Eric Brewe

This study examines survey data from 2,129 undergraduate women at the 2015 and 2019 American Physical Society Conference for Undergraduate Women in Physics (CUWiP) in order to classify what led them to study physics. We use expectancy-value and self-efficacy theory to create a coding framework based on different types of value and efficacy expectations in order to group responses. We find that the most common attractions are social persuasion, which is due to pressure or persuasion from people around the students, and intrinsic value, which is related to the inherent value of engaging in physics.

We analyze the results of two surveys administered to a Faculty Online Learning Community teaching a common physics curriculum designed primarily for pre-service elementary teachers. We use Social Network Analysis to represent the faculty network and compare members' closeness, a measure of how closely connected a person is with every other person in their network, to their reported experience in the community. We find that participants' self-efficacy, as well as their teaching and sense of benefitting from the community, are predictors of their centrality in the network as measured by closeness with other participants.

Active learning is broadly shown to improve student outcomes as compared with traditional lecture, but more work must be done to distinguish outcomes between different types of active learning. We collected self-reported student social network data at early and late-semester times in a Peer Instruction classroom. The subsequent networks are modeled using exponential random graph models (ERGMs), which are a family of statistical models used with relational data, like social networks. We discuss preliminary findings using this method for a Peer Instruction class. The best-fit ERGM predicts long "chains" of student edges, such as might arise from students talking along rows in the lecture hall. ERGMs appear to be a promising method for quantifying network topology in active learning classrooms.

From industry to government to academia, attracting and retaining science, technology, engineering, and mathematics majors is recognized as a key element of the 21st century knowledge economy. The ability to retain students seems to be intimately tied with understanding their immersion into the academic and social system of an institution. For instance, it has been noted that insufficient interactions with peers can lead to a low commitment to the university and, ultimately, affect one's decision about whether to drop out. Since nearly half of first-time students who leave a university by the end of the freshman year never come back to college, the importance of understanding experiences in introductory courses as a means for improving students' persistence is particularly pronounced. We investigate students' experiences in introductory physics courses, focusing on their self-reported perception of the value of out-of-class collaborations. We find that, even though students consider the out-of-class collaborations to be important for success, it takes a relatively long time before they start practicing collaborative learning.

Over a ten-year period, physics graduation rates at Florida International University (FIU) increased by about 480% [1]. To shed light on this phenomenon we conducted an interview study of upper division physics students to learn about their experiences, successes, and challenges. We interviewed 10 students using a semi-structured interview protocol based on the student engagement and persistence work of Tinto and Nora [2, 3]. We then followed Marton's approach to phenomenography to code and analyze the recorded interviews. Phenomenography is defined as "a research method for mapping the qualitatively different ways in which people experience, conceptualize, perceive, and understand various aspects of, and phenomena in, the world around them" [4]. This pilot analysis describes the engagement and persistence of two physics majors at FIU. Findings suggest that working as a Learning Assistant, integration with a consistent peer group, and social support from fellow students promote physics majors' persistence.

We present the preliminary results of a study on student use of representations in problem solving within the Modeling Instruction Physics 2 course (MI-Phys2), which covers introductory electricity and magnetism (E&M). Representational competence is a critical skill needed for students to develop a sophisticated understanding of college science topics and to succeed in their science courses. In this study, approximately 70 students from the MI-Phys2 course were given a survey of 25 physics problem statements both pre- and post- instruction, over both Newtonian mechanics (NM) and E&M. For each problem statement, students were asked to select one or more representations the would use in that given situation. We analyze the survey results through network analysis (NA) in order to identify which students selected similar representations. We also compare the student networks for those students who had previously taken the Modeling Instruction Physics 1 course (MI-Phys1) and those students who had taken an alternative Physics 1 course.

Summer academic bridge programs often play a dual role of supporting students' academic and social integration in the transition from high school to college. Assessment of the impact of such programs tends to rely on self-reported student surveys and institutional records and often does not control for self-selection effects. Using multivariate-matching methods, this study examines the effect of a summer bridge engineering program on subsequent academic performance such as cumulative GPA. Controlling for selection effects, the analysis accounts for pre-college academic and demographic covariates and creates a matched control and treatment group. Within this well-controlled framework, we find no impact on an academic outcome, which resonates with other research findings. Viewed through the lens of Nora's student engagement model, we discuss social integration outcomes which can potentially assess indirect programmatic effects such as participation in a Learning Assistant Program and enrollment in reformed STEM classes.

Active-learning approaches to teaching introductory physics have been found to improve student performance and learning gains. We report on longitudinal investigations of student performance in upper level physics courses after having previously taken Modeling Instruction introductory physics courses at Florida International University. Student performance data were analyzed for academic years 2005-2014 in upper level courses including Modern Physics, Mechanics, Electromagnetism, and Quantum Mechanics. We compare how male and female students who took traditional or reformed Modeling Instruction introductory courses perform in these subsequent courses. We look for differential effects between men and women who had these two types of introductory experiences. The implications of this work for our understanding of the impacts of active-learning experiences will be discussed.

Previous analysis of common exam questions in introductory physics at Florida International University has revealed differences in the number and type of epistemic games played by students in their solutions. Separated by course format (lecture/lab, lecture/lab/recitation, or inquiry-based), student work also shows varying use of multiple representational tools. Here we examine representation use in more detail to establish a descriptive picture of representation use across multiple instructors and course formats. We then compare these profiles with the epistemic games played by students, asking whether the same epistemic game shows the same pattern of representational tools across course types. We find that patterns of representation use vary by course format, but there are generally not clear representational "signatures" to uniquely identify epistemic games.

This study considers the impact of instructor on the gender gap in students' scores on the Force Concept Inventory (FCI) in Modeling Instruction (MI) courses at Florida International University (FIU). Earlier work has shown that MI had increased FCI scores overall when compared to traditional lecture courses; however, the gap between male and female students' scores in the MI courses increased over the course of the semester. Student data were collected from 559 students at FIU, over 18 semesters, with 10 different instructors. General linear regression was used to determine the significance of the student gender and instructor factors in predicting a student's FCI score post-instruction and the fraction of variance explained by these factors. Effect sizes were then calculated from the difference in female students' gains from male students' gains and compared between instructors. Analysis showed an instructor-independent, medium effect favoring male students' scores on the FCI.