A novel adaptive e-learning model based on Big Data by using competence-based knowledge and social learner activities

Birjali, Marouane; Beni‐Hssane, Abderrahim; Erritali, Mohammed

doi:10.1016/j.asoc.2018.04.030

Cited by 59 publications

(19 citation statements)

References 50 publications

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“…During the last decade, the ideas of student-oriented learning, student competency level estimation, and personalized e-learning gaining speed in Lithuania [1][2][3], as well as worldwide [4][5][6][7], have been proposed. However, the practical application of these ideas is not as smooth.…”

Section: Introductionmentioning

confidence: 99%

Hierarchy-Based Competency Structure and Its Application in E-Evaluation

Ramanauskaitė

Slotkienė

2019

Applied Sciences

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The development of information technologies changes the learning process. The amount of publicly available data of e-learning systems allows personalized studies. Therefore, the tutor sometimes is needed for the student’s evaluation and consultation only. To ensure clear evaluation requirements and objective evaluation process, the learning material, as well as the evaluation system, must be discrete and semantically expressed. The list of mastered competencies and skills is more important to the enterprise; therefore, during the last years, the study process has concentrated on competency evaluation too. However, the current practice, when students’ competencies are summarized and expressed as one quantitative metric (score), do not express the list of students’ competencies and their level. To solve the problem, in this paper, we proposed a method for the design of competencies’ tree. The competency tree has to be formatted based on context modeling principles and analysis of Scope-Commonality-Variability. The usage of competency tree for students’ competencies’ evaluation proposes clearly defined and semantically expressed evaluation method for both human and e-learning evaluation process. This paper presents the results of the empirical experiment to adapt the proposed competency tree design and application for competencies’ e-evaluation method, based on flexibility, adaptability, and granularity of learning material.

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Section: Introductionmentioning

confidence: 99%

Hierarchy-Based Competency Structure and Its Application in E-Evaluation

Ramanauskaitė

Slotkienė

2019

Applied Sciences

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“…Therefore, many adaptive techniques have been employed in the last decade, such as concept maps, fuzzy logic, expert system, Bayesian network, overlay model, stereotypes, big data techniques etc. to provide an effective adaptation system in the learning process [8], [9], [10], [11], [12], [13], [14].…”

Section: Introductionmentioning

confidence: 99%

Concept-based and Fuzzy Adaptive E-learning

Duhayyim

Newbury

2018

Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations - ICIEI 2018

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This study aims to test an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the topic. A fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain and produce a ranked concept list of learning materials to address weaknesses in the learner's understanding. This system will obtain information on a learner's understanding of concepts by an initial pre-test before the system is used for learning and a posttest after using the learning system. A fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance a learner's performance and understanding. In addition, this research aims to increase participants' overall learning level and effectiveness by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.

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“…The peculiarity of adaptive EOK is that the regulation of the rate of mastering the material, as well as the initial choice of the trajectory, takes place without the participation of the instructor in the automatic mode [4,5,[12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Development of Adaptive E-Learning Course in Moodle System

et al. 2018

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E-learning has been actively developing recently. To date, there are a large number of platforms and developed courses. The main drawback is the lack of adaptability. This paper presents the results of developing an adaptive e-learning course on the Moodle platform. The course is based on a tree of concepts and discipline operations; the course content is based on different standards. Training takes place along various trajectories depending on the characteristics and level of the student’s preparation, which will improve the learning achievement of students. The results of the development and implementation of an adaptive electronic course designed for students of the second year of full-time education are presented. In the process of learning, students follow a certain trajectory; on each trajectory, different material is represented.

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A novel adaptive e-learning model based on Big Data by using competence-based knowledge and social learner activities

Cited by 59 publications

References 50 publications

Hierarchy-Based Competency Structure and Its Application in E-Evaluation

Hierarchy-Based Competency Structure and Its Application in E-Evaluation

Concept-based and Fuzzy Adaptive E-learning

Development of Adaptive E-Learning Course in Moodle System

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