TY - JOUR AU - Taveira-Gomes, Tiago AU - Ferreira, Patrícia AU - Taveira-Gomes, Isabel AU - Severo, Milton AU - Ferreira, Maria Amélia PY - 2016 DA - 2016/08/01 TI -我们在医学教育中的计算机学习干预中寻找什么?系统综述JO - J医学互联网研究SP - e204vl - 18 IS - 8kw -医学教育KW -网络学习KW -计算机学习KW -电子学习KW -b -学习KW -系统综述AB -背景:计算机学习(CBL)在医学教育中已被广泛应用，关于其使用和有效性的报道范围广泛。大多数工作都是关于CBL方法与传统方法的有效性，而很少有人对CBL与CBL方法的效果进行比较。这些发现促使其他作者推荐这样的研究，希望提高关于哪种CBL方法在哪种环境下最有效的知识。目的:在本系统综述中，我们旨在描述最近关于软件平台发展和医学教育干预的研究，寻找研究之间的共同点，并评估是否考虑了CBL研究的建议。方法:我们对2003年至2013年发表的文献进行了系统综述。我们纳入了用英语撰写的研究，特别是在医学教育领域，涉及教学软件的开发或在培训或实践期间使用教学软件进行干预，报告了学习者的态度、满意度、知识、技能或软件使用情况。我们进行了2次潜在类别分析，根据平台特征和干预特征对文章进行分组。此外，我们还分析了摘要文章的参考文献和引文。结果:我们分析了251篇文章。 The number of publications rose over time, and they encompassed most medical disciplines, learning settings, and training levels, totaling 25 different platforms specifically for medical education. We uncovered 4 latent classes for educational software, characteristically making use of multimedia (115/251, 45.8%), text (64/251, 25.5%), Web conferencing (54/251, 21.5%), and instructional design principles (18/251, 7.2%). We found 3 classes for intervention outcomes: knowledge and attitudes (175/212, 82.6%), knowledge, attitudes, and skills (11.8%), and online activity (12/212, 5.7%). About a quarter of the articles (58/227, 25.6%) did not hold references or citations in common with other articles. The number of common references and citations increased in articles reporting instructional design principles (P=.03), articles measuring online activities (P=.01), and articles citing a review by Cook and colleagues on CBL (P=.04). There was an association between number of citations and studies comparing CBL versus CBL, independent of publication date (P=.02). Conclusions: Studies in this field vary highly, and a high number of software systems are being developed. It seems that past recommendations regarding CBL interventions are being taken into consideration. A move into a more student-centered model, a focus on implementing reusable software platforms for specific learning contexts, and the analysis of online activity to track and predict outcomes are relevant areas for future research in this field. SN - 1438-8871 UR - //www.mybigtv.com/2016/8/e204/ UR - https://doi.org/10.2196/jmir.5461 UR - http://www.ncbi.nlm.nih.gov/pubmed/27480053 DO - 10.2196/jmir.5461 ID - info:doi/10.2196/jmir.5461 ER -