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Dataset-Driven Research to Support Learning and Knowledge Analytics

Katrien Verbert, Nikos Manouselis, Hendrik Drachsler and Erik Duval
Journal of Educational Technology & Society
Vol. 15, No. 3, Learning and Knowledge Analytics (July 2012), pp. 133-148
Stable URL: http://www.jstor.org/stable/jeductechsoci.15.3.133
Page Count: 16
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Dataset-Driven Research to Support Learning and Knowledge Analytics
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Abstract

ABSTRACT In various research areas, the availability of open datasets is considered as key for research and application purposes. These datasets are used as benchmarks to develop new algorithms and to compare them to other algorithms in given settings. Finding such available datasets for experimentation can be a challenging task in technology enhanced learning, as there are various sources of data that have not been identified and documented exhaustively. In this paper, we provide such an analysis of datasets that can be used for research on learning and knowledge analytics. First, we present a framework for the analysis of educational datasets. Then, we analyze existing datasets along the dimensions of this framework and outline future challenges for the collection and sharing of educational datasets.

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