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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
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
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)
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
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
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
Sanal Kumar T. S.; R. Thandeeswaran – Education and Information Technologies, 2024
The COVID-19 pandemic has forced a significant increase in the utilization of video-based e-learning platforms for programming education. These platforms never considered the essential attributes of student characteristics and learning preferences while designing such a problematic subject having high dropout and failure rates. The traditional…
Descriptors: Blended Learning, Electronic Learning, Higher Education, Programming
Müslüm Atas; Helmut Lindner; Thomas Strametz; Fatima Jammoul; Johannes Feiner; Antonius Metry Saad – International Association for Development of the Information Society, 2024
With the rapid growth of digital education, e-learning has become essential for offering accessible and flexible learning opportunities. This paper investigates strategies to achieve long-term learning outcomes and reduce study time in e-learning. It explores various techniques, including self-testing, spaced repetition, and the serial position…
Descriptors: Electronic Learning, Time on Task, Memory, Learning Strategies
Razali, Fazilah; Sulaiman, Tajularipin; Ayub, Ahmad Fauzi Mohd; Majid, Noraziela Abdul – Asian Journal of University Education, 2022
Technology has been rapidly implemented in the learning process during the COVID-19 pandemic. It gives rise to new challenges, especially in higher learning institutions, in planning and mobilizing a sustainable learning environment. Initiatives have been taken to introduce different learning methods using the Learning Management System (LMS),…
Descriptors: Educational Technology, Electronic Learning, Blended Learning, Higher Education
Niu, Liwei; Wang, Xinghua; Wallace, Matthew P.; Pang, Hui; Xu, Yanping – Journal of Computer Assisted Learning, 2022
Background: In view of the widespread use of digital technologies in English as a foreign language (EFL) learning and the importance of students' approaches to learning (SAL) and digital competence, as well as the threats of technostress in digital settings, digital EFL learning requires a critical examination. Objectives: This study sought to…
Descriptors: English (Second Language), Educational Technology, Electronic Learning, Second Language Learning
Özüdogru, Gül – i.e.: inquiry in education, 2022
This study aimed to investigate preservice teachers' e-learning styles and their attitudes toward e-learning and present the relationship between them via a correlational survey model, a quantitative method. The study group was composed of 322 preservice teachers. The Demographic Information Form, the E-learning Styles Scale, and the Attitude…
Descriptors: Preservice Teachers, Student Attitudes, Electronic Learning, Educational Technology
Lin, Lin; Barber, Krystal A. – Excelsior: Leadership in Teaching and Learning, 2022
This paper outlines instructional strategies and course projects that demonstrate multiple means of engagement, representation, action, and expression, the essential principles of the Universal Design for Learning (UDL). The authors first share specific practices and examples related to each of the essential principles of UDL. Next, three projects…
Descriptors: Learner Engagement, Access to Education, Teaching Methods, Preservice Teacher Education
Ucar, Dilara; Yilmaz, Serkan – Journal of Baltic Science Education, 2023
E-learning is becoming more popular than conventional teaching methods, particularly in science education. The use of e-learning has increased worldwide, especially after the COVID-19 pandemic. Today, students' e-learning styles have gained even more importance. The participants of this survey, which aimed to examine e-learning styles for selected…
Descriptors: Preservice Teachers, Electronic Learning, Student Characteristics, Foreign Countries
Yang An; Yushi Duan; Yuchen Zhang – International Journal of Information and Communication Technology Education, 2024
Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper provides a bibliometric and visual analysis of the research trends, patterns, and topics in this field. Using the Web of Science database, the authors…
Descriptors: Bibliometrics, Educational Research, Higher Education, Information Technology
Khan, Nasreen; Sarwar, Abdullah; Chen, Tan Booi; Khan, Shereen – Knowledge Management & E-Learning, 2022
The remarkable advancements in technology have affected the way people engage, work, and learn. Digital literacy, also known as virtual learning, has the potential to improve lifelong learning. Workplace skills evolve at such a rapid pace that no school system can keep up with the continual need to alter how we work and live. Most crucially, our…
Descriptors: Technological Literacy, Higher Education, Labor Force, Electronic Learning