Discourse-centric learning analytics

A. Liddo, S. B. Shum, I. Quinto, Michelle Bachler, L. Cannavacciuolo
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引用次数: 136

Abstract

Drawing on sociocultural discourse analysis and argumentation theory, we motivate a focus on learners' discourse as a promising site for identifying patterns of activity which correspond to meaningful learning and knowledge construction. However, software platforms must gain access to qualitative information about the rhetorical dimensions to discourse contributions to enable such analytics. This is difficult to extract from naturally occurring text, but the emergence of more-structured annotation and deliberation platforms for learning makes such information available. Using the Cohere web application as a research vehicle, we present examples of analytics at the level of individual learners and groups, showing conceptual and social network patterns, which we propose as indicators of meaningful learning.
以话语为中心的学习分析
利用社会文化话语分析和论证理论,我们鼓励关注学习者的话语,作为识别与有意义的学习和知识建构相对应的活动模式的有前途的场所。然而,软件平台必须获得关于话语贡献的修辞维度的定性信息,以实现这种分析。这很难从自然发生的文本中提取出来,但更结构化的注释和学习审议平台的出现使这些信息变得可用。使用coherence web应用程序作为研究工具,我们展示了个体学习者和群体层面的分析示例,展示了概念和社会网络模式,我们将其作为有意义学习的指标。
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