishers. Thomson, P. (2008). Doing visual research with children and young people. London: Routledge. Wilson, M., & Otrel-Cass, K. (2010). Café scientifique in Hamilton and Tauranga. Paper presented at Science in the Public: A one day symposium on Cafe Scientifique and Related Events. Hamilton, New Zealand; 8 July 2010.

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Barker (2006), pp.27-29. I was reminded of Jane Gilbert’s (2005) ideas: “The ability to make sense of what is available is now a scant resource” (p.197) but that a powerful counter may be the notion of schooling as “knowledge-building” (p.201) and “the idea of restructuring all school activities so that they resemble the workings of research groups” (p.196). See also Hipkins (2006). Maynard Smith & Szathmary (1997), Vic pointed out, hold that achieving a synergy between humans and information technology will be a step significant enough to rank with the very greatest biological achievements on Earth. American journalist David Warsh’s (2006, p.xxii) notion that the economics of knowledge may turn out to be more fruitful than the traditional economics of people and things is prescient, Vic believes.

References Arcus, V. (2011). Data deluge needs a modern polymath. New Zealand Science Teacher, 126, 4-5. Barker (2006). Ripping yarns – a pedagogy for learning about the nature of science. New Zealand Science Teacher, 113, 27-37. Gilbert, J. (2005). Catching the knowledge wave? The knowledge society and the future of education. Wellington: NZCER Press.

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Hipkins, R. (2006). Learning to do research: Challenges for students and teachers. Wellington: NZCER Press. Hipkins, R. (2010). Public attitudes to science: rethinking outreach initiatives. New Zealand Science Review, 67(4), 107-114. Hipkins, R. (2011). A conversation about nanotechnology at the science/science education interface. New Zealand Science Teacher, 126, 12. Horgan, J. (1996). The end of science: Facing the limits of knowledge in the twilight of the scientific age. London: Abacus. Maynard Smith, J. & Szathmary, E. (1997). The major transitions in evolution. Oxford: Oxford University Press. Rees, M. (2008). A look ahead in J. Brockman (Ed.), Science at the edge: Conversations with leading scientific thinkers of today. New York: Union Square Press, pp.433-442. Rees, M. (2010). Conclusion: Looking fifty years ahead In B. Bryson (Ed.,) Seeing further: The story of science and the Royal Society. London: HarperPress. Warsh, D. (2006). Knowledge and the wealth of nations: A story of economic discovery. New York: Norton. Wilson, E.O. (1999). Consilience: The unity of knowledge. New York: Knopf. Wolfram, S. (2002). A new kind of science. London: Wolfram Media.


Students, teachers and environmental scientists collaborate in identifying and addressing coastal adaptation to climate change issues as Anne Hume from University of Waikato, Paul Scott, Jan Murgatroyd, Svargo from MBAS, and Terry Hume and Rob Bell from NIWA explain: Background This article reports on a successful collaboration between students, teachers and environmental scientists at Mercury Bay Area School, Whitianga, seeking to find solutions to problems associated with coastal adaptation to climate change. The resulting cross-curricular study in a Year 10 class, “…has made the students appreciate that they can have an impact on the environment and the things they value,” (Jan, teacher, MBAS).

Introduction Over the past two decades unprecedented development of the coast for holiday and permanent homes, along with tourism and associated facilities such as marinas, has resulted in a dramatic rise in the risk of coastal flooding, erosion and habitat change associated with sea level rise and climate extremes. The National Institute of Water and Atmospheric Research (NIWA) and its partners received a three-year grant in 2008 from the Foundation for Science Research and Technology (FRST) to create the necessary information and tools to enable adaptation by central and local government and communities to the impact of climate-induced change on the coastal environment. A team of environmental specialists including scientists, engineers, planners, social scientists and educators, along with support from Environment Waikato and Thames-Coromandel District Council, was brought together as part of the Coastal Adaptation to Climate Change (CACC) programme. A strand of the work involved engaging with the community of Whitianga to raise the awareness of the issues and risks and consider adaptation strategies for the local situation. Whitianga is a township on the eastern coast of the Coromandel Peninsula, which lies to the east of Auckland city in the North Island (see Figure 1).

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Involvement of the school community The CACC project team saw the local Mercury Bay Area School (MBAS) as an important contributor to this community-based initiative since school pupils are likely to experience the effects of climate-induced changes to their coast in their lifetimes. The chances were also high that these same students would have responsibility for making decisions in the future about how the Whitianga community might respond and adapt to these coastal changes. Thus, the school was invited to collaborate with the team to help the Whitianga community begin thinking about how to address these issues. An initial meeting was held between Paul Scott (joint head of the Science Department), and members of the project team to ‘test the waters’ and gauge how interested Paul and his fellow teaching staff might be in designing and delivering a cross-curricular unit for the middle school (Years 9–10) around the theme of adaptation to climate change. With assistance from teachers and scientists, students would have the opportunity to learn about the risk of coastal flooding, erosion and habitat change associated with sea-level rise and climate extremes and develop solutions to issues faced by their community related to future climate change and coastal adaptation.

Project goals and NZC The New Zealand Curriculum (NZC) [MoE] guides the development of schools’ teaching and learning programmes from 2010 onwards and promotes a future where young New Zealanders emerge from schooling as confident, connected, actively involved and lifelong learners. The CACC team believed a cross-curricular unit around the theme of coastal adaptation to climate change had the potential to embrace many of the guiding principles and values that underpin this national curriculum and could help students meet these aspirations with: • a community-based learning context that has relevance and meaning for them • ways and means of identifying and addressing a future-focused issue in their community that involved ecological sustainability and citizenship for the common good of all people • opportunities for community engagement in scientific activities that respect and complement local iwi histories and traditions, and encourage connectedness to the land and environment. The unit also addressed specific requirements of the new curriculum, namely that “links between learning areas should be explored” (p.39). As things eventuated, the invitation to develop such a cross-curricular unit was very timely for MBAS since it gave the teaching staff the opportunity to trial a pedagogical approach they had been exploring which was closely aligned with the goals of the recently implemented NZC (MoE, 2007). This project-based approach, known as ‘Understanding by Design’ (Wiggens & McTighe, 2004), supports teachers in developing learning and assessment with a focus on deepening students’ understanding of important ideas. It also promotes inquiry-based learning through authentic problem-solving learning in contexts of genuine importance and relevance to students. Learning outcomes are identified as knowledge (which can be short-term), skills and understanding (which are more likely to be long-term). Key to the approach is transformative learning where learners develop enduring New Zealand Association of Science Educators

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Educating the public about coastal processes at the MBAS Enviro-showcase.

