A Methodological Approach to Eliciting Affective Educational Recommendations

Abstract

The emotional situation of the learner can influence the learning process. For this reason, we are researching how educational recommender systems can take advantage of affective computing to improve the recommendation support in educational scenarios. The paper reports works carried out involving 18 educators and 77 learners to elicit and design emotional feedback to be provided for learners in terms of personalized recommendations. To this end, user centered design methods and data mining techniques are used.