Artificial Intelligence-based online platform assists blood cell morphology learning: A mixed-methods sequential explanatory designed research

在线学习 计算机科学 课程 人工智能 医学教育 数学教育 多媒体 心理学 医学 教育学
作者
Junxun Li,Juan Ouyang,Juan Liu,Fan Zhang,Zhigang Wang,Xin Guo,Min Liu,David Taylor
出处
期刊:Medical Teacher [Taylor & Francis]
卷期号:45 (6): 596-603 被引量:7
标识
DOI:10.1080/0142159x.2023.2190483
摘要

The study aimed to evaluate the effectiveness of learning blood cell morphology by learning on our Artificial intelligence (AI)-based online platform.Our study is based on mixed-methods sequential explanatory design and crossover design. Thirty-one third-year medical students were randomly divided into two groups. The two groups had platform learning and microscopy learning in diferent sequences with pretests and posttests, respectively. Students were interviewed, and the records were coded and analyzed by NVivo 12.0.For both groups, test scores increased significantly after online-platform learning. Feasibility was the most mentioned advantage of the platform. The AI system could inspire the students to compare the similarities and differences between cells and help them understand the cells better. Students had positive perspectives on the online-learning platform.The AI-based online platform could assist medical students in blood cell morphology learning. The AI system could function as a more knowledgeable other (MKO) and guide the students through their zone of proximal development (ZPD) to achieve mastery. It could be an effective and beneficial complement to microscopy learning. Students had very positive perspectives on the AI-based online learning platform. It should be integrated into the course and curriculum to facilitate the students.[Box: see text].
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