Taking teaching and learning to the next level

The University of Pretoria’s commitment to ensuring that its teaching and learning initiatives enable students to excel and graduate in the minimum time set out for a degree, and to continue to pursue postgraduate studies, is entrenched in a culture of excellence. With the assistance of the Department of Higher Education and Training (DHET) in the form of the Scholarship of Teaching and Learning (SOTL) grant, its academics have the opportunity to develop projects that will enhance their teaching and learning outcomes.

The DHET’s SOTL grants are awarded to academics to undertake research into the teaching of their discipline with the aim of developing their teaching and research capacity and improving student learning. The funds form part of the University’s Teaching Development Grant. The purpose of this grant is to promote institutional research to improve teaching and student learning and success.

In 2019, the Faculty of Engineering, Built Environment and Information Technology was fortunate to receive ten such grants across its three schools, which enabled the related research to be conducted in 2020.

This study is based on the hypothesis that interacting with real-life settings in design assignments as part of learners’ formation could benefit from a biophilic affinity for the living world to foster both experiential and transformative learning. It verifies the degree to which the exposure to real-life social and environmental living complexities in design projects stimulates learners’ learning processes and improves the final design outcomes.

Dean’s Office

ENGINEERING DIAGNOSTIC TEST

An engineering diagnostic test, which was written by all first-year Engineering students, was evaluated to determine its internal and external validity as a predictor of student success. This evaluation determined that the test was not measuring clear constructs, while the readiness test was found to be a weak predictor of engineering success. Considering other data, there were also no clear indicators of student success. In response to this, research is being conducted to target the issues of spatial visualisation and psycho-social skills more narrowly, as well as to conduct focus group interviews to interrogate students’ perceptions.

THE DEVELOPMENT OF A 3D APP FOR THE Department of Mechanical and Aeronautical Engineering

The first implementation of the 3D app is to aid in the understanding and interpretation of the thermodynamic properties of water. The database containing these properties was developed from current work in thermodynamic relations using free energy. Eight inter-related thermodynamic relations were incorporated into the database for rendering as 3D surfaces, with a fourth variable plotted using contours on this 3D surface.

To examine the phenomenon of scholarly assessment, a research project would be conducted to find an answer to the question: “How can a more scholarly approach towards assessment design be improved?” The research question would culminate in the development of an assessment application, embedded in a cognitive taxonomy, to provide structured guidance to university lecturers towards a more scholarly approach when designing assessment instruments such as test and examination papers.

The purpose of this research study was to develop a web-based platform that would facilitate the learning of INF 271 and INF 370 students. The INF 271 module provides an important foundation for preparing students to successfully complete the INF 370 capstone project. The initial framework of the platform has been developed and includes theoretical content, examples, lessons learnt and links to videos to two of the main study units of the module. The initial version of the platform has been released and feedback has been obtained.

A significant finding of research conducted on hybrid learning is that the members of Generation Z rely heavily on their peers for assistance, even though literature says their social skills are underdeveloped. This means that, as academics, we need to understand this generation and how they prefer to study, and then create content and tools for them so that they can indeed broaden their own knowledge and become lifelong learners.

The purpose of this research was to understand the way in which collaboration tools could assist with team construction and the enhancement, support and assessment of teamwork. To gain a deeper understanding of the factors that contribute to successful teamwork, data was gathered on the way in which students form project teams. This data has been linked to the iPeer assessment done throughout the year, as well as on the eventual project outcomes and success of each team.

Department of Informatics

Key findings related to the first-year Critical Thinking and Problem-solving module included evidence of the value of exposing students to a Maker philosophy, as well as design thinking, when presented with tasks that required creative problem solving. From feedback surveys, it was found that the teaching of critical thinking assisted students not only to analyse arguments, but also to better read and understand their exam questions and better evaluate online information.

Department for Education Innovation

The iPeer tool can be used for teamwork assessment and provides insight into team dynamics and individual performance. Sufficient data was attained to inform the design of an e-learning resource for “teamwork fundamentals”. The envisaged resource will create a learning opportunity for all students in the Faculty. A national and international collaborative network has been established to expand the iPeer project to better serve the Faculty’s students in teamwork across all borders and disciplines.

USING GENETIC PROGRAMMING AND Department of Computer Science

The main aim of this research study was to employ genetic programming to predict student performance. Two models were evolved using genetic programming. The first was a regression module to predict the student’s mark. The second was a decision tree classifier to predict whether the student would pass or fail. The approaches were applied to two Computer Science modules. Both models were found to predict the final mark and result based on the students’ semester marks. This would facilitate identifying students that would not pass and put support mechanisms like boot camps in place to assist these students.