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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/4636
Title: Dataset-Driven Research to Support Learning and Knowledge Analytics
Authors: Verbert, Katrien
Manouselis, Nikos
Drachsler, Hendrik
Duval, Erik
Keywords: dataTEL
learning analytics
educational datasets
open science
Issue Date: 20-Dec-2012
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.
Description: Verbert, K., Manouselis, N., Drachsler, H., & Duval, E. (2012). Dataset-Driven Research to Support Learning and Knowledge Analytics. Educational Technology & Society, 15(3), 133–148.
URI: http://hdl.handle.net/1820/4636
Appears in Collections:1. LMedia: Publications and Preprints

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