Thematic analysis of individual feedback: Improving cohort feedforward

Richard Edward Meredith

Abstract


Is there a practical way to identify academic at-risk students before the start of term? Or is there no alternative but to look for in-class cues and formative assessment patterns or even wait to mark summative submissions after the term is over? This conference reflection essay offers a potential contribution to answering those questions. It suggests Turnitin assessment text data be make visible rather than remaining unseen, unnoticed, and therefore unactionable (Bienkowski et al., 2012). A poster presentation at the University of Greenwich Learning and Teaching festival 2019 became a transformative learning experience that led to Turnitin assessment data being conceived as a new data source for learning analytics, modelled using Activity Theory.


Keywords


Learning Theories; Learner Analytics

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References


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DOI: https://doi.org/10.21100/compass.v13i1.1055

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