ICT Competence-Based Learning Object Recommendations for Teachers
International Conference on Cognition and Exploratory Learning in Digital Age (CELDA),
Recommender Systems (RS) have been applied in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Object (LO) selection and retrieval. Most of the existing approaches, however, aim at accommodating the needs of learners and teacher-oriented RS are still an under-investigated field. Moreover, the systems that focus on teachers, do not explicitly exploit their ICT competence profiles when providing LO recommendations. This is a significant drawback, since it can result in LO recommendations that are beyond the teachers' competence to use. Towards tackling this issue, this paper extends previous work and proposes a teacher ICT Competence-based RS that considers teachers' ICT Competence Profiles when recommending Learning Objects. Moreover, the results of its accuracy evaluation are presented. The results indicate that the proposed approach provides high predictive accuracy and outperforms commonly used, existing RS approaches. [The work presented in this paper has been partly supported by the Open Discovery Space Project that is funded by the European Commission's CIP-ICT Policy Support Programme (Project Number: 297229). For complete proceedings, see ED557311.]
Sergis, S., Zervas, P. & Sampson, D.G. (2014). ICT Competence-Based Learning Object Recommendations for Teachers. Presented at International Conference on Cognition and Exploratory Learning in Digital Age (CELDA) 2014.