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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
Mishra, Swaroop – ProQuest LLC, 2023
Humans have the remarkable ability to solve different tasks by simply reading textual instructions that define the tasks and looking at a few examples. Natural Language Processing (NLP) models built with the conventional machine learning paradigm, however, often struggle to generalize across tasks (e.g., a question-answering system cannot solve…
Descriptors: Natural Language Processing, Models, Readability, Mathematical Logic
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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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Aimee Weathers; Diana Curtis – Journal of Technology and Teacher Education, 2025
The purpose of this mixed-methods study was to investigate how generative AI tools, particularly ChatGPT, impact preservice teachers' lesson plans and attitudes toward mathematics. Fifty-five undergraduate students who were enrolled in their first semester of a teacher education program participated in the study. Each student created two lesson…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Mathematics Instruction
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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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Owen Henkel; Zach Levoninan; Millie-Ellen Postle; Chenglu Li – International Educational Data Mining Society, 2024
For middle-school math students, interactive question-answering (QA) with tutors is an effective way to learn. The flexibility and emergent capabilities of generative large language models (LLMs) has led to a surge of interest in automating portions of the tutoring process--including interactive QA to support conceptual discussion of mathematical…
Descriptors: Middle School Mathematics, Questioning Techniques, Algebra, Geometry
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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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Philip Slobodsky; Mariana Durcheva – International Journal of Mathematical Education in Science and Technology, 2025
AI-based bots (ChatGPT) are capable of solving mathematics problems, and students often use them for homework preparation, self-learning, etc. This raises a number of didactical and technical questions: How can students submit assignments containing complex mathematical expressions using only a keyboard? How should mathematics errors in ChatGPT's…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, 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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Kate Quane; Helen Booth – Australian Primary Mathematics Classroom, 2023
The authors define two mathematical cognitive verbs which are fundamental to the development of mathematical thinking and reasoning. They distinguish between 'describing' and 'explaining' in relation to doing mathematics, rather than using them interchangeably.
Descriptors: Mathematics Instruction, Teaching Methods, Thinking Skills, Verbs
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Lu, Hong; Leung, Frederick K. S.; Fan, Zhengcheng – ZDM: Mathematics Education, 2022
Research has revealed the extent and mechanism of the relation between language (dominated by alphabetic systems) and students' mathematics learning, but when it comes to Chinese language (an orthographic system), nature remains elusive. In this meta-analysis we aim to quantify the size of the relation between Chinese language and mathematics and…
Descriptors: Chinese, Mathematics Instruction, Learning Processes, Meta Analysis
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