United States

The Conceptual Survey of Electricity and Magnetism (CSEM) is a multiple-choice survey that contains a variety of electricity and magnetism concepts at the level of introductory physics used to help inform instructors of student mastery of those concepts. Prior studies suggest that many concepts on the survey are challenging for introductory physics students and the average student scores after traditional instruction are low. The research presented here compares the performance of students in introductory, upper-level, and graduate-level physics courses on five CSEM questions to understand the cross-sectional evolution of student understanding of these concepts from the introductory to upper-level to graduate-level. We discuss five CSEM questions that remain challenging for many upper-level and graduate students.

AAPT SM 21

Evolution in student conceptual understanding of electricity and magnetism

upper division

electricity and magnetism

graduate

introductory

csem

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technical paper

Modified Module Analysis using partial correlations (MMA-P) has proven to be a productive method for studying conceptual inventories. MMA-P can be used to analyze large datasets by forming networks of responses then using community detection algorithms to identify sets of responses that are consistently selected together. MMA-P can be extended by using multilevel network analysis. A multilevel network was constructed with pretest and post-test Force Concept Inventory (FCI) responses from five different institutions using samples ranging from N=10,000 to N=200. Each layer of the multilevel network was represented by a network made from the application of MMA-P to data from each institution. Within each layer, MMA-P finds communities of popular responses. Network comparison methods were then used to understand the similarities and differences between the sets of nodes and communities in the networks. This provides insight into the generality of previously identified properties of the FCI between institutions.

Multilevel Module Analysis of the FCI

This talk examines the retention of physics majors at a moderately sized physics department which struggles with increasing the number of graduates using 20 years of graduation data. 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. Logistic regression is used to explore the factors related to retention in general and through the first two years of college. Decision trees, a method applied in machine learning, is used to quantify the thresholds of these variables important to evaluating risk.


Exploring Factors Influencing the Retention of Physics Majors

Research on self-efficacy -- or the confidence in one’s capability to perform a task -- has been shown to predict achievement and persistence in the sciences. Throughout a student’s experience in curricular and/or co-curricular activities, they may face threats to their self-efficacy. To investigate the threats or supports to students’ self-efficacy, we are using a mixed methods approach. This novel design creates a holistic narrative of which curricular and/or co-curricular activities are impacting a student’s self-efficacy as well as how and why these activities may be affecting their self-efficacy. We use a mixed methods approach to collect in-the-moment information about lived experiences. Quantitatively, we employ the Experience Sampling Method (ESM) using surveys of domain-specific self-efficacy. Qualitatively, we use daily reflections to investigate threats and supports toward students’ self-efficacy. Using an example, we will present the research design while focusing on building this conversation between the ESM and qualitative reflections.

Identifying Threats and Supports to Self-Efficacy Using Mixed Methods Research

Modeling is an important skill in experimental physics and thus a learning outcome of many laboratory classes. One promising approach to encourage modeling is to incorporate multiweek open-ended projects within lab courses. However, not much work has been done on assessing student engagement with modeling in actual courses. We present an analysis of projects from three upper-level university lab courses at different institutions where we investigate how the students engage with modeling and how this engagement differs depending on features of the projects. The projects in our dataset vary widely with different degrees of model construction. We observe correlations between features of the projects and the ways the students engage with modeling, which may have implications for how instructors guide students towards choosing certain types of projects.

Student Engagement with Modeling in Multiweek Open-Ended Lab Projects

Earning a bachelor's degree is expensive and time-consuming. Many undergraduate students pursue Advanced Placement (AP) courses in high school or transfer coursework from other degree-granting institutions. However, the effect of those transfer courses on the time it takes students to graduate (time-to-degree) is currently not well understood. In this work, we investigated how incoming transfer courses impact students’ time-to-degree. To do so, we explored how well a logistic regression model would predict whether a student graduated before or after 8 semesters, 10 semesters, and 12 semesters. When discerning time-to-degree, there are several other features that were also considered in addition to transfer status: students’ demographic information such as race/ethnicity, gender, first-generation status, and their academic background preparation as measured by their high school GPA and math placement scores. Here, we will discuss the findings of our model as well as the effects of data imputation on our results.

