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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
Vui-Yee Koon – Interactive Learning Environments, 2023
Scientific research on mobile learning and its implications on humanistic education has grown tremendously. Within the context of an overview of its forerunners (i.e. educational technology) and critical characteristics concerning the humanistic perspective in education, bibliometric findings on mobile learning publications in humanistic education…
Descriptors: Journal Articles, Electronic Learning, Humanistic Education, Bibliometrics
He, Xiuling; Fang, Jing; Cheng, Hercy N. H.; Men, Qibin; Li, Yangyang – Education and Information Technologies, 2023
A deep understanding of the learning level of online learners is a critical factor in promoting the success of online learning. Using knowledge structures as a way to understand learning can help analyze online students' learning levels. The study used concept maps and clustering analysis to investigate online learners' knowledge structures in a…
Descriptors: Electronic Learning, Cognitive Structures, Concept Mapping, Learning Processes
Sarika Sharma; Jatinderkumar R. Saini – Interactive Learning Environments, 2024
During the COVID-19 pandemic period of almost two years, online teaching was adopted by Higher Educational Institutes (HEIs) mostly as an emergency measure to maintain endurance in teaching-learning activities in academics. Although a lot of research works have focussed on the teaching-learning strategies deployed during the pandemic period, the…
Descriptors: Online Courses, Electronic Learning, Cognitive Ability, Cognitive Style
Wijaya, Adi; Setiawan, Noor Akhmad; Shapiai, Mohd Ibrahim – Electronic Journal of e-Learning, 2023
This study aims to provide a comprehensive overview of the current state and potential future research in learning style detection. With the increasing number and diversity of research in this area, a quantitative approach is necessary to map out current themes and identify potential areas for future research. To achieve this goal, a bibliometric…
Descriptors: Bibliometrics, Cognitive Style, Diagnostic Tests, Content Analysis
Mu, Su; Cui, Meng; Wang, Xiao Jin; Qiao, Jin Xiu; Tang, Dong Mei – Interactive Technology and Smart Education, 2019
Purpose: This study aims to use eye-tracking technology to conduct an empirical study about online learning process analysis, thus aiming to understand the attentional preferences and learning paths in online learners. Design/methodology/approach: With eye movement tracking and data analysing technology, the Tobii X120 eye-tracking instrument,…
Descriptors: Attention, Preferences, Electronic Learning, Eye Movements
Ge, Zi-Gang – Interactive Learning Environments, 2021
The present study aims to explore the impact of mismatch between learners' media preference and media assigned to them on their learning performance. The participants were 214 adult Chinese e-learners enrolled for an English course, and were assigned to 6 groups based on their media preferences and the media assigned to them. A 2 × 3…
Descriptors: Educational Media, Multimedia Materials, Learning Modalities, Cognitive Style
El Aissaoui, Ouafae; El Alami El Madani, Yasser; Oughdir, Lahcen; El Allioui, Youssouf – Education and Information Technologies, 2019
Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of…
Descriptors: Classification, Cognitive Style, Models, Electronic Learning
Li, Wei; Chiu, Chuang-Kai; Tseng, Judy C. R. – Educational Technology & Society, 2019
In context-aware ubiquitous learning, the learning resources of the learning environment are limited, and the learners need to frequently move between learning targets. Therefore, how to provide appropriate learning paths for students in the real world is essential in context-aware ubiquitous learning. In this study, a personalized navigation…
Descriptors: Cognitive Style, Navigation, Electronic Learning, Educational Technology
Tacgin, Zeynep – Educational Media International, 2020
This research investigates the learning progress and bottlenecks of students during learning via an immersive virtual reality environment. At the planning stage of this action research, an immersive virtual reality learning environment -- myVOR- was designed and developed to teach concepts and procedures. myVOR was developed using the Unity game…
Descriptors: Computer Simulation, Simulated Environment, Electronic Learning, Learning Processes
Kolekar, Sucheta V.; Pai, Radhika M.; M. M., Manohara Pai – Education and Information Technologies, 2019
The term Adaptive E-learning System (AES) refers to the set of techniques and approaches that are combined together to offer online courses to the learners with the aim of providing customized resources and interfaces. Most of these systems focus on adaptive contents which are generated to the learners without considering the learning styles of…
Descriptors: Computer Interfaces, Computer Assisted Instruction, Electronic Learning, Online Courses
Alhasan, Khawla; Chen, Liming; Chen, Feng – International Association for Development of the Information Society, 2017
Various learners with various requirements have led to the raise of a crucial concern in the area of e-learning. A new technology for propagating learning to learners worldwide, has led to an evolution in the e-learning industry that takes into account all the requirements of the learning process. In spite of the wide growing, the e-learning…
Descriptors: Semantics, Models, Cognitive Style, Electronic Learning
Wanapu, Supachanun; Fung, Chun Che; Kerdprasop, Nittaya; Chamnongsri, Nisachol; Niwattanakul, Suphakit – Education and Information Technologies, 2016
The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system.…
Descriptors: Correlation, Cognitive Style, Resource Units, Foreign Countries
Czerkawski, Betul C. – Online Journal of Distance Learning Administration, 2015
While student data systems are nothing new and most educators have been dealing with student data for many years, learning analytics has emerged as a new concept to capture educational big data. Learning analytics is about better understanding of the learning and teaching process and interpreting student data to improve their success and learning…
Descriptors: Electronic Learning, Data, Data Analysis, Learning Processes
Liu, Sanya; Hu, Zhenfan; Peng, Xian; Liu, Zhi; Cheng, H. N. H.; Sun, Jianwen – International Journal of Distance Education Technologies, 2017
In a MOOC environment, each student's interaction with the course content is a crucial clue for learning analytics, which offers an opportunity to record learner activity of unprecedented scale. In online learning, the educators and the administrators need to get informed with students' learning states since the performance of unsupervised…
Descriptors: Online Courses, Electronic Learning, Cognitive Style, Educational Research

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