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Drachsler Hendrik, Verbert Katrien, Manouselis Nikos, Vuorikari Riina, Wolpers Martin, Lindstaedt Stefanie

Preface [Special issue on dataTEL–Data Supported Research in Technology-Enhanced Learning]

Int. J. Technology Enhanced Learning, 2012

Technology Enhanced Learning is undergoing a significant shift in paradigm towards more data driven systems that will make educational systems more transparent and predictable. Data science and data-driven tools will change the evaluation of educational practice and didactical interventions for individual learners and educational institutions. We summarise these developments and new challenges in the preface of this Special Issue under the keyword dataTEL that stands for ‘Data-Supported Technology-Enhanced Learning’.

Lindstaedt Stefanie , Beham Günter, Stern Hermann, Drachsler H., Bogers T., Vuorikari R., Verbert K., Duval E., Manouselis N., Friedrich M., Wolpers M.

dataTEL - Issues and Considerations regarding Sharable Data Sets for Recommender Systems in Technology Enhanced Learning

1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010), Procedia Computer Science, Elsevier, 2010

This paper raises the issue of missing data sets for recommender systems in Technology Enhanced Learning that can be used asbenchmarks to compare different recommendation approaches. It discusses how suitable data sets could be created according tosome initial suggestions, and investigates a number of steps that may be followed in order to develop reference data sets that willbe adopted and reused within a scientific community. In addition, policies are discussed that are needed to enhance sharing ofdata sets by taking into account legal protection rights. Finally, an initial elaboration of a representation and exchange format forsharable TEL data sets is carried out. The paper concludes with future research needs.
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