【作 者】：
张 涛， 张 思
【关 键 词 】：
学习者模型； 模型设计与计算； 粒计算； 学习活动流
【栏 目】：
学习环境与资源
【中文摘要】：
数据科学在教学实践领域的深度融合应用，为推动智能化决策和个性化学习、实现精准施教提供发展方向。学习者模型作为数字化教育实践领域的核心部件，以内部心理机制和外部行为结构理解学习者在学习实践场域中的结构形态。研究在学习实践场域下，融合学习活动流作用机制，提出一种学习者模型设计通用框架，关注模型的结构特征和内部层级关系。结合粒计算和数据分析方法分别对通用框架中的本体模型、知识模型、认知模型、行为模型和情感模型进行设计与计算分析。最后，基于有序偶表达形式构造元组间有序递归的完整学习者模型结构列表，实现可共享、重组的学习者数据模型。
【英文摘要】：
The deep integration of data science in the field of teaching practice provides a development direction for promoting intelligent decision-making, personalized learning and the realization of precise teaching. The learner model, as the core component of digital education practice, uses internal psychological mechanism and external behavioral structures to understand the structures of learner in the field of learning practice. In the field of learning practice, this paper integrates the mechanism of learning activity flow, and proposes a general framework for learner model design, focusing on the structural characteristics and internal hierarchical relationship of the model. Combined with the granular computing and data analysis methods, the ontology model, knowledge model, cognitive model, behavior model and emotion model in the general framework are designed and calculated. Finally, based on the ordered pair expression form, a complete learner model structure list with ordered recursion among tuples is constructed to realize a learner data model that can be shared and reorganized.