Literaturnachweis - Detailanzeige
Autor/inn/en | Abdous, M'hammed; He, Wu |
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Titel | Using Text Mining to Uncover Students' Technology-Related Problems in Live Video Streaming |
Quelle | In: British Journal of Educational Technology, 42 (2011) 1, S.40-49 (10 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 0007-1013 |
DOI | 10.1111/j.1467-8535.2009.00980.x |
Schlagwörter | Video Technology; Student Participation; Data Analysis; Learning Experience; College Students; Colleges; Higher Education; Data Processing; Pattern Recognition |
Abstract | 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. (Contains 4 figures and 1 table.) (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2017/4/10 |