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    在线学习领导者影响共享调节学习行为的 实证研究

    An Empirical Study of Effects of Online Learning Leaders on Shared Regulation Learning Behaviors

【作      者】:

郑旭东, 范小雨, 赵 冉


【关 键 词 】:

在线学习领导者; 在线协作学习; 共享调节学习行为; 调节性学习


【栏      目】:

网络教育


【中文摘要】:

学习者角色分工可决定在线协作学习活动的成败。在线学习领导者的类型及作用,也会对共享目标和监督调节等共享调节学习行为产生影响,进而决定协作学习目标的达成度。为了探明在线学习领导者(垂直型vs.共享型)如何影响协作小组的共享调节学习行为,研究实施了一项为期9周的准实验,通过滞后序列分析和社会网络分析发现:垂直领导协作组在共享监督行为方面具有显著优势,有效促进了共享计划和策略运用等行为,并形成了稳定的共享调节行为闭环,有助于在线协作任务的高质量完成及获得学习高分;垂直学习领导者处于中心地位并有效促进组内产生交互和共享等协作行为。为此,建议应重视在线协作学习领导力培养、强化协作学习活动的共享监控、灵活提供互动认知工具及调节支架,以提高学生的共享调节能力,促进与维系在线深度学习的有效发生。


【英文摘要】:

The division of learner roles can determine the success or failure of online collaborative learning activities. The type and role of the online learning leader can also have an impact on shared regulation learning behaviors such as shared goals and supervised regulation, which in turn determine the extent to which collaborative learning goals are achieved. To explore how online learning leaders (the vertical vs. the shared) influence the shared regulation learning behaviors of collaborative groups, this study conducts a 9-week quasi-experiment and through lag-sequential analysis and social network analysis finds that the vertical leadership collaborative group has significant advantages in shared supervisory behaviors, effectively facilitates shared planning and strategy use, and creates a stable closed loop of shared regulatory behaviors that contributes to high-quality completion of online collaborative tasks and high learning scores. Vertical learning leaders are at the center and effectively facilitate collaborative behaviors such as interaction and sharing within the group. To this end, it is recommended that the development of online collaborative learning leadership should be emphasized, shared monitoring of collaborative learning activities should be strengthened, and interactive cognitive tools and regulation scaffolding should be flexibly provided to improve students' shared regulation ability, and promote and sustain effective online deep learning.

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