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This is a report of a National Science Foundation-supported conference about integrating equity into whole school STEM reform. originally planned as an in-person conference in summer of 2020, it was moved to a virtual conference held in the spring of 2022. Researchers, policy-makers, and practitioners shared their visions of equity in STEM over the course of four days spread out over six weeks. The presentations and synthesis shared here set the stage for future empirical studies of equity in STEM education and whole-school reform. Findings from these presentations are primarily informal, as per our goal of providing concrete, practical findings for a broad audience of leaders, teachers, school staff and community partners, parents, and researchers.

STEM education programs are often formulated with a "hands-on activities" focus across a wide array of topics from robotics to rockets to ecology. Traditionally, the impact of these programs is based on surveys of youth on program-specific experiences or the youths’ interest and impressions of science in general. In this manuscript, we offer a new approach to analyzing science programming design and youth participant impact. The conceptual framework discussed here concentrates on the organization and analysis of common learning activities and instructional strategies. We establish instrument validity and reliability through an analysis of validity threats and pilot study results. We conclude by using this instrument in an example analysis of a STEM education program.

Participation on a robotics team affords students the opportunity to learn science and engineering skills in a competition-based environment. Mentors on these robotics teams play important roles in helping students acquire these skills. This study used an apprenticeship learning theory to examine how mentors on one high school robotics team contributed to students attaining the knowledge associated with designing and building a robot for competition. How active of a role did mentors play on their competition-based robotics team? How did mentors and students together handle the challenges they faced? The mentor-student interactions detailed in the research revealed an apprenticeship model where mentors played leadership roles reluctant to move beyond modeling tasks to students. The mentors’ roles bring into question if they were granting their students the full opportunities to develop skills associated with working on a robot. Despite these developmental concerns, the students on the team gradually took up simple tasks working side-by-side mentors, saw expert engineers model professional habits, and expressed being inspired while contributing to a winning team.

Aim/Purpose: In response to widespread efforts to increase the size and diversity of the biomedical-research workforce in the U.S., a large-scale qualitative study was conducted to examine current and former students’ training experiences in MD (Doctor of Medicine), PhD (Doctor of Philosophy), and MD-PhD dual-degree programs. In this paper, we aimed to describe the experiences of a subset of study participants who had dropped out their MD-PhD dual-degree training program, the reasons they entered the MD-PhD program, as well as their reasons for discontinuing their training for the MD-PhD. Background: To our knowledge, the U.S. has the longest history of MD-PhD dual-degree training programs dating back to the 1950s and produces the largest number of MD-PhD graduates in the world. Integrated dual-degree MD-PhD programs are offered at more than 90 medical schools in the U.S., and historically have included three phases – preclinical, PhD-research, and clinical training, all during medical-school training. On average, it takes eight years of training to complete requirements for the MD-PhD dual-degree. MD-PhD students have unique training experiences, different from MD-only or PhD-only students. Not all MD-PhD students complete their training, at a cost to funding agencies, schools, and students themselves. Methodology: We purposefully sampled from 97 U.S. schools with doctoral programs, posting advertisements for recruitment of participants who were engaged in or had completed PhD, MD, and MD-PhD training. Between 2011 and 2013, semi-structured, one-on-one phone interviews were conducted with 217 participants. Using a phenomenological approach and inductive, thematic analysis, we examined students’ reasons for entering the MD-PhD dual-degree program, when they decided to leave, and their reasons for leaving MD-PhD training. Contribution: Study findings offer new insights into MD-PhD students’ reasons for leaving the program, beyond what is known about program attrition based on retrospective analysis of existing national data, as little is known about students’ actual reasons for attrition. By more deeply exploring students’ reasons for attrition, programs can find ways to improve MD-PhD students’ training experiences and boost their retention in these dual-degree programs to completion, which will, in turn, foster expansion of the biomedical-research-workforce capacity. Findings: Seven participants in the larger study reported during their interview that they left their MD-PhD programs before finishing, and these were the only participants who reported leaving their doctoral training. At the time of interview, two participants had completed the MD and were academic-medicine faculty, four were completing medical school, and one dropped out of medicine to complete a PhD in Education. Participants reported enrolling in MD-PhD programs to work in both clinical practice and research. Very positive college research experiences, mentorship, and personal reasons also played important roles in participants’ decisions to pursue the dual MD-PhD degree. However, once in the program, positive mentorship and other opportunities that they experienced during or after college, which initially drew candidates to the program was found lacking. Four themes emerged as reasons for leaving the MD-PhD program: (1) declining interest in research, (2) isolation and lack of social integration during the different training phases, (3) suboptimal PhD-advising experiences, and (4) unforeseen obstacles to completing PhD research requirements, such as loss of funding. Recommendations for Practitioners: Though limited by a small sample size, findings highlight the need for better integrated institutional and programmatic supports for MD-PhD students, especially during PhD training. Recommendation for Researchers: Researchers should continue to explore if other programmatic aspects of MD-PhD training (other than challenges experienced during PhD training, as discussed in this paper) are particularly problematic and pose challenges to the successful completion of the program. Impact on Society: The MD-PhD workforce comprises a small, but highly trained cadre of physician-scientists with the expertise to conduct clinical and/or basic science research aimed at improving patient care and developing new diagnostic tools and therapies. Although MD-PhD graduates comprise a small proportion of all MD graduates in the U.S. and globally, about half of all MD-trained physician-scientists in the U.S. federally funded biomedical-research workforce are MD-PhD-trained physicians. Training is extensive and rigorous. Improving experiences during the PhD-training phase could help reduce MD-PhD program attrition, as attrition results in substantial financial cost to federal and private funding agencies and to medical schools that fund MD-PhD programs in the U.S. and other countries. Future Research: Future research could examine, in greater depth, how communications among students, faculty and administrators in various settings, such as classrooms, research labs, and clinics, might help MD-PhD students become more fully integrated into each new program phase and continue in the program to completion. Future research could also examine experiences of MD-PhD students from groups underrepresented in medicine and the biomedical-research workforce (e.g., first-generation college graduates, women, and racial/ethnic minorities), which might serve to inform interventions to increase the numbers of applicants to MD-PhD programs and help reverse the steady decline in the physician-scientist workforce over the past several decades.

