现代远距离教育

计算思维是现代人类必备的核心素养之一，高质量的同伴学习对学习绩效的提升具有重要意义，有效的同伴学习投入对于计算思维发展具有重要支持作用。对多类型、多样态同伴学习投入进行精准画像，探讨其对计算思维发展的影响机理并进行智能干预，具有理论意义与现实价值。研究提出了同伴学习投入和计算思维发展的关联关系分析与量化计算模型，其指向发现同伴学习行为、情感、认知与计算思维发展的关联机制并突破隐含变量发现与参数求解的难题；构建了面向计算思维发展的同伴学习投入精准画像模型，为实现同伴学习投入的计算和整合提供表征基础；基于关联机制的回归分析与同伴学习投入精准画像，提出了基于强化学习的面向计算思维发展的同伴学习投入智能干预模型。

Computational thinking is one of the core competencies that modern humans must possess, high quality peer learning is of great significance for improving learning performance, and effective peer learning engagement plays an important supportive role in the development of computational thinking. Accurately profiling the various types and forms of peer learning engagement, exploring their impact mechanisms on the development of computational thinking, and implementing intelligent interventions have theoretical significance and practical value. This research proposes a correlation analysis and representation model between peer learning engagement and computational thinking, aiming to explore the correlation mechanism between behavioral emotional, cognitive peer learning engagement and computational thinking development, including the discovery of hidden variables and parameter solving. This research also constructs a precise profiling model of peer learning engagement for the development of computational thinking, which is expected to provide a presentation basis for the calculation and integration of peer learning engagement. Based on the regression analysis of association mechanism and the accurate profiling of peer learning engagement, this research proposes an intelligent intervention model of peer learning engagement for the development of computational thinking.