Article(id=1320389060049359515, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320388968923902012, articleNumber=null, orderNo=null, doi=10.11876/mimt202505013, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792734883558, onlineDateStr=2026-10-23, pubDate=1760025600000, pubDateStr=2025-10-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792734883558, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792734883558, creator=13701087609, updateTime=1792734883558, updator=13701087609, issue=Issue{id=1320388968923902012, tenantId=1146029695717560320, journalId=1319373289681944729, year='2025', volume='31', issue='5', pageStart='1', pageEnd='108', issueExtLink='null', onlineDate='null', pubDate='1760025600000', pubDateStr='2025-10-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792734861832, creator='13701087609', updateTime=1792746392297, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320437331253900271, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320388968923902012, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320437331253900272, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320388968923902012, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=79, endPage=84, ext={EN=ArticleExt(id=1320389060212937372, articleId=1320389060049359515, tenantId=1146029695717560320, journalId=1319373289681944729, language=EN, title=Application of AI-assisted PBL method in physiology teaching for pharmacy majors, columnId=null, journalTitle=Modern Instruments & Medical Treatment, columnName=null, runingTitle=null, highlight=null, articleAbstract=

This study investigated the teaching effectiveness of applying an artificial intelligence (AI)-assisted problem-based learning (PBL) teaching model in physiology courses for undergraduate pharmacy majors. The research involved 214 undergraduate pharmacy students divided into a control group and an experimental group. For the control group (n=106), the traditional PBL teaching method was implemented. For the experimental group (n=108), the AI-assisted PBL teaching model was applied. The method involved teachers using an AI platform to intelligently generate teaching cases and guiding questions during lesson preparation. Students engaged in group collaboration, discussed cases, delivered presentations, and interacted with the AI platform in real-time, constructing a closed-loop teaching system of “problem generation-dynamic guidance-multidimensional evaluation”. Compared to the control group, the experimental group performed significantly higher scores in knowledge mastery, higher-order thinking skills, and learning engagement, with the difference being statistically significant (P<0.05). The satisfaction rate of the experimental group with the course teaching model was 87.50%. These findings suggest that the AI-assisted PBL teaching model can effectively improve the teaching outcomes of physiology for pharmacy undergraduates, offering a novel and effective approach to training high-quality pharmaceutical professionals.

, authors=Run Shi, Weiwei Hao, Ruixue Yu^*, authorsList=Run Shi, Weiwei Hao, Ruixue Yu, authorCompany=null, correspAuthors=Ruixue Yu, authorNote=null, correspAuthorsNote=null, copyrightStatement=All copyrights in 2025 belong to the sponsor of the journal.Not content published by the journal may be reproduced or abridged without authorization., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320389060598813341, articleId=1320389060049359515, tenantId=1146029695717560320, journalId=1319373289681944729, language=CN, title=AI辅助的PBL法在药学专业生理学教学中的应用, columnId=1320388907611566751, journalTitle=现代仪器与医疗, columnName=数字化医疗, runingTitle=null, highlight=null, articleAbstract=

探讨在药学专业本科生的生理学教学中，应用人工智能（artificial intelligence，AI）辅助的问题导向学习（problem-based learning，PBL）教学模式的教学效果。研究以214名药学专业本科生为研究对象，分为对照组和实验组，其中，针对对照组的106名本科生实施传统PBL教学；针对实验组的108名本科生实施AI辅助的PBL教学模式，方法为教师在备课过程中应用AI平台智能生成教学病例和导向问题，学生进行分组协作，围绕病例展开讨论及汇报，与AI平台实时互动，构建“问题生成—动态引导—多维评价”的闭环教学体系。本研究结果显示，实验组在知识掌握度、高阶思维能力及学习投入度3个评价维度的得分值均显著高于对照组，差异有统计学意义（P<0.05）；实验组对课程教学模式的满意度为87.50%。上述结果提示AI辅助的PBL教学模式可有效提升药学专业本科生的生理学教学效果，为培养新医科背景下的高素质药学人才提供了新的有效路径。

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师润，男，硕士研究生，讲师，研究方向：基础医学教育

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rfOrder=0, authorNames=null, journalName=null, refType=null, unstructuredReference=国务院办公厅. 国务院办公厅关于加快医学教育创新发展的指导意见[EB/OL]. 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