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Learning through online peer discourse: Structural equation modeling points to the role of discourse activities in individual understanding

机译:通过在线同伴话语学习:结构方程建模指出话语活动在个人理解中的作用

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摘要

Although learning through discourse activities seems well-documented, it is unclear which mechanisms and behavioral variables are involved. What exactly contributes to learning when two or more learners interact in online learning environments? To analyze interrelations between central discourse activities and individual learning outcomes at the level of constructs, we applied structural equation modeling to data collected from 160 dyads engaging in written online learning discourses within a series of homogeneous experiments. We analyzed three theory-based indicators of conceptual elaboration activities during online discourse: the number of questions asked to receive information and expand knowledge, the number of explanations formulated to express individual knowledge, and the amount of on-task discourse. Individual conceptual understanding was represented by objective learning parameters that varied in each particular experimental task. These measured general understanding of the topic addressed and particular understanding of conceptual terms, complemented by the gain in individual self-assessed knowledge. Results of structural equation modeling revealed a strong effect of dyadic conceptual elaboration on individual understanding at the construct level, demonstrating that dyadic elaboration fosters the development of an elaborated individual understanding of specialist concepts and general content knowledge. Moreover, conceptual elaboration was best measured by the number of explanations during discourse. Implications regarding which features of collaborative learning settings promote mutual conceptual elaboration are discussed.
机译:尽管通过演讲活动学习似乎有据可查,但尚不清楚涉及哪些机制和行为变量。当两个或多个学习者在在线学习环境中互动时,究竟对学习有何贡献?为了在构造水平上分析中心话语活动与个人学习结果之间的相互关系,我们将结构方程模型应用于在一系列同类实验中从160个从事在线书面学习话语的二元组收集的数据。我们分析了在线话语中概念阐述活动的三个基于理论的指标:要求获得信息和扩展知识的问题数量,为表达个人知识而制定的解释数量以及在职话语的数量。个体的概念性理解由客观的学习参数代表,这些参数在每个特定的实验任务中都不同。这些措施衡量了对所讨论主题的一般理解以及对概念术语的特殊理解,并辅以个人自我评估知识的获得。结构方程建模的结果表明,二进式概念阐述对建构层次上的个人理解具有强大的影响力,表明二进式详尽阐述促进了对专业概念和一般内容知识的详尽的个人理解的发展。此外,最好通过话语中的解释数量来衡量概念上的阐述。讨论了关于协作学习环境的哪些特征促进相互概念阐述的含义。

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