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The percentage of women receiving bachelor’s degrees in physics (25%) in the U.S. lags well behind that of men, and women leave the major at higher rates. Achieving equity in physics will mean that women stay in physics at the same rates as men, but this will require changes in the culture and support structures. A strong sense of belonging can lead to higher retention rates so interventions meant to increase dimensions of physics identity (interest, recognition, performance, and competence) may increase persistence overall and increase women’s retention differentially. We describe our model in which mentorship, an understanding of career options (career conceptualization), and leadership are inputs into the development of these dimensions of physics identity. This paper includes preliminary results from a qualitative study that aims to better understand how career conceptualization, leadership, and mentorship contribute to the development of physics identity and belonging. We report results from a survey of 15 undergraduate physics students which was followed up by interviews with 5 of those students. The students were from 2 institutions: a small private liberal arts college in the midwest region of the U.S. and a large public university in the southeast region of the U.S. classified as a Hispanic-serving institution (HSI). With respect to mentorship, consistent with the existing literature, we found that it could provide critical support for students’ engagement in the physics community. Leadership experiences have not previously been positioned as an important input into identity, yet we found that they helped women in physics feel more confident, contributing to their recognition of themselves as physics people. While the data on how career conceptualization contributed to the building of identity is limited, there are some connections to recognition and competence, and it will be an interesting avenue of future exploration. Published by the American Physical Society2024 

Abstract In the United States, the Next Generation Science Standards advocate for the integration of computational thinking (CT) as a science and engineering practice. Additionally, there is agreement among some educational researchers that increasing opportunities for engaging in computational thinking can lend authenticity to classroom activities. This can be done through introducing CT principles, such as algorithms, abstractions, and automations, or through examining the tools used to conduct modern science, emphasizing CT in problem solving. This cross‐case analysis of nine high school biology teachers in the mid‐Atlantic region of the United States documents how they integrated CT into their curricula following a year‐long professional development (PD). The focus of the PD emphasized data practices in the science teachers' lessons, using Weintrop et al.'s definition of data practices. These are: (a) creation (generating data), (b) collection (gathering data), (c) manipulation (cleaning and organizing data), (d) visualization (graphically representing data), and (e) analysis (interpreting data). Additionally, within each data practice, teachers were asked to integrate at least one of five CT practices: (a) decomposition (breaking a complex problem into smaller parts), (b) pattern‐recognition (identifying recurring similarities in data practices), (c) algorithms (the creation and use of formulas to predict an output given a specific input), (d) abstraction (eliminating detail in order to generalize or see the “big picture”), and (e) automation (using computational tools to carry out specific procedures). Although the biology teachers integrated all CT practices across their lessons, they found it easier to integrate decomposition and pattern recognition while finding it more difficult to integrate abstraction, algorithmic thinking, and automation. Implications for designing professional development experiences are discussed.