R
Riina Vuorikari
Researcher at European Schoolnet
Publications - 43
Citations - 1798
Riina Vuorikari is an academic researcher from European Schoolnet. The author has contributed to research in topics: Recommender system & Professional learning community. The author has an hindex of 18, co-authored 43 publications receiving 1600 citations. Previous affiliations of Riina Vuorikari include Katholieke Universiteit Leuven.
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DigComp 2.1: the digital competence framework for citizens
TL;DR: This work presents now 8 proficiency levels and examples of use applied to the learning and employment field based on the reference conceptual model published in DigComp 2.0.
Book ChapterDOI
Recommender Systems in Technology Enhanced Learning
TL;DR: Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. K., & Koper, R. (2011).
Proceedings ArticleDOI
Dataset-driven research for improving recommender systems for learning
Katrien Verbert,Hendrik Drachsler,Nikos Manouselis,Martin Wolpers,Riina Vuorikari,Erik Duval +5 more
TL;DR: An experimental comparison of the accuracy of several collaborative filtering algorithms applied to these TEL datasets are presented and implicit relevance data, such as downloads and tags, that can be used to improve the performance of recommendation algorithms are elaborate.
Journal ArticleDOI
Collaborative recommendation of e-learning resources: an experimental investigation
TL;DR: The case of developing a learning resources' collaborative filtering service for an online community of teachers in Europe was examined and results indicated that the development of such systems should be taking place considering the particularities of the actual communities that are to be served.
Journal ArticleDOI
Issues and considerations regarding sharable data sets for recommender systems in technology enhanced learning
Hendrik Drachsler,Toine Bogers,Riina Vuorikari,Katrien Verbert,Erik Duval,Nikos Manouselis,Guenter Beham,Stephanie Lindstaedt,Hermann Stern,Martin Friedrich,Martin Wolpers +10 more
TL;DR: The issue of missing data sets for recommender systems in Technology Enhanced Learning that can be used as benchmarks to compare different recommendation approaches is raised and an initial elaboration of a representation and exchange format for sharable TEL data sets is carried out.