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Rashmi Khazanchi; Daniele Di Mitri; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: Despite educational advances, poor mathematics achievement persists among K-12 students, particularly in rural areas with limited resources and skilled teachers. Artificial Intelligence (AI) based systems have increasingly been adopted to support the diverse learning needs of students and have been shown to enhance mathematics…
Descriptors: Mathematics Achievement, Rural Areas, Artificial Intelligence, Individualized Instruction
Yumeng Zhu; Caifeng Zhu; Tao Wu; Shulei Wang; Yiyun Zhou; Jingyuan Chen; Fei Wu; Yan Li – Education and Information Technologies, 2025
With the prevalence of Large Language Model-based chatbots, middle school students are increasingly likely to engage with these tools to complete their assignments, raising concerns about its potential to harm students' learning motivation and learning outcomes. However, we know little about its real impact. Through quasi-experiment research with…
Descriptors: Artificial Intelligence, Assignments, Middle School Students, Influence of Technology

Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages

Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Jiawei Huang; Ding Zhou – Education and Information Technologies, 2024
Technological advancements have ushered in a new era of global educational development. Artificial Intelligence (AI) holds the potential to enhance teaching effectiveness and foster educational innovation. By utilizing student posture as a proxy, computer vision technology can accurately gauge levels of student engagement. While previous efforts…
Descriptors: Human Posture, Artificial Intelligence, Educational Technology, Learner Engagement
Yun Long; Haifeng Luo; Yu Zhang – npj Science of Learning, 2024
This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue--a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using…
Descriptors: Classroom Communication, Computational Linguistics, Chinese, Mathematics Instruction
Ramon Mayor Martins; Christiane Gresse von Wangenheim; Marcelo Fernando Rauber; Jean Carlo Hauck – International Journal of Artificial Intelligence in Education, 2024
Although Machine Learning (ML) is found practically everywhere, few understand the technology behind it. This presents new challenges to extend computing education by including ML concepts in order to help students to understand its potential and limits and empowering them to become creators of intelligent solutions. Therefore, we developed an…
Descriptors: Artificial Intelligence, Information Technology, Technology Uses in Education, Computer Software
Dorothy Daniels – ProQuest LLC, 2021
In the United States the number of English Language Learner students is steadily increasing. Many ELLs speak and understand limited English, resulting in achievement that lags far behind that of their classmates (Thomas, 2015). Recruiting the support of educators who come in contact with ELL students on a daily basis promoted a solution to this…
Descriptors: Middle Schools, English Language Learners, Assistive Technology, Artificial Intelligence
Ethan Prihar; Morgan Lee; Mia Hopman; Adam Tauman Kalai; Sofia Vempala; Allison Wang; Gabriel Wickline; Aly Murray; Neil Heffernan – Grantee Submission, 2023
Large language models have recently been able to perform well in a wide variety of circumstances. In this work, we explore the possibility of large language models, specifically GPT-3, to write explanations for middle-school mathematics problems, with the goal of eventually using this process to rapidly generate explanations for the mathematics…
Descriptors: Mathematics Instruction, Teaching Methods, Artificial Intelligence, Middle School Students
Li Cheng; Ethan Croteau; Sami Baral; Cristina Heffernan; Neil Heffernan – Journal of Educational Computing Research, 2024
Chatbots represent a promising technology for engaging students in math learning. Guided by Jerome Bruner's constructivism and Lev Vygotsky's Zone of Proximal Development, we designed and developed a chatbot that incorporates scaffolding strategies and social-emotional considerations, and we integrated it into ASSISTments, an online math learning…
Descriptors: Artificial Intelligence, Learning Management Systems, Teaching Methods, Mathematics Instruction
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
John Corry Werth; Peter Charles Sinclair Taylor; Elisabeth Taylor – Australian Mathematics Education Journal, 2024
Over the past 20 years, the authors have designed an interdisciplinary approach that integrates Arts-based methods into STEM education. This integrated STEAM education perspective is particularly useful for enabling students to develop (i) not only their traditional scientific (and mathematical) understanding of the outer world but also (ii) their…
Descriptors: Mathematics Instruction, Artificial Intelligence, Computer Software, STEM Education
Yijia Yuan – Interactive Learning Environments, 2024
This experimental research examined the effectiveness of using chatbots in English as a Foreign Language (EFL) classrooms at a Chinese elementary school. Seventy-four students were divided into two groups: one employing traditional methods, and the other using chatbots. Before and after the 3-month teaching period, pre- and post-tests were used to…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, English (Second Language)
Catherine Lammert; Samuel DeJulio; Stephanie Grote-Garcia; Lucretia M. Fraga – Clearing House: A Journal of Educational Strategies, Issues and Ideas, 2024
Since ChatGPT launched in 2022, teachers and administrators have had the challenge of using generative Artificial Intelligence (AI) effectively while minimizing the negative consequences of its presence in schools. Today, AI-enabled lesson plan generators such as Diffit and MagicSchool AI are widely available to teachers, but no research has…
Descriptors: Artificial Intelligence, Lesson Plans, Access to Education, Educational Quality
Ahmet Baytak – Research in Social Sciences and Technology, 2024
Following the emergence of chatbots, especially ChatGPT, researchers have begun to examine their capabilities, credibility, and reliability in educational context. In this study, ChatGPT and Google Gemini are used as technological tools to create 7th-grade lesson plans for mathematics, science, literature, and social studies classes. Using…
Descriptors: Lesson Plans, Content Analysis, Artificial Intelligence, Synchronous Communication
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