Personalisation of Programming Tutoring System Using Tag-Based Recommender Systems

Collaborative tagging systems have grown in popularity over the Web in the last years based on their simplicity to categorize and retrieve content using open-ended tags. Besides helping user to organize his/her personal collections, a tag also can be regarded as a user´s or expert´s personal opinion expression. Thus, the tagging information can be used to make recommendations. In this paper, an innovative architecture for a tag-based recommender system dedicated to the e-learning environments is introduced. This system could support learners by recommending tags and learning resources, online learning activities or optimal browsing pathways, based on their preferences, learning style, knowledge level and the browsing history of other learners with similar characteristics.