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Analysing reflective text for learning analytics : an approach using anomaly recontextualisation

Authors
  • Gibson, Andrew
  • Kitto, Kirsty
Publication Date
Mar 16, 2015
Source
Queensland University of Technology ePrints Archive
Keywords
License
Unknown
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Abstract

Reflective writing is an important learning task to help foster reflective practice, but even when assessed it is rarely analysed or critically reviewed due to its subjective and affective nature. We propose a process for capturing subjective and affective analytics based on the identification and recontextualisation of anomalous features within reflective text. We evaluate 2 human supervised trials of the process, and so demonstrate the potential for an automated Anomaly Recontextualisation process for Learning Analytics.

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