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This project is an empirical research study using a resiliency-based framework to investigate the factors that contribute to American Indian and Alaska Native (AI-AN) success and achievement in STEM education and careers. The focus is on what makes people successful rather than what makes them fail. It was developed through a partnership between the American Indian Science and Engineering Society (AISES), the Office for Community Health (OCH) at the University of New Mexico (UNM), and Northwestern University. The aim of this research is to identify the role of culture, individual identity, epistemology and bi-cultural efficacy in this process. This information is particularly salient in the face of the continuing stagnation of AI-AN STEM graduation rates and the ongoing need for expansion and equity in the STEM pipeline that has been identified as a national priority (e.g. National Academy of Sciences, 2011). Our hypothesis is that AI-AN success in stem is influenced by dynamics of culture, epistemology and individual identity, with the role of bi-cultural efficacy being particularly significant. We are interested in knowing: (a) What factors positively influence AI-AN success in STEM?; (b) What role do the dynamics of culture, epistemology and individual identity play in AI-AN success in STEM and how are these dynamics played-out in individual experience?; and (c) Does bi-cultural efficacy play a role in this process, and if so, what is that role? This study has four specific research objectives: (1) To conduct an ethnographic study that will provide information to guide intervention efforts and investment of resources to support AI-AN students in STEM education by developing an understanding of factors associated with AI-AN STEM success. For example, the extent to which successful individuals develop a “STEM” identity, how this happens, how this process relates to an individual’s cultural identity and understanding of Native versus Western science, and the types of personal and cultural “assets” that successful individuals bring to bear on their educational and career pathways; (2) To leverage existing data on AI-AN through secondary analysis of a unique AISES archive to provide information to inform future AI-AN STEM interventions and funding, and to improve AISES’ capacity to capture longitudinal data related to AI-AN achievement in STEM; (3) To provide concrete opportunities for AI-AN scholars to obtain research experience to nurture concrete understanding of what it means to “do” science research as a career; and (4) To disseminate findings to AI-AN communities, policy makers, academic institutions, industry, the scientific community and to AISES members. Results of this study will expand understanding of AI-AN educational and professional outcomes in STEM, provide a roadmap for improving the efficacy of interventions intended to increase AI-AN participation and success in STEM, and indicate directions for future research.
This interdisciplinary project will partner researchers from Anthropology, Psychology and Economics/Public Health with AISES to contribute a unique perspective on Native participation in STEM. The proposed collaboration uses a mixed methods design, beginning with an ethnographic approach that will build on advances in knowledge from the extensive literature on deficits and barriers, and nascent research on epistemology, adding new empirical data. A conscious decision is being made to privilege voices of Native scholars whose experience is not well represented in mainstream perspectives or taken into consideration by policy makers. Adaptive project design through iterative data collection and analysis with synthesis and incorporation of findings from different components ongoing throughout the study will allow for dynamic inclusion of participant input. The study includes four separate but integrated research components: (1) 75 in-depth ethnographic interviews with 25 AI-AN STEM professionals and AISES members, conducted in three iterative sets of 25 each; (2) Three AI-AN undergraduate Student Research Scientists (SRS’s) from UNM will be mentored in the conduct of 36 peer interviews (12 each) with other AI-AN students; (3) Secondary analysis of unique AISES organizational archive with 35 years of information on more than 6000+ AI-AN involved in STEM; and (4) a preliminary survey will be conducted in year three of the project with 25 AISES members to validate measures of bi-cultural efficacy that contribute to AI-AN success in STEM. We will mentor Native scholars to develop protocols, collect and analyze data, present findings, and participate as members of the Research Team. A Project Advisory Board that includes national-level experts and scientists will provide guidance for research design, project evaluation, and dissemination of results. A Project Summit in Year #3 will disseminate project findings to a broad group of AISES stakeholders. This project will also structure a new role for AISES to play in the STEM community by leveraging the unique position of AISES as a national AI-AN STEM organization. Through this study, we will identify ways to enhance the capacity of AISES to generate improved and ongoing information on the AI-AN experience in STEM via the development of data collection protocols and data collection tools that can continue to be used for research in the future.
This research will reveal previously under-studied, poorly understood aspects of the AI-AN experience in STEM, using a non-deficit, resiliency-based, success-focused model. Results will inform understanding of how AI-AN individuals leverage personal and cultural assets in a way that embraces a congruency between Indigenous culture (Native science) and Western science as they achieve success in STEM. This information will contribute to the literature analyzing issues in AI-AN education and under-representation in STEM. And most importantly, this research may lay the foundation for increasing the proportion of AI-AN scientists. Factors that contribute to success and achievement of AI-AN in STEM are often unrecognized, underappreciated or poorly understood. The improved coherence of interventions that will result from better conceptualization of the strengths and needs of AI-AN students will provide a roadmap for developing best-practice and model-driven programming within universities, improve AI-AN educational outcomes in STEM, and in turn, contribute to improvements in AI-AN individual and community well-being. Better understanding of these issues, better allocation of resources and design of policies, more coherence to interventions, more focus on strengths and needs, and improvements in individual and community well-being will all contribute to increasing AI-AN participation in STEM. This information will provide a guide for targeting resources and interventions to improve educational and professional outcomes for AI-AN students in STEM. This, in turn, will increase AI-AN participation in STEM careers and career pathways with the expected indirect effect of reducing educational, career, and health disparities in AI-AN communities..