Student scientists ‘getting up close’ with beach features and processes.

understandings and come to ‘see things in a new light’. Cross-curricular input is essential for this project approach to work – a strategy strongly advocated by the new national curriculum. The real world context of coastal adaptation to change, the opportunity to work with other teachers across the school curriculum, and access to the collective expertise of the CACC team made this collaboration very attractive to the teachers, and so the school and staff accepted the invitation to be involved.

impact of climate change on their local environment and community. In the ‘Understanding by Design’ model (Wiggens & McTighe, 2004) planning is done using ‘backward design’, where teachers first establish broad learning goals and tangible outcomes before more specific planning of what and how learning is to occur. In this unit the overall learning goal was to raise student awareness and understanding of the need for adapting to climate change on our coast. Outcomes included: a student-designed and performed survey of the community’s current understanding about the need for coastal adaptation to change; recommendations to help protect the things their community values that are under threat from climate change; and a display of their findings at the school’s annual ‘Enviro-showcase’ in September which was open to the community. The teachers had begun work on other phases of the planning process: • identifying the enduring understandings students would need to achieve the goals and how these big ideas might be developed • asking essential questions (who, what where, why, when and how) to help focus on the goals • asking deeper philosophical questions (who should, how would, what might, where might) to guide future actions • identifying the knowledge and skills required to support development of the enduring understandings. As they described their intentions for the unit the teachers began articulating their own learning needs and what input they needed from the CACC team to teach the unit. This input often took the form of answers to specific questions concerning the science of climate change and likely scenarios. The teachers also sought information sources such as raw data on water temperature and sea level measurements in and around Whitianga, which the CACC team undertook to supply. Armed with this information the teachers set about finishing the planning of the unit and sorting out the logistics such as timing of classroom sessions, the field trip and teaching materials. When implemented, the unit was taught to a mixed ability Year 10 class for a seven-week period during Term 3, averaging 14 hours per week spread over Science, Mathematics, English and Social Studies timetabled classes (approximately 100 hours in total). Science occupied 28 hours of teaching time over a six-week period. Details of the teaching and learning sequence and students’ learning activities can be found on the school website at: http://www.mbas.ac.nz/.

Community Open Day A month later four teachers from the school attended a public Open Day on the topic of climate change and coastal adaptation run by the CACC project team in the Whitianga Town Hall. The Open Day exposed the public to past effects of climate change on the Whitianga environment as they walked through a photo gallery ‘time tunnel’ showing coastal flooding, storms and erosion. The public also participated in identifying the things they value about their environment (such as where they walk, kayak, launch their boats etc.) by placing pins and notes on large aerial photographs of the Whitianga area which showed where the coastal flooding erosion and habitat changes will occur in the next 50 years. At a subsequent follow-up workshop, members of the CACC team explained to the public and the teachers how climate change is likely to affect the temperature, sea level, coastal erosion and flooding, the frequency of storm events and habitat change in the estuary, and also provided some options to combat these effects. The audience questioned the information and participated in debate on the issues. Then, in a workshop activity, participants discussed and made recommendations about strategies for minimising the adverse effects of climate change on specific areas of the Whitianga community such as the beach front or the estuary and things they value. Each activity group had a member of the CACC team available to answer technical and/or scientific questions. The MBAS teachers found the day very stimulating and many potential ideas for their teaching unit began to crystallise. Paul (science) commented in a later interview that he took this opportunity to explore the complexities of climate change and ‘distil some key understandings.’

Planning with CACC At a follow-up joint planning day with CACC team members, the teachers described how they intended to approach the teaching and learning of the unit and what aspects they needed specialist help with. As mentioned earlier, the teachers had opted for a programme of learning where students would work together to produce a solution to a complex, real-world problem: that is, how to mitigate the 38

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Reflections on the experience On reflection the teachers found the cross-curricular


Promoting higher level critical thinking The decision to introduce the Geography Achievement Standard 1.6 Examining a contemporary geographic issue into the unit as a summative assessment caused some discussion amongst the teachers, and some were worried it may be too difficult for their students. However, the standard developed by Tony Nelson (HOD Social Sciences) did give some students the opportunity to demonstrate some very high levels of critical thinking. In the assessment, students were to read a fictitious newspaper article entitled “Coastal Management and Erosion at Buffalo Beach” that reported on the recommendations of a scientist employed by the regional council to investigate erosion in the area and how to prevent it. The article outlined the scientist’s proposal for the construction of an artificial dune and the reactions of various members of the local community to this proposal like individual beach residents, the Buffalo Beach Residents’ Association, the local surf club and a representative of the local iwi. A series of tasks followed that focused on: • selecting and examining economic, social and environmental aspects of coastal management and erosion at Buffalo Beach • examining the viewpoints of people towards coastal management and erosion at Buffalo Beach and providing reasons why different people may hold their viewpoints • evaluating the strengths and weaknesses for three possible courses of action for preventing erosion at

Buffalo Beach, such as the use of the experimental dune, groynes, rock cages, doing nothing or locals taking their own action. The students did find this assessment challenging, but some were able to achieve the standard, which was very gratifying to the teachers since it assessed understanding at Level 6 of the NZC. A few achieved at merit level by successfully identifying the strength and weakness of various options. For example, one student pointed out that while groynes (low rock walls that run from the dunes to the low tide level to trap sand driven alongshore by the waves) might be relatively cheap and don’t reduce access directly onto the beach, they do affect access along the beach in emergencies and can starve the beach of beach material (sand) with detrimental effects.

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Final thoughts Paul (science) summed up the learning experience for students as follows: “What I would like to see from now on is that when our young people walk along the beach they see the world through different eyes. I don’t know that this has been ‘transformative learning’ as such. The students didn’t hold any strong views or have a very conscious frame of reference at the beginning of this unit. (I don’t think we have destructed any previous knowledge or understanding, rather, we have built knowledge and understanding). But what we have attempted to do with the learning tasks that we have provided is to take them step by step on a journey in which they have come to an understanding of the complex process involved if communities are to actively adapt to change. I think that our students have developed an understanding and are more likely to have the confidence to enter the coastal adaptation debate. I feel we have been able to grow advocates for the environment; it’s not the erosion that is the ‘problem’ it’s human development! We have unwittingly developed houses and roads in a natural environment that is constantly changing.” The positive experience of teachers at MBAS for this collaborative, cross-curricular approach has prompted them to make their unit available to other New Zealand school via their school website. The unit is called ‘Coastal Adaptation to Climate Change’. The CACC team impressions of the benefits of the collaboration are best summed up in the words of Dr Terry Hume (NIWA): “It was a very rewarding experience for the project team to observe the way the teachers met the challenge of distilling complex scientific concepts of coastal processes and climate change into information the pupils could understand and relate to. Cross-curricular learning is a very logical learning methodology for students who one day will need to address environmental issues which are best addressed through an interdisciplinary approach. A personal highlight for me was seeing MBAS students at the NZ Coastal Society Conference in Whitianga proudly showing off their PowerPoint presentations and models of the Whitianga beach front prepared as part of their course work to members of the science, planning and engineering fraternity.” For further information contact: annehume@waikato.ac.nz Acknowledgements: The CACC team for the opportunity to take part in the project. The Coastal Adaptation to Climate Change Programme is funded by the Foundation for Science Research and Technology (FRST) under contract C01X0802.

