Detecting and making use of emotions to enhance student motivation in e-learning environments. (1st January 2014) - Rodriguez, Pilar; Ortigosa, Alvaro; Carro, Rosa M.
In this work, we investigate the possibility of detecting the student emotions by analysing their self-written essays. Detecting student emotions in e-learning environments would make it possible to enhance the learning processes accordingly. With that purpose, we have analysed 38 essays written by a student during her first three semesters in college. The results obtained support the idea that inferring user motivation from the emotions detected in texts is feasible. E-learning systems can use motivation information to propose activities aiming at increasing student engagement dynamically. In this direction, we present an example of use in an existing context-based adaptive e-learning system. Incorporating emotions to e-learning systems broadens their possibilities, allowing dynamic recommendation of activities and content adaptation according to student emotions. Finally, it makes it possible to detect potential problems within e-courses dynamically.