Bulletin of the American Physical Society
APS April Meeting 2019
Volume 64, Number 3
Saturday–Tuesday, April 13–16, 2019; Denver, Colorado
Session H07: Focused Collection: Quantitative Methods in Physics Education ResearchEducation Invited
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Sponsoring Units: GPER FEd Chair: John Aiken, University of Oslo Room: Sheraton Governor's Square 16 |
Sunday, April 14, 2019 10:45AM - 11:21AM |
H07.00001: Missing data and bias in physics education research: A case for using multiple imputation Invited Speaker: Jayson Micheal Nissen Physics education researchers (PER) commonly use complete-case analysis to address missing data. For complete-case analysis, researchers discard all data from any student who is missing any data. Despite its frequent use, no PER article we reviewed that used complete-case analysis provided evidence that the data met the assumption of missing completely at random (MCAR) necessary to ensure accurate results. Not meeting this assumption raises the possibility that prior studies have reported biased results with inflated gains that may obscure differences across courses. To test this possibility, we compared the accuracy of complete-case analysis and multiple imputation (MI) using simulated data. We simulated the data based on prior studies to have students who earned higher grades be more likely to participate so that the data were missing at random (MAR). PER studies seldom use MI, but MI uses all available data, has less stringent assumptions, and is more accurate and more statistically powerful than complete-case analysis. Results indicated that complete-case analysis introduced more bias than MI and this bias was large enough to obscure differences between student populations or between courses. We recommend that the PER community adopt the use of MI for handling missing data to improve the accuracy in research studies. |
Sunday, April 14, 2019 11:21AM - 11:57AM |
H07.00002: Two-phase study examining perspectives and use of quantitative methods in physics education research Invited Speaker: Alexis V Knaub We conducted a two-phase study to identify and understand issues within quantitative physics education research (PER). Based on a focus group and interviews with experts in quantitative PER during Phase 1, our plan for Phase 2 entailed examining 72 peer-reviewed manuscripts that used at least one of four conceptual or attitudinal assessments. During Phase 2, we coded manuscripts on whether they included sample descriptions, limitations, and how conclusions were reported. We also examined the data to see if there are any differences in reporting between earlier and more recent times. During this talk, we report our key findings as well as propose some questions to consider regarding how research is reported.
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Sunday, April 14, 2019 11:57AM - 12:33PM |
H07.00003: Mapping students' attitudes and identities without imposing a priori demographic categories: A quantitative study using topological data analysis Invited Speaker: Jacqueline Doyle We describe our use of an innovative analytic technique adapted for use with student educational data for the first time: topological data analysis via the Mapper algorithm. In this approach, students are clustered based on their similarity and a filter which partitions them into subsamples for iterative clustering. This results in a two-dimensional representation of a higher space showing both how students cluster together and how those clusters are related to each other. By using a variety of attitudinal constructs to inform the process, we limit the a priori categorization of students and can instead group students independently of demographic information such as race/ethnicity, gender, sexuality, and disability status, and produce new ways of describing students based on these emergent groupings. We outline the requirements for using Mapper, describe the steps to implement it, and demonstrate an example mapping of student data. Using a clustering algorithm like Mapper opens new avenues for discussion and interpretation of student attributes in both current and future work on student identity, how students navigate STEM programs, and normative cultures in STEM education by creating new emergent categories and describing how those categories are related to each other. |
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