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teaching was not without its difficulties, but on the whole very rewarding for staff and students. Jan (social sciences and English) enjoyed working with her colleagues and having the CACC team on call for their expertise and understanding. Paul (science) felt the unit helped teachers to make connections between the disciplines. He also commented, “Collaborative units are time-consuming and exhausting, but now it is in place it was worth it. The enduring understandings were in place before we started the unit but it was a case of developing learning tasks/ materials as we went so that they would help students to understand the concepts. A lot of flexibility was required.” One strategy that worked particularly well was the use of student folders that travelled with them in a box from class to class. These portfolios of cross-curricular activities covering aspects of science, mathematics, English and social sciences helped students to organise their learning materials and gave continuity to the study. The contribution of the CACC team was strongly evident in these activities, from the use of NIWA information sheets and data to the survey information about community values gathered on the public Open Day. Highlights for the students included the chances to study the beach firsthand and build models for the ‘Enviro-showcase’. The teachers emphasised that while some outcomes of the original planning did not eventuate – like the survey of community understanding of climate change and coastal adaptation – the processes were just as valuable for learning, and this is reflected in their in-school survey on people’s values and perspectives of coastal defence systems. The ‘Enviro-showcase’ did require students to use their knowledge to inform the community about values, how climate change will affect them and what strategies can be used to combat, for instance, coastal erosion which they did via PowerPoints and models. Students learned from each other building their models for display, and interestingly, their construction decisions were often based on where they lived. For example, students who had rock wall protection on the beach front in front of their homes placed a wall in their model, whereas those with dunes in front their homes featured dunes in their model.

References Ministry of Education. (2007). The New Zealand Curriculum. Wellington, NZ: Learning Media. Wiggins, G. & McTighe, J. (2004). Understanding by design. Virginia, USA: Association for Supervision & Curriculum Development.

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iPodTouch and science teaching Written by Chris Astall, NZAPSE National Co-ordinator. Professor John Hosking recently wrote in the NZST about the rapid growth of Internet-connected devices and the merging of voice, video and Web content (‘convergence of capabilities’). This, he noted, has led to a “revolution in the everyday use of ICT”, adding that we are currently experiencing the 5th cycle of ICT revolution, the mobile Internet.1 I recently had the opportunity to observe how one Principal has embraced this technology. Principal at Kaiapoi Borough School, Ash Maindonald is passionate about his school moving towards the goal of having one iPod Touch™ per child with 150 iPods currently in use. Ash views the use of these devices as “an everyday tool in a kid’s pocket” and notes that 3 iPod Touch™ devices are the same price as a cheap laptop, plus their applications and capability can offer children new and different ways of approaching learning. “Children can go out and undertake in-the-field research, take photos, take notes, use the GPS, use maps, dictionary, Google and Internet searches, which can all be carried in their pocket.”

Applications in the classroom I have been exploring the range of iPod applications (apps) that support children’s learning and thinking in science. Below are some of my top discoveries that are free at the Mac App Store. 1. Measuring apps One of my favourites apps is the Annoy-A-Teen which produces a continuous noise that can be adjusted from 8-18KHz frequency range. This is ideal for sound and hearing explorations. If you want to measure the loudness of sound, or the effectiveness of materials when insulating for noise, then use Decibel Meter. Heart Monitor and iSteth are two apps that can be used to measure heart rates, a fun way to explore exercise and the effects on the body. 2. Data collection apps There is a wide range of utility type apps that can be used to collect data. Timer is a simple stopwatch (countdown, countup, multiple laps). The viscosity (runniness) of different liquids can be explored by allowing them to run down an angled surface, and measuring this slope can be done using iLEVELi or iHandy Level. Apps such as iSeismo utilise the inbuilt three-axis gyroscope (motion measured backwards and forwards, side to side, and up and down) and the accelerometer within the iPod Touch™. Now just use your imagination for ways in which you can use this app as a seismograph or motion detector! Data can also be stored and uploaded to a spreadsheet. The camera on the iPod Touch allows you to record images quickly. Couple this with the voice recorder and children can easily gather and comment on data. Use NoteMaster to write without all the distractions of formatting and the simplicity of adding images to the text. This can then be uploaded and saved to Google Docs™ or emailed for sharing. Wikipedia and Dictionary can help with defining terms and supporting writing. Children can even draw and share their ideas at the same time using a Bluetooth app such as Whiteboard. 3. Research apps Some apps support the research phase of inquiry. Ash Maindonald explained how one class in his school had used the app WhatBirdNZ when trying to identify a bird by its call.

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Pocket Zoo™ not only allows you to find out more about different animals but has a link to live cameras in zoos around the world! Some useful apps I have found that could support the Planet Earth and Beyond strand are Planets, NASA, Moon Globe and NZ Quakes. Don’t forget Google Earth and Google Maps can be used as well as weather apps such as WeatherNZ. 4. Physics games I am also intrigued by the range of Physics games that are available. I challenge you to try Paper Toss, Cut the Rope, Float Free or Bungee Stickmen.

Technology in the classroom So what is the best way to manage these apps in school? At Kaiapoi Borough School, a common set of applications has been established. This ‘build set’ comprises of regularly used applications for use in supporting learning areas, or for productivity. Ash is the ‘finder’ of new apps which are then trialled with the teachers and if they are good enough they get added to the build set. Children have also been asked to evaluate applications. A quick visit to the school website (http://www.kbs.school.nz/) will give you a better indication of the range of apps in use across different learning areas. One challenge facing teachers as they start to use these mobile devices is that they need to develop an understanding of how the technology can be used to support students’ learning. Teacher and student understanding of the functionality of the technology may influence the effectiveness of the technology that is used to support children’s learning2. At Kaiapoi Borough School, Ash is still developing a range of strategies to help teachers and students use this mobile technology. During my visit to the school to observe a lesson on diversity of plants in the school grounds, one Year 3 student placed her iPod Touch™ on the table under the portable video camera. The image of the iPod screen was projected onto the whiteboard. She turned to the teacher and showed the rest of the class how she used the camera to take a series of photos of plants. The child enlarged and rotated the image and described the shape of the leaf. Using the video camera, placed above the iPod, has enabled teachers (and children) to demonstrate how to use the different apps. Children can share their understanding with the rest of the class and both teacher and children can develop the skills they need to use the technology. I would be interested to hear of your experiences using this type of technological tool in your school. I will also follow the exciting progress of Kaiapoi Borough School as they continue the journey towards their goal of ‘Working Towards a One-to-One Initiative’. For further information contact: chris.astall@canterbury.ac.nz

References 1

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Hosking, J. (2011). The disruptively changing face of ICT. New Zealand Science Teacher, 126, 8-9 For further reading about effective use of ICTs in science teaching, see the excellent article by Otrel-Cass et al. (2010) who explored how two Year 7/8 teachers used different ICTs to engage students in scientific inquiry about landforms and erosion. Otrel-Cass, K., Cowie, B. & Khoo, E. (2010). ICT in support of science teaching and learning: Teaching landforms and erosion. SET: Research Information for Teachers, 3, 15-21.


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nature of science activity Central to the NZC is the importance of developing children’s scientific attitudes, their understanding of ideas about science, what science is and how scientists do science2. The Nature of Science (NoS) is the core strand of the NZC, and there are contexts for developing ideas about it in the other four strands. The Shades of Colour activity is one way teachers can approach the Investigating in Science strand of the NoS through the Material World3. It begins with students playing around with colours in a very loosely structured activity, exploring what happens when they combine different colours. Teachers can encourage students by asking, “What does the information you have collected tell you?” This conversation with direct references to their actual mixing trays leads itself into, “Does what you see/now know raise any other questions to investigate?” Simple prompting or suggestions by the teacher can lead students into any of the activities that follow.

