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Results #1-#10 of 100+
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1.
Using machine learning to identify the most at-risk students in physics classes
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PER Literature
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J. Yang, S. DeVore, D. Hewagallage, P. Miller, Q. Ryan, and J. Stewart, Phys. Rev. Phys. Educ. Res.,
16
(2), 020130 (2020).
Machine learning algorithms have recently been used to predict students’ performance in an introductory physics class. The prediction model classified students as those likely to…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020130
2.
Network positions in active learning environments in physics
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A. Traxler, T. Suda, E. Brewe, and K. Commeford, Phys. Rev. Phys. Educ. Res.,
16
(2), 020129 (2020).
This study uses positional analysis to describe the student interaction networks in four research-based introductory physics curricula. Positional analysis is a technique for…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020129
3.
Grades, grade component weighting, and demographic disparities in introductory physics
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A. Simmons and A. Heckler, Phys. Rev. Phys. Educ. Res.,
16
(2), 020125 (2020).
Two set of studies were conducted to better understand grades and grading practices in physics courses, and how these might influence demographic representational disparities in…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020125
4.
Detecting the influence of item chaining on student responses to the Force Concept Inventory and the Force and Motion Conceptual Evaluation
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P. Eaton, B. Frank, and S. Willoughby, Phys. Rev. Phys. Educ. Res.,
16
(2), 020122 (2020).
Items that are chained, or blocked, together appear on many of the conceptual assessments utilized for physics education research. However, when items are chained together there is…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020122
5.
Development of a multiple-choice problem-solving categorization test for assessment of student knowledge structure
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Q. Chen, G. Zhu, Q. Liu, J. Han, Z. Fu, and L. Bao, Phys. Rev. Phys. Educ. Res.,
16
(2), 020120 (2020).
Problem-solving categorization tasks have been well studied and used as an effective tool for assessment of student knowledge structure. In this study, a traditional free-response…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020120
6.
Using virtual reality in electrostatics instruction: The impact of training
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C. Porter, J. Smith, E. Stagar, A. Simmons, M. Nieberding, C. Orban, J. Brown, and A. Ayers, Phys. Rev. Phys. Educ. Res.,
16
(2), 020119 (2020).
Recent years have seen a resurgence of interest in using virtual reality (VR) technology to benefit instruction, especially in physics and related subjects. As VR devices improve and…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020119
7.
Relative impacts of different grade scales on student success in introductory physics
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D. Webb, C. Paul, and M. Chessey, Phys. Rev. Phys. Educ. Res.,
16
(2), 020114 (2020).
In deciding on a student’s grade in a class, an instructor generally needs to combine many individual grading judgments into one overall judgment. Two relatively common numerical…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020114
8.
Designing upper-division thermal physics assessment items informed by faculty perspectives of key content coverage
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K. Rainey, M. Vignal, and B. Wilcox, Phys. Rev. Phys. Educ. Res.,
16
(2), 020113 (2020).
Though several conceptual inventories have been developed for thermal physics, none target upper-division material and all focus specifically on thermodynamics without including…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020113
9.
Development and validation of the moon phases concept inventory for middle school
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P. Chastenay and M. Riopel, Phys. Rev. Phys. Educ. Res.,
16
(2), 020107 (2020).
We present the development and validation of a new assessment tool, the Moon Phases Concept Inventory for Middle School (MPCI-MS), a concept inventory about the phases of the moon…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020107
10.
Demographics of physics education research
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S. Kanim and X. Cid, Phys. Rev. Phys. Educ. Res.,
16
(2), 020106 (2020).
Is physics education research based on a representative sample of students? To answer this question we skimmed physics education research papers from three journals for the years…
https://doi.org/10.1103/PhysRevPhysEducRes.16.020106
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Results #1-#10 of 100+
