Eric Brewe

Academic institutions are increasingly adopting active learning methods to enhance educational outcomes. Using functional magnetic resonance imaging (fMRI), we investigated neurobiological differences between active learning and traditional lecture-based approaches in university physics education. Undergraduate students enrolled in an introductory physics course underwent an fMRI session before and after a 15-week semester. Coactivation pattern (CAP) analysis was used to examine the temporal dynamics of brain states across different cognitive contexts, including physics conceptual reasoning, physics knowledge retrieval, and rest. CAP results identified seven distinct brain states, with contributions from frontoparietal, somatomotor, and visuospatial networks. Among active learning students, physics learning was associated with increased engagement of a somatomotor network, supporting an embodied cognition framework, while lecture-based students demonstrated stronger engagement of a visuospatial network, consistent with observational learning. These findings suggest significant neural restructuring over a semester of physics learning, with different instructional approaches preferentially modulating distinct patterns of brain dynamics.

This study uses an initial attitudinal survey and a subsequent follow-up survey to assess which qualities are correlated with the persistence of women in physics. The initial survey was given to participants at the Conference for Undergraduate Women and Gender Minorities in Physics, and the follow-up survey was given years later, after they graduated; 478 matched surveys were used in this work. Using these surveys, we study how attitudes correlate with retention. First, we examine whether affective factors, mainly situated in identity theory, have any clear correlation with persistence in physics. Then, we study individual questions of the survey, such as a student’s interest in research specifically, to determine more fine-grained correlations with retention. Both of these were examined using analyses of variance (ANOVAs) with post hoc Tukey tests. From studying the overarching factors, we find that respondents who remained in physics after completing their bachelor’s degree reported higher interest than respondents who left physics at earlier points, with a medium effect size. We also find small evidence of associations between sense of belonging and correlation; respondents who leave physics before obtaining a bachelor’s degree tend to have a higher sense of belonging than other groups, while respondents who stay in physics until graduating, then leave for another science, technology, engineering, and mathematics field tend to have a lower sense of belonging. This association, however, shows a small effect size and should be examined more carefully to draw definitive conclusions. We find that identity, perceived recognition, performance competence, success mindset, and sense of community show no significant correlation with long-term persistence. When examining individual questions, we find that people who remain in physics tend to have a higher interest specifically in research, as well as career aspirations of going to graduate school and becoming a professor in physics.

This project aims to understand physics faculty responses to transitioning to online teaching during the COVID-19 pandemic. We surveyed 662 physics faculty from the United States following the Spring 2020 term; of these, 258 completed a follow-up survey after the Fall 2020 term. We used natural language processing to measure the sentiment scores of 364 Spring 2020 responses and another 134 Fall 2020 responses of physics faculty who completed an optional written prompt. Additionally, we determined the change in sentiment scores of the 100 individuals who responded to both surveys. These sentiment scores measured between -1 and 1 for completely negative and completely positive, respectively. Sentiment scores after Spring 2020 were slightly positive with a median value of 0.2347. The distribution of sentiment changes was approximately normally distributed with a mean centered near zero. Analysis suggests the average sentiment did not change from the initial to follow-up surveys. To identify major topics within the responses for both surveys, latent Dirichlet allocation analysis was applied to the data. The topic distribution for the initial survey is given as course modifications and technology, negative aspects of the transition -primarily with labs and cheating, exam and evaluation difficulties, and difficulties with student understanding. The topics were noticeably different in the follow-up survey with differences between Fall and Spring, cooperative learning strategies, strategies that worked in the remote space, and benefits of in -person labs.

Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students.
Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task.
No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity.
These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.

The vast majority of research involving active learning pedagogies uses passive lecture methods as a baseline. We propose to move beyond such comparisons to understand the mechanisms that make different active learning styles unique. Here, we use COPUS observations to record student and instructor activities in six known styles of active learning in physics, and use latent profile analysis to classify these observations. Latent profile analysis using two profiles successfully groups COPUS profiles into interactive lecturelike and other. Five latent profiles successfully sorts observations into interactive lecturelike, Modeling Instruction, ISLE labs, context-rich problems labs, and recitationlike or discussionlike. This analysis serves as a proof of concept, and suggests instructional differences across pedagogies that can be further investigated using this method.

