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Javad Keyhan – International Journal of Technology in Education and Science, 2025
In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach…
Descriptors: Individualized Instruction, Artificial Intelligence, Models, Higher Education
Large Language Models and Intelligent Tutoring Systems: Conflicting Paradigms and Possible Solutions

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
Mengqian Wang; Wenge Guo – ECNU Review of Education, 2025
This review compares generative artificial intelligence with five representative educational technologies in history and concludes that AI technology can become a knowledge producer and thus can be utilized as educative AI to enhance teaching and learning outcomes. From a historical perspective, each technological breakthrough has affected…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, History
Da-Lun Chen; Kirsi Aaltonen; Hannele Lampela; Jaakko Kujala – Technology, Knowledge and Learning, 2025
The breakthrough in generative artificial intelligence (AI) has unlocked new possibilities for higher education. There are many studies on educational chatbots in the fields of science, technology, engineering, and mathematics; however, studies on designing and leveraging chatbots in a multidisciplinary field like project management have been…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Higher Education
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
Jessie S. Barrot – Technology, Knowledge and Learning, 2024
This emerging technology report delves into the role of ChatGPT, an OpenAI conversational AI, in language learning. The initial section introduces ChatGPT's nature and highlights its features, including accessibility, personalization, immersive learning, and instant feedback, which render it a valuable asset for language learners and educators…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Language Acquisition
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
Miguel Ángel Escotet – Prospects, 2024
Artificial Intelligence is a fast-evolving technology with enormous potential for education, higher education, and learning. AI can also negatively impact how societies and their citizens engage ethically with these generated, still-unexplored tools. These technological breakthroughs present both opportunity and potential peril. The problem of any…
Descriptors: Futures (of Society), Artificial Intelligence, Technology Uses in Education, Higher Education
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
Ibrahim Abba Mohammed; Ahmed Bello; Bala Ayuba – Education and Information Technologies, 2025
In spite of the emergence of studies seeking to integrate chatbot into education, there is a wide literature gap in the Nigerian contexts. While most studies focus on the design and development of chatbots, there exists a very scarce literature on the effect of ChatGPT chatbot on students' achievement. To address this gap, this study checked the…
Descriptors: Natural Language Processing, Artificial Intelligence, Academic Achievement, Computer Science Education
Jay Fie Paler Luzano – International Journal of Technology in Education, 2025
Integrating artificial intelligence (AI) technologies into various educational domains has garnered significant attention. Among these technologies, ChatGPT stands out as a powerful tool that holds the potential to revolutionize the landscape of mathematics education. This study aims to explore the emerging trends and critical issues surrounding…
Descriptors: Mathematics Education, Educational Trends, Artificial Intelligence, Technology Uses in Education
Moriah Ariely; Tanya Nazaretsky; Giora Alexandron – Journal of Research in Science Teaching, 2024
One of the core practices of science is constructing scientific explanations. However, numerous studies have shown that constructing scientific explanations poses significant challenges to students. Proper assessment of scientific explanations is costly and time-consuming, and teachers often do not have a clear definition of the educational goals…
Descriptors: Biology, Automation, Individualized Instruction, Science Instruction
Emerson, Andrew; Min, Wookhee; Azevedo, Roger; Lester, James – British Journal of Educational Technology, 2023
Game-based learning environments hold significant promise for facilitating learning experiences that are both effective and engaging. To support individualised learning and support proactive scaffolding when students are struggling, game-based learning environments should be able to accurately predict student knowledge at early points in students'…
Descriptors: Game Based Learning, Natural Language Processing, Prediction, Student Evaluation
Chenghao Wang; Xueyun Li – International Journal of Computer-Assisted Language Learning and Teaching, 2025
D-ID Creative Reality Studio (D-ID) is a platform for creating Artificial Intelligence (AI) presenter (digital human) videos, translating videos, and designing conversational agents. D-ID seamlessly integrates deep-learning face animation technology, large language models (LLMs), natural language processing (NLP), and speech synthesis and…
Descriptors: Artificial Intelligence, Design, Video Technology, Animation
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
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