An App-Building Approach to Teaching Computational Thinking and Coding in High School Biology NSF Award #1742373 A Sustainable Computer Modeling Curriculum for Mastery of Core Biology Concepts and Computational Thinking by Secondary School Students
The Premise of the Project
J Bret Bennington, Chair, Department of Geology, Environment, and Sustainability S. Stavros Valenti, Senior Associate Dean of Student Academic Affairs, Department of Psychology Krishnan Pillaipakkamnatt, Chair, Department of Computer Science Lian Duan, Department of Information Systems and Business Analytics Roberto Joseph, Department of Teaching, Learning, and Technology
Using Computation to Master Biology Concepts
We believe that by teaching students to code their own apps to accomplish tasks and investigate problems encountered in the Living Environment Biology Curriculum we can increase their interest in computational and STEM careers while helping them master concepts in biology.
Students explore important biological concepts such as trophic interactions in ecology using apps that model biological systems.
App Inventor
Some apps are pre-coded and some are coded by the students themselves. Students can access and modify the code in all of the apps.
MIT App Inventor is an intuitive, visual programming environment that allows students to build fully functional apps for smartphones and tablets. AI is freely available and is browser-based, requiring little investment on the part of schools wishing to use it.
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Laboratory exercise using the ecology simulation app
Coding to Apply Computational Thinking to Solving Biology Problems
Curriculum Development Year One of the project (2018-2019) was spent working with a group of seven teachers to identify topics, concepts, and lab activities in the Living Environment biology curriculum that benefit from a computational approach. Curriculum modules have been created for these topics that teach the students fundamentals of coding and computational thinking in the context of building apps that help them learn and experiment with the biological concepts taught in the Living Environment.
Curriculum Rollout Year Two (2019-2020) of the project saw the computationally enriched Living Environment curriculum piloted by the participating teachers. In Year Three / Four of the project (2020-2022) all of the participating teachers will use the new curriculum in their classes (Note: this phase of the project has been interrupted by the COVID pandemic).
Student Coding Exercises Teachers can chose from three versions of each curriculum module, tailored to how much prior experience students have had with coding. Exercises are scaffolded so that students with different levels of experience can learn the biology concepts while gaining new coding skills. This allows a classroom of students to work on the same topic, each at their comfort level, and it allows teachers to utilize different modules at any point in the school year.
Screenshot of the ecology simulation app
Computational Thinking • Abstraction creating a simple model of a complex system • Algorithmic thinking breaking a problem down into ordered steps • Programmatic thinking translating steps into computer code
• App to perform simultaneous metric conversions from any starting unit input
• App to assess hypertension level from blood pressure readings input
• App to calculate total magnification from objective and eyepiece magnification input
• App to simulate homeostasis in glucose regulating hormones
• App to transcribe and translate an input nucleic acid base sequence
Pre-coded Apps for Experimentation / Advanced Coding Teachers can opt to provide students with pre-coded, fully functional apps and accompanying lab exercises that engage the students in using computation to perform simulations and experiments to model important biological concepts. Students can “look under the hood” of these apps to learn how they are coded and to make modifications to the code to change their look or expand their functionality.
Assessment To assess the impact of the computationally enriched curriculum on students, data will be collected from both control and treatment groups measuring attitudes toward STEM and computer careers, application of computational thinking to problem solving, and mastery of key concepts in the biology curriculum.
• App and lab exercise to simulate how natural selection and sexual selection work to determine the mix of phenotypes in a population
• App and lab exercise to make Punnett square calculations of genotype and phenotype frequencies for combinations of alleles
• App and lab exercise to simulate the effect of sample size on statistical confidence in experimental outcomes
• App and lab exercise to help students learn the sequence of cellular events and the differences between mitosis and meiosis
• App and lab exercise to simulate the dynamic relationships between primary producer, herbivore, and carnivore populations