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, the adaptive learning systems provide a personalized learning experience based on the objectives, the prerequisites or even the learning styles generating thereafter a specific learning path. However their main issue remains the fact, that they assume that the generated learning path is necessarily the leading one, which is far from being true, since we can always detect some failure cases during the evaluation phase. In this paper we conduct a learning experience 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 analyze later the results of behavior tracking within the system.