Collaborative research: developing a causal map assessment tool for undergraduate career interest formation and decision-making

The National Science Foundation's Division of Undergraduate Education awarded Coastal Carolina University $131,916 under the STEM Education program (CFDA 47.076) to develop a Career Interests and Decisions Assessment (CIDA) tool for undergraduate physics students. The primary product is an innovative assessment instrument built around a causal map visualization format that captures how students' career interests develop throughout their undergraduate studies. The CIDA will document the influence of multiple factors on career pathway formation, including learning experiences (courses, research opportunities, student clubs), student beliefs and attitudes, awareness of career options, and evolving career interests. This graphical assessment tool is designed to generate rich, coherent narratives of student experiences that reveal why students choose physics as a major and how their interests in specialized subfields such as quantum technology, nuclear physics, and semiconductor physics evolve over time.

Beyond individual student narratives, the project will deliver secondary products including network analysis visualizations, comparative tables, and comprehensive reports intended for dissemination to physics departments and the broader research community. These aggregate analyses will identify patterns across multiple students' causal maps using mathematical and statistical techniques to provide actionable insights for educators and administrators seeking to improve pathways into physics careers of strategic national importance. The project runs from October 1, 2025, through September 30, 2028, and addresses the national priority of strengthening the physics workforce pipeline by enhancing understanding of undergraduate career decision-making processes.

Abstract

This project aims to develop a career interests and decisions assessment (cida) in the context of undergraduate physics education. In the united states, over 8000 students earn an undergraduate degree in physics each year. These students pursue a variety of careers in areas such as research, software development, engineering, and teaching. Many physics majors pursue careers in areas of strategic national importance, such as quantum technology, nuclear physics, semiconductor physics, and artificial intelligence. The project will investigate how students develop these specialized subfield interests and use those insights to help educators and administrators improve pathways into these crucial careers. The cida is built around a unique graphical format that we call a ?causal map assessment.? Visually similar to a concept or mind map, causal maps allow students to tell a rich, coherent, and visual story of their experiences both before and during college. Each map will reveal how various factors, including learning experiences (e.g., courses, research opportunities, student clubs, or interactions with peers), beliefs and attitudes (e.g., confidence in programming or a desire to do hands-on work), awareness of career options, and career interests, unfold over time. This data will help US understand why students initially choose to be physics majors and how their specific career interests take shape throughout their undergraduate studies. The power of causal maps will extend beyond individual stories. The analysis will combine many students? Maps to identify broader patterns using a set of mathematical and statistical techniques known as network analysis. The collective analysis will be used to generate visualizations, tables, and reports that are useful to other researchers and to physics departments, and to provide insights regarding national trends. The cida is intended to help physics departments increase students? Awareness of career options, increase access to positive influences and supports, and make improvements in response to negative influences. The design of the causal map assessment will be rooted in the constructs of social cognitive career theory (scct). Constructing their personal map using this new assessment tool will allow students to visually articulate the interplay between their past experiences, their beliefs about their capabilities (self-efficacy), their anticipated results (outcome expectations), their emerging interests, the goals they set, and the actions they take. The graphical format is designed to capture the dynamic and reciprocal nature of scct, enabling a deeper understanding of students? Career development process by revealing time ordering and causation in a way that is hard to elicit in an interview or likert-scale survey. This new assessment tool will therefore address longstanding limitations faced by researchers seeking to understand career interest development. Even a single map can be interpreted for meaningful insights, but this project will also treat causal maps as network data, which will open up the ability to aggregate and automate assessment and apply a wide range of network analysis techniques (e.g., centrality or motifs). Over three years, the project will conduct interviews and administer assessments with students from a broad range of institutions to thoroughly understand the rich array of factors influencing their interest formation; develop and test a user friendly online interface for the cida; gather evidence of validity and reliability; administer the cida to hundreds of students to collect a robust dataset; perform detailed qualitative analysis of individual causal maps; apply network analysis to identify patterns and make comparisons among causal maps; and automate the creation of graphics and tables for reports when analyzing groups of students (e.g., students in a specific undergraduate physics program). Ultimately, the outcomes of this work will not only extend research on career decision-making in physics but also provide powerful new tools for investigating complex decision processes in other stem fields. This project is supported by NSF's EDU core research (ECR) program. The ECR program emphasizes fundamental stem education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: stem workforce development, stem learning and stem learning environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.