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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
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Obeng, Asare Yaw – Cogent Education, 2023
The learning processes have been significantly impacted by technology. Numerous learners have adopted technology-based learning systems as the preferred form of learning. It is then necessary to identify the learning styles of learners to deliver appropriate resources, engage them, increase their motivation, and enhance their satisfaction and…
Descriptors: Predictor Variables, Cognitive Style, Electronic Learning, College Freshmen
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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
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Aeiad, Eiman; Meziane, Farid – Education and Information Technologies, 2019
With the rapid advances in E-learning systems, personalisation and adaptability have now become important features in the education technology. In this paper, we describe the development of an architecture for A Personalised and Adaptable E-Learning System (APELS) that attempts to contribute to advancements in this field. APELS aims to provide a…
Descriptors: Electronic Learning, Individualized Instruction, Computer Science Education, Computer System Design
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Hassan, Muhammad Awais; Habiba, Ume; Majeed, Fiaz; Shoaib, Muhammad – Interactive Learning Environments, 2021
With the removal of the barriers of time and distance, E-learning platforms have attracted millions of learners, but these platforms are experiencing a significant drop-out ratio. One of the primary reasons for this problem is the lack of motivation among the learners because of the similar learning experience provided to them despite their…
Descriptors: Game Based Learning, Electronic Learning, Cooperative Learning, Integrated Learning Systems
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Huang, Sheng-Bo; Jeng, Yu-Lin; Lai, Chin-Feng – Journal of Educational Computing Research, 2021
In recent years, the government has actively set up computer programming courses to train those with the relevant talent; however, the learning performance of the students is not ideal. Therefore, in order to learn programming skills, students usually adopt note-taking strategies because, due to the pressure of the course, the teachers do not have…
Descriptors: Notetaking, Learning Strategies, Cognitive Style, Peer Teaching
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Alshammari, Mohammad T.; Qtaish, Amjad – Journal of Information Technology Education: Research, 2019
Aim/Purpose: Effective e-learning systems need to incorporate student characteristics such as learning style and knowledge level in order to provide a more personalized and adaptive learning experience. However, there is a need to investigate how and when to provide adaptivity based on student characteristics, and more importantly, to evaluate its…
Descriptors: Electronic Learning, Cognitive Style, Knowledge Level, Individualized Instruction
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Hariyanto, Didik; Triyono, Moch. Bruri; Köhler, Thomas – Knowledge Management & E-Learning, 2020
One of the advanced technologies in e-learning deals with the systems' ability to fit the students' preferences. It emerged based upon the common conception that every person has different learning style. However, despite the many options of learning style models toward using personalized elearning, there are considerable challenges to assess the…
Descriptors: Usability, Electronic Learning, Individualized Instruction, Computer Assisted Instruction
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Mudrák, Marián; Turcáni, Milan; Reichel, Jaroslav – Journal on Efficiency and Responsibility in Education and Science, 2020
At current e-learning platforms, is often seen non-efficient usage of their possibilities when creating educational content. This article deals with the possibilities of using adaptive tools that are offered by learning management system (LMS) Moodle when creating a personalised e-course. The methodology created by the authors of the article for…
Descriptors: Individualized Instruction, Computer Science Education, Electronic Learning, Online Courses
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Pürbudak, Aysegül; Usta, Ertugrul – Participatory Educational Research, 2021
The aim of this research is to determine the learning styles of Web 2.0 based collaborative group activities; to examine the effects on academic achievement, online cooperative learning attitude level, computer thinking skill level. The research was carried out with a quantitative method and a pretest-posttest control group quasi-experimental…
Descriptors: Group Activities, Cooperative Learning, Electronic Learning, Cognitive Style
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Lin, Che-Chern; Liu, Zi-Cheng; Chang, Chih-Lin; Lin, Yu-Wen – IEEE Transactions on Education, 2019
Contribution: An online genetic algorithm-based remedial learning system is presented in order to strengthen students' understanding of object-oriented programming (OOP) concepts by tailoring personalized learning materials according to each student's strengths and weaknesses. Background: Prior studies on computer programming education have…
Descriptors: Individualized Instruction, Remedial Instruction, Computer Science Education, Programming Languages
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de Oliveira Costa Machado, Marcelo; Barrére, Eduardo; Souza, Jairo – International Journal of Distance Education Technologies, 2019
Adaptive curriculum sequencing (ACS) is still a challenge in the adaptive learning field. ACS is a NP-hard problem especially considering the several constraints of the student and the learning material when selecting a sequence from repositories where several sequences could be chosen. Therefore, this has stimulated several researchers to use…
Descriptors: Sequential Approach, Intelligent Tutoring Systems, Mathematics, Problem Solving
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de Villiers, M. R.; Becker, Daphne – Innovations in Education and Teaching International, 2017
From the perspective of parallel mixed-methods research, this paper describes interactivity research that employed usability-testing technology to analyse cognitive learning processes; personal learning styles and times; and errors-and-recovery of learners using an interactive e-learning tutorial called "Relations." "Relations"…
Descriptors: Mixed Methods Research, Tutorial Programs, Usability, Cognitive Processes
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Maaliw, Renato R. III; Ballera, Melvin A. – International Association for Development of the Information Society, 2017
The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…
Descriptors: Classification, Cognitive Style, Electronic Learning, Decision Making
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Mironova, Olga; Amitan, Irina; Vendelin, Jelena; Vilipõld, Jüri; Saar, Merike – Interactive Technology and Smart Education, 2016
Purpose: This paper aims to present a teaching approach to achieve the most personal support for students with different backgrounds and preferences in studying an Informatics course. Design/Methodology/Approach: The presented methodology is based on the main principles of flexible and blended learning. The authors considered three main aspects:…
Descriptors: Electronic Learning, College Freshmen, Information Science Education, College Instruction
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