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  1. Current structures of STEM graduate programs raise questions about addressing graduates’ interest in multiple career paths, and how programs prepare graduates for positions increasingly available in varied occupations. This problem is addressed through an innovative doctoral program in engineering, Pathways to Entrepreneurship (PAtENT), which works to develop a scalable alternative student-centered framework. This research explores how this program responds to calls for graduate STEM education to address changes in science and engineering, the nature of the workforce, career goals, and how program components build an entrepreneurial mindset. A mixed-methods design includes a curriculum analysis showing alignment of program components to recommendations for Ph.D. STEM programs from the National Academy of Sciences, Engineering, and Medicine. Direct measures include surveys and interviews developed for current doctoral students and faculty to describe students’ and faculty perspectives about program components, particularly entrepreneurship and the patent process. The curriculum analysis shows strong alignment of the PAtENT program components and activities to the ten elements of the National Academies’ recommendations. A survey of graduate students in engineering, computing, and business show strong measures in engineering and entrepreneurial self-efficacy. Interviews of program participants and faculty demonstrate strong interest in patents and developing entrepreneurship. This innovative program in engineering focusing on obtaining a patent as a capstone shows potential to reform doctoral studies, so candidates are prepared not only for academic careers but a range of industry and government work environments. This work will lead to development of a model for other graduate STEM programs. 
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    Free, publicly-accessible full text available December 31, 2025
  2. Black women remain severely underrepresented in computing despite ongoing efforts to diversify the field. Given that Black women exist at the intersection of both racial and gendered identities, tailored approaches are necessary to address the unique barriers Black women face in computing. However, it is difficult to quantitatively evaluate the efficacy of interventions designed to retain Black women in computing, since samples of computing students typically contain too few Black women for robust statistical analysis. Using about a decade of student survey responses from an National Science Foundation–funded Broadening Participation in Computing alliance, we use regression analyses to quantitatively examine the connection between different types of interventions and Black women’s intentions to persist in computing and how this compares to other students (specifically, Black men, white women, and white men). This comparison allows us to quantitatively explore how Black women’s needs are both distinct from—and similar to—other students. We find that career awareness and faculty mentorship are the two interventions that have a statistically significant, positive correlation with Black women’s computing persistence intentions. No evidence was found that increasing confidence or developing skills/knowledge was correlated with Black women’s computing persistence intentions, which we posit is because Black women must be highly committed and confident to pursue computing in college. Last, our results suggest that many efforts to increase the number of women in computing are focused on meeting the needs of white women. While further analyses are needed to fully understand the impact of complex intersectional identities in computing, this large-scale quantitative analysis contributes to our understanding of the nuances of Black women’s needs in computing.

     
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    Free, publicly-accessible full text available June 30, 2025
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  5. This full paper presents the Collaborative Active Learning and Inclusiveness (CALI) inventory, and an analytical model using the CALI inventory, demographic data, mindset surveys, and knowledge mastery assessment, to explore relationships between classroom climate and student experiences. The CALI inventory enables the investigation of the impact of the student experience in an active learning classroom by distinguishing the factors that characterize the structure, social learning, and inclusive practices. The Structure Index includes components related to course setup, organization, assessment, grading, and communications. The Sociality Index includes components related to opportunities for students to interact with each other. The Inclusiveness Index includes components related to how the instructor communicates a sense of belonging to the students through a growth mindset and inclusive policies and practices. A CS Mindset Instrument was developed based on research that measured students' self-efficacy by evaluating the extent of variation in their self-perceived ability to accomplish a task, sense of belonging in computing, and professional identity development. Demographic data is collected that allows for an analysis using an intersectional lens to acknowledge the complexity of social and cultural contexts. The knowledge and mastery assessments capture changes in competency through pre-post mastery quizzes. The combination of CALI with other instruments, including those that characterize student mindset, identity, and levels of mastery, enables investigation of how various practices of inclusive and collaborative active learning have differential effects on students with different identities in computer science. 
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