生成学习者群体动态的预测模型

Proceedings of the 1st International Conference on Learning Analytics and Knowledge Pub Date : 2011-02-27 DOI:10.1145/2090116.2090139

Chris Teplovs, Nobuko Fujita, Ravikiran Vatrapu

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引用次数: 16

摘要

在本文中，我们提出了一个学习者建模框架，该框架结合了在线话语的潜在语义分析和社会网络分析。该框架由新开发的软件支持，称为知识、交互和社会学生建模探索者(KISSME)，该软件采用学习者之间内容感知交互的高度交互式可视化。我们的目标是开发、使用和完善KISSME，以生成和测试学习者交互的预测模型，以优化学习。

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Generating predictive models of learner community dynamics

In this paper we present a framework for learner modelling that combines latent semantic analysis and social network analysis of online discourse. The framework is supported by newly developed software, known as the Knowledge, Interaction, and Social Student Modelling Explorer (KISSME), that employs highly interactive visualizations of content-aware interactions among learners. Our goal is to develop, use and refine KISSME to generate and test predictive models of learner interactions to optimise learning.

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Proceedings of the 1st International Conference on Learning Analytics and Knowledge

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