摘要
人工智能(artificial intelligence,AI)教材优势在于大规模个性化教学应用,但面临海量学习数据难以可视化呈现的新问题。研究应用了AI教材《医学生物化学》对436名学生的学习行为数据进行系统分析,着力解决数据可视化呈现的3大难题:①平行大班之间的学习特征差异;②平行大班内精细亚群的学习画像分析;③平行大班内AI交互深度思考的可视化分析。通过7个核心参数展示了平行大班间的学习特征差异;在一个平行大班内根据学习行为的异质性将学生细分为9个亚群,分析了亚群间的个性化差异;以自建的AI提问思维支架为牵引,对一个平行大班内所有学生和AI的互动问题进行聚类分析,实现了对学生深度思考效果的可视化评价。未来研究需基于上述策略开发AI教材数据可视化的自动展示功能,为大规模个性化教学决策提供依据。
While artificial intelligence(AI)textbooks offer the advantage of enabling largescale personalized teaching,they face the new challenge of difficulty in visualizing massive learning data.This study systematically analyzed the learning behaviors of 436 students using the AI textbook Medical Biochemistry,addressing three critical challenges in data visualization:①visualizing interclass variations across parallel large classes;②analyzing the fine-grained subgroup learning profiles within a parallel large class;③profiling the in-depth thinking reflected in AI interactions within a parallel large class.In this research,seven key parameters were used to demonstrate the differences in learning characteristics between parallel large classes.Within one parallel large class,students were subdivided into 9 subgroups based on behavioral heterogeneity,with personalized differences analyzed across subgroups.Using a self-developed scaffold questioning framework for AI interactions,cluster analysis was conducted on all interaction questions between students and AI in one parallel large class,enabling visual evaluation of students’in-depth thinking effects.Future research should develop an automatic display for AI textbook data visualization based on these strategies to support data-driven decision-making in large-scale personalized teaching.
作者
杨子岩
张翔
袁玉强
赵晶
YANG Ziyan;ZHANG Xiang;YUAN Yuqiang;ZHAO Jing(Department of Biochemistry and Molecular Biology,School of Basic Medicine,the Air Force Military Medical University,Xi’an,710032,China;Beijing Mosoink Company Limited,Beijing,100000,China)
出处
《医学分子生物学杂志》
2025年第5期516-523,共8页
Journal of Medical Molecular Biology
基金
陕西高等教育教学改革重点项目(No.23BZ090)
空军军医大学教学成果孵育项目(No.XJCG2022PY05)
西北联盟教学改革研究项目
中国教育技术协会网络课程建设工作委员会2025年度教育科研课题。
关键词
人工智能教材
生物化学
大规模个性化教学
数据可视化分析
artificial intelligence textbook
biochemistry
large-scale personalized teaching
data visualization analysis
