Journals Proceedings

International Journal of Advances in Computer Science and Its Applications

Prediction of an assistance scenario adapted to learning styles of learners



Assistance systems require a growing interest from a large community of researchers especially in the context of online learning, their main purpose is to provide a proactive or reactive support to accomplish a learning activity. The diversity of roles and skills required in tutoring (perception of behaviour, interaction analysis, increasing motivation and regulation rhythm, etc.) makes the task of tutor arduous and difficult to manage. Thus, the assistance of tutors is the main focus of several research offering assistance of answers in the form of learning situations models and support tools for the various tasks that the tutor must ensure to his learners. However, elementary and repetitive tasks of tutor are rarely taken into account specifically for their proactive character. Therefore, we propose to support learning scenario of learner by an assistance scenario suitable for his learning style, on the basis of a set of pre-defined assistance objects. The assistance of tutors allows then, on the one hand, to advise them on interventions that best respond to the need of learner, and on the other hand, to trigger an automatic assistance according to specific conditions, discharging the tutor automatable repetitive and arduous tasks. Our contribution aims to relieve the tutor in his simple and monotonous tasks thanks to prediction method based on the Model of Assistance Object (MAO). The model aims to facilitate to tutor the definition of assistance objects more precisely. These assistance objects are used then by our prediction method to predict those most suitable depending on the learner’s context, his learning style, and the feedback on the impact of objects of assistance which were previously presented.

No fo Author(s) : 3
Page(s) : 361 - 367
Electronic ISSN : 2250 - 3765
Volume 5 : Issue 2
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