Even though student-centered instruction leads to positive student outcomes, direct instruction methods are still prevalent. Multiple barriers prevent faculty from further adopting evidence-based student-centered practices and holistic approaches to faculty support are necessary to promote faculty change. The Collaborative for Institutionalizing Scientific Learning (CISL) is an HHMI-funded program to reform undergraduate science and mathematics education at a large Hispanic-Serving public research university. The program has established a Faculty Scholar support model to impact the number of science and mathematics faculty using evidence-based practices in their classrooms. Through this program, Scholars are selected to undertake a transformation of a course of their choice and conduct an assessment of the impact of the reform on students-while receiving multiple supports including summer salary, undergraduate Learning Assistants, professional development, course assessment and education research support, and opportunities to develop manuscripts on their course transformations. CISL has supported over 40 Faculty Scholars in the transformation of both introductory and upper division biology, chemistry, physics and mathematics courses. Faculty are motivated to transform a course due to factors related to their own experiences and beliefs, their students' needs, the course structure, and/or departmental elements. Quantitative analysis of the impact of the project on student success show that, overall, students in CISL-supported courses have higher passing rates compared to students in traditional classrooms. Survey and interviews of Faculty Scholars identified that the most valuable elements of the program were the personnel support from undergraduate Learning Assistants during reform implementation and guidance from the program's Assistant Director during design, implementation and evaluation. The CISL program provides an example of significant effort sustained over several years to systematically improve the quality and culture of undergraduate education in a large research-intensive Hispanic Serving Institution. The program has had an overall positive impact on the professional development of Faculty Scholars and led to an increase in the number of STEM courses implementing evidence-based teaching practices, thus, taking a step towards solidifying a culture of evidence-based instructional strategies in STEM departments. The online version contains supplementary material available at 10.1186/s40594-022-00353-z.

This study uses social network analysis and the classroom observation protocol for undergraduate STEM (COPUS) to characterize six research-based introductory physics curricula. Peer Instruction, Modeling Instruction, ISLE, SCALE-UP, Context-Rich Problems, and Tutorials in Introductory Physics were investigated. Students in each curriculum were given a survey at the beginning and end of term, asking them to self-identify peers with whom they had meaningful interactions in class. Every curriculum showed an increase in the average number of student connections from the beginning of term to the end of term, with the largest increase occurring in Modeling Instruction, SCALE-UP, and Context-Rich Problems. Modeling Instruction was the only curriculum with a drastic change in how tightly connected the student network was. Transitivity increased for all curricula except Peer Instruction. We also spent one week per research site in the middle of the term observing courses using COPUS. From these observations, the student COPUS profiles look nearly the same for Tutorials, ISLE recitations, and Context-Rich Problems discussion sections. This is likely due to the large resolution of activities that can be coded as "other group activity," suggesting the need for a more detailed observation instrument.

This study sought to describe the system of beliefs on gender, attitudes toward women, and wife beating, in young adults who live in Mysore, India. Furthermore, it identified structural sex differences in the interplay of values among these matters that can affect individual and community views toward domestic violence. Drawing from survey data gathered from 265 young adult Indian men and women, this study used network analysis to graph a correlation network of beliefs and attitudes toward domestic violence. Node, scale, and network structure descriptions allowed for comparisons among male and female participant responses. The findings support the assertion that there are sex differences among the system of beliefs toward wife beating among Indian young adults. Gender ideology, masculine role in relationships, and legal and social consequences of wife beating emerged as the most important values to focus on when addressing young men’s beliefs of domestic violence and attitudes toward women. In contrast, values influencing women’s perceptions of domestic violence are more complex and related to multiple beliefs about women’s power, family structure, and social and legal implications of domestic violence. The results highlight the importance of recognizing gender differences in the connectivity between gender and wife beating beliefs when designing interventions. There is a need for efforts to accurately target these values and attitudes to more effectively address gendered attitudes and beliefs about domestic violence in this population.

We surveyed a national sample of United States physics faculty about the COVID-19 transition to online learning. Most faculty had 1-2 weeks to prepare and no experience with teaching online. They relied on department peers to discuss approaches and used lecture adaptations such as video conferencing rather than new curricular elements. Their responses were empathetic to the students' situation, and 90% believed they were average or above at implementing online instruction. Faculty's preference for local resources and existing methods suggests that in a crisis, strong network ties will dominate as information sources, with consequences for professional development and instructional change.