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Motivational and Self-Regulated Learning Profiles of Students Taking a Foundational Engineering Course

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Bibliographic Details
Title: Motivational and Self-Regulated Learning Profiles of Students Taking a Foundational Engineering Course
Language: English
Authors: Nelson, Katherine G., Shell, Duane F., Husman, Jenefer, Fishman, Evan J., Soh, Leen-Kiat
Source: Journal of Engineering Education. Jan 2015 104(1):74-100.
Availability: Wiley Periodicals, Inc. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 27
Publication Date: 2015
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Metacognition, Engineering Education, Profiles, Barriers, Majors (Students), Student Motivation, Correlation, Gender Differences, Computer Science Education, Student Attitudes, Undergraduate Students
DOI: 10.1002/jee.20066
ISSN: 1069-4730
Abstract: Background: Technical, nonengineering required courses taken at the onset of an engineering degree provide students a foundation for engineering coursework. Students who perform poorly in these foundational courses, even in those tailored to engineering, typically have limited success in engineering. A profile approach may explain why these courses are obstacles for engineering students. This approach examines the interaction among motivation and self-regulation constructs. Purpose (Hypothesis): This project sought to determine what motivational and self-regulated learning profiles engineering students adopt in foundational courses. We hypothesized that engineering students would adopt profiles associated with maladaptive motivational beliefs and self-regulated learning behaviors. The effects of profile adoption on learning and differences associated with student major, minor, and gender were analyzed. Design/Method: Five hundred and thirty-eight students, 332 of them engineering majors, were surveyed on motivation and self-regulation variables. Data were analyzed from a learner-centered profile approach using cluster analysis. Results: We obtained a five-cluster learning profile solution. Approximately 83% of engineering students enrolled in an engineering-tailored foundational computer science course adopted maladaptive profiles. These students learned less than those who adopted adaptive learning profiles. Profile adoption depended on whether a student was considering a major or minor in computer science or not. Conclusions: Findings indicate the motivational and self-regulated learning profiles that engineering students adopt in foundational courses, why they do so, and what profile adoption means for learning. Our findings can guide instructors in providing motivational beliefs and self-regulated learning scaffolds in the classroom.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1255329
Database: ERIC
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Abstract:Background: Technical, nonengineering required courses taken at the onset of an engineering degree provide students a foundation for engineering coursework. Students who perform poorly in these foundational courses, even in those tailored to engineering, typically have limited success in engineering. A profile approach may explain why these courses are obstacles for engineering students. This approach examines the interaction among motivation and self-regulation constructs. Purpose (Hypothesis): This project sought to determine what motivational and self-regulated learning profiles engineering students adopt in foundational courses. We hypothesized that engineering students would adopt profiles associated with maladaptive motivational beliefs and self-regulated learning behaviors. The effects of profile adoption on learning and differences associated with student major, minor, and gender were analyzed. Design/Method: Five hundred and thirty-eight students, 332 of them engineering majors, were surveyed on motivation and self-regulation variables. Data were analyzed from a learner-centered profile approach using cluster analysis. Results: We obtained a five-cluster learning profile solution. Approximately 83% of engineering students enrolled in an engineering-tailored foundational computer science course adopted maladaptive profiles. These students learned less than those who adopted adaptive learning profiles. Profile adoption depended on whether a student was considering a major or minor in computer science or not. Conclusions: Findings indicate the motivational and self-regulated learning profiles that engineering students adopt in foundational courses, why they do so, and what profile adoption means for learning. Our findings can guide instructors in providing motivational beliefs and self-regulated learning scaffolds in the classroom.
ISSN:1069-4730
DOI:10.1002/jee.20066