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

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

Content Provider	ACM Digital Library
Author	Ferguson, Rebecca Buckingham Shum, Simon Wei, Zhongyu He, Yulan
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.
Starting Page	85
Ending Page	93
Page Count	9
File Format	PDF
ISBN	9781450317856
DOI	10.1145/2460296.2460313
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-04-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Social learning analytics Educational assessment Cue-phrase matching Social learning Sociallearn Exploratory dialogue Learning analytics Maxent Self-training framework k-nearest neighbour Synchronous dialogue Computational linguistics Discourse analytics Educational dialogue
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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