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Understanding Learning and Learning Design in MOOCs: A Measurement-Based Interpretation

机译:了解MOOC中的学习和学习设计:基于度量的解释

摘要

The paper describes empirical investigations of how participants in a MOOC learn, and the implications for MOOC design. A learner capability to generate higher order learning in MOOCs — called crowd-sourced learning (C-SL) capability — was defined from learning science literature. The capability comprised a complex yet interrelated array of attitudes, beliefs, and understandings about learning that participants bring to a MOOC and which shape their behaviour and explain why individuals differ in their ability to generate higher order learning. The capability was formulated as a developmental progression describing behaviours associated with five levels, from novice to expert, charting the degree to which learners regulate their own learning, effectively exploit the scale and diversity of MOOCs, and harness opportunities for distributed teaching. Item response theory was applied to log stream data in two MOOCs to construct empirically validated measures of this capability, enabling each MOOC learner to be assessed for learning capability on a scale from novice to expert. The majority of participants did not behave in ways conducive to the generation of higher order learning, but the C-SL progression suggested principles to guide MOOC design to make them more efficacious, which, when empirically investigated, were found to be efficacious.
机译:本文描述了关于MOOC参与者如何学习以及对MOOC设计的影响的实证研究。从学习科学文献中定义了一种在MOOC中产生高级学习的学习者能力-称为众包学习(C-SL)能力。该功能包括参与者对MOOC所带来的关于学习的态度,信念和理解,这些复杂但相互关联的数组构成了参与者的行为,并解释了为什么个人在产生高级学习上的能力不同。该能力被描述为一种发展过程,描述了从新手到专家的五个层次的行为,标明了学习者调节自己的学习程度,有效利用MOOC的规模和多样性以及利用分布式教学机会的程度。将项目响应理论应用于两个MOOC中的日志流数据,以构建对此能力进行经验验证的度量,从而使从新手到专家的每个评估MOOC学习者的学习能力得到评估。大多数参与者的行为方式不适合于生成高阶学习,但是C-SL的进步提出了指导MOOC设计以使其更有效的原则,经实证研究,这些原则被认为是有效的。

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