Investigating Impact of Transfer Credits on Time-to-Degree using Regression Models

Transfer students’ and two-year college (TYC) students’ experiences are understudied, but we know they can face unique challenges after transferring and can miss some of the positive aspects of their TYCs at their receiving institutions. We use narrative analysis or narrative inquiry to tell the story of one transfer student from a TYC to a four-year college (FYC) named Nicole. Nicole has social anxiety, but thrived in her relationships with peers and professors while at her TYC. Then she faced difficulties finding study groups and a sense of community belonging at her receiving institution. Pulling from a variety of data sources, including observational field notes, written journal reflections, and semi-structured interviews, we will describe the supporting characters or lack thereof and the aspects of the different settings that contributed to Nicole’s differing experiences at the two institutions.

Narrative Analysis of Two-Year College Transfer Student’s Experiences

Physics majors need context to improve their experiences with physics as a discipline and prepare them for a variety of impactful career paths. Yet, the majority of context-based physics learning comes from internships and research experiences that are not always available to all students. As part of the APS PIPELINE Network and Physics for Tomorrow initiatives, we examined students’ experiences with context-rich physics through internships, co-ops, and undergraduate research. We compared these with students’ perception of physics as it relates to their future career goals and career-relevant skills. Responses from 149 physics majors at 12 institutions were analyzed using descriptive quantitative methods for multiple select questions and emergent thematic qualitative approaches for open-ended questions. We offer considerations for the importance of context-rich physics experiences, as well as how to integrate these into lecture and lab coursework, so that context-based learning can become more accessible to all physics majors.

Preparing students for impactful careers through context-rich physics learning

In this talk, we qualitatively analyze physics majors’ identity development as they transfer from a community college to a four-year university. Students in the study attend a large, public four-year university in which a significant fraction of undergraduate physics majors are transfer students. Research participants had previously enrolled in a required 1-credit introduction to the physics major course designed to cultivate community and identity, as well as foster a broad set of physics-related skills. In one-on-one interviews, students discussed their academic and personal experiences before, during, and after their transition from community college to a four-year university. In this talk, we will discuss how their academic and personal experiences as well as their interactions with physics community members shaped their identity development as physics students. We then consider implications for building institutional supports for physics transfer students.

Research on Identity Development Among Physics Transfer Students

We analyse a session where high school students in a 2-day science camp were asked to explain the workings of a mercury barometer. The session was designed to provide students with opportunities to participate in the knowledge construction process. The pedagogy was inspired by literature on modelling practices and sense making in physics. Given that traditional classrooms in India (and elsewhere) are often dominated by the lecture format, it is important to investigate the tensions that arise when the students from a traditional physics classroom are asked to
engage with modeling and sensemaking. We analysed the video recording of the session to unpack these tensions and characterised them under four broad categories vis a vis: Instructor versus student agency; Answer-making versus sense-making; Qualitative reasoning versus mathematisation; and Substance versus process ontology. Our analysis shows how the flow of conversation was guided by the push and pull of these entangled tensions.

Unpacking tensions in a pedagogical transition from lectures to modelling

We report on an investigation in which we compare the conceptual performance of upper-level undergraduates and graduate students, who worked on two different validated Quantum Interactive Learning Tutorials (QuILTs). One of the QuILTs incorporates mathematical reasoning while focusing on helping students develop a good conceptual understanding of quantum optics using a Mach-Zehnder Interferometer with single photons and polarizers. Performance of students who engaged with this “hybrid” (integrated conceptual and quantitative) QuILT is compared with those who engaged with a conceptual QuILT focusing on the same topics without quantitative tools. Both QuILTs use a guided inquiry-based approach to learning and are based on research on student difficulties in learning these challenging concepts as well as a cognitive task analysis from an expert perspective. We find that the posttest performance on conceptual questions of physics graduate students who engaged with the hybrid QuILT was generally better than those who engaged with the conceptual QuILT. For undergraduate students, the results were mixed.

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