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Sage on the Stage: Big Data, Customized Learning, and the Desire for Human Interaction

Sage on the Stage: Big Data, Customized Learning, and the Desire for Human Interaction

Ersoy-Babula, Idil ORCID: 0000-0003-3046-9240 and Babula, Michael ORCID: 0000-0002-3567-6700 (2018) Sage on the Stage: Big Data, Customized Learning, and the Desire for Human Interaction. In: 24th Annual Conference and Exhibition of the SLA/AGC Big Data and its investment prospects, 06 - 08 March 2018, Muscat, Oman.

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Abstract

A research question arising in academia is whether the desire by administrators to collect, analyze, and disseminate ‘big data’ has become a driving force in how education is delivered. One area where data is being collected on students is through the use of Virtual Learning Environments (VLEs). We wanted to explore whether students believed that the mass information collected on them would lead to improved customized education, or whether it would be used a cost-cutting mechanism to eliminate the lecturer. Lecturers salaries tend to make up the majority of academic budgets. Focus groups were conducted among first, second and final year undergraduate business students. Participants report that they do not wish to see VLEs replace traditional lectures or tutorials and there is some push-back by students in that they do not want the ‘sage on the stage’ to be replaced the use of data to customized student led learning. Business students in this sample view the value in VLEs to disseminate textbook and journal article information and to promote collaborative learning and contribute to employability. Implications for higher education are discussed.

Item Type: Conference or Conference Paper (Paper)
Uncontrolled Keywords: Big data, VLE’s, austerity, flexible learning, online learning
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Systems Management & Strategy
Last Modified: 05 Aug 2018 00:11
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/20894

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