Activity: Shades of Colour Part 1: Investigating different colours Make up three different colours (using red, blue and yellow food colouring in water). Students, using pipettes or eye droppers, are asked to see how many different colours they can make using just these three in the mini-trays (for younger students chocolate moulds or mini ice cube trays work well for this; for older students you can use bubble wrap by filling the bubbles with liquid (this does require making small holes in each bubble with the pipettes and then these make great window displays).

This activity can be used with any age group of students and ideally students work individually, but the number of mixing trays tends to be the limiting factor for this activity. The younger the students the longer this activity will take and may require them to explore mixing colours, emptying out the trays and starting over to prepare a tray of different colours once they grasp an understanding of mixing. Older students are able to do this activity in only a couple of minutes (if using the trays), but if using bubble wrap the time depends on how many pockets they are filling. This activity is an example of how the NoS can be taught in the classroom, i.e. making careful observations, being curious, asking questions, being creative, looking for patterns in their data, and exploring their ideas. The mixing of colours allows students to investigate how different colours can be created out of combinations of just three colours. Depending on the students and lesson, this could be used to build upon the concept of primary, secondary and shades of colours and how they are perceived by the human eye4. As this is a mixing activity, no colour combination is incorrect. It is important that the students be able to discuss what they are doing and how they are creating colours. Remember, a focus on Investigating in Science means students expand their world through exploration, play and asking questions. If any assessment is needed, it should be gathered through discussions with students or by listening to students explaining to you or each other what they are doing and what is the result of their mixing.

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This is the second article about the Nature of Science and Steve Sexton of the NZAPSE describes a useful activity about the shades of colour that focuses on ‘Investigating in Science1.

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Mini-mixing tray 2.

Mini-mixing tray 1. 1

At Levels 1/2: Extend their experiences and personal explanations of the natural world through exploration, play, asking questions, and discussing simple models. At Levels 3/4: Build on prior experiences, working together to share and examine their own and others’ knowledge. Ask questions, find evidence, explore simple models, and carry out appropriate investigations to develop simple explanations. Achievement aims and objectives can be found at: http://nzcurriculum.tki.org.nz/Curriculum-documents/The-New-ZealandCurriculum/Learning-areas/Science/Science-curriculum-achievement-aimsand-objectives or the shorter Web-address is: http://tinyurl.com/2utnn6t. 2 Ministry of Education, The New Zealand Curriculum, Learning Media, Wellington, 2007, pp.28-29 3 Levels 1/2 – Properties and changes of matter: Observe, describe, and compare physical and chemical properties of common materials and changes that occur when materials are mixed, heated, or cooled.

Part 2: Investigating shades of colour Once the children have explored how the combinations of these three colours create different colours they will probably also have discovered that they can create different shades of the same colour. Age appropriate vocabulary will be needed at this point for students. Younger students should be able to grasp that ‘dark blue’, ‘blue’, and ‘light blue’ are the same basic colour of blue but different shades of blue. Older students could take this even further and using colour wheels or Internet resources5 to determine actual 4

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http://www.webopedia.com/DidYouKnow/Computer_Science/2002/Color.asp provides an explanation of primary, secondary and shades of pigment colours and compares this to light colours. Or for the shorter version: http://tinyurl. com/3q2b3yk. http://www.december.com/html/spec/colorshades.html

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names of their various shades, for example: ‘peacock’, ‘topaz’ or ‘blue mist’. This leads into the main activity: Shades of Colour. Through this activity children of any age can now create different shades of the same colour by using colour combinations. For younger children provide guiding instructions such as, 1 drop of blue and one drop of yellow make green; 2 drops of blue and 1 drop of yellow, and 1 drop of blue and 2 drops of yellow creates three different shades of green. Older students will most likely be able to continue on with this activity with minimal teacher intervention. Younger children can be extended further by creating their own rainbow. Using the three primary colours ask them to create: red, orange, yellow, green, blue, indigo, and violet. For older children they can use the bubble wrap in a 10 x 10 grid pattern to create their own colour chart. It is important to note that Investigating in Science covers a wide range, so questions help the children think about the investigation process. Questions also allow the children to realise that investigating in science requires a plan for the investigation. Further ideas: repeat the test, decide on what evidence and how to gather it, use their evidence to come up with

an explanation, use a variety of investigative approaches (not all fair test), look for trends and patterns in data, be prepared to discuss their findings – peer review, be open-minded, realise that their knowledge/understanding may change in light of new evidence. There are many questions teachers can ask to help students express themselves while they are engaged in the activity:6 What do you want to find out? What is the best method to find out? Is your method dangerous? How will you measure or record your data? What does the information you have collected tell you? Did the investigation you planned provide the evidence to answer your question? and Does the evidence you gathered raise a new question to investigate? Investigating in Science allows students to answer their own questions through their own actions. Teachers can, and when appropriate should, guide students through the investigation. Science should be fun, but students also need to know why they are having fun. For further information contact: steven.sexton@otago.ac.nz 6

This list is taken from Bull, A., Joyce, C., Spiller, L. & Hipkins, R. (2010). Kick Starts: Kick-starting the Nature of Science. Wellington, New Zealand: NZCER Press.

continued from page 43 level; think about what you are doing, and probably the biggest tool for class control is ‘THE HOOTER’ (from the $2 shop). When heard all work/fun stops, put everything down, hands on head ready to listen.” He approaches his lessons as learning through a science context, so he usually uses the Ministry of Education’s Building Science Concepts books and the Making Better Sense of…. (Ministry of Education, 1999a, 1999b, 2001a, 2001b) books when planning a lesson. He often refers the students back to the ‘BIG IDEA’ as a means to keep the students focused on the learning. In this example for the New Entrant class, they wanted to explore which parachute design they created took the longest time to fall to the ground. This was modified from Building Science Concept #34–Parachutes (Ministry of Education, 2003) big idea, “The design of objects can influence their rate of movement through air by decreasing or increasing the action of air resistance on them”. In every lesson, Mr Science encourages creativity in thought and action, so no idea is considered silly. If a student comes up with a different way he encourages them to “go for it!” This kind of thinking is new for a lot of children, but once they get the hang of it, it is embraced and they run with it (literally sometimes). Many teachers will, and do, approach their classes like this – creative freedom and belief in oneself – as it all ties in with curriculum’s key competencies and values. However, it is Mr Science’s science content knowledge and PCK (Pedagogical Content Knowledge) that give Stirling the confidence to allow the children to develop their ideas, rather than dismissing them. For this New Entrant class a large portion of the time was spent constructing the parachutes which included measuring out the plastic and string. Part of the learning context for these students was exploring different parachute designs to build on their initial ‘WOW’ activity of floating and sinking in air. For these parachutes they used a marble as a weight. There was, however, plenty of time for them to trial all of their different designs. With students, Mr Science believes you really need to allow time to reflect and 42

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critique which design was better and why. Learning from previous mistakes means the students can rebuild and do a better job next time.

