Course Satisfaction in Engineering Education Through the Lens of Student Agency Analytics
Heilala, V., Saarela, M., Jääskelä, P., & Kärkkäinen, T. (2020). Course Satisfaction in Engineering Education Through the Lens of Student Agency Analytics. In FIE 2020 : Proceedings of the 50th IEEE Frontiers in Education Conference. IEEE. Conference proceedings : Frontiers in Education Conference. https://doi.org/10.1109/FIE44824.2020.9274141
DisciplineHuman and Machine based Intelligence in LearningKoulutusteknologia ja kognitiotiedeKoulutuksen tutkimuslaitosDigitalization in and for learning and interactionHuman and Machine based Intelligence in LearningLearning and Cognitive SciencesFinnish Institute for Educational ResearchDigitalization in and for learning and interaction
© IEEE 2020
This Research Full Paper presents an examination of the relationships between course satisfaction and student agency resources in engineering education. Satisfaction experienced in learning is known to benefit the students in many ways. However, the varying significance of the different factors of course satisfaction is not entirely clear. We used a validated questionnaire instrument, exploratory statistics, and supervised machine learning to examine how the different factors of student agency affect course satisfaction among engineering students (N = 293). Teacher’s support and trust for the teacher were identified as both important and critical factors concerning experienced course satisfaction. Participatory resources of agency and gender proved to be less important factors. The results provide convincing evidence about the possibility to identify the most important factors affecting course satisfaction.
Parent publication ISBN978-1-7281-8962-8
ConferenceFrontiers in Education Conference
Is part of publicationFIE 2020 : Proceedings of the 50th IEEE Frontiers in Education Conference
Publication in research information system
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