A mechanism was designed to synergize theoretical and computer-aided engineering (CAE) education using Simscape Multibody developed by Mathworks Inc. Educational outcomes were examined by observing students' scores in theory and CAE assignments after each class via decision tree analysis and Bayesian networks. The decision tree analysis showed that the scores on a calculation of gear dimensions influenced the grades of the students the most and were related to their understanding of CAE. Students with high assignment scores were eventually able to model and simulate a mechanism described in a technical book, which was a synergistic effect of theoretical and CAE education. However, it was observed that students with poor assignment scores were inept in the CAE learning process, leading up to the quadric crank chain mechanism. The Bayesian networks showed low dependency between classes in the CAE learning process, which implied that the intended educational outcomes were not achieved. Based on these analyses, which were demonstrated to be effective in evaluating class design, the curriculum, time allocation, and follow-up system of the educational process will be improved and classes will be conducted effectively.
Read full abstract