Baltimore , Maryland
June 25, 2023
June 25, 2023
June 28, 2023
Educational Research and Methods Division (ERM)
21
10.18260/1-2--43349
https://peer.asee.org/43349
363
Dr. Qin Liu is Senior Research Associate with the Institute for Studies in Transdisciplinary Engineering Education and Practice, Faculty of Applied Science and Engineering, University of Toronto, Canada. Her research interests include engineering students' learning experiences and outcomes, including competency development and career pathways.
GREG EVANS PhD, P.Eng, FCEA, FAAAS is the Director of the Institute for Studies in Transdisciplinary Engineering Education and Practice (ISTEP), Director of the Collaborative Specialization in Engineering Education, a 3M national Teaching Fellow, and a m
Yunze Wei is an undergraduate student currently studying Engineering Science (Machine Intelligence) at the Faculty of Applied Science and Engineering, University of Toronto, Canada. She is interested in the incorporation of interdisciplinary learning and professional development in engineering education. She also enjoys learning about machine learning and data analysis.
Kashish Mistry is an undergraduate computer engineering student at the Faculty of Applied Science and Engineering, University of Toronto, Canada. She enjoys exploring the technical aspects of software such as artificial intelligence, database development, and computer networks. In addition to her studies, she is interested in improving engineering education for students and learning about how to better implement an inclusive and supportive environment for them.
Grounded in the existing literature on learning effectiveness in postsecondary education, this study aimed to develop better understandings of learning effectiveness in the context of increased digital teaching and learning in the post-pandemic era. We applied interpretative phenomenological analysis to focus group data collected from undergraduate engineering students at a comprehensive Canadian university during summer 2022. The findings of this study confirm students’ interpretation of learning effectiveness in terms of both learning outcomes and processes. The learning process perspective was related to the affective, cognitive, and behavioural domains of student engagement. Efficiency in learning and ease of access to learning resources were also identified as indicators of learning effectiveness. In particular, under the mixed in-person and online instruction modes, engineering students interpreted their learning effectiveness as a result of individual-contextual interactions. Students developed their own perspectives on the advantages and disadvantages of in-person and online instruction based on their experiences during the pandemic. For some engineering students, their discipline-based understandings of learning contexts in various courses shaped their perceptions of learning effectiveness, which suggests the role of engineering and personal epistemologies in perceived learning effectiveness. This can be an area of future research on learning effectiveness. Scholarly and practical implications from these findings are discussed.
Liu, Q., & Evans, G., & Wei, Y., & Moghaddas, M., & Mistry, K., & Kecman, T. (2023, June), Engineering Students’ Perceptions of Learning Effectiveness: Implications from the Lived Experiences Amidst a Mixture of In-Person and Online Instruction Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43349
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