Alexandra Aster, Arietta Lotz, Matthias Carl Laupichler, Tobias Raupach
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The chatbots differed in the manner of query entry, with one requiring students to formulate history taking questions themselves, while the other provided a long menu of selectable questions. The dependent variables analyzed included the history taking data entered into the chatbots, represented as a quantified history score, as well as students' comparative self-assessments of their learning outcomes.</p><p><strong>Results: </strong>Comparing only the first measurement point, students achieved higher scores in the free-entry chatbot (85.2 ± 27.7) compared to the long menu chatbot (78.8 ± 35.7). Students achieved significantly higher scores in the second than in the first session in the long menu chatbot (<i>t</i>(315) = -2.918, <i>p</i> = .004, <i>d</i> = -0.229) but not in the free-entry chatbot after receiving the guideline. In terms of students' self-assessment, no significant difference between both serious games was found.</p><p><strong>Discussion: </strong>The results suggest that history taking benefits from self-directed learning in a long menu format relying on cued recall but not in a free-entry chatbot relying on free recall. Since serious games are partially artificial learning environments for training history taking, future studies should examine the extent to which students can transfer their learning in and out of serious games.</p>","PeriodicalId":47656,"journal":{"name":"Medical Education Online","volume":"30 1","pages":"2527175"},"PeriodicalIF":3.8000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12247099/pdf/","citationCount":"0","resultStr":"{\"title\":\"Impact of providing a customized guideline on virtual medical history taking in two serious games for medical education.\",\"authors\":\"Alexandra Aster, Arietta Lotz, Matthias Carl Laupichler, Tobias Raupach\",\"doi\":\"10.1080/10872981.2025.2527175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Serious games are known as safe learning environments, allowing medical students to train their skills without endangering patients' safety. 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引用次数: 0
摘要
背景:严肃游戏被认为是安全的学习环境,可以让医学生在不危及患者安全的情况下训练他们的技能。通过聊天机器人整合虚拟病人,严肃游戏提供了练习历史记录的机会。该研究通过采用嵌入在严肃游戏中的两种不同聊天机器人系统的定制历史指南来调查自主学习的影响。方法:将159名四年级医学生随机分为两组,每组分别代表一个急诊科,模拟不同的临床情景。学生们在两个测量点玩严肃游戏,并在两次测试之间收到指导方针。这两个聊天机器人在查询输入方式上有所不同,其中一个要求学生自己提出历史问题,而另一个则提供了一长串可选问题的菜单。分析的因变量包括输入聊天机器人的历史数据,以量化的历史分数表示,以及学生对学习成果的比较自我评估。结果:仅比较第一个测量点,学生在自由进入聊天机器人中的得分(85.2±27.7)高于长菜单聊天机器人(78.8±35.7)。在长菜单聊天机器人中,学生在第二阶段的得分明显高于第一阶段(t(315) = -2.918, p =)。004, d = -0.229),但在收到指南后的自由进入聊天机器人中没有。在学生自我评价方面,两种严肃游戏之间没有显著差异。讨论:结果表明,历史学习受益于依赖线索回忆的长菜单形式的自主学习,而不是依赖自由回忆的自由进入聊天机器人。由于严肃游戏在一定程度上是训练历史学习的人工学习环境,未来的研究应该检查学生在多大程度上可以将他们的学习转移到严肃游戏中。
Impact of providing a customized guideline on virtual medical history taking in two serious games for medical education.
Background: Serious games are known as safe learning environments, allowing medical students to train their skills without endangering patients' safety. By integrating virtual patients via chatbots, serious games provide the opportunity to practice history taking. The study investigated the impact of self-directed learning by means of a customized guideline on history taking in two distinct chatbot systems embedded in serious games.
Methods: Fourth-year medical students (N = 159) were randomized to one of two serious games, each representing an emergency department and simulating different clinical scenarios. Students played the serious games at two measurement points and received a guideline between both sessions. The chatbots differed in the manner of query entry, with one requiring students to formulate history taking questions themselves, while the other provided a long menu of selectable questions. The dependent variables analyzed included the history taking data entered into the chatbots, represented as a quantified history score, as well as students' comparative self-assessments of their learning outcomes.
Results: Comparing only the first measurement point, students achieved higher scores in the free-entry chatbot (85.2 ± 27.7) compared to the long menu chatbot (78.8 ± 35.7). Students achieved significantly higher scores in the second than in the first session in the long menu chatbot (t(315) = -2.918, p = .004, d = -0.229) but not in the free-entry chatbot after receiving the guideline. In terms of students' self-assessment, no significant difference between both serious games was found.
Discussion: The results suggest that history taking benefits from self-directed learning in a long menu format relying on cued recall but not in a free-entry chatbot relying on free recall. Since serious games are partially artificial learning environments for training history taking, future studies should examine the extent to which students can transfer their learning in and out of serious games.
期刊介绍:
Medical Education Online is an open access journal of health care education, publishing peer-reviewed research, perspectives, reviews, and early documentation of new ideas and trends.
Medical Education Online aims to disseminate information on the education and training of physicians and other health care professionals. Manuscripts may address any aspect of health care education and training, including, but not limited to:
-Basic science education
-Clinical science education
-Residency education
-Learning theory
-Problem-based learning (PBL)
-Curriculum development
-Research design and statistics
-Measurement and evaluation
-Faculty development
-Informatics/web