Open Learner Models in Smart Learning Environments

Angeliki Leonardou, Maria Rigou, J. Garofalakis
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引用次数: 6

Abstract

Smart learning environments (SLEs), like all adaptive learning systems, are built around the learner model and use it to support a variety of interventions such as mastery learning, scaffolding, adaptive sequencing, and adaptive navigation support. Open learner models (OLMs) “expose” the learner data to users through easily perceivable visual representations aiming to improve student self-reflection and self-regulated learning and also increase user motivation and even foster collaboration. This chapter presents the evolution and current state of OLMs, summarizes related research in the field emphasizing on OLM types, locus of control between the system and the user and visualizations categorized on the basis of quantized/continuous and structured/unstructured representations. OLM cases implementing typical SLEs features are described, along with representative real-life scenarios of incorporating OLMs in SLEs. Moreover, the chapter provides guidelines for designing effective OLMs and discusses current research trends in this active scientific field.
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智能学习环境中的开放式学习者模型
像所有自适应学习系统一样,智能学习环境(SLEs)是围绕学习者模型构建的,并使用它来支持各种干预措施,如掌握学习、脚手架、自适应排序和自适应导航支持。开放学习者模型(olm)通过易于感知的视觉表示将学习者数据“暴露”给用户,旨在提高学生的自我反思和自我调节学习,并增加用户动机,甚至促进协作。本章介绍了OLM的发展和现状,总结了该领域的相关研究,重点介绍了OLM的类型、系统与用户之间的控制点以及基于量化/连续和结构化/非结构化表示分类的可视化。本文描述了实现典型SLEs特性的OLM案例,以及在SLEs中合并OLM的代表性现实场景。此外,本章还提供了设计有效olm的指导方针,并讨论了这一活跃科学领域的当前研究趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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