COMPARISON OF R AND MATLAB SIMULINK in Educating High School Students with ODE Modeling Skills

Abstract

US high school (HS) students are lagging behind their foreign peers in math performance. It is thus necessary to design teaching modules that motivate US HS students to learn more math and to improve their math skills. Our study set out to test two different software programs designed for the development of such skills. MATLAB Simulink provides a friendly interface with which HS students can build ordinary differential equation (ODE) models. An alternative programming language, the R language is free and extensively used in the field of statistical learning and engineering. In this study, a group of HS students first got trained in both Simulink and R and then solved an ODE model of a microbial fuel cell (MFC), which can convert the organic compounds found in waste water into electricity, using both Simulink and R. Three anonymous surveys were conducted for: 1) students' feedback on the module-based teaching approaches with R and Simulink training, 2) students' self-evaluation in the improvement of their skills in solving ODE models following their training in R and Simulink, and 3) students' comparison of R and Simulink in their learning and modeling experience. The instructor also evaluated students' modeling skills with R and Simulink based on their performance in developing the MFC ODE model. Both students' self-evaluation and the instructor's direct evaluation indicate that students' skills in solving ODE models with both R and Simulink were significantly improved after this R-Simulink modeling project. The surveys show that students generally enjoyed the module-based teaching format and that they would recommended this project to their peers. It was shown in the surveys that students preferred Simulink over R in solving ODE models and that they preferred learning Simulink first and then following up by learning R. Students' comments for opening questions indicate that the major hurdle in this project was their limited background knowledge in biology and electrochemistry for microbial fuel cells.