Application of AI-assisted multi-advisor system combined with BOPPPS teaching model in clinical pharmacy education
Abstract Background The development of clinical pharmacy in China has been relatively slow, and standardized, effective training for clinical pharmacists remains a major challenge. At present, traditional teaching methods are not conducive to cultivating clinical practice abilities or critical think...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-05-01
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| Series: | BMC Medical Education |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12909-025-07394-2 |
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| Summary: | Abstract Background The development of clinical pharmacy in China has been relatively slow, and standardized, effective training for clinical pharmacists remains a major challenge. At present, traditional teaching methods are not conducive to cultivating clinical practice abilities or critical thinking, leading to a lack of enthusiasm among students. To address this issue, a hybrid teaching model combining an AI-assisted multi-advisor system with the BOPPPS (bridge, objective, pre-assessment, participatory learning, post-assessment, summary) teaching method was applied in clinical pharmacy education. Methods In this study, a teaching model was developed that consists of five components: advisor system, teaching strategy, teaching method, teaching mode, and assessment methods. The model was implemented in the Pharmacy Department of Xiangya Hospital at Central South University in Changsha, China, from spring 2023 to spring 2024. After the spring 2024 training session, anonymous questionnaires were completed by students. The effects of the teaching reform were evaluated. The questionnaire focused on clinical practice effectiveness, course design rationality, improvement in professional ability, interest in learning, and perceptions of ChatGPT as a teaching tool. Results A total of 81 students participated in the study, with 69 completing the questionnaire survey (response rate: 85.2%, n = 69). Overall, students gave positive comments regarding the instructional improvements. A higher proportion of interns and advanced students considered the courses difficult (32.4%, n = 12 and 31.6%, n = 6, respectively). Identified shortcomings include the frequent periodic assessments and increased pressure. Regarding the use of ChatGPT, 49 students (71.0%, n = 49) commented that it played a multidimensional role in teaching. The most valued asset was its ability to provide massive data information (43.5%, n = 30), while the lack of interactivity was a prominent issue (56.5%, n = 39). Conclusion This innovative teaching model integrating an AI-assisted BOPPPS framework with a supervised ChatGPT implementation may facilitate the comprehensive self-evaluation of abilities. This research offers a replicable model for AI-driven educational transformation in clinical pharmacy training. |
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| ISSN: | 1472-6920 |