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Showing 1 to 15 of 24 results Save | Export
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Nurassyl Kerimbayev; Karlygash Adamova; Rustam Shadiev; Zehra Altinay – Smart Learning Environments, 2025
This review was conducted in order to determine the specific role of intelligent technologies in the individual learning experience. The research work included consider articles published between 2014 and 2024, found in Web of Science, Scopus, and ERIC databases, and selected among 933 ?articles on the topic. Materials were checked for compliance…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Computer Software, Databases
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Punya Mishra; Danielle S. McNamara; Gregory Goodwin; Diego Zapata-Rivera – Grantee Submission, 2025
The advent of Large Language Models (LLMs) has fundamentally disrupted our thinking about educational technology. Their ability to engage in natural dialogue, provide contextually relevant responses, and adapt to learner needs has led many to envision them as powerful tools for personalized learning. This emergence raises important questions about…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology
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Klarisa I. Vorobyeva; Svetlana Belous; Natalia V. Savchenko; Lyudmila M. Smirnova; Svetlana A. Nikitina; Sergei P. Zhdanov – Contemporary Educational Technology, 2025
In this analysis, we review artificial intelligence (AI)-supported personalized learning (PL) systems, with an emphasis on pedagogical approaches and implementation challenges. We searched the Web of Science and Scopus databases. After the preliminary review, we examined 30 publications in detail. ChatGPT and machine learning technologies are…
Descriptors: Individualized Instruction, Artificial Intelligence, Intelligent Tutoring Systems, Ethics
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Youngjin Lee – Education and Information Technologies, 2025
This study investigates the development and evaluation of a Retrieval-Augmented Generation (RAG)-based statistics tutor designed to assist students with quantitative analysis methods. The RAG approach was employed to address the well-documented issue of hallucination in Large Language Models (LLMs). A computer tutor was developed that utilizes…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Teachers, Students
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Yujie Han; Sumin Hong; Zhenyan Li; Cheolil Lim – TechTrends: Linking Research and Practice to Improve Learning, 2025
This scoping review investigates the roles of intelligent learning companion systems (LCS) within educational settings, as well as the presences artificial intelligence (AI) embodies within these roles, and their application in education. Employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for…
Descriptors: Artificial Intelligence, Definitions, Classification, Technology Uses in Education
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Nicolas J. Tanchuk; Rebecca M. Taylor – Educational Theory, 2025
AI tutors are promised to expand access to personalized learning, improving student achievement and addressing disparities in resources available to students across socioeconomic contexts. The rapid development and introduction of AI tutors raises fundamental questions of epistemic trust in education. What criteria should guide students' critical…
Descriptors: Individualized Instruction, Artificial Intelligence, Technology Uses in Education, Tutors
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Luiz Rodrigues; Guilherme Guerino; Thomaz E. V. Silva; Geiser C. Challco; Lívia Oliveira; Rodolfo S. da Penha; Rafael F. Melo; Thales Vieira; Marcelo Marinho; Valmir Macario; Ig I. Bittencourt; Diego Dermeval; Seiji Isotani – International Journal of Artificial Intelligence in Education, 2025
Intelligent Tutoring Systems (ITS) possess significant potential to enhance learning outcomes. However, deploying ITSs in global south countries presents challenges due to their frequent lack of essential technological resources, such as computers and internet access. The concept of AIED Unplugged has emerged to bridge this digital divide,…
Descriptors: Teacher Attitudes, Intelligent Tutoring Systems, Numeracy, Mathematics Education
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
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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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Thiemo Wambsganss; Ivo Benke; Alexander Maedche; Kenneth Koedinger; Tanja Käser – International Journal of Artificial Intelligence in Education, 2025
Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner control and inter- activity within them remains underexplored. This paper introduces…
Descriptors: Learner Controlled Instruction, Interaction, Intelligent Tutoring Systems, Persuasive Discourse
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Erick Fernando; Rosilah Hassan; Dina Fitria Murad; Zeyad Ghaleb Al-Mekhlafi – Educational Process: International Journal, 2025
Background/purpose: Education continues to evolve along with technological advances, and one of the biggest changes is the application of artificial intelligence (AI) in the learning process. The main problem in this study is the lack of in-depth understanding of the factors that influence the effectiveness of using AI in self-paced learning…
Descriptors: Literature Reviews, Meta Analysis, Bibliometrics, Artificial Intelligence
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Ling Zhang; Zijun Yao; Arya Hadizadeh Moghaddam – Journal of Teacher Education, 2025
Educator preparation, personalized learning (PL) implementation, and applications of Generative AI converge as three interrelated systems that, when carefully designed, can help achieve the long-sought goal of providing inclusive education for all learners. However, realizing this potential comes with challenges resulting from theoretical…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Faculty Development
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Chee-Kit Looi; Fenglin Jia – Education and Information Technologies, 2025
Since the advent of chatbots enabled by Generative AI such as ChatGPT, their application in the domain of education has been linked to promises of personalizing learning (PL). Through a study of conversational interactions of graduate students with such chatbots, this paper provides an empirical study of how current ChatGPT technologies can enable…
Descriptors: Individualized Instruction, Artificial Intelligence, Technology Uses in Education, Educational Technology
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Ji Hyun Yu; Devraj Chauhan – Education and Information Technologies, 2025
This paper presents a comprehensive analysis of the major themes in Natural Language Processing (NLP) applications for personalized learning, derived from a Latent Dirichlet Allocation (LDA) examination of top educational technology journals from 2014 to 2023. Our methodology involved collecting a corpus of relevant journal articles, applying LDA…
Descriptors: Natural Language Processing, Individualized Instruction, Educational Technology, Emotional Intelligence
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Murat Polat; Ibrahim Hakan Karatas; Nurgün Varol – Leadership and Policy in Schools, 2025
The incorporation of artificial intelligence (AI) into educational management offers personalized learning, adaptive tutoring, and efficient resource management. However, ethical considerations such as fairness, transparency, accountability, and privacy are crucial. This paper reviews literature and conducts a bibliometric analysis on ethical AI…
Descriptors: Ethics, Artificial Intelligence, Technology Uses in Education, Leadership
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