Please provide a short abstract of 100 to 250 words. The abstract should not contain any undefined abbreviations or unspecified references. Work planned but not completed should not appear in the abstract.

User Modeling and User-Adapted Interaction

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

With the rapid growth of technology, computer learning has become increasingly integrated with artificial intelligence techniques in order to develop more personalized educational systems. ...

Intelligent tutoring systems: a systematic review of characteristics, applications, and evaluation methods

An adaptive learning environment provides personalised information to the learner through self-directed study. An adaptive learning environment model can be subdivided into a learner model, domain model, instructional model and adaptive engine. Personal traits comprise part of the components in a learner model and can be identified either explicitly or implicitly in an adaptive learning environment. In such an environment, the e-learning system should adapt to a learner's needs. However, even though academic research on adaptive learning environments has increased, the field lacks a comprehensive literature analysis of learners' personal traits in these environments. This study conducts a systematic literature review to identify the most commonly used personal traits in modelling the learner and the existing techniques suitable for identifying personal traits in an adaptive learning environment. A total of 140 articles spanning the years 2010–2017 are initially reviewed, from which 78 are selected based on the inclusion and exclusion criteria relevant to this study. This study provides an overview of learners' personal traits and the techniques used to identify them to provide a basis for improving adaptive learning environments. The findings indicate that most of the previous works used a learning style from the cognition learning domain category to model individual personal traits, while the computer-based detection technique was commonly applied to identify a learner's personal traits in adaptive learning environments. This study reveals the common learner characteristics used to develop learner models and the techniques for implementing such models. The findings of this paper can guide other researchers to recognise various personal traits and the identification technique for further studies, as well as assist developers in the development of the adaptive learning system.

Identification of personal traits in adaptive learning environment: Systematic literature review

In this paper, we use Kansanen's didactic triangle to structure and analyse research on the teaching and learning of programming. Students, teachers and course content are the three entities that form the corners of the didactic triangle. The edges of the triangle represent the relationships between these three entities. We argue that many computing educators and computing education researchers operate from within narrow views of the didactic triangle. For example, computing educators often teach programming based on how they relate to the computer, and not how the students relate to the computer. We conclude that, while research that focuses on the corners of the didactic triangle is sometimes appropriate, there needs to be more research that focuses on the edges of the triangle, and more research that studies the entire didactic triangle.

Introductory programming and the didactic triangle

In this paper we present a model of an adapting learning system based on a recommendation system, operating after assessment to correct learning path of the learners who have experienced difficulties in the assessment. Our approach aims to correct the learning path of learners who have not passed the assessment successfully, by calculating the similarities in behaviors between them and those who did.

http://ieeexplore.ieee.org/iel7/6830040/6841931/06841985.pdf

Exploitation of the recommendation systems in the calculation of the learning path

In this paper we propose a model that uses Job needs and organizations requirement to define an e-learning path that help the learner to be able to satisfy the job targeted. We review existing literature on adaptive learning systems, thereby; we propose a model using the recommendation of differentiated pedagogy, also the learner's profile and the Job characteristics. In this model, the system can offer the user a suggested learning path to meet appropriate learning of a job objective.

An adaptive learning system based on a Job model, the differentiated instruction and Felder and Silverman's learning styles model

In this paper we revisit the classical approach of the didactic triangle designed for the classical learning situation (face to face) and adapt it to the situation of an adaptive learning system, we discuss also the different components involved in this didactic triangle and how they interact and influence the learning process in an adaptive learning system.

/pdf/revisiting-the-didactic-triangle-in-the-case-of-an-adaptive-2kssgb3gmk.pdf

Revisiting the Didactic Triangle in the Case of an Adaptive Learning System

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.

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

The aim of this paper is to use the Unified Modeling Language in order to design and implement an adaptive learning system that assigns learning objects according to the Fielder and Silverman learning styles (FSLSM), using the Bayesian networks. This system include also correcting the resultant learning path in the case of a failure in an evaluation, by calculating the similarities in behaviors between the struggling learner and the other succeeding learners, and then correct the corresponding learning path, either by recommending other versions of the same Learning object, which are designed previously according to the recommendations of the differentiated pedagogy, or by going back to his initial profile and correct the outcome of FSLSM according to what is observed as an adopted behavior within the system.

/pdf/implementation-of-an-adaptive-learning-system-that-include-4ws13chsei.pdf

Yassine Zaoui Seghroucheni

Papers

Exploitation of the recommendation systems in the calculation of the learning path

An adaptive learning system based on a Job model, the differentiated instruction and Felder and Silverman's learning styles model

Revisiting the Didactic Triangle in the Case of an Adaptive Learning System

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

Implementation of an Adaptive Learning System that Include Correction of Learning Path Based on the Differentiated Pedagogy and the Bayesian Network