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Hani Y. Ayyoub; Omar S. Al-Kadi – IEEE Transactions on Learning Technologies, 2024
Education is a dynamic field that must be adaptable to sudden changes and disruptions caused by events like pandemics, war, and natural disasters related to climate change. When these events occur, traditional classrooms with traditional or blended delivery can shift to fully online learning, which requires an efficient learning environment that…
Descriptors: Cognitive Style, Individualized Instruction, Learning Management Systems, Artificial Intelligence
Seongyune Choi; Hyeoncheol Kim – Education and Information Technologies, 2025
Attention to programming education from K-12 to higher education has been growing with the aim of fostering students' programming ability. This ability involves employing appropriate algorithms and computer codes to solve problems and can be enhanced through practical learning. However, in a formal educational setting, it is challenging to provide…
Descriptors: Foreign Countries, High School Freshmen, Programming, Artificial Intelligence
O. S. Adewale; O. C. Agbonifo; E. O. Ibam; A. I. Makinde; O. K. Boyinbode; B. A. Ojokoh; O. Olabode; M. S. Omirin; S. O. Olatunji – Interactive Learning Environments, 2024
With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…
Descriptors: Cognitive Style, Individualized Instruction, Learning Processes, Preferences
Pedro Luis Saraiva Barbosa; Rafael Augusto Ferreira do Carmo; João P. P. Gomes; Windson Viana – Education and Information Technologies, 2024
Adaptive learning is a teaching approach aiming to personalize the learning experience for each student. In Computer Science Education (CSE), Adaptive Learning Systems (ALS) can provide students with customized lessons, exercises, and assessments based on their previous knowledge, strengths, and weaknesses. Some literature reviews focus on…
Descriptors: Teaching Methods, Individualized Instruction, Educational Technology, Technology Uses in Education
Mustapha Riad; Mohammed Qbadou; Es-Saâdia Aoula; Soukaina Gouraguine – Journal of Education and Learning (EduLearn), 2023
E-learning has increased in popularity, especially during the COVID-19, due to its numerous advantages that allow learners to study anywhere and anytime. Therefore, recommending a list of the most appropriate learning objects for learners according to their specific needs is a great challenge for adaptive e-learning systems. In an e-learning…
Descriptors: Electronic Learning, COVID-19, Pandemics, Cognitive Style
Clarivando Francisco Belizário Júnior; Fabiano Azevedo Dorça; Luciana Pereira de Assis; Alessandro Vivas Andrade – International Journal of Learning Technology, 2024
Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…
Descriptors: Artificial Intelligence, Educational Technology, Individualized Instruction, Cognitive Style
Levey, Sandra – Journal of Education, 2023
This review presents the Universal Design Learning (UDL) approach to education. Classrooms have become increasingly diverse, with second language learners, students with disabilities, and students with differences in their perception and understanding information. Some students learn best through listening, while others learn best when presented…
Descriptors: Access to Education, Teaching Methods, Cognitive Style, Inclusion
Gatewood, Jessica; Tawfik, Andrew; Gish-Lieberman, Jaclyn J. – TechTrends: Linking Research and Practice to Improve Learning, 2022
Differentiated instruction contends that teachers should vary their instructional strategies to match the learners' individual differences. However, this is challenging due to various constraints of classroom and contextual variables. Adaptive systems offer a solution to this challenge, especially as instruction has increasingly moved towards an…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Cognitive Ability, Cognitive Style
Zayet, Tasnim M. A.; Ismail, Maizatul Akmar; Almadi, Sara H. S.; Zawia, Jamallah Mohammed Hussein; Mohamad Nor, Azmawaty – Education and Information Technologies, 2023
Online learning has significantly expanded along with the spread of the coronavirus disease (COVID-19). Personalization becomes an essential component of learning systems due to students' different learning styles and abilities. Recommending materials that meet the needs and are tailored to learners' styles and abilities is necessary to ensure a…
Descriptors: Electronic Learning, Individualized Instruction, Artificial Intelligence, Cognitive Style
El-Sabagh, Hassan A. – International Journal of Educational Technology in Higher Education, 2021
Adaptive e-learning is viewed as stimulation to support learning and improve student engagement, so designing appropriate adaptive e-learning environments contributes to personalizing instruction to reinforce learning outcomes. The purpose of this paper is to design an adaptive e-learning environment based on students' learning styles and study…
Descriptors: Electronic Learning, Educational Environment, Cognitive Style, Correlation
Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
Li, Kam Cheong; Wong, Billy Tak-ming – Journal of Computing in Higher Education, 2023
This paper reports a comprehensive review of literature on personalised learning in STEM and STEAM (or STE(A)M) education, which involves the disciplinary integration of Science, Technology, Engineering, and Mathematics, as well as Arts. The review covered the contexts of STE(A)M education where personalised learning was adopted, the objectives of…
Descriptors: Individualized Instruction, STEM Education, Art Education, Educational Objectives
Joseph W. Rotondo – ProQuest LLC, 2021
In the education system, many educators find it difficult to differentiate the lessons for their students as they lack the strategies to do so. The purpose of this study is to determine if a correlation exists between video game genres and learning style preferences. The framework that this study uses is the cognitive behavioral theoretical…
Descriptors: Educational Technology, Video Games, Cognitive Style, Preferences
Wu, Sirui – International Association for Development of the Information Society, 2020
The usefulness and limitation of Adaptive Hypermedia Learning System (AHLS) using Learning Style as an adaptor has been long discussed, and many empirical studies show the system can help students increase their academic performance comparing with the traditional classroom learning, but these studies were based on different subjects and…
Descriptors: Meta Analysis, Hypermedia, Cognitive Style, Academic Achievement
Mingmei Qu – European Journal of Education, 2025
This study investigates the interplay between EFL students' needs, proficiency levels, learning styles and AI-powered adaptive learning platforms in fostering academic engagement. A positive and significant relationship was observed, demonstrating that AI-powered platforms effectively cater to EFL students' individual needs, proficiency levels and…
Descriptors: Second Language Learning, English (Second Language), Technology Uses in Education, Artificial Intelligence