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Title: Work in Progress: A Study of Variations in Motivation and Efficacy for Computational Modeling in First-year Engineering Students
Computational modeling skills are critical for the success of both engineering students and practicing engineers and are increasingly included as part of the undergraduate curriculum. However, students' belief in the utility of these skills and their ability to succeed in learning them can vary significantly. This study hypothesizes that the self-efficacy and motivation of engineering students at the outset of their degree program varies significantly and that engineering students pursuing some disciplines (such as computer, software, and electrical engineering) will begin with a higher initial self-efficacy than others (such as materials science and engineering and biomedical engineering). In this pilot study, a survey was used to investigate the motivational and efficacy factors of approximately 70 undergraduate students in their first year of engineering studies at a large public university. Surveys were implemented after students were introduced to MATLAB in their first-year engineering design course. The data was analyzed for variations in baseline motivation based on the students' intended major. The results of this survey will help determine whether efficacy and interest related to computational modeling are indeed lower for certain engineering disciplines and will inform future studies in this area.  more » « less
Award ID(s):
2025093
NSF-PAR ID:
10350501
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
2021 IEEE Frontiers in Education Conference (FIE)
Page Range / eLocation ID:
1 to 6
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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