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Applying Quantified Self Approaches to Support Reflective Learning
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, стр. 111–114. New York, NY, USA, Association for Computing Machinery, (2012)
DOI: 10.1145/2330601.2330631
Аннотация
This paper presents a framework for technical support of reflective learning, derived from a unification of reflective learning theory with a conceptual framework of Quantified Self tools -- tools for collecting personally relevant information for gaining self-knowledge. Reflective learning means returning to and evaluating past experiences in order to promote continuous learning and improve future experiences. Whilst the reflective learning theories do not sufficiently consider technical support, Quantified Self (QS) approaches are rather experimental and the many emergent tools are disconnected from the goals and benefits of their use. This paper brings these two strands into one unified framework that shows how QS approaches can support reflective learning processes on the one hand and how reflective learning can inform the design of new QS tools for informal learning purposes on the other hand.
