What Works: Creating Adaptive and Intelligent Systems for Collaborative Learning Support
作者： Nia M Dowell , Whitney L Cade , Yla Tausczik , James Pennebaker , Arthur C Graesser
DOI: 10.1007/978-3-319-07221-0_15
关键词:
摘要: An emerging trend in classrooms is the use of collaborative learning environments that promote lively exchanges between learners order to facilitate learning. This paper explored possibility using discourse features predict student and group performance during interactions. We investigated linguistic patterns chats, within an online exercise, on five dimensions automated facility, Coh-Metrix. The results indicated students who engaged deeper cohesive integration generated more complicated syntactic structures performed significantly better. overall level groups expository style interactions better posttests. Although do not directly express knowledge construction cognitive processes, our indicate these states can be monitored by analyzing language discourse. Implications are discussed regarding computer supported ITS's productive communication environments.
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