Related papers: Exploring gender differences in the Force Concept …
Alessandro Strumia recently published a survey of gender differences in publications and citations in high-energy physics (HEP). In addition to providing full access to the data, code, and methodology, Strumia (2020) systematically…
There has been a significant amount of debate around gender differences in intellectual functioning, however, most of this research concerns typically developing populations and lacks research into atypically developing populations and…
Generative Artificial Intelligence (GenAI) is transforming how firms create, process, and apply knowledge, yet little is known about the heterogeneity of its productivity effects across users. We report results from a randomized controlled…
The rising demand for higher education has led universities to offer courses in multiple formats, including Intensive Instruction Courses (IICs), to meet the needs of a diverse student body. While active teaching methods improve physics…
The physics community explores and explains the physical world through a blend of theoretical and experimental studies. The future of physics as a discipline depends on training of students in both the theoretical and experimental aspects…
This study investigates perceptions and use of generative artificial intelligence (GenAI) tools among students and faculty in statistics and data science at a historically Black college or university. Survey data from 119 valid student…
In this study, headcounts of all personnel in Nobel Prize-winning labs were collected and sorted by gender. These results are used to determine gender representation of graduate students in elite institutions on the pipeline towards higher…
The research presented in this thesis was motivated by the need to improve introductory physics courses. Introductory physics courses are generally the first courses in which students learn to create models to solve complex problems.…
Class-level evaluation can conceal substantial performance disparities across subconcepts within the same class, causing models that perform well on average to fail on specific subpopulations. Prior work has shown that common evaluation…
Traditional federated learning (FL) methods often rely on fixed weighting for parameter aggregation, neglecting the mutual influence by others. Hence, their effectiveness in heterogeneous data contexts is limited. To address this problem,…
Many studies demonstrate that there is still a significant gender bias, especially at higher career levels, in many areas including science, technology, engineering, and mathematics (STEM). We investigated field-dependent, gender-specific…
Implementation of cognitive apprenticeship in an introductory physics lab group problem solving exercise may be mitigated by epistemic views toward physics of non-physics science majors. Quantitative pre-post data of the Force Concept…
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 receive an A or B or students likely to receive a grade of C,…
Name-based gender classification has enabled hundreds of otherwise infeasible scientific studies of gender. Yet, the lack of standardization, proliferation of ad hoc methods, reliance on paid services, understudied limitations, and…
Deep learning methods have greatly increased the accuracy of face recognition, but an old problem still persists: accuracy is usually higher for men than women. It is often speculated that lower accuracy for women is caused by…
Diversity has an important, multifaceted role in the success of education. I have used a corpus analysis of the first ten years of Physical Review Physics Education Research to investigate the diversity, broadly defined, of physics…
Despite more than a decade of reform efforts, students continue to experience difficulty understanding and applying statistical concepts. The predominant focus of reform has been on content, pedagogy, technology and assessment, with little…
This paper studies change-points in human brain functional connectivity (FC) and seeks patterns that are common across multiple subjects under identical external stimulus. FC relates to the similarity of fMRI responses across different…
The lack of diversity in physics remains a persistent worldwide problem. Despite being a quantitative discipline which relies on measurements to construct and validate hypotheses, there remains a paucity of data on both demographics and…
Influence functions (IFs) elucidate how training data changes model behavior. However, the increasing size and non-convexity in large-scale models make IFs inaccurate. We suspect that the fragility comes from the first-order approximation…