Concluding remarks What Stirling does as Mr Science is not unique, but he does bring to the Nelson area schools (which use him) teaching experience in science. His content knowledge just happens to be in an area of the curriculum that many primary teachers do not feel as comfortable teaching. So he not only brings the ‘WOW’ of science to the students, but also supports classroom teachers with follow-up activities they can then use to further build upon and extend these experiences. In effect, there are two outcomes of this kind of approach to bringing science into the classroom. First, students get to participate in activities with a science focus that stimulate their interest and keep them engaged. Second, classroom teachers get to observe a specialist teacher approach to learning through a science context, and to use his follow-up activities, gaining the opportunity to build their own content knowledge. This provides the whole class and often the entire school with a feeling of achievement and success. For further information contact: steven.sexton@otago.ac.nz Disclaimer: The views expressed in this article are not necessarily those of the NZASE/NZST and the use of entrepreneurs, such as Mr Science, in primary school science programmes is an individual school decision – Ed.

References Ministry of Education (2003). Building Science Concepts #34—Parachutes: Floating and falling in air. Wellington, New Zealand: Learning Media. Ministry of Education (1999a). Making Better Sense of Physical World. Wellington, New Zealand: Learning Media. Ministry of Education (1999b). Making Better Sense of Planet Earth and Beyond. Wellington, New Zealand: Learning Media. Ministry of Education (2001a). Making Better Sense of Living World. Wellington, New Zealand: Learning Media. Ministry of Education (2001b). Making Better Sense of Material World. Wellington, New Zealand: Learning Media. Sexton, S.S. (2011). Mr Science - Part 1. New Zealand Science Teacher, 126, p.40.


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Mr Science – part 2 Stirling Cathman, as Mr Science, is an example of how some schools are bringing science back into, and out of, the classrooms in the Nelson region. In Part 1 (NZST Issue 126), Clifton Terrace School, Hampden Street School and Victory Primary School explained that Mr Science is impacting positively on the students’ views of science and the teachers’ confidence to follow-up on his activities. As stated in Part 1, both students and their teachers await, with anticipation, their next science lesson.

Mr Science puts on his lab coat. In this article we focus on Victory Primary School’s New Entrant students enjoying a classroom visit from Mr Science, and discuss and explain the how and why Mr Science does what he does. As reported in Part 1, a 90-minute primary science lesson has 80% of the time spent on students doing the main activity, with 20% or less of the time focused on Stirling. This is so that once the concept to be explored is presented and discussed, the students become the focus of the lesson. Mr Science tells the children that they will be trying to think in some different ways and trying new things, so they should not be afraid to come up with new ideas; this is science and sometimes there can be more than one answer to a problem. He ensures they understand that it is okay to make mistakes, as many important scientific discoveries were made by mistake.

tell them, because as they go around the room each group builds on the ideas heard previously. By the time they have heard from everyone, the whole class usually has it figured out and in so doing provides a feeling of achievement and success by allowing everyone the opportunity to express their ideas in a positive environment. This method of whole class discussion links closely to Nature of Science Understanding about Science, in that explanations based on evidence are what science is about. For example, the New Entrant class lesson started with a hair dryer and Ping-Pong ball demonstration. The hair dryer was turned on and the Ping-Pong ball placed in the path of the moving air. The students discussed what is floating and what is falling in air; how they could speed up or slow down the rate of falling by changing the object’s shape and this then led into the main activity of designing their own parachute. Once they are thinking, questioning and discussing ideas, then out comes the ‘LAB COAT!’ Mr Science explains that his lab coat has a mysterious power that turns him into a scientist, which includes wondering, predicting, noticing things, asking questions, and trying to figure stuff out. He usually makes a big show when he puts on the coat. “When I put on my coat I turn into a scientist, and when I turn into a scientist, YOU! turn into little scientists.” At this point “I’ve got ‘em,” and he is surrounded by excited students with wide open eyes waiting for what comes next. The main lesson activity is designed so that students have their brains and hands on. Mr Science says, “This is where I get into the stuff that has scared a lot of teachers.” He believes that primary science needs to be exciting and that this should get the students excited. It can be hard to manage an exciting science lesson. Students may not be used to having eyeballs, fire, chicken body parts, pops, bangs, bubbles or whatever in their classroom. So his idea of classroom management is a bit different. Allowing for playfulness is a big objective for him so it does get a bit noisy at times. While there is a bit of freedom to explore, there are also clear behavioural expectations such as: “Being respectful to people around you which includes no talking when I am talking; noise needs to be kept to an acceptable

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Promoting thinking and problem solving in the primary schools, written by Steve Sexton.

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The science lesson Mr Science usually starts a lesson with a short demonstration or ‘WOW’ factor experiment and asks the class to explain what has happened. He runs this activity as a group problem solving exercise, along the lines of think, pair, and share. Usually groups of 3-4 will come up with ideas of what has happened then present them to the rest of the class. If they do get it right away he normally won’t

Mr Science and the parachute.

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chemistry news... Written by Suzanne Boniface International Chemistry Olympiad 2011 This year, the International Chemistry Olympiad (ICO) will be held in Ankara, Turkey. The New Zealand team, selected at a training camp held in the April school holidays, will be the twentieth team to represent NZ at this international competition. NZ sent its first team in 1992, following a scoping visit in 1991 by Dr Robert Maclagan (University of Canterbury) to the 23rd International Chemistry Olympiad in Lodz, Poland. Our first team competed in Pittsburgh, USA, coming home with two bronze medals. Since then New Zealand has sent a team of four students to the International Competition every year, and those students have won a total of 41 bronze medals and 12 silver medals. The ICO was founded in 1968 in Eastern Europe. By1992 there were 132 students from 33 countries involved in the competitition, and last year it was held in Japan with 267 students from 68 countries. In 1992, the Australian Airlines magazine used the term ‘Intellectual Olympics’ to describe the Olympiad competitions. And this is what they are – a real challenge for the very best and brightest minds in Chemistry from around the world. To compete, a student must be under 20 years of age and enrolled in a secondary school. Each country may send a team of up to four students with each student competing on an individual basis. The two days of examinations are arduous, with a practical examination and theoretical examination, each lasting 4–5 hours. The rest of the week is spent marking and adjudication while the students from around the world have time to meet, socialise and

make friends. They are also able to get acquainted with the various aspects of life in the host country. So why is the IOC worthwhile? The opportunity to attend provides a very powerful motivation and challenge for capable students, often attracting top students into a career in science. And because it attracts worldwide participation, the IOC helps to set an international standard of excellence for all Chemistry students. The standard of the competition is so high that each year the questions in the exams would challenge even the best senior undergraduates. And yet the performances of our teams during the past nineteen years demonstrate that the New Zealand education system produces students that are equal to the best in the world. Also, participation in this international competition provides useful contact for students and teachers with their international counterparts, thereby benefiting chemistry education in New Zealand. This year, Dr Maclagan is retiring from his involvement in the NZ Chemistry Olympiad. We would like to thank Robert for all the work he has done over the past 20 years in setting up the NZ Chemistry Olympiad Trust, as well as promoting and organising the selection, training and travel for the NZ teams. Robert’s vision for NZ participation in this competition, and his drive to see us succeed, has benefited several generations of our top chemistry students. Dr Jan Giffney, from St Cuthbert’s College, will succeed Robert as Chair of the Trust. Further information about the NZ Chemistry Olympiad can be found at: http://www.chem.canterbury.ac.nz/ Olympiad/

International Year of Chemistry 2011

Students at this year’s training camp, April 2011. The team members to represent NZ are: Andy Chen (Macleans College), Kailun Wang (Auckland Grammar School), Thomas Fellowes (Christ’s College) and Jade Leung (St Cuthbert’s College).

