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

Publisher:
ACM
Publication Type:
Conference Proceeding
Citation:
Proceedings of the Fifth International Conference on Learning Analytics And Knowledge, 2015, pp. 275 - 279
Issue Date:
2015
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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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