智慧学习环境下学习分析的理论模型及其机制

Learning Analysis Theoretical Model and Mechanism in Smart Learning Environment

智慧学习环境为学习者提供了个性化学习服务。在智慧学习环境中,学习分析技术是其关键技术之一,因此开展学习分析模型的研究是为学习者提供个性化服务的重要基础。文章通过对国内外学习分析模型要素的综述,以联通主义学习理论、学习目标划分理论、数据分析方法及教育评价与测量理论为基础,从学习数据变量、学习数据类化、学习数据处理和学习测评服务四个方面建构了智慧学习环境下学习分析的理论模型,并据此提出了学习服务智慧化导向下的学习分析机制:多源动态学习数据的高效采集和存储机制、多模态异构学习数据的智能管理和分析机制、多通道分析结果的模型自适应反馈机制。文章所提出的学习分析理论模型及其机制,将提高智慧学习环境下学习分析的有效性。

Smart learning environment will provide personalized service to learners. Learning analytics is the key point in smart learning environment. Therefore, the study of learning analytics theoretical model is important for providing personalized services for learners. Based on connectivism learning theory, the theory of classification of learning objectives, data analysis method, and educational evaluation and measurement theory, this paper summarized the elements of learning analysis model, and constructed the theoretical model of learning analytics in smart learning environment. The theoretical model includes four parts: learning data variables, learning data generalization, learning data processing and learning evaluation services. Based on this theoretical model, this paper proposed a learning and service oriented learning analytics mechanism, which includes three parts: an efficient data acquisition and storage mechanism for multi-source dynamic learning, an intelligent management and analysis mechanism for multimodal heterogeneous learning data, and an automatic model feedback mechanism for multi-channel results analysis. The theoretical model and mechanism mentioned will improve the effectiveness of learning analytics in smart learning.