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Lachlan McGinness; Peter Baumgartner – Physical Review Physics Education Research, 2025
This paper explores the potential of large language models to accurately extract and translate equations from typed student responses into a standard format. This is a useful task as standardized equations can be graded reliably using a computer algebra system or a satisfiability modulo theories solver. Therefore physics instructors interested in…
Descriptors: Artificial Intelligence, Computer Uses in Education, Physics, Grading
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Kaitlin Gili; Kyle Heuton; Astha Shah; David Hammer; Michael C. Hughes – Physical Review Physics Education Research, 2025
Advances in machine learning (ML) offer new possibilities for science education research. We report on early progress in the design of an ML-based tool to analyze students' mechanistic sensemaking, working from a coding scheme that is aligned with previous work in physics education research (PER) and that is amenable to recently developed ML…
Descriptors: Physics, Science Education, Educational Research, Artificial Intelligence
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Yavuz Dinc; Sarah Malone; Verena Ruf; Steffen Steinert; Stefan Küchemann; Jochen Kuhn – Physical Review Physics Education Research, 2025
Prior research has demonstrated that students' performance on physics test items can be accurately predicted using machine learning algorithms based on their gaze behavior. These gaze data are typically recorded during item completion and capture students' visual attention to both the verbal item stem and accompanying visual representations, such…
Descriptors: Artificial Intelligence, Computer Uses in Education, Eye Movements, Test Items
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Mhamed Ben Ouahi; Mohamed Droui; Elyazid Hida; Taoufik Hassouni; El Mehdi AL Ibrahmi – Knowledge Management & E-Learning, 2025
Science education, particularly physics, remains a priority for many countries, as their future economic prosperity is closely linked to student success in science and technology. Given the persistent challenges faced by teachers in stimulating students' interest in this discipline, the integration of innovative teaching methods has become…
Descriptors: Science Education, Physics, Student Attitudes, Middle School Students
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Nedim Slijepcevic; Ali Yaylali – Journal of Teaching and Learning, 2025
This mixed-methods study investigated the effectiveness of Generative AI (GenAI) powered intelligent tutoring systems (ITS) in undergraduate physics education, specifically comparing learning outcomes between students using Khanmigo (Khan Academy's AI tutor) and the Google search engine. The study involved 69 undergraduate students divided into…
Descriptors: Undergraduate Students, Science Education, Physics, Scientific Concepts
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Soojeong Jeong; Justin Rague; Kaylee Litson; David F. Feldon; M. Jeannette Lawler; Kenneth Plummer – Education and Information Technologies, 2025
DBL is a novel pedagogical approach intended to improve students' conditional knowledge and problem-solving skills by exposing them to a sequence of branching learning decisions. The DBL software provided students with ample opportunities to engage in the expert decision-making processes involved in complex problem-solving and to receive…
Descriptors: Decision Making, Learning Processes, Introductory Courses, Science Education