Session D43: Advancing Understanding of Physics Retention Using Quantitative Research Methods

Exploring Factors Influencing the Retention of Physics Majors

This talk examines the retention of physics majors at a two

moderately sized physics departments which struggle with

increasing the number of graduates. The two institutions have

undergraduate populations with substantially different levels of

high school preparation. Survival analysis identifies the point of

highest risk for two potential paths out of the major: leaving

college and changing majors. Substantial risk of losing majors

exists through the first two years of college. The results for

changing major while staying in college were very different

between the two institutions. Logistic regression is used to

explore the factors related to retention in general and through

the first two years of college. The factors most related to the

risk of leaving the major were different for changing to another

major and leaving college altogether. At the less selective

institution, math readiness is a crucial factor predicting

retention.   

More than the final grade: Analyzing multiple channels and levels of student data

Final course grades can predict retention to some extent, but a single grade cannot capture the important complexity of student achievement or the student experience. Indeed, richer data is needed to better inform us on how to improve our instruction, student learning, and the student experience. Over the course of several studies, we have collected five kinds of student data: 1) More detailed course performance data, including performance on individual assignments and individual exam items, 2) student survey data on psychological factors such as psychological stress and self-efficacy, 3) submission times of assignments and quizzes, and 4) data on scores and (when available) speed on standardized tests, and 5) data on gender, race and first-generation status. Using data from thousands of physics students, we report on complex associations and interactions among these dimensions of data and highlight how these results can challenge our assumptions of what grades measure, what we want them to measure, and to what extent traditional grading practices may be part of the systemic issues of inequity in demographic participation and performance in physics courses.   

Physics stands out when it comes to driving women out of the discipline and out of STEM entirely

The national six-year graduation rate in science, technology, engineering, and mathematics (STEM) is far lower than most college majors, and STEM degree completion rates for historically marginalized students (women, students of color, and first-generation students) are typically much lower than their privileged counterparts. This trend has motivated a substantial amount of quantitative and qualitative research on STEM persistence over the past few decades. Despite this, relatively little research has studied the problem of retention within individual STEM disciplines like physics. Indeed, the problem of retention in physics is perhaps more salient than in other disciplines as only 2% of STEM degrees awarded in the United States are in physics, and physics typically has the lowest rates of representation of marginalized students among STEM disciplines. For this talk, I will focus on the retention of women in physics in comparison to other STEM disciplines. I found that the one-year retention rate of women in physics was not only lower than all other STEM majors at a public research university but was the lowest of any major across all colleges. Similarly, the fraction of women leaving physics for non-STEM majors (as opposed to other STEM majors) was among the highest of all STEM disciplines. Data collected from women who left physics suggest that increased support (academic and otherwise), more positive interactions between women and their male peers and professors, and improved instruction in introductory weed-out courses would help to keep women in physics. To this end, I will discuss data showing how both evidence-based teaching practices and external support programs at this same university have improved the persistence of women in engineering and discuss related programs in physics that should be studied and replicated. I will also discuss the limits of working with institutional data and provide suggestions on how equity issues in retention should be studied within departments and universities to avoid over-simplification of the retention problem.   

Opportunities and Potential Pitfalls: Considerations when measuring student outcomes in physics learning environments

Quantitative metrics are of high interest for many wishing to understand how to better support students in physics learning spaces. Metrics cover a wide array of areas including assessment of physics knowledge, social interactions, experiences within the department, etc. as well as demographics (e.g., race, gender). Various metrics and methods have limitations as well as potential pitfalls that could produce inaccurate results. This talk will go over some common, less common, and new promising methods in quantitative physics education research, along with additional considerations before embarking on such work.   

Assessing the integration of mathematical and physical conceptual reasoning in introductory physics problem solving

The creation of new assessments has been a cornerstone of Physics Education Research (PER).  These research-based assessments operationalize the learning goals of physics education and continue to drive instructional innovations that improve student learning and academic success.  In this talk, I will discuss a past and current direction in physics problem-solving assessment: coherence between physical concepts and mathematics. I will present three novel assessments that measure students’ skills at detecting errors, finding conceptual shortcuts, and choosing to use calculations on qualitative questions.  These skills each indicate the integration of mathematical and physical reasoning.  I will share the results of a quasi-experimental teaching comparison where these assessments were instrumental in detecting the learning benefits of a course focused on developing mathematical sensemaking.  Finally, I will discuss potential connections between conceptual/mathematical coherence and physics students’ long-term success and retention in STEM.