Explaining Need-based Educational Recommendations Using Interactive Open Learner Models

Explaining Need-based Educational Recommendations Using Interactive Open Learner Models
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使用交互式开放学习者模型解释基于需求的教育建议

DOI:
10.1145/3314183.3323463
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发表时间:
2019
期刊:
UMAP '19
影响因子:
--
通讯作者:
Brusilovsky, Peter
Brusilovsky, Peter
中科院分区:
--
文献类型:
--
作者:
Barria-Pineda, Jordan;Akhuseyinoglu, Kamil;Brusilovsky, Peter

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学生在整个学习过程中可能追求不同的目标。例如,他们可能正在寻找新的材料来扩大他们目前的知识水平,重复以前课程的内容来准备考试,或者致力于解决他们最近的误解。多个潜在目标需要一个适应性的电子学习系统来推荐适合学生意图的学习内容,并在这个目标的背景下解释这一建议。在以前的工作中,我们探索了针对最典型的知识扩展目标的可解释推荐。在本文中,我们关注学生在解决编程问题时纠正误解的迫切需要。我们生成学习内容推荐,以针对学生最近遇到的困难的概念。同时,我们为该推荐目标提供解释,以支持学生理解为什么推荐某些学习活动。本文概述了这个可解释的教育推荐系统的设计,并描述了其正在进行的评估
Students might pursue different goals throughout their learning process. For example, they might be seeking new material to expand their current level of knowledge, repeating content of prior classes to prepare for an exam, or working on addressing their most recent misconceptions. Multiple potential goals require an adaptive e-learning system to recommend learning content appropriate for students' intent and to explain this recommendation in the context of this goal. In our prior work, we explored explainable recommendations for the most typical 'knowledge expansion goal". In this paper, we focus on students' immediate needs to remedy misunderstandings when they solve programming problems. We generate learning content recommendations to target the concepts with which students have struggled more recently. At the same time, we produce explanations for this recommendation goal in order to support students' understanding of why certain learning activities are recommended. The paper provides an overview of the design of this explainable educational recommender system and describes its ongoing evaluation
通过细粒度的开放学习者模型使教育建议透明化
DOI: --
发表时间: 2019
期刊: IUI 2019
影响因子: --
作者:
Barria-Pineda, Jordan;Brusilovsky, Peter
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