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Force Concept Inventory14
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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
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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
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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
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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
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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
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
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Aiken, John M.; De Bin, Riccardo; Lewandowski, H. J.; Caballero, Marcos D. – Physical Review Physics Education Research, 2021
Across the field of education research there has been an increased focus on the development, critique, and evaluation of statistical methods and data usage due to recently created, very large datasets and machine learning techniques. In physics education research (PER), this increased focus has recently been shown through the 2019 Physical Review…
Descriptors: Physics, Science Education, Educational Research, Statistical Analysis
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Eaton, Philip – Physical Review Physics Education Research, 2021
A performance gap between the genders has been observed on the Force Concept Inventory (FCI) almost since its introduction. Many studies have sought to characterize this gender gap, however, few have tested the consistency of the factor structure across the genders. This study fills in this gap by offering the first piece of evidence that the…
Descriptors: Error of Measurement, Factor Structure, Gender Differences, Achievement Gap
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Van Dusen, Ben; Nissen, Jayson – Physical Review Physics Education Research, 2019
Physics education researchers (PER) often analyze student data with single-level regression models (e.g., linear and logistic regression). However, education datasets can have hierarchical structures, such as students nested within courses, that single-level models fail to account for. The improper use of single-level models to analyze…
Descriptors: Physics, Science Education, Educational Research, Hierarchical Linear Modeling
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Li, Qiuye; Xu, Shaorui; Chen, Yilin; Lu, Chuting; Zhou, Shaona – Physical Review Physics Education Research, 2022
In science education, it is vital for teachers to consider students' academic and emotional needs. Teachers' prediction of students' learning states has been commonly regarded as an indicator to measure that competence to understand students. This study aimed to explore the outcome and the process of prediction to reflect teachers' pedagogical…
Descriptors: Eye Movements, Attention Control, Preservice Teachers, Prediction
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Knaub, Alexis V.; Aiken, John M.; Ding, Lin – Physical Review Physics Education Research, 2019
While other fields such as statistics and education have examined various issues with quantitative work, few studies in physics education research (PER) have done so. We conducted a two-phase study to identify and to understand the extent of these issues in quantitative PER. During phase 1, we conducted a focus group of three experts in this area,…
Descriptors: Physics, Educational Research, Research Methodology, Science Education
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Khayi, Nisrine Ait; Rus, Vasile – International Educational Data Mining Society, 2019
In this paper, we applied a number of clustering algorithms on pretest data collected from 264 high-school students. Students took the pre-test at the beginning of a 5-week experiment in which they interacted with an intelligent tutoring system. The primary goal of this work is to identify clusters of students exhibiting similar knowledge…
Descriptors: High School Students, Cluster Grouping, Prior Learning, Intelligent Tutoring Systems
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Al-Rsa'i, Mohammad S.; Khoshman, Jebreel M.; Abu Tayeh, Khalid – Journal of Turkish Science Education, 2020
The objective of this study was to investigate the physics student-teachers misconceptions in force and motion concepts in Jordanian universities by using the Force Concept Inventory (FCI) test and to identify the cause of misconceptions related to these concepts. Also, the FCI has been used to detect whether misconceptions vary according to…
Descriptors: Preservice Teachers, Undergraduate Students, Late Adolescents, Science Education
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Henderson, J. Bryan – Harvard Educational Review, 2019
Peer Instruction, a pedagogy utilizing handheld classroom response technology to promote student discussion, is one of the most popular research-based instructional practices in STEM education. Yet, few studies have shed theoretical light on how and why Peer Instruction is effective. In this article, J. Bryan Henderson explores the Peer…
Descriptors: Active Learning, Peer Teaching, Learning Activities, Learning Theories