Mining fuzzy motivation indicator in learning environment through Human Computer Interaction

Mining traces of Human Computer Interaction (HCI) in Computing Environment for Human Learning allows identification and detection of the learner´s activities and motivation. Motivation is a key factor in all areas of life; it is a concept that has received much attention in psychology learning. The learner´s motivation is a dynamic process that evolves constantly over time, depending on his personality and his traits. The higher learner´s motivation is, the higher his ability will be. In this paper, we combine web mining types and fuzzification in order to supply the decision process about the learner´s motivation. Web mining is a valuable source of information that depict the leaner´s behavior; the proposed approach thereby, suggests an extraction model of motivation indicator during the learning session through learner´s browsing trace. However, motivation is very vague notion; we consider fuzziness as a concept in which the scale of motivation construction is based.