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Feng Hsu Wang – IEEE Transactions on Learning Technologies, 2024
Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…
Descriptors: Learning Processes, Models, Man Machine Systems, Cooperative Learning
Daryn A. Dever; Megan D. Wiedbusch; Sarah M. Romero; Roger Azevedo – British Journal of Educational Technology, 2024
Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self-regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in…
Descriptors: Intelligent Tutoring Systems, Scaffolding (Teaching Technique), Independent Study, Prompting
Carvalho, Floran; Henriet, Julien; Greffier, Francoise; Betbeder, Marie-Laure; Leon-Henri, Dana – Journal of Education and e-Learning Research, 2023
This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…
Descriptors: Learning Processes, Algorithms, Artificial Intelligence, Programming Languages
Yuhui Yang; Hao Zhang; Huifang Chai; Wei Xu – Interactive Learning Environments, 2023
The COVID-19 pandemic has accelerated the transformation of education forms, and the combination of online and offline teaching has become the core development direction of university teaching at present and in the future. Therefore, appropriate teaching space is urgently needed to support the practice of blended teaching. Firstly, this paper…
Descriptors: Intelligent Tutoring Systems, Instructional Design, Universities, Blended Learning
Hyeon-Ah Kang; Adam Sales; Tiffany A. Whittaker – Grantee Submission, 2023
Increasing use of intelligent tutoring systems in education calls for analytic methods that can unravel students' learning behaviors. In this study, we explore a latent variable modeling approach for tracking learning flow during computer-interactive artificial tutoring. The study considers three models that give discrete profiles of a latent…
Descriptors: Intelligent Tutoring Systems, Algebra, Educational Technology, Learning Processes
Anirudhan Badrinath; Zachary Pardos – Journal of Educational Data Mining, 2025
Bayesian Knowledge Tracing (BKT) is a well-established model for formative assessment, with optimization typically using expectation maximization, conjugate gradient descent, or brute force search. However, one of the flaws of existing optimization techniques for BKT models is convergence to undesirable local minima that negatively impact…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Problem Solving, Audience Response Systems
Juan Zheng; Shan Li; Tingting Wang; Susanne P. Lajoie – International Journal of Educational Technology in Higher Education, 2024
Emotions play a crucial role in the learning process, yet there is a scarcity of studies examining emotion dynamics in problem-solving with fine-grained data and advanced tools. This study addresses this gap by investigating the emotional trajectories during self-regulated learning (SRL) phases (i.e., forethought, performance, and self-reflection)…
Descriptors: Medical Students, Problem Solving, Intelligent Tutoring Systems, Nonverbal Communication
Wu, Ting-Ting; Lee, Hsin-Yu; Li, Pin-Hui; Huang, Chia-Nan; Huang, Yueh-Min – Journal of Educational Computing Research, 2024
This study combines ChatGPT, Apple's Shortcuts, and LINE to create the ChatGPT-based Intelligent Learning Aid (CILA), aiming to enhance self-regulation progress and knowledge construction in blended learning. CILA offers real-time, convergent information to learners' inquiries, as opposed to traditional Google search engine that provide divergent…
Descriptors: Independent Study, Learning Processes, Blended Learning, Artificial Intelligence
Yizhou Fan; Luzhen Tang; Huixiao Le; Kejie Shen; Shufang Tan; Yueying Zhao; Yuan Shen; Xinyu Li; Dragan Gaševic – British Journal of Educational Technology, 2025
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of supports from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. In particular, there has been a surge of academic interest in human-AI collaboration and…
Descriptors: College Students, Writing Achievement, Writing Exercises, Artificial Intelligence
Francisco Niño-Rojas; Diana Lancheros-Cuesta; Martha Tatiana Pamela Jiménez-Valderrama; Gelys Mestre; Sergio Gómez – International Journal of Education in Mathematics, Science and Technology, 2024
The use of intelligent tutoring systems (ITSs) is growing rapidly in the field of education. In mathematics, adaptive and personalized scenarios mediated by these systems have been implemented to aid concept comprehension and skill development. This study presents a systematic review on the current status of the use of ITSs in mathematics…
Descriptors: Intelligent Tutoring Systems, Higher Education, Mathematics Instruction, Teaching Methods
Jobin Jose; Alice Joselph; Pratheesh Abraham; Roshna Varghese; Beenamole T.; Sony Mary Varghese; Suby Elizabeth Oommen – Online Submission, 2024
As a major shift in education technologies, Adaptive Learning Systems (ALS) use artificial intelligence and similar technologies, adapting the lessons to the needs of individual students. Emphasizing transformative pedagogy and teaching strategies that transform the learners' cognitive and interactive patterns, this study presents a comprehensive…
Descriptors: Transformative Learning, Bibliometrics, Trend Analysis, Artificial Intelligence
Guido Makransky; Ban M. Shiwalia; Tue Herlau; Steven Blurton – Educational Psychology Review, 2025
Generative artificial intelligence (GenAI) has emerged as a transformative tool in education, offering scalable individualized learning. However, there is a lack of theoretically informed and methodologically rigorous research on how GenAI can effectively augment learning. This manuscript addresses this gap by investigating the potential of a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Learning Processes, College Students
Mao, Shun; Zhan, Jieyu; Wang, Yizhao; Jiang, Yuncheng – IEEE Transactions on Learning Technologies, 2023
For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Prediction, Prior Learning
Liping Sun; Marjaana Kangas; Heli Ruokamo – Interactive Learning Environments, 2024
Intelligent game-based learning environments have developed and created dynamic, effective, and engaging learning experiences, serving as a tutoring framework for students of different educational levels. Although game-based features have recently been shown to have the potential to improve intelligent tutoring systems in these learning…
Descriptors: Game Based Learning, Literature Reviews, Intelligent Tutoring Systems, Influence of Technology
Sebastian Hobert; Florian Berens – Educational Technology Research and Development, 2024
Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Learning Processes, Teaching Methods

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