Analysing the outcome of a learning process conducted within the system ALS_CORR[LP]

Abstract

This paper presents the results of an experiment, conducted on a sample of computer science students, using the adaptive learning system called ALS_CORR[LP]1. Indeed, unlike the traditional LMS, adaptive learning systems provide a personalized learning experience based on specific objectives, prerequisites and learning styles, generating thereby a specific learning path. However, the main issue resides in the fact that they assume that the generated learning path is supposedly the leading one, which is far from being true, as we can always detect some failure cases during the evaluation phase. In this paper we will conduct a learning experiment using the system ALS_CORR[LP], which has the ability to correct the generated learning path by recommending the most relevant learning objects, and update the learner model based on a calculation of similarity in behavior between the struggling learner and the succeeding ones. We will later analyze the results of behavior tracking within the system.