Innovative learning analytics research at a data-driven HEI

Azcona, David, Corrigan, Owen, Scanlon, Philip and Smeaton, Alan F. (2017) Innovative learning analytics research at a data-driven HEI.

Abstract

A university campus is comprised of Schools and Faculties attended by students whose primary intention is to learn and ultimately graduate with their desired qualification. From the moment students apply to a university and thereafter gain acceptance and attend the campus they create a unique digital footprint of themselves within the university IT systems. Students’ digital footprints are a source of data that is of interest to groups including teachers, analysts, administrators and policy makers in the education, sociology, and pedagogy domains. Learning analytics can offer tools to mine such data producing actionable knowledge for purposes of improving student retention, curriculum enhancement, student progress and feedback, and administrative evolution. In this paper, we summarise three ongoing Learning Analytics projects from an Irish university, demonstrating the potential that exists to enhance Higher Education pedagogical approaches. First year students often struggle with making the transition into University as they adapt to life and study at a Higher Education Institution. The research projects in the area of Learning Analytics at our institution focus on: improving test performance using analytics from a general-purpose VLE like Moodle, identifying studying groups and the performance peer effect using on-campus geolocation data, and detecting lower-performing or at-risk students on programming modules.

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