It has come to our attention that Dr Herb Thompson, professor of Economics and Chair of the Economics department, devotes his first assignment to discovering exactly that. He asks his students to fill an on-line questionnaire on Learning Styles and to hand him the results of this questionnaire. We have asked him to write a piece on “learning styles” for our New Chalk Talk series. We have also asked him to share the results of the questionnaires which he has conducted over two semesters in his Microeconomics class. Dr Thompson has agreed to do this and for that we thank him very much. New Chalk Talk will devote the next two or three issues to this subject. They will appear starting next Tuesday.

Learning and Teaching Styles

The aim of this paper is to present the adaptive learning system called ALS_CORR[LP]1. This system belongs to a very specific class of the e-learning systems, which is the adaptive learning ones. In fact they have the ability to adapt the learning process according to each learner needs, learning styles, objectives, etc. ALS_CORR[LP] is based on the learner prerequisites and the learning styles of Felder-Silverman, to design the learner model. As for the domain model, it is designed according to the recommendations of the differentiated pedagogy, which advocates creating multiple versions of the same learning object. Finally in order to ensure the adaptation inside the system, a Bayesian network, to match the designed learning object with the specifics of the learner profile was developed. It is also necessary to emphasize, that the major feature of the system is, its ability to correct the generated learning path in case of a failure in the evaluation phase. The learning path relevance is questioned, based on a recommendation system which enables updating the initial profile, or recommending the most relevant versions of the learning object, in case where the similarity calculation in behavior, reveals that the observed behavior in the system does not fit the initial profile description.

ALS_CORR[LP]: An adaptive learning system based on the learning styles of Felder-Silverman and a Bayesian network

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.

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Analysing the Outcome of a Learning Process Conducted Within the System ALS_CORR[LP]

The adaptation of the Computing Environment for Human Learning allows adapting the process of learning to needs, to rhythms of every learner, to styles of learning and to preferences, but they do not guarantee an individualized real time follow-up, by favoring the learning of a domain of the acquisition of the knowledge by a learner.One of the objectives of the systems based on the acquisition of the knowledge is to build computer systems allowing the sharing and the re-use of the past experiences, to ensure personalized learning in real-time, by basing on the profile and the rhythm of learning of every learner. The approach of Case-Based Reasoning seems to be a good candidate for the sharing and the re-use of the experience. In this article, we are going to present our architecture of a System of Adaptive Learning by using a Dynamic Case-Based Reasoning and the traces of interactions of the learner with the learning system as the support of reasoning.

Our Architecture of an Adaptive Learning System Based on the Dynamic Case-Based Reasoning and the Learner Traces

Learning styles, learners’ preferred ways to learn, can be applied to design personalized learning courses for the individual learner. One of those applications is the recommender system. This study ran a systematic literature review on the recommender system utilizing learning styles from two dependable academic libraries, IEEE Xplore and ScienceDirect, which included six reviewed topics; research objective, research methodology, educational recommendation, learning styles theory, learning style identification, and recommendation algorithm. Finally, the obtained information was examined and summarized in order to develop a unique strategy for leveraging the utilization of learning style theory for a recommender system to improve learning efficiency. 

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Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review

In this paper we provide an application to index the didactic resources intended to run in an adaptive learning system, which operates using the Learning styles of Felder-Silverman and according to the recommendations of the differentiated pedagogy, by offering multiple versions of the same learning object. The established application relates on the learning objects designed true to the SCORM standard, which are created by exe eLearning software. The main reason behind the implementation of this application, is to offer the possibility to index the didactic resources, available in the adaptive learning system, with so much information about the learning objects, that usually are not available in the common learning objects' softwares, mainly the learning styles and teaching styles, since the adaptive learning system which we take as a basis, relies a lot on this kind of information, to correct the generated learning paths in case it turned out to be not the leading ones.

Nihad Elghouch

Papers

An application to index the didactic resources in an adaptive learning system (ALS)

ALS_CORR[LP]: An adaptive learning system based on the learning styles of Felder-Silverman and a Bayesian network