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Yasin Memis – Journal of Pedagogical Research, 2025
The integration of artificial intelligence (AI) into mathematical problem-solving has shown significant potential to enhance student learning and performance. However, while AI tools offer numerous benefits, they are prone to occasional conceptual and arithmetic errors that can mislead users and obscure understanding. This research examines such…
Descriptors: Artificial Intelligence, Mathematics Instruction, Problem Solving, Error Patterns
Chi Hong Leung; Winslet Ting Yan Chan – Asian Journal of Contemporary Education, 2025
This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Error Patterns
Jionghao Lin; Zifei Han; Danielle R. Thomas; Ashish Gurung; Shivang Gupta; Vincent Aleven; Kenneth R. Koedinger – International Journal of Artificial Intelligence in Education, 2025
One-on-one tutoring is widely acknowledged as an effective instructional method, conditioned on qualified tutors. However, the high demand for qualified tutors remains a challenge, often necessitating the training of novice tutors (i.e., trainees) to ensure effective tutoring. Research suggests that providing timely explanatory feedback can…
Descriptors: Artificial Intelligence, Technology Uses in Education, Tutor Training, Trainees
Tom Madou; Fien Depaepe; Phillip Ward; Peter Iserbyt – Physical Education and Sport Pedagogy, 2025
Background: Teaching strategies using peers to influence student-learning outcomes are commonly used in physical education. Reciprocal peer learning is a teaching strategy where students work in pairs as tutor and tutee. Effective peer tutoring requires knowledge about the critical elements for correct performance (i.e. common content knowledge,…
Descriptors: Physical Education, Peer Teaching, Reciprocal Teaching, Undergraduate Students
Yu-Ju Lan; Scott Grant; Hui-Chin Yeh – Educational Technology & Society, 2025
This study investigated the use of virtual chatbots in a 3D multi-user virtual environment (3D MUVE) to enhance the communication skills of Chinese as a foreign language (CFL) learners. Several virtual chat agents, developed using pattern matching techniques and embedded in Second Life, created a blended learning environment in which CFL learners…
Descriptors: Artificial Intelligence, Communication Skills, Educational Technology, Technology Uses in Education
Marie Alina Yeo; Benjamin Luke Moorhouse; Yuwei Wan – TESL-EJ, 2025
This paper looks at Google's NotebookLM, an AI-powered research assistant tool that can represent dense academic content in a range of output modes, like FAQs, timelines, study guides, and, most uniquely, as "Deep Dive" discussions. The discussions mimic a talk-show, where two AI-hosts unpack complex ideas from reading or audio texts,…
Descriptors: Artificial Intelligence, Research Tools, Technology Uses in Education, Computer Mediated Communication
Ali Sartaz Khan; Tolulope Ogunremi; Ahmed Attia; Dorottya Demszky – International Educational Data Mining Society, 2025
Speaker diarization, the process of identifying "who spoke when" in audio recordings, is essential for understanding classroom dynamics. However, classroom settings present distinct challenges, including poor recording quality, high levels of background noise, overlapping speech, and the difficulty of accurately capturing children's…
Descriptors: Audio Equipment, Acoustics, Classroom Environment, Models
Sam Sedaghat – Journal of Academic Ethics, 2025
Chatbots such as ChatGPT have the potential to change researchers' lives in many ways. Despite all the advantages of chatbots, many challenges to using chatbots in medical research remain. Wrong and incorrect content presented by chatbots is a major possible disadvantage. The authors' credibility could be tarnished if wrong content is presented in…
Descriptors: Plagiarism, Artificial Intelligence, Medical Research, Error Patterns
Iria Estévez-Ayres; Patricia Callejo; Miguel Ángel Hombrados-Herrera; Carlos Alario-Hoyos; Carlos Delgado Kloos – International Journal of Artificial Intelligence in Education, 2025
The emergence of Large Language Models (LLMs) has marked a significant change in education. The appearance of these LLMs and their associated chatbots has yielded several advantages for both students and educators, including their use as teaching assistants for content creation or summarisation. This paper aims to evaluate the capacity of LLMs…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Mediated Communication, Technology Uses in Education
Xinli Zhang; Ruiting Huang; Ruihua Zhang; Mingyi Li; Yun-Fang Tu; Yuchen Chen; Lailin Hu; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2025
Background: Primary school is key to developing writing skills. However, students may face challenges in identifying and revising articles due to weak language skills, organisational thinking, comprehension, and analytical skills. Therefore, improving the writing skills of primary school students with writing difficulties has become important.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Revision (Written Composition), Elementary School Students
Ömer Sahin – International Journal for Mathematics Teaching and Learning, 2025
This research analyzed the effect of digital storytelling (DST) on the development of pedagological content knowledge (PCK) of prospective secondary school mathematics teachers on mistakes made by students in algebra. The research applied sub-domains of PCK, the knowledge of content and students (KCS) and the knowledge of content and teaching…
Descriptors: Electronic Learning, Story Telling, Pedagogical Content Knowledge, Preservice Teachers
Ian Thacker; Hannah French; Shon Feder – International Journal of Science Education, 2025
Presenting novel numbers about climate change to people after they estimate those numbers can shift their attitudes and scientific conceptions. Prior research suggests that such science learning can be supported by encouraging learners to make use of given benchmark information, however there are several other numerical estimation skills that may…
Descriptors: Climate, Computation, College Students, Hispanic American Students
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – International Journal of Artificial Intelligence in Education, 2025
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change

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