机器学习在科学教育评估中的应用:维度、领域与规律  

Application of Machine Learning in Science Education Evaluation:Dimensions,Domains and Laws

作　　者：高守宝[1] 张舒婷 孟现美[1] 丁雨楠 王晶莹 Shoubao GAO;Shuting ZHANG;Xianmei MENG;Yunan DING;Jingying WANG(School of Physics and Electronics,Shandong Normal University,Jinan 250000,Shandong;Tengzhou No.1 Middle School,Tengzhou 277500,Shandong;Faculty of Education,Beijing Normal University,Beijing 100875)

机构地区：[1]山东师范大学物理与电子科学学院,山东济南250000 [2]山东省滕州市第一中学,山东济南250000 [3]北京师范大学教育学部,北京100875

出　　处：《中国教育信息化》2023年第10期83-92,共10页Chinese Journal of ICT in Education

基　　金：北京市教育科学“十四五”规划2022年度优先关注课题“大数据教育评价研究”(编号:CDEA22008)。

摘　　要：为阐明机器学习优化教育评估与教育教学过程的效用及其规律,重构机器学习教育应用效果分析框架,从技术性、有效性、应用性三方面分析机器学习应用于科学教育的六个案例,阐明机器学习在评分策略、学习测评与教育干预领域的应用优势。同时,归纳机器学习在科学教育评估中的应用规律:机器学习通过复杂实践参与和自动反馈系统提高评估效率;机器学习支持多模态评估,帮助拓宽评估途径;机器学习在复杂结构、高阶思维和多维学习的应用中表现出巨大潜力;机器学习整合神经科学,能够帮助还原认知发展过程。然后,就机器学习进一步广泛应用给出建议:重视反馈在教学中的作用;聚焦机器学习应用的具体场景;关注教师在应用场景中扮演的角色。In order to clarify the efficacy and laws of machine learning optimizing education evaluation and education and teaching process,this research reconstructs the analysis framework of the application effect in education of machine learning,and analyzes six cases from three aspects:technology,efficacy and applicability and illustrates the advantages of machine learning in the fields of scoring strategies,learning assessment,and educational intervention assessment.At the same time,the application laws of machine learning in science education evaluation are summarized:Machine learning improves evaluation efficiency through complex practice participation and automatic feedback systems;It supports multi-modal evaluation and helps to broaden evaluation approach;Machine learning shows great potential in the application of complex structure,higher-order thinking and multi-dimensional learning;Machine learning integrated with neuroscience can help restore the cognitive development process.Finally,suggestions are given for further extensive application of machine learning:Pay attention to the role of feedback in teaching;Focus on specific scenarios of machine learning applications;And focus on the role of teachers in application scenarios.

关 键 词：机器学习 科学教育评估 维度分析 

分 类 号：G434[文化科学—教育学]