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Ani Grubišic; Ines Šaric-Grgic; Angelina Gašpar; Branko Žitko – Journal of Computer Assisted Learning, 2025
Background: Adaptive educational systems have gained increasing attention due to their ability to personalise educational content based on individual learner progress. Prior research highlights that intelligent tutoring systems (ITSs) and adaptive courseware models improve learning outcomes by dynamically adjusting instructional materials.…
Descriptors: Usability, Courseware, Natural Language Processing, Intelligent Tutoring Systems
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Abdullah Al-Abri – Education and Information Technologies, 2025
This study explores the impact of ChatGPT, an advanced Large Language Model (LLM), as a virtual tutor in online education across five key dimensions: answering questions, writing assistance, study resources, exam preparation, and availability. Utilizing an experimental design, 68 undergraduate students from a public university interacted with…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Intelligent Tutoring Systems
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Yufeng Wang; Dehua Ma; Jianhua Ma; Qun Jin – IEEE Transactions on Learning Technologies, 2024
As one of the fundamental tasks in the online learning platform, interactive course recommendation (ICR) aims to maximize the long-term learning efficiency of each student, through actively exploring and exploiting the student's feedbacks, and accordingly conducting personalized course recommendation. Recently, deep reinforcement learning (DRL)…
Descriptors: Electronic Learning, Student Interests, Artificial Intelligence, Intelligent Tutoring Systems
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Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
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Milos Ilic; Goran Kekovic; Vladimir Mikic; Katerina Mangaroska; Lazar Kopanja; Boban Vesin – IEEE Transactions on Learning Technologies, 2024
In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…
Descriptors: Artificial Intelligence, Academic Achievement, Prediction, Programming
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Sanzharbek S. Erdolatov; Almazbek D. Ibraev; Gulzat A. Esenalieva; Marlis M. Bekezhanov; Salidin K. Kaldybaev – Education in the Asia-Pacific Region: Issues, Concerns and Prospects, 2025
The research aims to study the state of the use of information technologies in the higher education system of Kyrgyzstan. Within the research framework, the authors studied strategic plans and programs aimed at creating an information society in Kyrgyzstan. The authors described the problems that have arisen as a result of the impact of digital…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, Higher Education
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Xinyi Wu; Xiaohui Chen; Xingyang Wang; Hanxi Wang – Education and Information Technologies, 2025
With the application of virtual venues in the field of education, numerous educational empirical studies have examined the impact of deep learning in the learning environment of virtual venues, but the conclusions are not always in agreement. The present study adopted the meta-analysis method and RStudio software to test the overall effect of 45…
Descriptors: Literature Reviews, Meta Analysis, Artificial Intelligence, Intelligent Tutoring Systems
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A. N. Varnavsky – IEEE Transactions on Learning Technologies, 2024
The most critical parameter of audio and video information output is the playback speed, which affects many viewing or listening metrics, including when learning using tutoring systems. However, the availability of quantitative models for personalized playback speed control considering the learner's personal traits is still an open question. The…
Descriptors: Hierarchical Linear Modeling, Intelligent Tutoring Systems, Individualized Instruction, Electronic Learning
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Md. Mirajul Islam; Xi Yang; John Hostetter; Adittya Soukarjya Saha; Min Chi – International Educational Data Mining Society, 2024
A key challenge in e-learning environments like Intelligent Tutoring Systems (ITSs) is to induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL) often suffers from "sample inefficiency" and "reward function" design difficulty, Apprenticeship Learning (AL) algorithms can overcome them.…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Teaching Methods, Algorithms
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Yasemin Copur-Gencturk; Chandra Hawley Orrill – Grantee Submission, 2025
The scalability and accessibility of quality professional development (PD) is an ongoing concern in the teacher education community, yet little research has been conducted on potential solutions. We aimed to address this gap by developing an interactive, virtual PD program that uses intelligent tutoring systems and provides instant feedback to…
Descriptors: Faculty Development, Online Courses, Teacher Education, Intelligent Tutoring Systems
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Yasemin Copur-Gencturk; Chandra Hawley Orrill – Journal of Mathematics Teacher Education, 2025
The scalability and accessibility of quality professional development (PD) is an ongoing concern in the teacher education community, yet little research has been conducted on potential solutions. We aimed to address this gap by developing an interactive, virtual PD program that uses intelligent tutoring systems and provides instant feedback to…
Descriptors: Faculty Development, Online Courses, Teacher Education, Intelligent Tutoring Systems
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Peng, Tzu-Hsiang; Wang, Tzu-Hua – Journal of Educational Computing Research, 2022
Pedagogical agents (PAs) are a crucial aspect of the e-learning environment. A PA is defined as a virtual character presented on an interface, and they are designed to promote student learning. PAs have been widely discussed in academic papers. However, an appropriate analysis framework has not been proposed because of the diversity and complexity…
Descriptors: Electronic Learning, Instructional Effectiveness, Intelligent Tutoring Systems, Evaluation Methods
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Zhou, Guojing; Azizsoltani, Hamoon; Ausin, Markel Sanz; Barnes, Tiffany; Chi, Min – International Journal of Artificial Intelligence in Education, 2022
In interactive e-learning environments such as Intelligent Tutoring Systems, pedagogical decisions can be made at different levels of granularity. In this work, we focus on making decisions at "two levels": whole problems vs. single steps and explore three types of granularity: "problem-level only" ("Prob-Only"),…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Decision Making, Problem Solving
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Linghong Li; Wayne F. Patton – Journal of Educational Technology Systems, 2025
The evolving landscape of higher education demands integrating advanced technologies to foster engaging and inclusive learning environments. This paper examines the practical integration of Stellarium, a virtual planetarium software, and ChatGPT, an AI conversational agent, in an asynchronous online undergraduate astronomy course. Stellarium…
Descriptors: Electronic Learning, Astronomy, Science Education, Artificial Intelligence
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Benmesbah, Ouissem; Lamia, Mahnane; Hafidi, Mohamed – Interactive Learning Environments, 2023
Adaptive learning has garnered researchers' interest. The main issue within this field is how to select appropriate learning objects (LOs) based on learners' requirements and context, and how to combine the selected LOs to form what is known as an adaptive learning path. Heuristic and metaheuristic approaches have achieved significant progress on…
Descriptors: Algorithms, Teaching Methods, Educational Innovation, Genetics
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