<b>COMPUTATIONAL MODELING AND SIMULATION EXPERIENCES OF UNDERGRADUATE ENGINEERING STUDENTS</b>

<p dir="ltr">Computing has become an essential component of engineering, and one of the fundamental skills engineering students need to develop is modeling and simulation, which is often supported by computational methods. To this end, this three-paper dissertation explores the experiences of biomedical and agricultural undergraduate engineering students as they engage in computational modeling and simulation. Here, students learn disciplinary content and apply computer programming to model physical and biological processes while collaborating in teams. The first study investigates changes in the self-beliefs of second-year students taking a thermodynamics course after completing three computational modeling projects. The results suggest an improvement in their programming self-efficacy. The second study investigates the effects of a team-based modeling intervention aimed at supporting fourth-year students’ self-regulated learning in computational modeling assignments. The results highlight students’ self-reported confidence levels, indicating that seven teams reported an increase in confidence as the project progressed, three teams reported a decrease, and two teams initially struggled but experienced an increase in confidence upon completing the assignment. The third study examines the commitments made towards team coordination by second-year students in a thermodynamics course. The results reveal four characterizations of the teams’ coordination commitments: Scheduling and Meeting Coordination, Task Management and Delegation, Collaboration and Teamwork, and Time Management, with a shift in emphasis across the three projects. In Project 1, the emphasis was on Task Management and Delegation, which shifted to Scheduling and Meeting Coordination in Project 2, and then to Collaboration and Teamwork in Project 3. Time Management remained consistent across all three projects. Altogether, the three studies highlight the need for instructional approaches that support engineering students’ learning beliefs and learning behaviors during computational modeling and simulation.</p>