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首页> 外文期刊>Journal of Educational Data Mining >Evaluating the Impact of Instructional Support Using Data Mining and Process Mining: A Micro-Level Analysis of the Effectiveness of Metacognitive Prompts
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Evaluating the Impact of Instructional Support Using Data Mining and Process Mining: A Micro-Level Analysis of the Effectiveness of Metacognitive Prompts

机译：使用数据挖掘和过程挖掘评估教学支持的影响：元认知提示有效性的微观分析

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In computer-supported learning environments, the deployment of self-regulatory skills represents an essential prerequisite for successful learning. Metacognitive prompts are a promising type of instructional support to activate students’ strategic learning activities. However, despite positive effects in previous studies, there are still a large number of students who do not benefit from provided support. Therefore, it may be necessary to consider explicitly the conditions under which a prompt is beneficial for a student, i.e., so-called adaptive scaffolding. The current study aims to (i) classify the effectiveness of prompts on regulatory behavior, (ii) investigate the correspondence of the classification with learning outcome, and (iii) discover the conditions under which prompts induce regulatory activities (i.e., the proper temporal positioning of prompts). The think-aloud data of an experiment in which metacognitive prompts supported the experimental group (n = 35) was used to distinguish between effective and non-effective prompts. Students’ activities preceding the prompt presentation were analyzed using data mining and process mining techniques. The results indicate that approximately half of the presented prompts induced metacognitive learning activities as expected. Moreover, the number of induced monitoring activities correlates positively with transfer performance. Finally, the occurrence of orientation and monitoring activities, which are not well-embedded in the course of learning, increases the effectiveness of a presented prompt. In general, our findings demonstrate the benefits of investigating metacognitive support using process data, which can provide implications for the design of effective instructional support.
机译：在计算机支持的学习环境中，自律技能的部署是成功学习的必要先决条件。元认知提示是一种有前途的教学支持，可以激发学生的战略学习活动。但是，尽管先前的研究取得了积极的效果，但仍有大量学生没有从所提供的支持中受益。因此，可能有必要明确考虑提示对学生有益的条件，即所谓的适应性脚手架。当前的研究旨在（i）对提示对调节行为的有效性进行分类;（ii）研究分类与学习结果的对应关系;（iii）发现提示促使调节活动的条件（即适当的时间定位）提示）。元认知提示支持实验组（n = 35）的实验的思维能力数据用于区分有效提示和无效提示。使用数据挖掘和过程挖掘技术分析了在快速演示之前学生的活动。结果表明，所提出的提示中大约有一半引起了预期的元认知学习活动。此外，诱导的监控活动的数量与传输性能呈正相关。最后，定向和监控活动的发生，在学习过程中没有被很好地嵌入，提高了提示的有效性。总的来说，我们的发现证明了使用过程数据研究元认知支持的好处，这可以为有效的教学支持设计提供启示。

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