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International Year of Chemistry events are happening around New Zealand with a variety of international chemists being invited to speak at various times at different centres throughout the year. Visit: http://yearofchemistry. org.nz/ to see what is happening in your area, or for fun things to do with chemistry. And keep checking the website for new and interesting events coming up later in the year – such as ‘knitting the Periodic Table’. For senior secondary students, local branches of the NZ Institute of Chemistry will be running a competition to select a team to attend the National Quiz to be held in Wellington on July 5th. Teams will be hosted by the Wellington Branch of NZIC and Victoria University Wellington and will get a taste of ‘Science in the Capital’ as well as the chance to compete for some great prizes and the top team trophy. For further information contact: Suzanne.Boniface@vuw.ac.nz


Vic Arcus (author of ‘Data deluge needs a modern polymath’, NZST Issue 126) and Miles Barker, the University of Waikato, explore the science/science education interface: Vic Arcus’s eye swept across the little lake, bathed in late summer sunlight, in the centre of the University of Waikato campus. “Think of how incredibly much we know after all these years about E. coli, the most studied organism on the planet – and yet how much we COULD know about everything in this lake. It’s quite within our reach to get all the bacteria, protozoa and plant DNA out of this lake and sequence all of it, but that would just generate a book with no grammar or words, just letters, so superimposing meaning on top of it is an awesome task.” As my conversation with him would show, Vic Arcus, research leader and teacher in the Department of Biological Sciences, is engagingly willing to negotiate and speculate about matters that often fall in the ill-defined but intensely seminal territory between the conduct of professional science and science teaching and learning.1

Future paths for research The growing issue over the next twenty years, according to Vic in his recent article in ‘New Zealand Science Teacher’2 will lie not in our capacity to gather data. Rather, as he explained to me, it will reside in a looming “mammoth divergence between the amount of data we collect and store and our ability to understand it.” I put two well-publicised but conflicting scenarios to Vic. John Horgan’s ‘end of science’ view contends that we may be entering a period of incrementally diminishing returns to questions such as: “Could quarks and electrons be composed of still smaller particles ad infinitum?” and “Just how inevitable was life’s origin and its subsequent history?”3 In contrast, Martin Rees contends that science research will continue to be an unending quest to elucidate the patterns, structures and interconnections that lie beneath such complex questions as how water waves break, and how insects behave.4 Vic is “very much with Martin Rees”; the issue is much more with our limits of conception rather than perception, although Vic admits that powerful new conceptual tools will be needed if the data deluge is to be accommodated. One such tool may be the exciting notions of British physicist Stephen Wolfram, who suggests that underlying complex natural systems may be a small number of very simple ‘rules’ out of which the system may be meaningfully generated.5 For Vic, two other essential elements in coping with the data deluge will be more effective community-scientist dialogue, and the part that schooling might play in nurturing people with sufficiently wide vision to cope with the deluge – polymaths.

Towards more effective dialogue Vic sees community-scientist dialogue as a powerful but under-utilised tool in the quest for meaning and the unification of knowledge.6 Just as the Human Genome Project (unlike the earlier Manhattan Project) involved ethicists from the start, so do wider communities instinctively bring an essential values’ perspective to

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debates about data. And not just the scientific community, but “everyone is a specialist”, according to Vic – market gardeners, lawyers, mechanics and environmentalists can make essential contributions7 and the complex questions of Martin Rees’s scenario (how shoals of kahawai operate; how human aging occurs) map precisely on to those specialisations. Setting up more effective community-scientist forums is a pressing future challenge: “There are simply not appropriate forums available; the so-called debates on climate change and genetic modification, largely carried on by default in the media, have been distressingly ineffectual so far.”

Nurturing polymaths I asked Vic: “Has the age of polymaths – people who, like Francis Bacon, ‘take all knowledge as my province’8 and who may be equipped to deal with the data deluge – now passed? Or are there signs that our education system may yet foster such learners?” Certain features of university education, in Vic’s view, often mediate sadly against the flourishing of widely eclectic scholars: the absence of undergraduate General Studies papers; the lack of kudos accorded time-consuming exploratory dialogue between, say, science and sociology faculty (as opposed to safe, quick in-house discourse); and the lack of encouragement given to youthful fresh speculation in the face of ponderous pronouncements of authority figures. Vic felt unprepared to comment on secondary schools, but he had some encouraging things to say about the primary sector, especially its espousal of pupil research projects: “Our human biological history tells us that we are, intrinsically, all researchers…and children are fantastic researchers.”9 For example, Vic’s son’s collaborative science investigation into ‘Why some swimming pools are faster than others’ had fostered an admirable ability to make sense of a wealth of complex physical, biological and psychological data.

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A parting thought Thinking about my wide-ranging conversation with Vic, I realised how often he had used the phrase ‘scientific literacy’, and how crucial a factor he considers that a pervasive public scientific literacy will be in accommodating the data deluge. Vic himself willingly and earnestly exemplifies the power of scientific literacy – during our conversation he had brought to bear on the data deluge problem ideas from fields as widely dispersed as evolutionary biology10, education and society, the theory of knowledge, and economics.11 For further information contact: mbarker@waikato.ac.nz

Footnotes 1 2 3 4

5 6

7

See Hipkins (2011) for the rationale for this conversation. Arcus (2011). Horgan (1996), pp.6-7. Rees (2010), pp.469, 474. See also Rees’s (2008, p.437) rejection of Horgan’s argument. Wolfram (2002). For Vic, American biologist E. O. Wilson’s (1999) notion of ‘consilience’ epitomises this quest. I noted that Vic’s position resonates strongly with Hipkins’s (2010) eschewing of ‘deficit thinking’ about public debates.

continued on page 36 New Zealand Association of Science Educators

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bathroom scale demos DevelopedbyPaulKing Bathroom scales are cheap enough to have one, two or even four in every lab, and they are useful in any number of ‘real world’ demonstrations of physical principles. And, using ‘big’ equipment always makes lessons more noteworthy. Here are three practicals that use one, two, and four sets of scales.

Moments (all class levels) 1. Using a pair of scales set up the classic seesaw as in the diagram. 2. Have an adventurous student shuffle carefully towards the end of the plank to show that at the tipping point R1 falls to zero, while R2 climbs to be equal to the weight of the plank and the student added together. 3. Take the clockwise moment of the student and show that it is equal to the anticlockwise moment from the weight of the plank. Or use the fact that the moments must be equal to work out the weight of the plank. Then use the scales to confirm it. Perhaps, ask if the students realise how the scales work. 4. Station students at R1 so that they can all experience the lever effect as they, nearly effortlessly, push down and lift the student at the far end. How much further do they push compared to the rise of the student?

