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Showing 1 to 15 of 24 results Save | Export
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Clayton Cohn; Caitlin Snyder; Joyce Horn Fonteles; Ashwin T. S.; Justin Montenegro; Gautam Biswas – British Journal of Educational Technology, 2025
Recent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open-ended environments. AI…
Descriptors: Cooperation, Researchers, Artificial Intelligence, STEM Education
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Alberto Gandolfi – International Journal of Artificial Intelligence in Education, 2025
In this paper, we initially investigate the capabilities of GPT-3 5 and GPT-4 in solving college-level calculus problems, an essential segment of mathematics that remains under-explored so far. Although improving upon earlier versions, GPT-4 attains approximately 65% accuracy for standard problems and decreases to 20% for competition-like…
Descriptors: Artificial Intelligence, Reliability, Problem Solving, Mathematics Skills
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Rebecca Marrone; Andrew Zamecnik; Srecko Joksimovic; Jarrod Johnson; Maarten De Laat – Technology, Knowledge and Learning, 2025
This article examines students' opinions regarding the use of artificial intelligence (AI) as a teammate in solving complex problems. The overarching goal of the study is to explore the effectiveness of AI as a collaborative partner in educational settings. In the study, 15 groups of grade 9 students (59 students total) were assigned a challenging…
Descriptors: Student Attitudes, Artificial Intelligence, Problem Solving, Teamwork
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Kole Norberg; Husni Almoubayyed; Stephen E. Fancsali; Logan De Ley; Kyle Weldon; April Murphy; Steve Ritter – Grantee Submission, 2023
Large Language Models have recently achieved high performance on many writing tasks. In a recent study, math word problems in Carnegie Learning's MATHia adaptive learning software were rewritten by human authors to improve their clarity and specificity. The randomized experiment found that emerging readers who received the rewritten word problems…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Artificial Intelligence, Intelligent Tutoring Systems
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Jyun-Chen Chen; Chia-Yu Liu – Journal of Computer Assisted Learning, 2025
Background: Based on the embodied cognition perspective, interdisciplinary hands-on learning combines several disciplines, such as science, technology, engineering and mathematics (STEM), to improve students' capacity to solve real-world problems. Despite the popularity of interdisciplinary hands-on learning, particularly the six-phase 6E model,…
Descriptors: Interdisciplinary Approach, Experiential Learning, STEM Education, Problem Solving
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Peter H. F. Ng; Peter Q. Chen; Astin C. H. Wu; Ken S. K. Tai; Chen Li – IEEE Transactions on Learning Technologies, 2024
This study examines a practical teaching and learning cycle tailored to integrate cutting-edge technologies (artificial intelligence (AI) and machine learning (ML) game development) and social entrepreneurship within a "STEM with meaning" approach. This cycle, rooted in service learning and the 5E constructivist teaching model (engage,…
Descriptors: Artificial Intelligence, STEM Education, Educational Games, Service Learning
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Sebastian Kilde-Westberg; Andreas Johansson; Jonas Enger – Physical Review Physics Education Research, 2025
Generative AI tools, including the popular ChatGPT, have had a significant impact on discourses about future work and educational practices. Previous research in science education has highlighted the potential of generative AI in various education-related areas, including generating valuable discussion material, solving physics problems, and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Science Laboratories, Physics
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Qian Xu – Discover Education, 2024
This research suggests a methodology to examine the effectiveness Artificial Intelligence (AI) on the cognitive abilities of college students so that future researchers can utilize this experimental project to focus on how AI-powered Intelligent Tutoring Systems (ITSs) affect learning outcomes. As AI continues to revolutionize all walks of life,…
Descriptors: Artificial Intelligence, Cognitive Ability, College Students, Intelligent Tutoring Systems
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Maya Usher; Miri Barak – International Journal of STEM Education, 2024
As artificial intelligence (AI) technology rapidly advances, it becomes imperative to equip students with tools to navigate through the many intricate ethical considerations surrounding its development and use. Despite growing recognition of this necessity, the integration of AI ethics into higher education curricula remains limited. This paucity…
Descriptors: Artificial Intelligence, Ethics, Ethical Instruction, Online Courses
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Roland Kiraly; Sandor Kiraly; Martin Palotai – Education and Information Technologies, 2024
Deep learning is a very popular topic in computer sciences courses despite the fact that it is often challenging for beginners to take their first step due to the complexity of understanding and applying Artificial Neural Networks (ANN). Thus, the need to both understand and use neural networks is appearing at an ever-increasing rate across all…
Descriptors: Artificial Intelligence, Computer Science Education, Problem Solving, College Faculty
Senapati, Biswaranjan – ProQuest LLC, 2023
A neurological disorder, along with several behavioral issues, may be to blame for a child's subpar performance in the academic journey (such as anxiety, depression, learning disorders, and irritability). These symptoms can be used to diagnose children with ASD, and supervised machine learning models can help differentiate between ASD traits and…
Descriptors: Artificial Intelligence, Educational Technology, Autism Spectrum Disorders, Models
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Tippawan Meepung – Journal of Education and Learning, 2025
This study explores the development and evaluation of a digital learning ecosystem through metaverse experiences aimed at enhancing the competencies of modern digital entrepreneurs. The objectives were as follows: (1) to study the digital learning ecosystem through metaverse experiences, (2) to design and develop a digital learning ecosystem using…
Descriptors: Electronic Learning, Ecology, Artificial Intelligence, Skill Development
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Ramadhan Prasetya Wibawa; Hari Wahyono; Wahjoedi; Endang Sri Andayani – Educational Process: International Journal, 2025
Background/purpose: This study aimed to identify publication trends regarding the implementation of Project Based Learning (PjBL) in junior high schools over a specific period based on bibliometric data; To analyze the most frequently occurring keywords in the PjBL literature for junior high schools to understand the main research focus; To…
Descriptors: Student Projects, Active Learning, Program Effectiveness, Junior High School Students
Husni Almoubayyed; Rae Bastoni; Susan R. Berman; Sarah Galasso; Megan Jensen; Leila Lester; April Murphy; Mark Swartz; Kyle Weldon; Stephen E. Fancsali; Jess Gropen; Steve Ritter – Grantee Submission, 2023
We present a recent randomized field trial delivered in Carnegie Learning's MATHia's intelligent tutoring system to a sample of 12,374 learners intended to test whether rewriting content in a selection of so-called "word problems" improves student mathematics performance within this content, especially among students who are emerging as…
Descriptors: Word Problems (Mathematics), Intelligent Tutoring Systems, Mathematics Achievement, English Learners
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AlGhamdi, Azza Abdullah – International Journal of Higher Education, 2022
In this study, we aimed to review scientific studies and research to present a view of artificial intelligence in education to achieve sustainable development in accordance with the foundations of the Kingdom's Vision 2030. We conducted a systematic review of previous literature by extrapolating and analyzing 17 previous studies published from…
Descriptors: Artificial Intelligence, Technology Uses in Education, Sustainable Development, Foreign Countries
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