Learning analytics to identify exploratory dialogue within synchronous text chat

As work on SocialLearn progresses, learning analytics increasingly become a focus of the research work.

Internationally, interest in learning analytics is also growing, with the first Learning Analytics and Knowledge donference taking place in Banff.

I didn’t make it to the conference, but co-author Simon Buckingham Shum presented our paper instead.

Ferguson, Rebecca and Buckingham Shum, Simon (2011). Learning analytics to identify exploratory dialogue within synchronous text chat. In: LAK 2011: 1st International Conference on Learning Analytics & Knowledge, 27 Feb – 01 Mar 2011, Banff, Alberta.

Abstract

While generic web analytics tend to focus on easily harvested quantitative data, Learning Analytics will often seek qualitative understanding of the context and meaning of this information. This is critical in the case of dialogue, which may be employed to share knowledge and jointly construct understandings, but which also involves many superficial exchanges. Previous studies have validated a particular pattern of “exploratory dialogue” in learning environments to signify sharing, challenge, evaluation and careful consideration by participants. This study investigates the use of sociocultural discourse analysis to analyse synchronous text chat during an online conference. Key words and phrases indicative of exploratory dialogue were identified in these exchanges, and peaks of exploratory dialogue were associated with periods set aside for discussion and keynote speakers. Fewer individuals posted at these times, but meaningful discussion outweighed trivial exchanges. If further analysis confirms the validity of these markers as learning analytics, they could be used by recommendation engines to support learners and teachers in locating dialogue exchanges where deeper learning appears to be taking place.

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