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Xiaorui Wang; Chao Liu; Jing Guo – International Journal of Web-Based Learning and Teaching Technologies, 2025
This research works on creating a hybrid Knowledge Recommendation System (KRS) for an Entrepreneurship Course using the Knowledge Graph (KG) and Clustering Technologies (CTs). The system aims at improving students' learning experience by providing relevant learning materials and even focusing on learner preferences. These results are already part…
Descriptors: Entrepreneurship, Individualized Instruction, Learning Experience, Feedback (Response)
Xueyu Sun; Ting Wang – International Journal of Information and Communication Technology Education, 2024
This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an "interest" parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. Controlled experiments, spanning diverse online platforms, validate the ARM model's…
Descriptors: Models, Design, Algorithms, Individualized Instruction
Jyoti Prakash Meher; Rajib Mall – IEEE Transactions on Education, 2025
Contribution: This article suggests a novel method for diagnosing a learner's cognitive proficiency using deep neural networks (DNNs) based on her answers to a series of questions. The outcome of the forecast can be used for adaptive assistance. Background: Often a learner spends considerable amounts of time in attempting questions on the concepts…
Descriptors: Cognitive Ability, Assistive Technology, Adaptive Testing, Computer Assisted Testing
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
Clarivando Francisco Belizário Júnior; Fabiano Azevedo Dorça; Luciana Pereira de Assis; Alessandro Vivas Andrade – International Journal of Learning Technology, 2024
Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…
Descriptors: Artificial Intelligence, Educational Technology, Individualized Instruction, Cognitive Style
Basil Hanafi; Mohammad Ali; Devyaani Singh – Discover Education, 2025
Quantum computing is the beginning of a new age for diverse industries, and educational technologies will significantly benefit from such quantum developments. This is a novel approach, applying quantum algorithms to enhance educational technologies, with no previous studies addressing the integration of quantum computing for personalized…
Descriptors: Educational Technology, Computer Security, Ethics, Algorithms
Wawan Kurniawan; Khairul Anwar; Jufrida Jufrida; Kamid Kamid; Cicyn Riantoni – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: This study aims to implement and evaluate a personalized digital learning environment (PDLE) that delivers differentiated instruction for enhancing computational thinking competencies through robotics education. Background: The background emphasizes the growing demand for computational thinking skills in the modern workforce and the…
Descriptors: Individualized Instruction, Electronic Learning, Computation, Thinking Skills
MiJeong Kim; JaMee Kim; WonGyu Lee – Education and Information Technologies, 2025
In the digital age, computational thinking (CT)-based problem-solving skills have emerged as essential competencies. Particularly, students with intellectual disabilities need equal educational opportunities and high-quality informatics education to cultivate CT-based problem-solving skills. However, research on the enhancement of CT-based…
Descriptors: Intellectual Disability, Programming, Computation, Thinking Skills
Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
Jian-hui Wu – Journal of Educational Computing Research, 2025
The objective of this research is to investigate how AI-improved dynamic physical education materials impact middle school education in physical settings. Utilizing a randomized controlled crossover approach, a 16-week study involved 120 students aged 12 to 18 to evaluate the impact of AI-enhanced physical education courses against traditional…
Descriptors: Artificial Intelligence, Physical Education, Instructional Materials, Middle School Students
Punya Mishra; Danah Henriksen; Lauren J. Woo; Nicole Oster – TechTrends: Linking Research and Practice to Improve Learning, 2025
The emergence of generative artificial intelligence (GenAI) has reignited long-standing debates about technology's role in education. While GenAI potentially offers personalized learning, adaptive tutoring, and automated support, it also raises concerns about algorithmic bias, de-skilling educators, and diminishing human connection. This…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational History, Influence of Technology
Sy-Miin Chow; Jungmin Lee; Jonathan Park; Prabhani Kuruppumullage Don; Tracey Hammel; Michael N. Hallquist; Eric A. Nord; Zita Oravecz; Heather L. Perry; Lawrence M. Lesser; Dennis K. Pearl – Journal of Statistics and Data Science Education, 2024
Personalized educational interventions have been shown to facilitate successful and inclusive statistics, mathematics, and data science (SMDS) in higher education through timely and targeted reduction of heterogeneous training disparities caused by years of cumulative, structural challenges in contemporary educational systems. However, the burden…
Descriptors: Individualized Instruction, Instructional Design, Science Education, Higher Education
Eun Ok Baek; Romina Villaflor Wilson – International Journal of Adult Education and Technology, 2024
The emergence of generative AI technologies has provoked considerable debate among educators regarding their role in education. This study is an investigation of the benefits, disadvantages, and potential strategies for integrating generative AI in educational settings by analyzing societal impacts based on a literature review. We have surveyed…
Descriptors: Artificial Intelligence, Technology Uses in Education, Information Technology, Educational Strategies
Brendan Bartanen; Andrew Kwok; Andrew Avitabile; Brian Heseung Kim – Educational Researcher, 2025
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…
Descriptors: Career Choice, Teaching (Occupation), Preservice Teachers, Student Attitudes
Jian-Wei Tzeng; Nen-Fu Huang; Yi-Hsien Chen; Ting-Wei Huang; Yu-Sheng Su – Educational Technology & Society, 2024
Massive open online courses (MOOCs; online courses delivered over the Internet) enable distance learning without time and place constraints. MOOCs are popular; however, active participation level among students who take MOOCs is generally lower than that among students who take in-person courses. Students who take MOOCs often lack guidance, and…
Descriptors: MOOCs, Artificial Intelligence, Electronic Learning, Student Participation
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