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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
Yousaf, Yousra; Shoaib, Muhammad; Hassan, Muhammad Awais; Habiba, Ume – Interactive Learning Environments, 2023
Learning trend has been shifted from a conventional way to a digital way in the form of E-learning, but it faces a high dropout ratio. Lack of engagement is one of the primary factors reported for this issue as the same type of course content is presented to learners despite their different background, knowledge and learning styles. Different…
Descriptors: Intelligent Tutoring Systems, Cognitive Style, Learner Engagement, Academic Achievement
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
Ezequiel Scott; Marcelo Campo – Interactive Learning Environments, 2023
Scrum is one of the most used frameworks for agile software development because of its potential improvements in productivity, quality, and client satisfaction. Academia has also focussed on teaching Scrum practices to prepare students to face common software engineering challenges and facilitate their insertion in professional contexts.…
Descriptors: Computer Simulation, Training, Computer Software, Computer Science Education
Miitta Järvinen; Katriina Sipiläinen; Janne Roslöf; Sami Lehesvuori; Lauri Kettunen; Raija Hämäläinen – European Journal of Engineering Education, 2025
This study explored the learning experiences of first-year information technology students at the beginning of their studies. Identifying the early experiences is important, as we know they can predict later challenges and persistence in studies. We focus on a novel understanding of relations between learning approaches, self-efficacy and burnout…
Descriptors: Information Technology, College Freshmen, Computer Science Education, Self Efficacy
Rayed AlGhamdi – Education and Information Technologies, 2024
This research investigates the impact of ChatGPT-generated feedback on the writing skills of first-year computing students at a Saudi University. Employing a qualitative research design, the study involved 111 male students, blinded to the switch from human to ChatGPT-generated feedback, ensuring unbiased reflections on their experiences. Over six…
Descriptors: Artificial Intelligence, Feedback (Response), Technical Writing, Writing Skills
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
Jui-Hung Chang; Chi-Jane Wang; Hua-Xu Zhong; Hsiu-Chen Weng; Yu-Kai Zhou; Hoe-Yuan Ong; Chin-Feng Lai – Educational Technology Research and Development, 2024
Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students' learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study…
Descriptors: Artificial Intelligence, Technological Advancement, Student Evaluation, Models
Lily R. Liang; Rui Kang – International Journal for the Scholarship of Teaching and Learning, 2024
This study examines the impact of a situated learning class framework on student learning and sense of belonging in a first-year introductory computer programming course offered at an urban commuter campus. The framework provided students opportunities to engage in hands-on activities embedded in authentic contexts facilitated or led by students…
Descriptors: Undergraduate Students, Computer Science Education, Commuting Students, Sense of Community
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
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
Sözeri, Mahmut Can; Kert, Serhat Bahadir – International Journal of Computer Science Education in Schools, 2021
In this study, the effects of interactive video usage in programming education on academic achievement and self-efficacy perception of programming were investigated by taking into account learning styles. The research was patterned according to the causal-comparative model, and also, correlation analysis was performed for related research.…
Descriptors: Correlation, Interactive Video, Programming, Academic Achievement
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
Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
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