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Analyzing Contextualized Attention Metadata with Rough Set Methodologies to Support Self-regulated Learning

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3 Author(s)
Scheffel, M. ; Fraunhofer Inst. for Appl. Inf. Technol. FIT, St. Augustin, Germany ; Wolpers, M. ; Beer, F.

A learner's interaction with her computer can be recorded and stored in the format of Contextualized Attention Metadata. The collected data can then be analyzed to support the learner in her self-reflection processes. We present two ways to discover patterns in the collected attention metadata by applying methodologies based on the Rough Set Theory and explain how these results can support a learner when learning in a self-regulated way.

Published in:

Advanced Learning Technologies (ICALT), 2010 IEEE 10th International Conference on

Date of Conference:

5-7 July 2010

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