Study on the Relations Among Students’ Self-efficacy, Task Value Appraisal and Learning Engagement in Medical School in Taiwan (75303)

Session Information: Higher Education
Session Chair: Emma Mayhew

Friday, 24 November 2023 14:05
Session: Session 3
Room: Room 604
Presentation Type: Oral Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

Changes in medical education require a rethinking of medical curriculum. Currently, the reform of medical education in many countries has focused on the block/integrated curriculum. Many universities have integrated basic and clinical science into the curriculum. It shows the importance of integrated curriculum in medical education. Student engagement during learning activities is a significant and heavily researched educational topic (Christenson et al., 2011). Student’s learning engagement is defined as behavioral, cognitive, emotional and agentic aspects of students' academic experience in teaching, learning and research through interacting with other students and teaching faculty (Reeve & Tseng, 2011). Despite the growing interest in the field of student’s learning engagement, medical education research in this area is still fragmented. Therefore, the researcher constructed the learning process model and collected the data to examine it. The study attempted to understand students’ learning processes in block curriculum in the school of medicine in Taiwan. The study analyzed the data in 4th grade in school of medicine in C University at fall semester in 2022 by quantitative methods. Participants were asked to complete the learning process scale. All items adopted a 6-point Likert scale with a focus on each block curriculum. Structural equation modeling was used to analyze the data. The results of the present study indicated that the learning process model had an excellent fit with the data. Medical students with higher self-efficacy can positively predict their learning engagement in the block curriculum. Medical students with higher task value appraisal can positively predict their learning.

Authors:
Yun-Ting Huang, National Cheng Kung University, Taiwan
Shyh-Jou Shieh, National Cheng Kung University, Taiwan
Yuk-Ying Tung, National Cheng Kung University, Taiwan


About the Presenter(s)
Dr Yun-Ting Huang is a University Assistant Professor/Lecturer at National Cheng Kung University in Taiwan

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00