Towards a new adaptive E-learning framework for adapting content to presentation

Janati, Salma El; Maach, Abdelilah

doi:10.1109/isacv.2017.8054970

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…Adaptive hypermedia systems for education combine a set of technologies to offer the student recommendations appropriate to their needs (El Janati & Maach, 2017). The adaptation model is based on the information contained in the user model and relates it to the domain model, in this way it generates adaptations referring to content suggestions, in different formats, styles or learning contexts (DeCoux, 2016).…”

Section: Related Wordsmentioning

confidence: 99%

Adaptive hypermedia system in times of COVID-19: Application in Management Accounting course 1 at the University of Havana.

López

Vidal

Balmaseda

2021

Preprint

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New trends in higher education, accentuated by the global COVID19 pandemic, visualize the need for more flexible virtual courses. The Faculty of Accounting and Finance of the University of Havana, analyzes new technological configurations that facilitate the personalization of the educational process. In this context, this work aims to design an adaptive hypermedia system prototype applied to the Management Accounting 1 course at the University of Havana to guarantee the delivery, distribution, and variety of learning content to students in a personalized way. An empirical research supported by an experimental method is presented, with a sample of 94 students, a Control Group made up of 41 students and an Experimental Group made up of 53 students; Descriptive statistics and the Pareto principle support the results. It is concluded that, 1. The personalization of the educational process through the application of adaptive techniques leads to academic success at an individual and group level, in this sense, the Experimental group only needed a final exam session compared to the three calls of the group of control; 2. Need to continue investigating new adaptation criteria, in this sense, the mean scores obtained by the Experimental group did not have a significant increase in relation to that of the Control group. This work also contributes to visualizing educational equity referring to the capacity of the educational system to offer special supports that guarantee that educational objectives are achieved in a broader dimension; innovation is related to technologies and new strategies to optimize online educational processes.

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Section: Related Wordsmentioning

confidence: 99%

Adaptive hypermedia system in times of COVID-19: Application in Management Accounting course 1 at the University of Havana.

López

Vidal

Balmaseda

2021

Preprint

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“…Regarding types of AI enabled learning environments, intelligent tutoring systems and adaptive learning systems were the most utilized. Our mapping of the literature revealed that the use of both these types of systems play an important role to improve performance of students through personalization of their learning, and mitigating poor levels of motivation [15], [48]- [50]. A possible reason of adaptive learning systems and intelligent tutoring systems to be mostly used is the recent acknowledgement of AI enabled learning environments in assisting teaching languages, several courses and programming languages.…”

Section: Rq: What Ai Enabled Learning Environments Designed To Domentioning

confidence: 99%

Learning Environments in the 21st Century: A Mapping of the Literature

Kabudi¹,

Pappas²,

Oslen³

2020

Re-Imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation

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Education has been transformed by significant breakthroughs in AI, mobile internet, cloud computing and Big Data technologies. More personalized educational settings are developed by increasingly integrating contemporary learning environments with new technologies. However, few examples of executed AI enabled learning interventions have been identified. Therefore, a mapping of literature on AI enabled learning systems was done. 121 studies published in the last five years were analyzed. This paper presents a discussion regarding on what mainly AI enabled contemporary learning environments are designed to achieve. The major contribution of the study is bringing awareness to researchers and system developers on the purposes of AI enabled contemporary learning environments. This review will act as a guide for future studies on how to better design AI enabled learning environments.

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“…AE-LS is a set of technologies and approaches that combined to give learners an adequate content meeting their needs [3]. In adaptive e-learning approach, each learner has different characteristics, which not suitable for another type of learners [4].…”

Section: A Adaptive E-learning System (Ae-ls)mentioning

confidence: 99%

“…In adaptive e-learning approach, each learner has different characteristics, which not suitable for another type of learners [4]. AE-LS covers a variety of systems: E-learning Platform [3], Learning Management Systems (LMS) [5], Intelligent Tutoring Systems (ITS) [6], Adaptive Hypermedia Systems (AHS) [7], and Dynamic Adaptive Hypermedia Systems (DAHS) [8]. The adaptation in AE-LS is divided into four elements: adaptive content aggregation, adaptive presentation, adaptive navigation, and adaptive collaboration support as is presented in Fig.…”

Section: A Adaptive E-learning System (Ae-ls)mentioning

confidence: 99%

Learning Analytics Framework for Adaptive E-learning System to Monitor the Learner’s Activities

Janati¹,

Maach²,

Ghanami³

2019

IJACSA

Self Cite

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The adaptive e-learning system (AE-LS) research has long focused on the learner model and learning activities to personalize the learner's experience. However, there are many unresolved issues that make it difficult for trainee teachers to obtain appropriate information about the learner's behavior. The evolution of the Learning Analytics (LA) offers new possibilities to solve problems of AE-LS. In this paper, we proposed a Business intelligence framework for AE-LS to monitor and manage the performance of the learner more effectively. The suggested architecture of the ALS proposes a data warehouse model that responds to these problems. It defines specifics measures and dimensions, which helps teachers and educational administrators to evaluate and analyze the learner's activities. By analyzing these interactions, the adaptive e-learning analytic system (AE-LAS) has the potential to provide a predictive view of upcoming challenges. These predictions are used to evaluate the adaptation of the content presentation and improve the performance of the learning process.

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Towards a new adaptive E-learning framework for adapting content to presentation

Cited by 3 publications

References 8 publications

Adaptive hypermedia system in times of COVID-19: Application in Management Accounting course 1 at the University of Havana.

Adaptive hypermedia system in times of COVID-19: Application in Management Accounting course 1 at the University of Havana.

Learning Environments in the 21st Century: A Mapping of the Literature

Learning Analytics Framework for Adaptive E-learning System to Monitor the Learner’s Activities

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