A Framework for Adaptive E-learning Systems Based on Self-regulated Learning Strategies

Babori, Abdelghani; Falih, Noureddine; Ouchitachen, Hicham

doi:10.1007/978-3-031-01942-5_38

Cited by 1 publication

(2 citation statements)

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“…In expression (11), R represents learning material; DL i represents the level of learning material, and it is under the range of DL i ∈{1, 2, 3, 4}. Under general circumstances, the value of DL i is set up by the course teacher or system manager during the establishment of curriculum resources on the back-stage management web page.…”

Section: User Cognitive Level Modelmentioning

confidence: 99%

“…Specifically speaking, the commonly utilized recommendation technology mainly includes content-based recommendation, collaborative filtering recommendation, association rule recommendation, and integrated recommendation [ 10 ]. In terms of ALS modeling, there are also some typical representative achievements: Babori et al suggested that the frameworks model of ALS should be composed of three components: learner model, domain model, and adaptation model, and then invented a framework based on self-regulated learning (SRL) [ 11 ]. Vesin et al [ 12 ] considered that an intelligent tutoring system should provide smart and interactive content, personalization options, adaptive features, and then they presented the interactive learning analytics component developed in ProTu, so as to deeply discuss the key technologies of ALS recommendation.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Construction of the User Characteristic Model in the Adaptive Learning System for Personalized Learning

Zhao

Long

2022

Computational Intelligence and Neuroscience

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Adaptive Learning System (ALS) is a supportive environment, which dynamically provides learners with services that can satisfy their demand for personalized learning in accordance with the differentiation of their individual traits. At present, study on ALS is still in the exploratory stage, and there are still many fields that deserve to be studied thoroughly. User characteristic model is the foundation and core of ALS and the key to the implementation of intelligent and personalized recommendation service. Based on this, this paper intends to analyze learners’ characteristics in ALS through several dimensions, such as basic information, interest, preference, cognitive level and learning style, through which learners’ user characteristic model is established. In the end, ALS, which supports the function of personalized recommendation, is implemented based on this model. It is suggested by the result of the simulation experiment that ALS, which is developed through this model, demonstrates a satisfying effect in recommendation, and it can dynamically recommend appropriate learning resources in accordance with learners’ personalized demands through which learners’ quality and efficiency of learning can be effectively enhanced to a certain extent.

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Section: User Cognitive Level Modelmentioning

confidence: 99%