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An evaluation of learning analytics to identify exploratory dialogue in online discussions

Ferguson, Rebecca; Wei, Zhongyu; He, Yulan and Buckingham Shum, Simon (2013). An evaluation of learning analytics to identify exploratory dialogue in online discussions. In: Third Conference on Learning Analytics and Knowledge (LAK 2013), 8-12 April 2013, Leuven, Belgium, ACM, pp. 85–93.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1145/2460296.2460313
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Abstract

Social learning analytics are concerned with the process of knowledge construction as learners build knowledge together in their social and cultural environments. One of the most important tools employed during this process is language. In this paper we take exploratory dialogue, a joint form of co-reasoning, to be an external indicator that learning is taking place. Using techniques developed within the field of computational linguistics, we build on previous work using cue phrases to identify exploratory dialogue within online discussion. Automatic detection of this type of dialogue is framed as a binary classification task that labels each contribution to an online discussion as exploratory or non-exploratory. We describe the development of a self-training framework that employs discourse features and topical features for classification by integrating both cue-phrase matching and k-nearest neighbour classification. Experiments with a corpus constructed from the archive of a two-day online conference show that our proposed framework outperforms other approaches. A classifier developed using the self-training framework is able to make useful distinctions between the learning dialogue taking place at different times within an online conference as well as between the contributions of individual participants.

Item Type: Conference or Workshop Item
Copyright Holders: 2013 ACM
ISBN: 1-4503-1785-5, 978-1-4503-1785-6
Keywords: computational linguistics; cue-phrase matching; discourse analytics; educational dialogue; exploratory dialogue; learning analytics, educational assessment; k-nearest neighbour; MaxEnt;self-training framework; social learning analytics; social learning; SocialLearn; synchronous dialogue
Academic Unit/School: Learning Teaching and Innovation (LTI) > Institute of Educational Technology (IET)
Learning Teaching and Innovation (LTI)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Education and Educational Technology (CREET)
Centre for Research in Computing (CRC)
Related URLs:
Item ID: 36664
Depositing User: Rebecca Ferguson
Date Deposited: 21 Feb 2013 09:24
Last Modified: 07 Feb 2017 19:00
URI: http://oro.open.ac.uk/id/eprint/36664
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