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Direct linkBo Jiang; Yuang Wei; Meijun Gu; Chengjiu Yin – Interactive Learning Environments, 2024
The purpose of this study is to explore students' backtracking patterns in using a digital textbook, reveal the relationship between backtracking behaviors and academic performance as well as learning styles. This study was carried out for 2 semesters on 102 university students and they are required to use a digital textbook system called DITeL to…
Descriptors: Student Behavior, Electronic Learning, Electronic Publishing, Textbooks
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
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
Li, Huiyong; Majumdar, Rwitajit; Chen, Mei-Rong Alice; Yang, Yuanyuan; Ogata, Hiroaki – Interactive Learning Environments, 2023
Self-directed learning (SDL) ability, its usefulness in higher education and life-long learning have been highlighted in previous literature. However, there has been much less understanding of the effects of SDL ability in the school settings, specifically the effects on learners' SDL behaviors and processes. To address this limitation, this study…
Descriptors: Junior High School Students, Independent Study, Student Behavior, Reading Achievement
Premlatha, K. R.; Dharani, B.; Geetha, T. V. – Interactive Learning Environments, 2016
E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…
Descriptors: Electronic Learning, Profiles, Automation, Classification
Hsiao, Hsien-Sheng; Chang, Cheng-Sian; Lin, Chien-Yu; Hsu, Hsiu-Ling – Interactive Learning Environments, 2015
This study focused on an intelligent robot which was viewed as a language teaching/learning tool to improve children's reading ability, reading interest, and learning behavior. The iRobiQ, with its multimedia contents, was employed to encourage children to read, speak, and answer questions. Fifty-seven pre-kindergarteners participated in this…
Descriptors: Robotics, Artificial Intelligence, Teaching Methods, Reading Ability
