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Sarah K. Cox; Elizabeth Hughes – School Science and Mathematics, 2025
Students with autism spectrum disorder (ASD) are included in the general education classroom more often than ever before. Despite mathematical strengths and early success, these students experience poor outcomes (academic and employment) compared to their typically developing peers. The language of mathematics increases in complexity, use, and…
Descriptors: Students with Disabilities, Autism Spectrum Disorders, Inclusion, Mathematics Instruction
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Eunhye Flavin; Sunghwan Hwang; Melita Morales – Journal of Teacher Education, 2025
Generative artificial intelligence (AI)-powered conversation agents such as ChatGPT are increasingly being used in teacher education. Although ChatGPT can provide ample resources for lesson planning, little attention has been paid to how teacher candidates construct prompts and evaluate AI-generated outputs in real time to develop lesson plans.…
Descriptors: Preservice Teachers, Mathematics Instruction, Lesson Plans, Natural Language Processing
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Bihao Hu; Longwei Zheng; Jiayi Zhu; Lishan Ding; Yilei Wang; Xiaoqing Gu – IEEE Transactions on Learning Technologies, 2024
This study explores and analyzes the specific performance of large language models (LLMs) in instructional design, aiming to unveil their potential strengths and possible weaknesses. Recently, the influence of LLMs has gradually increased in multiple fields, yet exploratory research on their application in education remains relatively scarce. In…
Descriptors: Artificial Intelligence, Natural Language Processing, Instructional Design, Prompting
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Selahattin Alan; Eyup Yurt – International Journal of Modern Education Studies, 2024
The limitations of traditional education models and the advancement of technology have revealed the need to transform the learning experience. The "Flipped Learning" approach, born out of this need, is a model where students study learning materials in advance and participate in more interactive and hands-on activities in the classroom.…
Descriptors: Flipped Classroom, Natural Language Processing, Artificial Intelligence, Educational Innovation
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Muhammet Remzi Karaman; I?dris Göksu – International Journal of Technology in Education, 2024
In this research, we aimed to determine whether students' math achievements improved using ChatGPT, one of the chatbot tools, to prepare lesson plans in primary school math courses. The research was conducted with a pretest-posttest control group experimental design. The study comprises 39 third-grade students (experimental group = 24, control…
Descriptors: Artificial Intelligence, Natural Language Processing, Lesson Plans, Instructional Effectiveness
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Ha Tien Nguyen; Conrad Borchers; Meng Xia; Vincent Aleven – Grantee Submission, 2024
Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…
Descriptors: Middle School Mathematics, Intelligent Tutoring Systems, Caregivers, Caregiver Attitudes
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Derar Serhan; Natalie Welcome – International Journal of Technology in Education and Science, 2024
Educators are faced with the sudden infiltration of AI, including artificially intelligent tools that generate content far more sophisticated than any prior technological advancement. In this study, the researchers investigated the use of ChatGPT (currently the most used generative AI tool) as a means of learning Calculus. The study examined…
Descriptors: Technology Uses in Education, Artificial Intelligence, Calculus, Mathematics Instruction
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Bima Sapkota; Liza Bondurant – International Journal of Technology in Education, 2024
In November 2022, ChatGPT, an Artificial Intelligence (AI) large language model (LLM) capable of generating human-like responses, was launched. ChatGPT has a variety of promising applications in education, such as using it as thought-partner in generating curricular resources. However, scholars also recognize that the use of ChatGPT raises…
Descriptors: Cognitive Processes, Difficulty Level, Artificial Intelligence, Natural Language Processing
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Seyum Getenet – International Electronic Journal of Mathematics Education, 2024
This study compared the problem-solving abilities of ChatGPT and 58 pre-service teachers (PSTs) in solving a mathematical word problem using various strategies. PSTs were asked to solve a problem individually. Data was collected from PSTs' submitted assignments, and their problem-solving strategies were analyzed. ChatGPT was also given the same…
Descriptors: Problem Solving, Ability, Preservice Teachers, Artificial Intelligence
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Yaniv Biton; Ruti Segal – International Journal of Education in Mathematics, Science and Technology, 2025
The use of generative AI (Chat GPT) for the process of posing mathematical problems was introduced to 15 pre-service teachers (henceforth referred to as "teachers") in a re-training program aimed at teaching advanced secondary school mathematics. After solving mathematical problems, they were given an assignment to pose and refine…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Preservice Teachers
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Eli Bagno; Thierry Dana-Picard; Shulamit Reches – Open Education Studies, 2024
As soon as a new technology emerges, the education community explores its affordances and the possibilities to apply it in education. In this article, we analyze sessions with ChatGPT around topics in basic linear algebra. We reflect on the affordances and changes between two versions of ChatGPT since its worldwide publication in our area of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Algebra
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Taylor Lesner; Ben Clarke; Derek Kosty; Geovanna Rodriguez; Elizabeth L. Budd; Christian Doabler – Grantee Submission, 2025
This secondary analysis of data from a randomized control trial of an early mathematics intervention, ROOTS, explored whether patterns of intervention response were best categorized by the typical response/non-response binary or a more complex framework with additional response profiles. Participants included kindergarten students at risk for…
Descriptors: Mathematics Instruction, Response to Intervention, At Risk Students, Kindergarten