Home / Event / The Anna Karenina principle: One university’s approach to the adoption of learning analytics

The Anna Karenina principle: One university’s approach to the adoption of learning analytics

Date: Saturday, 2nd November 2019
Time: 12:45 PM
Location: CIC Ideation Studio


Presenter: Dr. Irina Elgort (Presenter), Steven Warburton & Derek White Victoria University of Wellington, New Zealand

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Many institutions are making significant investments to build their learning analytics capability yet creating a successful platform for large-sale adoption of learning analytics (LA) is not simple. Building on existing knowledge about LA, we outline our attempt to resolve tensions early in the adoption process and thus, hopefully, “avoid failure” (Ferguson & Clow, 2017) in the future. In this case study, we describe the development and adoption of a three-tier model designed for cross institutional engagement, buy-in and implementation of LA. We outline the actions taken at the three differentiated but interconnected levels of governance, projects and community. In relation to the first tier, we describe a contextualised policy development initiative based on the SHEILA framework and present an outcome proto-governance model for LA. The scope of the second tier was confined to five small-scale pilots of tools and approaches that utilize learning data to support, understand and optimise learning, which included basic LA tools provided in the institutional LMS, StudentVis (a faculty homegrown data visualisation tool), OnTask, AcaWriter and Quantext. The third tier concerned open community building and shared research enterprise. We analyse the results from activity in these three areas and mark out a set of recommendations for future action that we anticipate will continue to build, drive and gain value from LA deployment across the institution.

Dr Irina Elgort is Senior Lecturer in Higher Education at Victoria University of Wellington, New Zealand. Her professional and research interests include learning analytics, automated text analysis (with a focus on the analysis of first and second language student writing), computer assisted language learning and second language acquisition (with a focus on lexical development).