基于xAPI的精准学习者模型构建研究

Construction of an Accurate Learner Model based on the Experience API

教育智能时代,学习者模型的构建是个性化学习、自主性学习的核心和关键。xAPI作为新一代学习标准和规范,能够完整准确地记录和存储学习者的学习经历数据,而学习经历数据又体现了学习者的各项行为特征,这些行为特征为构建精准学习者模型提供了强大的数据支撑。结合学习者模型相关研究成果,设计了一个七维度的学习者特征分析模型。以此为基础,通过对LRS中的行为数据进行分析提取学习者各项特征,同时将时间和位置要素融入学习者情境,以时间熵和位置熵刻画不同类型的学习群体,基于相似学习情境的学习群体,通过算法库中的各种算法,生成学习者模型,从而构建了一个标准开放、实现闭环、模型动态的学习者模型总体框架,并系统化阐述了精准学习者模型的生成过程。

In the era of educational intelligence,the construction of learner model is the core and key of personalized learning and autonomous learning.xAPI,as a new generation of learning standards and norms,can record and store learners’learning experience data completely and accurately,and the learning experience data reflects learners’behavior characteristics,which provide strong data support for the construction of accurate learner model.Combined with the related research results of learner model,a seven-dimension learner characteristic analysis model is designed.On this basis,through the analysis of the behavior data in LRS,the characteristics of learners are extracted.At the same time,time and location elements are integrated into the learner situation.Different types of learning groups are described by time entropy and location entropy.Based on the learning groups in similar learning situations,the learner model is generated by various algorithms in the algorithm library.Finally,a learner model general framework with a standard open,implemented closed-loop,model dynamics is constructed,and the generation process of precise learner model is described systematically.