在可说服的开放式学习者模型中引入学习可视化和元认知支持

S. Bull, B. Ginon, Clelia Boscolo, Matthew D. Johnson
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引用次数: 63

摘要

本文将开放式学习者模型描述为学习者学习的可视化,特别关注如何使用有关他们学习的信息来帮助他们反思自己的技能,识别技能差距,并规划未来的学习。我们提供了一种方法,除了提供他们学习的可视化,允许学习者提出改变他们的学习者模型。这样做的目的是通过考虑学生对自己学习的看法来帮助提高学习者模型的准确性,同时也促进学习者对自己学习的反思,作为讨论学习者模型内容的一部分。这与最近对学习者学习分析的呼吁是一致的。基于先前的研究表明学习者将使用开放式学习模型,我们在此调查他们对开放式学习模型特征的初始反应,以确定在可选的基础上提供开放式学习模型的上下文中接受的可能性。我们关注的是大学生对一系列可视化的看法,以及他们对查看学习者模型数据证据和提出价值变更建议的设施的偏好。
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Introduction of learning visualisations and metacognitive support in a persuadable open learner model
This paper describes open learner models as visualisations of learning for learners, with a particular focus on how information about their learning can be used to help them reflect on their skills, identify gaps in their skills, and plan their future learning. We offer an approach that, in addition to providing visualisations of their learning, allows learners to propose changes to their learner model. This aims to help improve the accuracy of the learner model by taking into account student viewpoints on their learning, while also promoting learner reflection on their learning as part of a discussion of the content of their learner model. This aligns well with recent calls for learning analytics for learners. Building on previous research showing that learners will use open learner models, we here investigate their initial reactions to open learner model features to identify the likelihood of uptake in contexts where an open learner model is offered on an optional basis. We focus on university students' perceptions of a range of visualisations and their stated preferences for a facility to view evidence for the learner model data and to propose changes to the values.
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