Abstract:

In this paper, we discuss a use-case of integrating a recommender for a blended e-learning system in vocational education. The recommender takes into account general and specific parameters that are relevant in the learning content suggestion in the construction work domain, obtained through literature review and practitioners' experience of the project D-MasterGuide (funded by the German Federal Ministry of Education and Research under reference 01PZ16010F). The main goal of the project in general is not only to foster the acquisition of domain knowledge but also to build up media literacy and self-competence of students – increasing digitalization pace requires new skills from the learners whereas the domain of skilled crafts lags behind the other domains. To achieve that, we built eight digital learning stations in a smart-guided learning management system based on the vocational education training of plaster workers in Germany. The recommender system in question pursues the goal of simplification of the content exploration by suggesting supposedly more relevant items for the specific user. In the article we discuss the process of creation of the recommender and design decisions behind that, report results of preliminary usability study and discuss various ways of showing recommendations to the user. The outcomes of this paper suggest practitioners with the lessons learned from the qualitative observations of the project in general and quantitative evaluations of the recommender system in particular. Specifically, we discussed timings and wordings of suggestions made by the recommender: e.g., what would be seen as more valuable, the suggestion that a lot of classmates find a learning unit useful or suggestion that a tutor? when recommendations are seen as more useful, when they specifically asked by the users or when suggested by the system? The results suggest that use of recommender system can increase coverage and exploration of new learning material. On the other hand, we also report problems concerning implementation and integration of the used system and give implications for the future works in that direction.

Keywords:

VET, e-learning, LMS, Recommendation System.