Investigating Undergraduate Engineering Students' Motivations: An Early-Stage Analysis

Ribhav Galhotra; Panting Yu; Jiafei Wang; Ibrahim H. Yeter

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: July 12, 2024
Conference Session: Educational Research and Methods Division (ERM) Technical Session 3
Tagged Division: Educational Research and Methods Division (ERM)
Permanent URL: https://peer.asee.org/47704

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Paper Authors

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Ribhav Galhotra Nanyang Technological University

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Ribhav Galhotra is a senior undergraduate pursuing a double degree in Aerospace Engineering and Economics at Nanyang Technological University, Singapore. He is working on research projects relating to undergraduate engineering education as part of Dr. Yeter’s research team. With a keen interest in aerospace technologies and education, Ribhav has a strong inclination to enhance the education systems for the development of future engineers.

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Panting Yu The University of Edinburgh

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Panting Yu earned a master's degree in education from the University of Edinburgh, Scotland. As a STEM teacher, she plays an integral role in Dr. Yeter’s Research Team, bridging academic research with daily educational practice. Panting brings expertise in educational and practical studies, providing a unique perspective on STEM+C teaching and educational innovation.

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Jiafei Wang The Education University of Hong Kong

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Jiafei Wang is a master student majoring in STEM Education at The Education University of Hong Kong. He actively participates in Dr. Yeter’s Research, focusing on projects related to engineering education and computational thinking. Drawing on his experience as a mechanical engineer, Jiafei's comprehensive understanding on engineering education allows him to develop innovative ideas that enrich learning experiences for engineering students.

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Ibrahim H. Yeter Nanyang Technological University orcid.org/0000-0002-0175-2306

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Ibrahim H. Yeter, Ph.D., is an Assistant Professor at the National Institute of Education (NIE) at Nanyang Technological University (NTU) in Singapore. He is an affiliated faculty member of the NTU Centre for Research and Development in Learning (CRADLE) and the NTU Institute for Science and Technology for Humanity (NISTH). He serves as the Director of the World MOON Project and holds editorial roles as Associate Editor of the IEEE Transactions on Education and Editorial Board Member for the Journal of Research and Practice in Technology Enhanced Learning. He is also the upcoming Program Chair-Elect of the PCEE Division at ASEE. His current research interests include STEM+C education, specifically artificial intelligence literacy, computational thinking, and engineering.

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Abstract

This study examines students' motivations and learning strategies at an undergraduate-level engineering education. The Motivated Strategies for Learning Questionnaire (MSLQ) compares the value engineering students obtain from their education and learning strategies with their expectancy of success, which is the main instructional method in this research. The students rate themselves on a seven-point Likert scale, with one being ‘very unlike them’ and seven being ‘very much like them.’ The survey questions split motivational factors into (a) intrinsic goal orientation, (b) extrinsic goal orientation, and (c) task value. Learning strategies can be categorized into more specific groups, including cognitive methods such as rehearsal, organization, and critical thinking. Students may expect success in different forms based on their motivations, which can be associated with their self-efficacy and self-regulation. The overarching research question is, what are the associations between undergraduate engineering students' motivation and learning strategies? This study collected data from a single engineering discipline from thirty-five undergraduate engineering students in Singapore. A statistical analysis method based explicitly on Cronbach’s alpha coefficient will identify the reliability of the scales, and the following analysis using the Pearson correlation coefficient and the Mann-Whitney U test provides comparative details. The results convey high correlations among certain motivational factors and learning strategies and specific differences between the results based on the sample in Singapore and general work that is also based on MSLQ. This could enable an understanding of the effectiveness of undergraduate engineering education in Singapore and whether the undergraduate programs may be overly demanding for students. Singapore university students come from diverse secondary school academic backgrounds. Thus, identifying engineering undergraduates' motivational strategies for learning could help cater to the wide variety of students in the region. Considering this, a teaching system based on increasing the value of engineering education for the students could be designed in the future, helping students to further their interest in engineering fields and obtain sustained success. Future studies will be performed to include a larger representative sample and analysis of learning styles not mentioned in the questionnaire.

Citation
Format

Galhotra, R., & Yu, P., & Wang, J., & Yeter, I. H. (2024, June), Investigating Undergraduate Engineering Students' Motivations: An Early-Stage Analysis Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47704

TY - CPAPER
AB - This study examines students&#39; motivations and learning strategies at an undergraduate-level engineering education. The Motivated Strategies for Learning Questionnaire (MSLQ) compares the value engineering students obtain from their education and learning strategies with their expectancy of success, which is the main instructional method in this research. The students rate themselves on a seven-point Likert scale, with one being ‘very unlike them’ and seven being ‘very much like them.’ The survey questions split motivational factors into (a) intrinsic goal orientation, (b) extrinsic goal orientation, and (c) task value. Learning strategies can be categorized into more specific groups, including cognitive methods such as rehearsal, organization, and critical thinking. Students may expect success in different forms based on their motivations, which can be associated with their self-efficacy and self-regulation. The overarching research question is, what are the associations between undergraduate engineering students&#39; motivation and learning strategies? This study collected data from a single engineering discipline from thirty-five undergraduate engineering students in Singapore. A statistical analysis method based explicitly on Cronbach’s alpha coefficient will identify the reliability of the scales, and the following analysis using the Pearson correlation coefficient and the Mann-Whitney U test provides comparative details. The results convey high correlations among certain motivational factors and learning strategies and specific differences between the results based on the sample in Singapore and general work that is also based on MSLQ. This could enable an understanding of the effectiveness of undergraduate engineering education in Singapore and whether the undergraduate programs may be overly demanding for students. Singapore university students come from diverse secondary school academic backgrounds. Thus, identifying engineering undergraduates&#39; motivational strategies for learning could help cater to the wide variety of students in the region. Considering this, a teaching system based on increasing the value of engineering education for the students could be designed in the future, helping students to further their interest in engineering fields and obtain sustained success. Future studies will be performed to include a larger representative sample and analysis of learning styles not mentioned in the questionnaire.
AU - Ribhav Galhotra
AU - Panting Yu
AU - Jiafei Wang
AU - Ibrahim H. Yeter
CY - Portland, Oregon
DA - 2024/06/23
PB - ASEE Conferences
TI - Investigating Undergraduate Engineering Students' Motivations: An Early-Stage Analysis
UR - https://peer.asee.org/47704
ER -