A Learning Object Recommendation Model with User Mood Characteristics

Emotions influence human cognition, affecting perception and understanding of a specific situation; therefore emotions can affect positively or negatively the learning process. Currently there are few information systems that analyze users’ emotions to optimize their learning. This article proposes a model that includes users’ temporary emotions to recommend Learning Objects (LO) and deliver relevant educational materials. Three stages are set; initially, the model recognizes a user’s emotions and learning style; then a recommendation system is applied to identify relevant LOs; and finally, the presentation of this information is showed to the user. In this work we present a method that identifies the emotion of the user based on facial recognition, and the process of recommendation is presented.