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Li KJ, Zhou YJ, Wu HD, Luo CL, Liu W, Hung P, Wang K, Hu X, Wang Y, Li Y, Wen C, Cheung JCW, Fu H, Wong MS, Ma CZH. Enhancing university students' engagement in studying assistive technology by case-based active learning: a pilot study in Hong Kong. Disabil Rehabil Assist Technol 2025:1-13. [PMID: 39754706 DOI: 10.1080/17483107.2024.2448722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 10/21/2024] [Accepted: 12/27/2024] [Indexed: 01/06/2025]
Abstract
Assistive technology (AT) professionals are in pressing need with nowadays growing aged/disabled population, so as well-designed higher education programs in this field. This study designed and implemented a case-based active learning approach within an undergraduate course related to AT in Hong Kong, and assessed its impact on enhancing student engagement over two academic years. A total of twelve multimedia patient case dossiers on six major physical disabilities were created. Two cohorts of students enrolled in course "Rehabilitation Engineering and Assistive Technology" were instructed to utilize the case dossiers to facilitate their learning, understanding, and application of ATs for aged/disabled individuals. The Revised Two-Factor Study Process Questionnaire was employed to evaluate the student feedback on their learning experience, engagement, and learning approaches (i.e., Deep Approach, DA; and Surface Approach, SA) before and after the course. Upon completing the course, students' DA scores significantly increased from 29.4 ± 6.9 to 31.4 ± 8.9 (p = 0.013). Additionally, significantly moderate positive correlations were found between the DA-SA value and students' individual written report grades (p = 0.004) and overall grades (p = 0.048). In contrast, a significantly moderate negative correlation was identified between students' individual report grades and SA scores (p = 0.019). These findings support the feasibility and effectiveness of implementing case-based active learning in higher education within the field of AT, supporting future large-scale implementation and optimization of such case-based active learning and teaching strategy in the AT field.
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Affiliation(s)
- Ke-Jing Li
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yu-Jing Zhou
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Department of Rehabilitation Sciences, Hunan University of Chinese Medicine, Changsha, China
| | - Hui-Dong Wu
- Department of Prosthetic and Orthotic Engineering, School of Rehabilitation, Kunming Medical University, Kunming, China
| | - Chang-Liang Luo
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Department of Prosthetic and Orthotic Engineering, School of Rehabilitation, Kunming Medical University, Kunming, China
| | - Wei Liu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Percy Hung
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Kubert Wang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yan Wang
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Yan Li
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Chunyi Wen
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - James Chung-Wai Cheung
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Hong Fu
- Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong SAR, China
| | - Man-Sang Wong
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Christina Zong-Hao Ma
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong SAR, China
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