Reaction forces and angles (senior classes) 1. Support the lab plank at various angles to the horizontal (see diagram). The scales will want to slide so some form of stop against the feet of the scales will probably be needed; I tacked a sheet of hardboard to the plank. 2. With a person of known weight (W) record on a table the scale readings for several different angles (). At the very least the students will recognise that 30˚ constitutes a very steep slope. 3. For each angle the students should calculate the expected Normal reaction force from the scales (W cos ). How close is the agreement? I found good agreement below 20˚, with widening disagreement  at 30˚, but still within the (rather generous) error bounds. I didn’t try any steeper than 30˚– too inflexible. 4. Discuss: Does the disagreement between the calculated result and the measured result have any significance? What are your error bounds?

Reaction forces and dynamic loading

Womeninscienceconference

1. Using four scales, one under each leg of the stool, have teams of recorders noting the reaction forces on each leg of the stool as one student ‘squirms’ into a number of contorted positions in their vain search for comfort. 2. Put the scales under the legs of a table, and walk on it. Even run on it, to trigger debate about dynamic loading. It is certain that both you and your students can develop your own innovative demonstrations using this simple equipment and when you do, please…share it with us!! For further information contact: dhousden@xtra.co.nz

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women in science conference Association of Women in Science Conference Venue: Skycity, Auckland Date: 28 t0 29 July Are you interested in hearing from women working in the NZ science sector? The Association for Women in the Sciences (AWIS) is running its sixth triennial conference in July. The Conference theme, Developing Women – Advancing Science, will provide a forum for women who have an interest in science, including science educators and students. Speakers include: TVNZ meteorologist Karen Olsen, biotechnology entrepreneur Jilly Evans, academic researcher Gillian Lewis and former MacDiarmid Young Scientist of the Year Claire French. The programme also includes a panel discussion on ‘Current challenges in New Zealand science’, chaired by Di McCarthy, CEO of the Royal Society. Speakers will include New Zealand Association of Science Educators

Helen Anderson, former Chief Executive of the Ministry of Research, Science and Technology, to give her perspective on science policy; Professor Jane Harding, Deputy Vice Chancellor (Research) at The University of Auckland, who will talk about science in academia; Tracey Sunderland, Chief Operating Officer of CoDa Therapeutics, speaking about science and industry; and Lindsey Conner, President of the NZASE, talking about science education. The Conference programme has three concurrent streams: Professional Development, Personal Development and Science snapshots. The Science snapshot sessions are likely to be of particular interest to science teachers and students because women working in the following five areas will talk about their work and experiences: Nanotechnology, Chemistry, Food security, Climate change and Medical science. Science teachers may also be interested in the Communicating with schools session, which looks at ways in which scientists are interacting with school students. For more information visit: awis.org.nz/conference2011


NZ

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proving that Earth is old Bristlecone Pines (California) indicate Earth is 8000 years (min). Because these trees live up to 4000 years due to their resinous wood, grow in very cold climates, and dead wood decay is extremely slow dead and live wood annual rings provide a continuous chronology of more than 8,000 years. European Oaks (Europe) indicate Earth is 10,434 years (min). Oak trees chronologies from the same species in two or more different locations are cross correlated with other species and climatic markers (such as the Little Ice Age – a cold period between 1550 AD and 1850 AD). All the species show the same trends in world climate whenever they overlap. German Pine (Germany) indicate Earth is 12,405 years (min). A significant climate marker seen in the dendrochronology is the Younger Dryas, a very cold period about 12,000 years ago. The above three methods of tree ring dating cross correlate with an error of only about 0.5%. This also means that there was NO worldwide flood during the past 12,405 years, as there would be no possible overlap of tree ring chronologies if the trees were dead. Tree rings are also used to calibrate the carbon-14 dating method making it more accurate.

2. Varve layers Cores taken from the centre of Lake Suigetsu in Japan indicate Earth is 35,987 years (min). The varve layers are created by spring diatom growth seen in the sediment cores as alternating dark-coloured clay with white layers.

3. Ice cores Dunde Ice Core (China) indicates Earth is 40,000 years (min). Taken from the mountain range between Qiadam Basin and the Gobi, where snow has been accumulating for 40,000 years (back to the last ice age) the core has layers of dust from the surrounding desert. Climate information from the oxygen isotope ratio (16O to 18O) matches known climate and environment markers such as dust and pollen from variations in the summer monsoon. Vegetation in the Qinghai-Tibetan Plateau region is sensitive to abrupt, century-scale climatic changes and so will be very useful to monitor greenhouse warming. Greenland Ice Cores indicate an Earth age between 37,957 and 250,000 years. These cores provide information on long-term (millennial, supra-millennial) and short-term (sub-millennial to annual or seasonal) cycles or trends in the Earth’s past environmental history, as well as on important one-off events, such as major volcanic eruptions or particularly pronounced climatic shifts. The annual ice layers can be visually counted because the summer snow has coarser crystals than winter snow due to the sun (which only shines in the summer) and give an Earth age of 37,957 years (min). However, in late winter and early spring winds blow dust onto the snow from as far away as the Southern Hemisphere. The annual dust layers indicate an Earth age of 60,000 years (min). Ice layers, in different cores, have been counted down to 100,000 yr BP without coming to an end and can be used to determine even subtle and fast climate i

This article is adapted from an article written by Paul Smith, http://razd. evcforum.net/Age_Dating.htm

change events. The Little Ice Age, Medieval Warm Period and the Younger Dryas periods are examples of climate markers that show up in ice cores, and these cross correlate with oxygen isotope ratios, and with tree ring data. Annual layers can also be distinguished via the electrical conductivity of the layers, indicating an Earth age of about 110,000 years. Volcanic ash layers also correlate with similar layers found in Atlantic sea cores and the annual measurement of layers by measuring dust levels correlates with volcanic eruptions and the other dating methods for the layers down to 250,000 yr BP. Antarctica Ice Cores indicate Earth is aged 422,776 to 900,000 years (min). Trapped bubbles of atmospheric carbon dioxide, methane and nitrous oxide are measured and variation found can be used to cross correlate the ice cores from different sites. Annual layers in the Vostok Ice Core indicate the age is 422,776 but 70 metres of ice (the EPICA Ice Core) has now been drilled which means that records now go back more than 900,000 years. The ice at the bottom of these drillings has some ice crystals bigger than 40 centimetres.

earthsciencespaceeducators

Students often want to know how we can be so sure that the Earth is old. Here is a useful list of methods with cross correlationsi, writes Jenny Pollock. 1. Dendrochronology (Tree rings)

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4. Speleotherms Devils Hole (Nevada) calcite deposition radiometric analysis indicate Earth aged 567,700 years. Devils Hole is a tectonically-formed cavern in south-central Nevada where water drips down the cave walls, depositing calcite and various other minerals and impurities, elements that are soluble in water, including trace levels of radioactive isotopes of uranium which can then be used for radiometric dating. The insoluble Thorium-230 is measured which has decayed from the soluble Uranium-234. The calcite was deposited after being dissolved in water so the Th-230 could only come from the decay of the parent U-234, giving an accurate measurement of the age of the layers of calcite. The short-lived Pa-231 can also be measured. Buried in the calcite layers are also the elements of oxygen and carbon, and the ratios of oxygen-18 to oxygen-16 and of carbon-13 to carbon-12 are markers of climate.

