中国医学教育技术2025，Vol.39Issue(6)：709-717,9.DOI:10.13566/j.cnki.cmet.cn61-1317/g4.202506005
数智环境下基于学习者分类的个性化学习评价研究
Research on personalized learning evaluation based on learner classification in the digital intelligence environment
摘要
Abstract
The diversification and personalized reconstruction of learning evaluation is one of the directions for educational evaluation reform in the new era.Personalized learning evaluation fo-cuses on local aspects from a holistic perspective,enabling differentiated analysis of learners'behav-ioral patterns,emotional states,and literacy levels.The development trajectory of personalized learn-ing evaluation is manifested as the process from differentiated evaluation of learning performance to in-dividualized measurement of learning effectiveness,from behavioral investment evaluation to cogni-tive and emotional measurement,from adaptive learning evaluation analysis to dynamic learning inter-action evaluation,and then from learner characteristic modeling evaluation to cognitive thinking differ-entiation evaluation.Overall,it reflects the characteristics of standardization to customization,from single dimension to multiple dimensions,and from static data to dynamic data.On this basis,the inter-nal logic of personalized learning evaluation is elaborated from three aspects:evaluation entry point,evaluation strategy,and evaluation objectives,and the design principle of three-dimensional feature classification evaluation is proposed.This principle aims at the development of literacy,supported by individual characteristics,and centered on learner classification.Through the interaction and integra-tion of the three,an evaluation system that adapts to learner classification is formed.According to the performance characteristics of learners in cognitive processes,emotional experiences,and learning in-teractions,learners are classified into nine categories based on feature similarity,and corresponding evaluation strategies are formed according to the characteristics of each category.Using two rounds of expert interviews,an evaluation system consisting of five primary indicators and fifteen secondary indi-cators was constructed,and the weights of the secondary indicators were determined using the fuzzy analytic hierarchy process.Finally,by linking the indicator system with the evaluation strategy,a set of evaluation schemes that can adapt to different types of learners can be formed,providing useful ref-erences for conducting large-scale differentiated learning evaluations.关键词
学习者分类/个性特征/个性化学习评价/评价目标/指标体系Key words
learner classification/personality traits/personalized learning evaluation/evalua-tion objectives/indicator system分类
教育学引用本文复制引用
牟智佳,时秋,冯西雅,李连义..数智环境下基于学习者分类的个性化学习评价研究[J].中国医学教育技术,2025,39(6):709-717,9.基金项目
2024年度国家社会科学基金教育学一般项目"数智环境下基于大语言模型的个性化学习设计与评价研究"(BCA240055) （BCA240055）
