Enacting inclusive science: Culturally responsive higher education practices in science, technology, engineering, mathematics, and medicine (STEMM).

Novel approaches in higher education are needed to reverse underrepresentation of racial/ethnic groups in science, technology, engineering, mathematics, and medicine (STEMM). Building on theoretical frameworks for practice in diverse learning environments, this study provides evidence for Inclusive Science as a conceptual model that reflects initiatives intended to diversify biomedical research training for undergraduates. Using multiple case study design and cross-case analysis, we analyzed data from 10 higher education sites that were awarded the Building Infrastructure Leading to Diversity (BUILD) grant funded by the National Institutes of Health (NIH). We identified the following dimensions of the Inclusive Science model: promoting participation of diverse researchers; introducing diversity innovations in science and research curriculum; improving campus climate for diversity; providing tangible institutional support; creating partnerships with diverse communities; and integrating students' social identities with science identity. We illustrate each dimension of the model with examples of campus practices across BUILD sites. While many may doubt that science can be responsive to diversity, the interventions developed by these campuses illustrate how colleges and universities can actively engage in culturally responsive practices in STEMM undergraduate training that integrate trainees' identities, knowledge of diverse communities, and create a greater awareness of the climate for diversity that affects student training and outcomes. Implications include culturally responsive strategies that many more higher education institutions can employ to support scientific career training for historically excluded groups.

Investigating the relationship between participation in the building infrastructure leading to diversity (BUILD) initiative and intent to pursue a science career: A cross-sectional analysis.

This paper presents an analysis of survey data to examine the association between supervised structured mentoring and students' intent to pursue a career in science. Data were collected from students in the 10 Building Infrastructure Leading to Diversity (BUILD) research training programs, developed through grants from the National Institutes of Health. Propensity score matching and multinomial logistic regression demonstrated that exposure to BUILD programs-meaning participation in undergraduate research, receipt of mentoring from a primary mentor, and/or participation as a funded scholar and/or associate of each BUILD site's training program-was associated with increased intent to pursue a science career. These findings have implications for STEM program evaluation and practice in higher education.

A meta-analysis approach for evaluating the effectiveness of complex multisite programs.

The National Institutes of Health (NIH) created the Building Infrastructure Leading to Diversity (BUILD) initiative to incentivize undergraduate institutions to create innovative approaches to increasing diversity in biomedical research, with the ultimate goal of diversifying the NIH-funded research enterprise. Initiatives such as BUILD involve designing and implementing programs at multiple sites that share common objectives. Evaluation of initiatives like this often includes statistical analyses that combine data across sites to estimate the program's impact on particular outcomes. Meta-analysis is a statistical technique for combining effect estimates from different studies to obtain a single overall effect estimate and to estimate heterogeneity across studies. However, it has not been commonly applied to evaluate the impact of a program across multiple different sites. In this chapter, we use the BUILD Scholar program-one component of the broader initiative-to demonstrate the application of meta-analysis to combine effect estimates from different sites of a multisite initiative. We analyze three student outcomes using a typical "single-stage" modeling approach and a meta-analysis approach. We show how a meta-analysis approach can provide more nuanced information about program impacts on student outcomes and thus can help support a robust evaluation.

Implementing case study design to evaluate diverse institutions and STEM education contexts: Lessons and key areas for systematic study.

This chapter highlights the important contributions of case study research to the evaluation of student-centered programs and broader STEM initiatives in higher education. We summarize the Diversity Program Consortium's case study evaluation of the Building Infrastructure Leading to Diversity (BUILD) initiative, funded by the National Institutes of Health (NIH), with aims to enhance diversity in the NIH-funded workforce. We describe lessons learned from the case study design used for the evaluation of BUILD that applies to administrators of STEM initiatives who are interested in case study methods and to evaluators who are familiar with case studies and tasked with program evaluation of a multisite STEM program. These lessons include practical considerations for logistics and the importance of clarifying the goals of the case study design within the larger program evaluation, fostering the continuation of knowledge within the evaluation team, and embedding trust building and collaboration throughout all stages of the case study.