Smart e-Learning Systems with Big Data

Nowadays, the Internet connects people, multimedia and physical objects leading to a new-wave of services. This includes learning applications, which require to manage huge and mixed volumes of information coming from Web and social media, smart-cities and Internet of Things nodes. Unfortunately, designing smart e-learning systems able to take advantage of such a complex technological space raises different challenges. In this perspective, this paper introduces a reference architecture for the development of future and big-data-capable e-learning platforms. Also, it showcases how data can be used to enrich the learning process

Mathematical Model for Adaptive Technology in E-learning Systems

The emergence of a large number of e-learning platforms and courses does not solve the problem of improving the quality of education. This is primarily due to insufficient implementation or lack of mechanisms for adaptation to the individual parameters of the student. The level of adaptation in modern e-learning systems to the individual characteristics of the student makes the organization of human-computer interaction relevant. As the solution of the problem, a mathematical model of the organization of human-computer interaction was proposed in this work. It is based on the principle of two-level adaptation that determines the choice of the most comfortable module for studying at the first level. The formation of an individual learning path is performed at the second level. The problem of choosing an e-module is solved using a fuzzy logic. The problem of forming a learning path is reduced to the problem of linear programming. The input data are the characteristics of the quality of student activity in the education system. Based on the proposed model the computer technology to support student activities in modular e-learning systems is developed. This technology allows increasing the level of student’s cognitive comfort and optimizing the learning time. The most important benefit of the proposed approach is to increase the average score and increase student satisfaction with learning

E-LEARNING PROGRAM IS IT A NEW HYBRID FROM OF EDUCATION?

Since e-learning was introduced as part of the higher education landscape, many universities have adopted e-learning in their learning designs. However, developing e-learning requires internet technology skills, learning design, and high mastery of substance, so e-learning development becomes complicated and expensive for some universities. Because of this, many universities have started researching and experimenting with hybrid Universitas Terbuka (UT), has been designed to provide distance higher education (PTJJ). UT has organized hybrid education. Hybrid education in this study combines face-to-face education, distance education with media outside the network, and education with online media. So far, most of the hybrid education described in the literature uses the flipped classroom model. Other e-learning models are also often applied in the curriculum. Distance education is in dire need of management support. Several studies report the importance of adequate institutional support in implementing hybrid education policies and their benefits from a curricular perspective. Institutional support and effective employee engagement will improve organizational performance. This study explores the opportunities that arise from the use of e-learning in the learning process. This paper presents the policy implementation of a hybrid education model and a framework that describes the e-learning hybridization initiative with conventional education as a two-factor continuum, namely: (1) institutional support for the use of e-learning and (2) aligning curriculum content between e-learning and hybridization programs. In addition, hybrid education suggests indicators to measure the impact of these initiatives at the education and university level

Towards an Intelligent Hybrid Recommendation System for E-Learning Platforms Using Data Mining

Nowadays, Information and communications technology (ICT) becomes a very important thing in human life in different fields. They are used in many fields as information systems (software, middleware) using various telecommunication media to give users the ability to manipulate digital data. In addition, with new technology development, a new concept appeared in the late 90s and early millennium, which is distance learning through e-Learning platform. Recommendation systems become increasingly used in information systems and especially in e-learning platform. These systems are used to propose and recommend content of these platforms to users according to needs of the latter in order to allow them to have the maximum information for learning. In this paper, we present an intelligent hybrid recommendation system based on data mining. This system has four parts, the first for data collection and for center of interest construction by two modes: explicit data collection, which based on users and what they filled in their profiles, and implicit and automatic data collection by proposing a survey to users in order to gather information about their interest. A second part for processing information already collected in the previous part and for creating the learning model, classifying users who posted the content and classifying content also in order to send the results to the recommendation module. The third part is for making the similarity between learners and content and doing the recommendation for learners and the final part is for creating a log file of recommendation by learner, which will be used in the upcoming recommendation. According to results already done, we noticed that our proposition is satisfactory and the system is well optimized in terms of accuracy, response and processing time compared to the standard recommendation

Les systèmes de recommandations pour soutenir l'agentivité des enseignantes et des enseignants au collégial dans leur développement professionnel

