The Effect of ElectronixTutor on Undergraduate Students' Acquisition of Conceptual Learning, Problem Solving, and Model Building of Electronic Circuits

We investigated whether an intelligent tutoring system, ElectronixTutor, improved students' types of knowledge, including conceptual learning, problem-solving, and model building in the domain of electronic circuits. Specific research questions were (1) Can students improve their deep learning through interacting with ElectronixTutor through conceptual learning, problem-solving, and model building modules? And (2) What are student learning characteristics as they proceed through each model and learning mode? We conducted a recorded interview procedure with 10 participants as they learned with ElectronixTutor, and gave them a pre-, mid-, and posttest in order to assess their overall learning gain as well as learning transfer. We found that, although there were no significant effects due to our small sample size, the results from the means suggest both learning gain and learning transfer. Qualitative analyses were conducted on each of the three different learning modes. Collectively we found that participants were very good at problem-solving using equations and writing formulas but struggled on the application or conceptual questions. Our study suggests that there is a need for building or improving more sophisticated learning or tutoring technologies on STEM domains that focus on the integration of knowledge and skills.