数字化时代在线学习行为结构及其作用机理研究——自我调节理论视角

Research on the Behavior Structure and Its Functional Mechanism of Online Learning in Digital Era--From the Perspective of Self-regulation Theory

数字技术与数字社会的高速发展为教育结构变革注入力量,在线学习研究成为推动中国教育数字化转型的重要领域。合理全面地识别与分析在线学习行为是厘清在线学习活动规律、顺应数字化时代发展之基石。让学生在线学习时保持学习行为参与进而实现良好的自我调节是一项重要的科学问题。基于自我调节理论,从计划、表现和反思三个阶段系统梳理在线学习行为,采用随机森林算法精细化识别最能影响在线自我调节学习的关键行为,并利用解释结构模型方法分析在线自我调节学习的行为结构,进一步揭示数字化时代在线学习行为对自我调节学习的作用机理。研究成果提供了对在线自我调节学习行为涌现及其演化规律的新见解,为未来开展灵活、精准、个性化的大规模数字教育提供理论与实践依据。

The rapid development of digital technology and digital society has injected strength into the reform of educational structure.Online learning has become an important field to promote the digital transformation of education in China.Comprehensive and reasonable i-dentification and analysis of online learning behavior is the cornerstone of clarifying the law of online learning activities and complying with the development of the digital era.It is an important scientific issue that students can keep their participating in learning behavior during online learning,and then realize good self-regulation.Based on the self-regulation theory,this paper systematically combs the online learning behavior from the three stages of forethought,performance,and self-reflection,and uses the random forest algorithm to finely identify the key behavior that can most affect online self-regulated learning.The Interpretative structural modeling method is used to analyze the behavior structure of online self-regulated learning and further reveal the functional mechanism of online learning behavior on self-regulated learning in the digital era.The research results provide new insights into the emergence of online self-regulated learning behavior and its evolutionary laws and provide a theoretical and practical basis for carrying out flexible,accurate,and personalized large-scale digital education in the future.