5. Corals Coral growth indicate Earth aged >400,000,000 years. Calcium carbonates produced biologically (such as corals, shells, teeth, and bones) take in small amounts of uranium, but not thorium. A new coral reef has no thorium-230 but as it ages, some of its uranium decays to thorium-230. The uranium-234/thorium-230 method has been used to date corals for several decades. Coral heads also put down seasonal growth layers (just like trees). Ancient corals also record variations in the Earth’s rotation because it affects the tidal forces and slows down 2 sec per 100,000 years. Day length has increased throughout geological time and that the number of days per year has decreased (e.g. 400 day/ year – Devonian, 390 day/year – Pennsylvanian), so there is very close correlation between the predicted number of days, the measured number of days and the measured age of the fossil corals.

6. Radiometric correlations There are over 40 different radiometric dates that show a consistent accuracy to the methods used, and an age for the Earth of ~4,500,000,000 years old. The above dating methods agree (most of the time), with differences close to the margin of error, giving a scientific Earth age of ~4,500,000,000 years. For further information contact: jenny.pollock@xtra.co.nz New Zealand Association of Science Educators

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science education priorities By Ian de Stigter, ScienceTechnician, Mt Albert Grammar School In July 2009, Professor Sir Peter Gluckman, the newly appointed Chief Science Advisor to the Prime Minister, spoke to the science research community about bringing NZ science out of the ‘doldrums’, with an emphasis on the contribution that scientific research and successful transfer of research findings would make to transforming New Zealand society. The primary vehicle of that transformation was to be economic, based on science and technology businesses. He added that research funding had to be better directed, and better arrangements had to be developed for technology transfer. There have since been steps to rationalise the use of public research facilities. Sir Peter has subsequently moved his focus to science education, which has for decades been under-resourced and given scant attention. In doing so he has demonstrated a broadened perspective of science imperatives by recognising science education as itself having a direct major role in bringing about important social changes. In his April 2011 paper Looking Ahead: Science Education for the Twenty-First Century, Gluckman reviewed ideas about what may be needed to develop more effective and appropriate science education. An August 2010 background paper from NZCER Inspired by Science identified the reasons for publicly funding a science education and discussed what is currently being provided. The general level of science education in New Zealand has compared favourably with that in other countries, although the proportion of under-achievers is a concern. This led in turn to a November 2010 discussion paper from the Prime Minister’s Science Advisory Committee, Engaging Young New Zealanders with Science. Priorities for Action in School Science Education, which incorporated feedback from many in the education sector. This paper acknowledged that successes of science education in New Zealand compulsory education had been achieved by teachers with limited resources. The limits to resources were not examined, but some future additional resources were proposed. Whereas the implicit purpose for secondary science education has in the past been preparation for a career in science or a related discipline, the New Zealand Curriculum sets a different direction for learning, with science seen as an investigative process of solving problems rather than a body of required knowledge. The growing importance of science to society means that science education is not only for those intending a science career. Sir Peter agrees it is essential that all citizens have some level of understanding of the scientific issues that governments and society confront. Sir Peter believes, however, that a curriculum based on citizen-focused objectives will not be adequate to prepare students for tertiary science studies. He suggests that separate streams for these distinct purposes might be useful. In addition to needing continuous professional development to keep teachers abreast of science developments and technology, teachers will be challenged to teach students with different learning objectives together. To attempt this, science teachers will need in-school resourcing at a level not currently available. The Ministry of Education/NZEI/NZSTA Support Staff Working Group Phase Two Report of March 2011 considered the goal of using support staff to enhance achievement of education outcomes for students. While recognising that

New Zealand Association of Science Educators

some schools were exemplars in aspects of this, the report found that qualified and experienced support staff had a greater contribution to make than was being utilised. It was recommended that the three parties in the working group consider exploring what constitutes best practice in the working relationships of teachers and support staff. This recommendation goes well with the comments which follow, about supporting science education in secondary schools. Robyn Baker, in the 1997 NZASE report Science technicians in New Zealand secondary schools, suggested the need for more support in science education: “The level of support given to teachers of science for the practical components of their classroom programme has always been a problematic area for New Zealand teachers. In a survey undertaken by NZASE in 1996 science teachers commented that while many aspects of teaching were common to all subjects, the laboratory preparation, the maintenance of resources, and the management of practical activities with large classes placed additional demands on them as teachers.” In a 2009 study of science technician resourcing in Australian secondary schools, Hackling wrote that, “Authentic and inquiry-oriented science curricula that engage students and inspire them to continue their studies in science... depend heavily on good facilities and high quality technical support.” Science technical support levels in New Zealand secondary schools are variable, but the median of technician hours/ teaching hours (support factor) is less than half that which Australian schools have and consider seriously inadequate. It is evident that those schools which have little technician support relative to their science teaching hours could provide more technician hours for basic technician duties, including administration. There is also an emerging trend for science technicians to be promoted to manage laboratories, with assignment of varying degrees of additional responsibility to relieve the load of science teachers and department or faculty heads. This appears to be a cost-effective solution to increased teaching demands on science teachers. If young New Zealanders are to be enthused by science and enabled to participate in it, then plans need to be laid for an interesting and challenging practical science programme. The answers are not all to be found in visits to research facilities and Internet links with scientists. Given that in-school resources are acknowledged to be a constraint for science learning in compulsory education, it is disappointing that Sir Peter’s advisors have not pressed for closer attention to this constraint. While school laboratory resourcing will always be more limited than judged to be ideal, steps are required to provide resourcing in an efficient and cost-effective manner. Part of the solution is in developing the potential of science technicians, so releasing teachers to be continuously developing their scientific and teaching skills, and to inspiring the next generation of learners. For further information contact: bemckinnell@papatoetoehigh.school.nz Disclaimer: The views expressed in this article are not necessarily those of the NZASE – Ed.


EARTH AND SPACE SCIENCE BIENNIAL FIELD TRIP 2011 From Mt John Observatory in Tekapo to Kaikoura Craig Steed - Convenor, Email: SteedC@freyberg.ac.nz

If you are interested contact jenny.pollock@xtra.co.nz

National NZIP Conference

CONSTANZ ‘11

The 15th National NZ Institute of Physics Conference

The Science Technicians’ Association of NZ Conference 2011

17-19 October 2011

10 to 12 October 2011

Victoria University, Wellington Energise your physics teaching with three days of ideas, stimulation and interactions! For further details visit: www.nzip.org.nz

John McGlashan College, Dunedin This Conference will appeal to all school science technicians, and also some technicians from tertiary institutions (such as Polytechnics) For further information contact: Margaret Woodford - Conference Convenor, Margaret.Woodford@kvc.school.nz or

CONSTANZ ‘11 Anne-Marie Pulham - Secretary, ampulham@kavanagh.school.nz


NZASE #127  

New Zealand Science Teacher #127

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