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Type: Conference paper
Title: A framework for topic generation and labeling from MOOC discussions
Author: Atapattu Mudiyanselage, T.
Falkner, K.
Citation: Proceedings of the Third (2016) ACM Conference on Learning @ Scale, 2016, pp.201-204
Publisher: ACM New York
Publisher Place: NY, USA
Issue Date: 2016
ISBN: 978-1-4503-3726-7
Conference Name: Learning at Scale (25 Apr 2016 - 26 Apr 2016 : Edinburgh, UK)
Statement of
Thushari Atapattu, Katrina Falkner
Abstract: This study proposes a standardised open framework to automatically generate and label discussion topics from Massive Open Online Courses (MOOCs). The proposed framework expects to overcome the issues experienced by MOOC participants and teaching staff in locating and navigating their information needs effectively. We analysed two MOOCs - Machine Learning and Statistics: Making Sense of Data offered during 2013 and obtained statistically significant results for automated topic labeling. However, more experiments with additional MOOCs from different MOOC platforms are necessary to generalise our findings.
Rights: Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author. Copyright is held by the owner/author(s).
DOI: 10.1145/2876034.2893414
Appears in Collections:Aurora harvest 8
Computer Science publications

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