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Purwoko Haryadi Santoso; Bayu Setiaji; Wahyudi; Johan Syahbrudin; Syamsul Bahri; Fathurrahman; A. Suci Rizky Ananda; Yusuf Sodhiqin – Physical Review Physics Education Research, 2024
The Force Concept Inventory (FCI) is one of the research-based assessments established by the physics education research community to measure students' understanding of Newtonian mechanics. Former works have often recorded the notion of gendered mean FCI scores favoring male students notably in the North American (NA) based studies. Nevertheless,…
Descriptors: Gender Differences, Physics, Science Instruction, Science Tests
Vy Le; Jayson M. Nissen; Xiuxiu Tang; Yuxiao Zhang; Amirreza Mehrabi; Jason W. Morphew; Hua Hua Chang; Ben Van Dusen – Physical Review Physics Education Research, 2025
In physics education research, instructors and researchers often use research-based assessments (RBAs) to assess students' skills and knowledge. In this paper, we support the development of a mechanics cognitive diagnostic to test and implement effective and equitable pedagogies for physics instruction. Adaptive assessments using cognitive…
Descriptors: Physics, Science Education, Scientific Concepts, Diagnostic Tests
Bahtaji, Michael Allan A. – Journal of Baltic Science Education, 2023
Exploring students' physics conceptions, science engagement and misconceptions in physics together with their association to certain variables (gender, educational background, and program of study) are essential in improving physics teaching and learning. However, few studies have been conducted to explore these three measures and almost none…
Descriptors: Physics, Science Education, Scientific Concepts, Misconceptions
Wheatley, Christopher; Wells, James; Pritchard, David E.; Stewart, John – Physical Review Physics Education Research, 2022
The Force Concept Inventory (FCI) is a popular multiple-choice instrument used to measure a student's conceptual understanding of Newtonian mechanics. Recently, a network analytic technique called module analysis has been used to identify responses to the FCI and other conceptual instruments that are preferentially selected together by students;…
Descriptors: Physics, Science Instruction, Concept Formation, Scientific Concepts
Fabian Kieser; Peter Wulff; Jochen Kuhn; Stefan Küchemann – Physical Review Physics Education Research, 2023
Generative AI technologies such as large language models show novel potential to enhance educational research. For example, generative large language models were shown to be capable of solving quantitative reasoning tasks in physics and concept tests such as the Force Concept Inventory (FCI). Given the importance of such concept inventories for…
Descriptors: Physics, Science Instruction, Artificial Intelligence, Computer Software
Jannis Weber; Thomas Wilhelm – Physical Review Physics Education Research, 2024
Students experience many difficulties learning the fundamental relationships in Newtonian mechanics, partly due to preexisting mental models that originate from their everyday lives. These preconceptions often persist even after instruction in mechanics and lead to a supposed incompatibility between physics lessons in school and personal…
Descriptors: Physics, Science Instruction, Scientific Concepts, Mechanics (Physics)
Lan Yang; Leheng Huang; Xianqiu Wu; Jianwen Xiong; Lei Bao; Yang Xiao – Physical Review Physics Education Research, 2024
In physics education, a number of studies have developed assessments of teachers' knowledge of student understanding (KSU) of specific physics concepts with modified versions of existing concept inventories, in which teachers were asked to predict the popular incorrect answers from students. The results provide useful but indirect information to…
Descriptors: Preservice Teachers, Knowledge Level, Science Education, Scientific Concepts
Yasuda, Jun-ichiro; Hull, Michael M.; Mae, Naohiro – Physical Review Physics Education Research, 2023
We aim to graphically analyze the depth of conceptual understanding behind the Force Concept Inventory (FCI) responses of students, focusing on three questions (questions 1, 15, and 28). In our study, we created and implemented subquestions to clarify and quantify the students' reasoning steps in reaching their responses to the original FCI…
Descriptors: Scientific Concepts, Concept Formation, Misconceptions, Visual Aids
Salima Aldazharova; Gulnara Issayeva; Samat Maxutov; Nuri Balta – Contemporary Educational Technology, 2024
This study investigates the performance of GPT-4, an advanced AI model developed by OpenAI, on the force concept inventory (FCI) to evaluate its accuracy, reasoning patterns, and the occurrence of false positives and false negatives. GPT-4 was tasked with answering the FCI questions across multiple sessions. Key findings include GPT-4's…
Descriptors: Physics, Science Tests, Artificial Intelligence, Problem Solving
Gibin Raju; Paul Feldkamp; Whitney Gaskins – Journal of STEM Education: Innovations and Research, 2024
Enrollment in high school physics across the United States of America is notably lower than in other scientific disciplines. Given that physics serves as a prerequisite for admission into many STEM (Science, Technology, Engineering and Mathematics) degree programs, the lack of completion of this course at the high school level can significantly…
Descriptors: High School Students, Student Attitudes, Academic Persistence, Summer Programs
Wells, James; Henderson, Rachel; Stewart, John; Stewart, Gay; Yang, Jie; Traxler, Adrienne – Physical Review Physics Education Research, 2019
Module analysis for multiple-choice responses (MAMCR) was applied to a large sample of Force Concept Inventory (FCI) pretest and post-test responses (N[subscript pre] = 4509 and N[subscript post] = 4716) to replicate the results of the original MAMCR study and to understand the origins of the gender differences reported in a previous study of this…
Descriptors: Physics, Misconceptions, Science Tests, Scientific Concepts
Shoji, Yoshihiko; Munejiri, Shuji; Kaga, Eiko – Physical Review Physics Education Research, 2021
In this study, we evaluate the validity of question 29 (Q.29) in the Force Concept Inventory (FCI), which requires an understanding of atmospheric pressure. At least in some Japanese physics classes, the rate of the correct answer to Q.29 is reduced between the pretest and post-test. To examine this deterioration of a student's response, we…
Descriptors: Science Tests, Physics, Test Validity, Pretests Posttests
Achmad Samsudin; Aldi Zulfikar; Duden Saepuzaman; Andi Suhandi; Adam Hadiana Aminudin; Supriyadi Supriyadi; Bayram Costu – Journal of Turkish Science Education, 2024
This study aims to reconstruct Grade 11 students' misconceptions about force through the Conceptual Change Model (CCM) making use of Predict, Discuss, Explain, Observe, Discuss, Explore, Explain (PDEODEE) tasks. This study was conducted using a mixedmethod approach. The participants in this study were 65 students (33 students in the experiment…
Descriptors: Scientific Concepts, Concept Formation, Misconceptions, Foreign Countries
Timothy K. Osborn – ProQuest LLC, 2024
Concept inventories are widely used in physics education research, yet numerous studies show that concept inventories measure dramatically different learning gains in different demographic groups. Prior studies show that the performance gaps between demographic groups are already present in their preinstruction responses, suggesting that the…
Descriptors: Science Education, College Science, Physics, College Students
Ferrarelli, Paola; Iocchi, Luca – Technology, Knowledge and Learning, 2021
Novel technology has been applied to improve students' learning abilities in different disciplines. The research in this field is still finding suitable methodologies, tools, and evaluation mechanisms to devise learning frameworks with high impact on students' performance. This article describes an instructional method to perform Newtonian physics…
Descriptors: Physics, Scientific Concepts, Programming, Robotics