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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
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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
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Tsubasa Minematsu; Atsushi Shimada – International Association for Development of the Information Society, 2024
In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…
Descriptors: Educational Technology, Technology Uses in Education, Error Patterns, Sentences
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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
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Fatma Bayrambas; Emine Sendurur – Education and Information Technologies, 2024
Incidental learning is a type of informal learning occurring consciously with unintentional acts. Within the scope of this study, informal learning on a digital learning platform was examined in the context of cognitive load. The current study investigated the changes in incidental learning within two different scenarios: extraneous irrelevant…
Descriptors: Incidental Learning, Cognitive Processes, Difficulty Level, Biofeedback
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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
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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
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Salima Aldazharova; Gulnara Issayeva; Samat Maxutov; Nuri Balta – Contemporary Educational Technology, 2024
This study investigates the performance of GPT-4, an advanced AI model developed by OpenAI, on the force concept inventory (FCI) to evaluate its accuracy, reasoning patterns, and the occurrence of false positives and false negatives. GPT-4 was tasked with answering the FCI questions across multiple sessions. Key findings include GPT-4's…
Descriptors: Physics, Science Tests, Artificial Intelligence, Problem Solving
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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
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Jayaron Jose; Blessy Jayaron Jose – Electronic Journal of e-Learning, 2024
The study on "Educators' Academic Insights on Artificial Intelligence -- Challenges and Opportunities" was conducted to gain a deeper understanding of the rapidly evolving phenomenon of AI in education. This research serves multiple objectives. Firstly, it aims to foster awareness regarding the integration of AI into teaching and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Definitions
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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
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Norbert Noster; Sebastian Gerber; Hans-Stefan Siller – Digital Experiences in Mathematics Education, 2024
The use of large language models like ChatGPT is widely discussed for educational purposes. Using this technology requires teachers to have appropriate competences that incorporate knowledge of how to make use of this technology. In this study, we investigate pre-service teachers' knowledge through the lens of the KTMT model ("Knowledge for…
Descriptors: Preservice Teachers, Mathematics Skills, Problem Solving, Technology Uses in Education
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Zeng-Wei Hong; Ming-Hsiu Michelle Tsai; Chin Soon Ku; Wai Khuen Cheng; Jian-Tan Chen; Jim-Min Lin – Cogent Education, 2024
Although the existing research on educational robots has exhibited the assistance for EFL learners' English skills, the evidence which shows robot-assisted systems' effect on adult learners' English read-aloud is still rare. Nevertheless, read-aloud is still treated as a useful approach in English classes for speech pronunciations in particular in…
Descriptors: Foreign Countries, English (Second Language), Second Language Instruction, Pronunciation
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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
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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
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