Using text mining to uncover students' technology-related problems in live video streaming

Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streami...

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Bibliographic Details
Published in:British journal of educational technology 2011-01, Vol.42 (1), p.40-49
Main Authors: Abdous, M'hammed, He, Wu
Format: Article
Language:English
Subjects:
British
College Students
Colleges
Data Analysis
Data mining
Data Processing
Education
Educational technology
Higher Education
Learning
Learning Experience
Mining
Pattern Recognition
Streaming media
Student Participation
Students
Texts
Video Technology
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Summary:Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related‐problems and to improve their learning experience, we applied text mining to data culled from LVS interactions. Our findings revealed low LVS student participation, which triggered us to initiate several actions to promote more active student participation. Our findings support previous studies regarding the effectiveness of data mining in transforming raw educational data into knowledge and decision‐making tools.
ISSN:0007-1013
1467-8535
DOI:10.1111/j.1467-8535.2009.00980.x