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Showing 1 to 15 of 22 results Save | Export
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Clayton Cohn; Surya Rayala; Caitlin Snyder; Joyce Horn Fonteles; Shruti Jain; Naveeduddin Mohammed; Umesh Timalsina; Sarah K. Burriss; Ashwin T. S.; Namrata Srivastava; Menton Deweese; Angela Eeds; Gautam Biswas – Grantee Submission, 2025
Collaborative dialogue offers rich insights into students' learning and critical thinking. This is essential for adapting pedagogical agents to students' learning and problem-solving skills in STEM+C settings. While large language models (LLMs) facilitate dynamic pedagogical interactions, potential hallucinations can undermine confidence, trust,…
Descriptors: STEM Education, Computer Science Education, Artificial Intelligence, Natural Language Processing
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Sarah Levine; Sarah W. Beck; Chris Mah; Lena Phalen; Jaylen PIttman – Journal of Adolescent & Adult Literacy, 2025
Educators and researchers are interested in ways that ChatGPT and other generative AI tools might move beyond the role of "cheatbot" and become part of the network of resources students use for writing. We studied how high school students used ChatGPT as a writing support while writing arguments about topics like school mascots. We…
Descriptors: Natural Language Processing, Artificial Intelligence, Technology Uses in Education, Writing (Composition)
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Mathias Benedek; Roger E. Beaty – Journal of Creative Behavior, 2025
The PISA assessment 2022 of creative thinking was a moonshot effort that introduced significant advancements over existing creativity tests, including a broad range of domains (written, visual, social, and scientific), implementation in many languages, and sophisticated scoring methods. PISA 2022 demonstrated the general feasibility of assessing…
Descriptors: Creative Thinking, Creativity, Creativity Tests, Scoring
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Alexandra S. Dylman; Marie-France Champoux-Larsson; Candice Frances – Educational Psychology, 2025
We report four experiments investigating the effect of prosody on listening comprehension in 11-13-year-old children. Across all experiments, participants listened to short object descriptions and answered content-based questions about said objects. In Experiments 1-3, the descriptions were read in an emotionally positive or neutral tone of voice.…
Descriptors: Intonation, Middle School Students, Foreign Countries, Listening Comprehension
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Brian Heseung Kim; Julie J. Park; Pearl Lo; Dominique Baker; Nancy Wong; Stephanie Breen; Huong Truong; Jia Zheng; Kelly Rosinger; OiYan A. Poon – Research in Higher Education, 2025
Letters of recommendation from school counselors are required to apply to most selective universities. We use cutting-edge natural language processing techniques to algorithmically analyze a national dataset of over 600,000 student applications and counselor recommendation letters submitted through the Common Application. We examine how the length…
Descriptors: Letters (Correspondence), Advocacy, School Counselors, High Schools
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Chia-Ju Lin; Wei-Sheng Wang; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Journal of Educational Computing Research, 2025
This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time…
Descriptors: Natural Language Processing, Computational Linguistics, Technology Uses in Education, STEM Education
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Wei Li; Jia-Wei Ji; Judy C. R. Tseng; Cheng-Ye Liu; Ji-Yi Huang; Hai-Ying Liu; Mo Zhou – Educational Technology & Society, 2025
Education is an important way to achieve global Sustainable Development Goals (SDGs), while classroom engagement and collective efficacy are key factors that influence SDG learning outcomes. However, students' in-depth thinking could be limited when they apply to search engines such as Google to support their learning of SDG-related topics. Large…
Descriptors: Learner Engagement, Self Efficacy, Critical Thinking, Artificial Intelligence
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Eunhye Shin – Journal of Computer Assisted Learning, 2025
Background: Analysing classroom dialogue is a widely used approach for understanding students' learning, often requiring team-based collaborative research. This presents a challenge for single researchers due to the labour-intensive nature of the process. Emerging advancements in large language models (LLMs) such as ChatGPT, enhance qualitative…
Descriptors: Artificial Intelligence, Technology Uses in Education, Science Education, Coding
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Mary Rice; Nicholas DePascal; Joaquín T. Argüello de Jesús; Helen McFeely; Amy Traylor; Lehman Heaviland – Professional Development in Education, 2025
With the introduction of artificial intelligence (AI), particularly Generative AI (GenAI) to school settings, teachers are likely to be drawn into professional learning scenarios where they will be expected to learn how to use programs and applications for remediation and tutoring of children. Previous research highlights how professional learning…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Andrew Potter; Mitchell Shortt; Maria Goldshtein; Rod D. Roscoe – Grantee Submission, 2025
Broadly defined, academic language (AL) is a set of lexical-grammatical norms and registers commonly used in educational and academic discourse. Mastery of academic language in writing is an important aspect of writing instruction and assessment. The purpose of this study was to use Natural Language Processing (NLP) tools to examine the extent to…
Descriptors: Academic Language, Natural Language Processing, Grammar, Vocabulary Skills
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Xiaohong Liu; Baoxin Guo; Wei He; Xiaoyong Hu – Journal of Educational Computing Research, 2025
Generative artificial intelligence (GenAI) has significant potential for educational innovation, although its impact on students' learning outcomes remains controversial. This study aimed to examine the impact of GenAI on the learning outcomes of K-12 and higher education students, and explore the moderating factors influencing this impact. A…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Tobias Wyrwich; Marcus Kubsch; Hendrik Drachsler; Knut Neumann – Physical Review Physics Education Research, 2025
Students struggle to acquire the needed energy understanding to meaningfully participate in the energy discourse about socially relevant topics, such as energy transformation or climate change. Identifying students on differing learning trajectories, as well as differences in knowledge used, is essential to help students achieve the needed energy…
Descriptors: Learning Processes, Physics, Energy, Science Instruction
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Antonio Vivone; Dominik Rumlich; Andreas Lehmann-Wermser – Learning: Research and Practice, 2025
This research addresses lexical deficits among EFL learners by investigating the pedagogical potential of vocal training with authentic pop songs for multi-word unit acquisition. Drawing on cognitive neuroscience, the study builds on evidence that music enhances brain plasticity and that musical and linguistic syntax share neural processing…
Descriptors: Music Education, Singing, Brain Hemisphere Functions, Syntax
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Xuefan Li; Tingsong Li; Minjuan Wang; Sining Tao; Xiaoxu Zhou; Xiaoqing Wei; Naiqing Guan – IEEE Transactions on Learning Technologies, 2025
With the rapid advancement of generative artificial intelligence (GAI), its application in educational settings has increasingly become a focal point, particularly in enhancing students' analytical capabilities. This study examines the effectiveness of the ChatGPT prompt framework in improving text analysis skills among students, specifically…
Descriptors: Artificial Intelligence, Technology Uses in Education, High School Students, Foreign Countries
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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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