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Mengning Mu; Man Yuan – Interactive Learning Environments, 2024
The necessity for students to clarify their own cognitive structure and the amount of their knowledge mastery for self-reflection is often ignored in building the student model in the adaptive model, which makes the construction of the cognitive structure pointless. Simultaneously, knowledge forgetting causes students' knowledge level to fall…
Descriptors: Individualized Instruction, Cognitive Processes, Graphs, Cognitive Structures
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Peidi Gu; Zui Cheng; Cheng Miaoting; John Poggio; Yan Dong – Journal of Computer Assisted Learning, 2025
Background: Today, the importance of STEM (Science, Technology, Engineering and Mathematics) education and training is widely recognised and accepted. Computer programming courses have become essential in higher education to nurture students' programming, analysis and computational skills, which are vital for success in all STEM fields and areas.…
Descriptors: Active Learning, Student Projects, Individualized Instruction, Student Motivation
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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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Tri Puspa Rinjeni; Nur Aini Rakhmawati; Reny Nadlifatin – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This study identifies gamification element preferences based on Myers-Briggs Type Indicator (MBTI) characteristics. It measures the influence of preferences on learning motivation through a pre-experimental design of one group pre-test post-test. Background: Incorporating information technology in education has led to the introduction…
Descriptors: Foreign Countries, Personality Measures, College Students, Information Systems
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Meina Zhu – Journal of Computer Assisted Learning, 2025
Background: Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning. Objectives: This study aims to examine the sentiments and primary topics discussed in YouTube comments…
Descriptors: Computer Science Education, Programming, Social Media, Video Technology
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Da Teng; Xiangyang Wang; Yanwei Xia; Yue Zhang; Lulu Tang; Qi Chen; Ruobing Zhang; Sujin Xie; Weiyong Yu – Education and Information Technologies, 2025
The swift advancement of artificial intelligence, especially large language models (LLMs), has generated novel prospects for improving educational methodologies. Nonetheless, the successful incorporation of these technologies into pedagogical methods, such as flipped classrooms, continues to pose a challenge. This study investigates the…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Flipped Classroom, Technology Uses in Education
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Rani Van Schoors; Sohum M. Bhatt; Jan Elen; Annelies Raes; Wim Van den Noortgate; Fien Depaepe – International Journal of Designs for Learning, 2024
Due to swift technological changes in society, programming tasks are proliferating in formal and informal education around the globe. However, challenges arise regarding the acquisition of programming skills. Many students are unequipped to develop programming skills due to limited instruction or background and therefore feel insecure when…
Descriptors: Secondary School Students, Grade 1, Individualized Instruction, Electronic Learning
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Hajar Majjate; Youssra Bellarhmouch; Adil Jeghal; Ali Yahyaouy; Hamid Tairi; Khalid Alaoui Zidani – Education and Information Technologies, 2025
In recent times, there has been a growing interest in enhancing recommendation systems for e-learning platforms to deliver a personalised learning experience that meets each learner's distinct requirements and preferences. Nevertheless, it is crucial to recognise the ethical considerations surrounding this technology, as it heavily relies on…
Descriptors: Ethics, Artificial Intelligence, Technology Uses in Education, Student Attitudes
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Sonia Triana-Vera; Omar López-Vargas – Contemporary Educational Technology, 2025
This research aimed to determine the effects of motivational scaffolding and adaptive scaffolding on academic and online self-efficacy in learners interacting with a multimedia learning environment within the field of technology. The study involved 146 students from four tenth-grade classes at a public institution in the municipality of Soacha…
Descriptors: Self Efficacy, Electronic Learning, Scaffolding (Teaching Technique), High School Students
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Mehmet Firat; Saniye Kuleli – Journal of Educational Technology and Online Learning, 2024
This research investigates the comparative effectiveness of the ChatGPT and the Google search engine in facilitating the self-learning of JavaScript functions among undergraduate open and distance learning students. The study employed a quasi-experimental post-test control group design to analyze the variables of disorientation, satisfaction,…
Descriptors: Comparative Analysis, Web Sites, Computer Software, Artificial Intelligence