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Koh YYJ, Schmidt HG, Low-Beer N, Rotgans JI. Team-Based Learning Analytics: An Empirical Case Study. ACADEMIC MEDICINE : JOURNAL OF THE ASSOCIATION OF AMERICAN MEDICAL COLLEGES 2020; 95:872-878. [PMID: 31972678 PMCID: PMC7242170 DOI: 10.1097/acm.0000000000003157] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Many medical schools that have implemented team-based learning (TBL) have also incorporated an electronic learning architecture, commonly referred to as a learning management system (LMS), to support the instructional process. However, one LMS feature that is often overlooked is the LMS's ability to record data that can be used for further analysis. In this article, the authors present a case study illustrating how one medical school used data that are routinely collected via the school's LMS to make informed decisions. The case study started with one instructor's observation that some teams in one of the undergraduate medical education learning modules appeared to be struggling during one of the team activities; that is, some teams seemed unable to explain or justify their responses to items on the team readiness assurance test (tRAT). Following this observation, the authors conducted 4 analyses. Their analyses demonstrate how LMS-generated and recorded data can be used in a systematic manner to investigate issues in the real educational environment. The first analysis identified a team that performed significantly poorer on the tRAT. A subsequent analysis investigated whether the weaker team's poorer performance was consistent over a whole module. Findings revealed that the weaker team performed poorer on the majority of the TBL sessions. Further investigation using LMS data showed that the weaker performance was due to the lack of preparation of one individual team member (rather than a collective poor tRAT performance). Using the findings obtained from this case study, the authors hope to convey how LMS data are powerful and may form the basis of evidence-based educational decision making.
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Affiliation(s)
- Ying Yun Juliana Koh
- Y.Y.J. Koh is research associate, Medical Education and Scholarship Unit, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; ORCID: https://orcid.org/0000-0003-2062-5617
| | - Henk G. Schmidt
- H.G. Schmidt is professor of psychology, Institute of Medical Education Research, Erasmus University Medical Center, Rotterdam, the Netherlands; ORCID: https://orcid.org/0000-0001-8706-0978
| | - Naomi Low-Beer
- N. Low-Beer is professor and director, Medical Education and Scholarship Unit, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; ORCID: https://orcid.org/0000-0002-6801-0091
| | - Jerome I. Rotgans
- J.I. Rotgans is assistant professor, Medical Education and Scholarship Unit, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; ORCID: https://orcid.org/0000-0003-4043-8261
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Chan LK, Ganotice F, Wong FKY, Lau CS, Bridges SM, Chan CHY, Chan N, Chan PWL, Chen HY, Chen JY, Chu JKP, Ho CC, Ho JMC, Lam TP, Lam VSF, Li Q, Shen JG, Tanner JA, Tso WWY, Wong AKC, Wong GTC, Wong JYH, Wong NS, Worsley A, Yu LK, Yum TP. Implementation of an interprofessional team-based learning program involving seven undergraduate health and social care programs from two universities, and students' evaluation of their readiness for interprofessional learning. BMC MEDICAL EDUCATION 2017; 17:221. [PMID: 29157232 PMCID: PMC5697117 DOI: 10.1186/s12909-017-1046-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Accepted: 11/02/2017] [Indexed: 05/20/2023]
Abstract
BACKGROUND Interprofessional learning is gaining momentum in revolutionizing healthcare education. During the academic year 2015/16, seven undergraduate-entry health and social care programs from two universities in Hong Kong took part in an interprofessional education program. Based on considerations such as the large number of students involved and the need to incorporate adult learning principles, team-based learning was adopted as the pedagogy for the program, which was therefore called the interprofessional team-based learning program (IPTBL). The authors describe the development and implementation of the IPTBL program and evaluate the effectiveness of the program implementation. METHODS Eight hundred and one students, who are predominantly Chinese, participated in the IPTBL. The quantitative design (a pretest-posttest experimental design) was utilized to examine the students' gains on their readiness to engage in interprofessional education (IPE). RESULTS Three instructional units (IUs) were implemented, each around a clinical area which could engage students from complementary health and social care disciplines. Each IU followed a team-based learning (TBL) process: pre-class study, individual readiness assurance test, team readiness assurance test, appeal, feedback, and application exercise. An electronic platform was developed and was progressively introduced in the three IUs. The students' self-perceived attainment of the IPE learning outcomes was high. Across all four subscales of RIPLS, there was significant improvement in student's readiness to engage in interprofessional learning after the IPTBL. A number of challenges were identified: significant time involvement of the teachers, difficulty in matching students from different programs, difficulty in making IPTBL count towards a summative assessment score, difficulty in developing the LAMS platform, logistics difficulty in managing paper TBL, and inappropriateness of the venue. CONCLUSIONS Despite some challenges in developing and implementing the IPTBL program, our experience showed that TBL is a viable pedagogy to be used in interprofessional education involving hundreds of students. The significant improvement in all four subscales of RIPLS showed the effects of the IPTBL program in preparing students for collaborative practice. Factors that contributed to the success of the use of TBL for IPE are discussed.
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Affiliation(s)
- Lap Ki Chan
- The University of Hong Kong, Hong Kong, People’s Republic of China
- School of Biomedical Sciences, Bau Institute of Medical and Health Sciences Education, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pok Fu Lam Hong Kong, People’s Republic of China
| | - Fraide Ganotice
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | | | - Chak Sing Lau
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | - Susan M. Bridges
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | | | - Namkiu Chan
- The Hong Kong Polytechnic University, Hong Kong, People’s Republic of China
| | | | - Hai Yong Chen
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | - Julie Yun Chen
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | | | - Charlene C. Ho
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | | | - Tai Pong Lam
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | | | - Qingyun Li
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | - Jian Gang Shen
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | | | | | | | | | | | - Nai Sum Wong
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | - Alan Worsley
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | - Lei King Yu
- The University of Hong Kong, Hong Kong, People’s Republic of China
| | - Tin Pui Yum
- The University of Hong Kong, Hong Kong, People’s Republic of China
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Fernández-Alemán JL, López-González L, González-Sequeros O, Jayne C, López-Jiménez JJ, Toval A. The evaluation of i-SIDRA – a tool for intelligent feedback – in a course on the anatomy of the locomotor system. Int J Med Inform 2016; 94:172-81. [PMID: 27573325 DOI: 10.1016/j.ijmedinf.2016.07.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2015] [Revised: 07/05/2016] [Accepted: 07/10/2016] [Indexed: 11/24/2022]
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