L’objectif général de cette thèse est de contribuer au soutien du développement professionnel des enseignantes et des enseignants au collégial en investiguant leur agentivité avec le numérique. L’agentivité est définie ici comme la capacité à définir et à poursuivre des objectifs de développement professionnel. Cette recherche, qui met en œuvre une méthodologie d’expérimentation de devis, s’est déroulée en trois phases. Dans une première phase, nous avons investigué des besoins d’enseignantes du collégial en nous intéressant aux buts que devait soutenir une plateforme numérique soutenant l’exercice de l’agentivité. Pour y parvenir, trois ateliers de codesign ont été menés et analysés sous l’angle du modèle de l’expérience utilisateur de Hassenzahl (2003). Ces ateliers, inspirés des Future Workshop (Muller et Druin, 2012), ont permis d’identifier des buts motivationnels des participantes, c’est-à-dire ce qu’elles souhaitaient qu’une plateforme misant sur l’exercice d’agentivité puisse combler : faire du développement professionnel une priorité, poser un regard réflexif sur l’innovation, faciliter l’accès aux ressources, et faciliter les échanges et le partage. Les ateliers ont aussi permis d’identifier des buts fonctionnels et opérationnels, c’est-à-dire les fonctionnalités qui permettent de combler les besoins motivationnels. Parmi eux, plusieurs se sont révélés être liés aux systèmes de recommandations, qui sont des outils et techniques qui suggèrent les items les plus susceptibles d’intéresser un utilisateur (Ricci et al., 2015). C’est pourquoi une revue systématique de la littérature a été réalisée afin d’identifier notamment les techniques utilisées et les façons d’évaluer les systèmes de recommandations utilisés dans un contexte d’apprentissage. Dans cette deuxième phase de cette recherche doctorale, ce sont 56 articles scientifiques revus par les pairs, parus entre 2008 et 2018, qui ont été analysés sous trois grandes questions et une cinquantaine d’aspects. Ils ont permis d’orienter le développement de la plateforme, dont l’implantation et les améliorations ont constitué la troisième et dernière phase. Cette phase s’est déroulée en trois itérations de conception, intervention, analyse et amélioration. Durant chacune des itérations, les six participantes ont expérimenté la plateforme, répondu à un questionnaire et reçu une rétroaction personnalisée. Le questionnaire visait à analyser le potentiel de la plateforme pour répondre aux buts motivationnels identifiés à la première phase, à analyser la satisfaction à l’égard des ressources recommandées (Erdt et al., 2015), de même qu’à analyser l’expérience utilisateur (Hassenzahl, 2003). Pour des fins d’analyse, les réponses aux questionnaires ont été croisées avec les données entrées par le personnel enseignant dans la plateforme ainsi que les actions faites dans la plateforme et entrées au journal d’évènements. Cette analyse nous a permis d’observer une augmentation de la perception du soutien à l’agentivité des enseignantes, en particulier la capacité de la plateforme à faciliter l’accès aux ressources pour mieux connaitre les occasions de développement professionnel et pour accéder aux activités de développement professionnel les plus appropriées. Au fil des itérations, nous avons également observé une augmentation de la satisfaction à l’égard des ressources recommandées grâce à une approche basée sur le contenu. La variation de la moyenne globale des aspects hédoniques et pragmatiques est elle aussi positive à chacune des itérations. C’est dire que le codesign d’un environnement numérique dans le cadre d’une recherche avec des enseignantes a été une forme de développement professionnel, et le codesign en contexte de développement professionnel a favorisé l’exercice de l’agentivité des participantes. Le design itératif de cette recherche a contribué à faire du développement professionnel une priorité, un besoin identifié durant la phase de codesign. Cette étude a permis d’identifier et de mettre en œuvre des pistes permettant de faciliter l’exercice de l’agentivité des enseignantes et des enseignants.The general objective of this thesis is to contribute to supporting the professional development of college teachers by investigating their agency with the support of digital technology. Agency is defined here as the ability to define and pursue professional development goals. This research, which implements a design-based research methodology, was carried out in three phases. In the first phase, we investigated the needs of college teachers by looking at the goals that a digital platform supporting the exercise of agency should support. To achieve this, three codesign workshops were conducted and analyzed from the perspective of Hassenzahl's (2003) user experience model. These workshops, inspired by the Future Workshop (Muller & Druin, 2012), made it possible to identify the participants' “be-goals”, i.e., what they wanted a platform based on the exercise of agency to achieve: to make professional development a priority, to take a reflective look at innovation, to facilitate access to resources, and to facilitate exchanges and sharing. The workshops also made it possible to identify “do-goals” and “motor-goals”, i.e., the functionalities that make it possible to meet be-goals. Among them, several were found to be related to recommendation systems, which are tools and techniques that suggest the items most likely to interest a user (Ricci et al., 2015). For this reason, a systematic review of the literature was conducted to identify the techniques used and the ways to evaluate the recommendations systems used in a learning context. In this second phase of this doctoral research, 56 peer-reviewed scientific articles, published between 2008 and 2018, were analyzed under three main questions and about 50 aspects. They were used to help guide the development of the platform, whose implementation and improvements constituted the third and final phase. This phase took place in three iterations of design/implementation, intervention, analysis and improvement. During each iteration, the six participants experimented with the platform, answered a questionnaire and received personalized feedback. The questionnaire aimed to analyze the platform's potential to meet the motivational goals (“be-goals”) identified in the first phase, to analyze satisfaction with the recommended resources (Erdt et al., 2015), and to analyze the user experience (Hassenzahl, 2003). For analysis purposes, the responses to the questionnaires were cross-referenced with the data entered by the teaching staff in the platform as well as the actions taken in the platform and entries in the event log. This analysis allowed us to observe an increase in the perception of support for teachers' agency, in particular the platform's ability to facilitate access to resources to learn more about professional development opportunities and to access the most appropriate professional development activities. Over the iterations we also observed an increase in satisfaction with the recommended resources through a content-based approach. The variation in the overall average of the hedonic and pragmatic aspects is also positive in each iteration. This means that codesigning a digital environment in the context of research with female teachers was a form of professional development, and codesigning in a professional development context promoted the participants' exercise of agency. The iterative design of this research contributed to making professional development a priority, a need identified during the codesign phase. This study made it possible to identify and implement avenues to facilitate teachers' exercise of agency

A multi-agent approach to adaptive learning using a structured ontology classification system

Diagnostic assessment is an important part of human learning. Tutors in face-to-face classroom environment evaluate students’ prior knowledge before the start of a relatively new learning. In that perspective, this thesis investigates the development of an-agent based Pre-assessment System in the identification of knowledge gaps in students’ learning between a student’s desired concept and some prerequisites concepts. The aim is to test a student's prior skill before the start of the student’s higher and desired concept of learning. This thesis thus presents the use of Prometheus agent based software engineering methodology for the Pre-assessment System requirement specification and design. Knowledge representation using a description logic TBox and ABox for defining a domain of learning. As well as the formal modelling of classification rules using rule-based approach as a reasoning process for accurate categorisation of students’ skills and appropriate recommendation of learning materials. On implementation, an agent oriented programming language whose facts and rule structure are prolog-like was employed in the development of agents’ actions and behaviour. Evaluation results showed that students have skill gaps in their learning while they desire to study a higher-level concept at a given time