Related papers: Using machine learning to understand physics gradu…
This work aims to understand how effective the typical admissions criteria used in physics are at identifying students who will complete the PhD. Through a multivariate statistical analysis of a sample that includes roughly one in eight…
Despite limiting access to applicants from underrepresented racial and ethnic groups, the practice of using hard or soft GRE cut-off scores in physics graduate program admissions is still a popular method for reducing the pool of…
One argument for keeping the physics GRE is that it can help applicants who might otherwise be missed in the admissions process stand out. In this work, we evaluate whether this claim is supported by physics graduate school admissions…
There are many factors that can influence the outcome for students in a mathematics PhD program: bachelor's GPA (BGPA), bachelor's major, GRE scores, gender, Under-Represented Minority (URM) status, institution tier, etc. Are these…
We use self-reported data from 2011--2014 and determine the academic profile of accepted students at physics graduate programs in the United States. We analyze the accepted students' grade point averages and physics Graduate Record…
Gaining recognition as a physics person by peers is an important contributor to undergraduate students' physics identity and their success in physics courses. Previous research has separately demonstrated that women perceive less…
An analysis of 1,955 physics graduate students from 19 PhD programs shows that undergraduate grade point average predicts graduate grades and PhD completion more effectively than GRE scores. Students' undergraduate GPA (UGPA) and GRE…
Rubric-based admissions are claimed to help make the graduate admissions process more equitable, possibly helping to address the historical and ongoing inequities in the U.S. physics graduate school admissions process that have often…
The Physics GRE is currently a required element of the graduate admissions process in nearly all U.S. astronomy programs; however, its predictive power and utility as a means of selecting "successful" applicants has never been examined. We…
Joining a research group is one of the most important events on a graduate student's path to becoming an independent physics researcher and earning a PhD. However, graduate students' perspectives on the experience of finding a research…
Graduate admissions have become increasingly competitive. This study highlights the need for a hybrid machine learning framework for graduate admission prediction, focusing on high-quality similar applicants and a recommendation system. The…
Student beliefs in introductory physics courses can influence their course outcomes and retention in STEM disciplines and future career aspirations. This study used survey data from 501 students in the first of two-semester algebra-based…
Gender representation in the physical sciences remains inequitable and continues to lag behind other fields. Even though there exists adequate documentation regarding programmatic postures and innovations, difficulties persist within the…
Physics education research has used quantitative modeling techniques to explore learning, affect, and other aspects of physics education. However, these studies have rarely examined the predictive output of the models, instead focusing on…
Students from statistically underrepresented minority (URM) groups and women earn a smaller fraction of undergraduate and graduate degrees in most physical sciences, particularly physics. This underrepresentation is also prevalent at the…
As systematic inequities in higher education and society have been brought to the forefront, graduate programs are interested in increasing the diversity of their applicants and enrollees. Yet, structures in place to evaluate applicants may…
Although different organizations have defined policies towards diversity in academia, many argue that minorities are still disadvantaged in university admissions due to biases. Extensive research has been conducted on detecting partiality…
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,…
This article addresses the challenge of validating the admission committee's decisions for undergraduate admissions. In recent years, the traditional review process has struggled to handle the overwhelmingly large amount of applicants'…
After completing their undergraduate studies, many computer science (CS) students apply for competitive graduate programs in North America. Their long-term goal is often to be hired by one of the big five tech companies or to become a…