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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
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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
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Engin Demir; Huseyin Cevik – Turkish Online Journal of Distance Education, 2025
Students' attitudes towards distance education can be shaped by the compatibility of their learning styles with this new educational environment. The study aimed to investigate whether various variables and e-learning styles predict student's attitudes towards distance education. The present research was conducted on 387 students enrolled in the…
Descriptors: Student Attitudes, Electronic Learning, Educational Technology, Predictor Variables
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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
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Sönmez, Selami; Korucuk, Murat – Shanlax International Journal of Education, 2023
In this study, students' e-learning styles (ELS) and attitudes towards online learning were examined. Besides, it was also aimed to reveal the relationship between students' ELS and their attitudes towards online learning. Another of the main aims of the study is; the aim of this study is to explain the effect of university students' e-learning…
Descriptors: Educational Technology, Electronic Learning, Student Attitudes, Cognitive Style
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Ashraf, Erum; Manickam, Selvakumar; Karuppayah, Shankar; Malik, Sufiana Khatoon – Journal of Educators Online, 2023
As the drive to move from traditional face-to-face classroom learning to e-learning is ever in demand, the knowledge corpus exposed to students can be overwhelming because there is a need to automate certain functions of the e-learning framework. One of these functions is the course recommendation feature. Course recommendations help students save…
Descriptors: Electronic Learning, Cognitive Style, Student Behavior, Course Selection (Students)
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Yang, Tzu-Chi; Chen, Sherry Y. – Interactive Learning Environments, 2023
Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…
Descriptors: Student Behavior, Educational Technology, Electronic Learning, Cognitive Style
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Muhammad Turmuzi; I Gusti Putu Suharta; I Wayan Puja Astawa; I Nengah Suparta – Journal of Technology and Science Education, 2024
The purpose of this study is to comprehensively describe the results of the analysis of the ability to understand concepts and misconceptions in terms of differences in learning styles, as well as gender differences. The data to be collected in this study is in the form of primary data and secondary data. The primary data is obtained from primary…
Descriptors: Misconceptions, Cognitive Style, Gender Differences, Educational Technology
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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
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Feng Feng; Wenxia Yang – Education and Information Technologies, 2025
The emergence of digital game types has opened up significant opportunities to facilitate language acquisition through feedback provision, attracting diverse research strands to explore their potential as arenas for technology-assisted language learning. This study investigates the effects of learner-, peer-, and collaborative-regulated feedback…
Descriptors: Foreign Countries, Computer Games, Game Based Learning, Feedback (Response)
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Valentina Nachtigall; Selina Yek; Nikol Rummel – Journal of Computer Assisted Learning, 2024
Background: With the increasing availability of immersive technologies such as 360° videos for educational purposes, research needs to shift from media comparison studies to value-added studies in order to identify conditions for effective learning with such technologies. For the educational use of history-related virtual reality media, which are…
Descriptors: Computer Simulation, Video Technology, Technology Uses in Education, Educational Technology
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
Kimble Teresa Parkman-Colbert – ProQuest LLC, 2023
Microlearning is a relatively new educational technology that allows students to learn through short, direct segments using various modalities. The nursing profession has used microlearning to provide continuing medical education (CME). The problem addressed through this study was that instructional designers who create microlearning for medical…
Descriptors: Instructional Design, Nursing Education, Cognitive Style, Professional Continuing Education
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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
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Banagiri, Richa; Kumar, Anuj; Pandey, Anoop – International Journal of Education and Development using Information and Communication Technology, 2021
In today's modern world, globalization has completely changed the way of working. How we live, learn, work, and even define work has changed due to new information and communication technologies. It can be stated that human capital fuels the modern economy, but in reality, the information and communication technology revolution has turned…
Descriptors: Educational Technology, Technology Uses in Education, Vocational Education, Foreign Countries
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