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Angélique Létourneau; Marion Deslandes Martineau; Patrick Charland; John Alexander Karran; Jared Boasen; Pierre Majorique Léger – npj Science of Learning, 2025
The use of artificial intelligence in education (AIEd) has grown exponentially in the last decade, particularly intelligent tutoring systems (ITSs). Despite the increased use of ITSs and their promise to improve learning, their real educational value remains unclear. This systematic review aims to identify the effects of ITSs on K-12 students'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intelligent Tutoring Systems, Elementary Secondary Education
Lu, Yu; Wang, Deliang; Chen, Penghe; Meng, Qinggang; Yu, Shengquan – International Journal of Artificial Intelligence in Education, 2023
As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Data Analysis
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
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
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
Aaron Haim; Eamon Worden; Neil T. Heffernan – Grantee Submission, 2024
Since GPT-4's release it has shown novel abilities in a variety of domains. This paper explores the use of LLM-generated explanations as on-demand assistance for problems within the ASSISTments platform. In particular, we are studying whether GPT-generated explanations are better than nothing on problems that have no supports and whether…
Descriptors: Artificial Intelligence, Learning Management Systems, Computer Software, Intelligent Tutoring Systems
Emilia Eichinger; Verena Oberhofer; Christian Seifert; Simon J. Preis – International Journal on E-Learning, 2025
Artificial intelligence (AI) is becoming ever better and more powerful, which is why it can be found in many areas of everyday life. AIs like ChatGPT have also found their way into universities and more and more students are trusting them. Previous studies found opportunities of ChatGPT in academic education such as personalized and interactive…
Descriptors: Foreign Countries, Higher Education, Undergraduate Students, Artificial Intelligence
Jiyou Jia; Tianrui Wang; Yuyue Zhang; Guangdi Wang – Asia Pacific Journal of Education, 2024
In designing an intelligent tutoring system, a core area of the application of AI in education, tips from the system or virtual tutors are crucial in helping students solve difficult questions in disciplines like mathematics. Traditionally, the manual design of general tips by teachers is time-consuming and error-prone. Generative AI, like…
Descriptors: Problem Solving, Artificial Intelligence, Learning Processes, Prompting
David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)
Conrad Borchers; Alex Houk; Vincent Aleven; Kenneth R. Koedinger – Grantee Submission, 2025
Active learning promises improved educational outcomes yet depends on students' sustained motivation to engage in practice. Goal setting can enhance learner engagement. However, past evidence of the effectiveness of setting goals tends to be limited to non-digital learning settings and does not scale well as it requires active teacher or parent…
Descriptors: Learner Engagement, Educational Benefits, Goal Orientation, Rewards
Mangera, Elisabet; Supratno, Haris; Suyatno – Pegem Journal of Education and Instruction, 2023
This studied focus on the relationship between transhumanist and artificial intelligence in the Education Context; Particularly Teaching and Learning Process at private university in Makassar, South Sulawesi, Indonesia. Anchored by a qualitative analysis and participated by five teachers, the data were analyzed in-depth interview. It was designed…
Descriptors: Humanism, Artificial Intelligence, Learning Processes, Postsecondary Education
Sarsa, Sami; Leinonen, Juho; Hellas, Arto – Journal of Educational Data Mining, 2022
New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Memory
Jonathan Brazil; Suijing Yang; Fabienne van der Kleij – Australian Council for Educational Research, 2025
This document provides guiding principles and practical examples for using AI in teaching and learning. Underpinned by a human-centred approach, the PATH principles serve as key guidance to ensure the ethical and effective integration of AI systems into teaching and learning. The PATH principles are: Promote teaching and learning; Advance…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Educational Principles

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