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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
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
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
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
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
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
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
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
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
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
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
Martin, Tim; Frisch, Kayt; Zwart, John – Physics Teacher, 2020
Video analysis helps students to connect physical, mathematical, and graphical models with the phenomena that the models represent and improves student kinematic graph interpretation skills. The wide-spread availability of easy to use software packages like Logger Pro (Vernier), Capstone (PASCO), and Tracker have led to many introductory physics…
Descriptors: Video Technology, Science Instruction, Educational Technology, Technology Uses in Education
Miao, Dezhuang; Dong, Yu; Lu, Xuesong – International Educational Data Mining Society, 2020
In colleges, programming is increasingly becoming a general education course of almost all STEM majors as well as some art majors, resulting in an emerging demand for scalable programming education. To support scalable education, teaching activities such as grading and feedback have to be automated. Recently, online judge systems have been…
Descriptors: Programming, Prediction, Error Patterns, Models
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