This paper raises the issue of missing data sets for recommender systems in Technology Enhanced Learning that can be used as benchmarks to compare different recommendation approaches. It discusses how suitable data sets could be created according to some initial suggestions, and investigates a number of steps that may be followed in order to develop reference data sets that will be adopted and reused within a scientific community. In addition, policies are discussed that are needed to enhance sharing of data sets by taking into account legal protection rights. Finally, an initial elaboration of a representation and exchange format for sharable TEL data sets is carried out. The paper concludes with future research needs.status: publishe
The dataTEL white paper develop during the dataTEL workshop at the ARV2011. The workshop was motivat...
This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their ...
Personalisation, adaptation and recommendation are central features of TEL environments. In this con...
AbstractThis paper raises the issue of missing data sets for recommender systems in Technology Enhan...
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G., Lindst...
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G., Lindsta...
Abstract. This paper raises the issue of missing standardised data sets for recommender systems in T...
Drachsler, H. (2011, 29 March). dataTEL - Datasets for Recommender Systems in Technology-Enhanced Le...
In the world of recommender systems, it is a common practice to use public available datasets from d...
As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical inno...
Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that ...
The workshop was motivated by the issue that very less educational datasets are publicly available i...
This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their...
Drachsler, H., Verbert, K., Sicilia, M. A., Wolpers, M., Manouselis, N., Vuorikari, R., Lindstaedt,...
This paper discusses challenges and possible solutions of recommender systems for Technology-Enhance...
The dataTEL white paper develop during the dataTEL workshop at the ARV2011. The workshop was motivat...
This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their ...
Personalisation, adaptation and recommendation are central features of TEL environments. In this con...
AbstractThis paper raises the issue of missing data sets for recommender systems in Technology Enhan...
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G., Lindst...
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G., Lindsta...
Abstract. This paper raises the issue of missing standardised data sets for recommender systems in T...
Drachsler, H. (2011, 29 March). dataTEL - Datasets for Recommender Systems in Technology-Enhanced Le...
In the world of recommender systems, it is a common practice to use public available datasets from d...
As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical inno...
Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that ...
The workshop was motivated by the issue that very less educational datasets are publicly available i...
This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their...
Drachsler, H., Verbert, K., Sicilia, M. A., Wolpers, M., Manouselis, N., Vuorikari, R., Lindstaedt,...
This paper discusses challenges and possible solutions of recommender systems for Technology-Enhance...
The dataTEL white paper develop during the dataTEL workshop at the ARV2011. The workshop was motivat...
This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their ...
Personalisation, adaptation and recommendation are central features of TEL environments. In this con...