Background The purpose of this article is to describe neonatal intensive care unit clinician perceptions of a continuous predictive analytics technology and how those perceptions influenced clinician adoption. Adopting and integrating new technology into care is notoriously slow and difficult; realizing expected gains remain a challenge. Methods Semistructured interviews from a cross-section of neonatal physicians (n = 14) and nurses (n = 8) from a single U.S. medical center were collected 18 months following the conclusion of the predictive monitoring technology randomized control trial. Following qualitative descriptive analysis, innovation attributes from Diffusion of Innovation Theory-guided thematic development. Results Results suggest that the combination of physical location as well as lack of integration into work flow or methods of using data in care decisionmaking may have delayed clinicians from routinely paying attention to the data. Once data were routinely collected, documented, and reported during patient rounds and patient handoffs, clinicians came to view data as another vital sign. Through clinicians' observation of senior physicians and nurses, and ongoing dialogue about data trends and patient status, clinicians learned how to integrate these data in care decision making (e.g., differential diagnosis) and came to value the technology as beneficial to care delivery. Discussion The use of newly created predictive technologies that provide early warning of illness may require implementation strategies that acknowledge the risk–benefit of treatment clinicians must balance and take advantage of existing clinician training methods.

Despite the fact that most science learning takes place outside of school, little is known about how engagement in informal science learning (ISL) experiences affects learners’ knowledge, skill development, interest, or identities over long periods of time. Although substantial ISL research has documented short-term outcomes such as the learning that takes place during a science center visit, research suggests that the genuine benefits of informal experiences are long-term transformations in learners as they pursue a “cascade” of experiences subsequent to the initial educational event. However, a number of major methodological challenges have limited longitudinal research projects investigating the long-term effects of ISL experiences. In this paper we identify and address four key issues surrounding the critical but challenging area of how to study and measure the long-term effects or impacts of ISL experiences: attribution, attrition, data collection, and analytic approaches. Our objective is to provide guidance to ISL researchers wishing to engage in long-term investigations of learner outcomes and to begin a dialogue about how best to address the numerous challenges involved in this work.

Research shows that early scientific interest is associated with science degree completion and career selection. However, little is known about the conditions that support early scientific interest. Using a “funds of knowledge” theoretical framework, this study examined the role of parents, family, and extended social networks in fostering early interest in science. Using interview narratives from 116 scientists (physicists and chemists) in the United States, we conducted a qualitative thematic content analysis. Findings suggest that children who become scientists in adulthood often received early, informal opportunities to use and manipulate material objects and discover how the world works. Second, families used a wide variety of scientific terms at home and encouraged children to pursue their interests whether in science or other fields. Third, these future scientists were often networked with extended family members or friends to observe and do science when they were quite young. Collectively, these findings highlight the specific ways in which families fostered early scientific interest and aided in supporting a student-directed learning environment.

In the intensive care unit, clinicians monitor a diverse array of data inputs to detect early signs of impending clinical demise or improvement. Continuous predictive analytics monitoring synthesizes data from a variety of inputs into a risk estimate that clinicians can observe in a streaming environment. For this to be useful, clinicians must engage with the data in a way that makes sense for their clinical workflow in the context of a learning health system (LHS). This article describes the processes needed to evoke clinical action after initiation of continuous predictive analytics monitoring in an LHS.

In longitudinal studies, measurement invariance is required to conduct substantive comparisons over time or across groups. In this study, we examined measurement invariance on a recently developed instrument capturing student preferences for seven instructional strategies related to science learning and career interest. We have labeled these seven instructional strategies as Collaborating, Competing, Caretaking, Creating/Making, Discovering, Performing, and Teaching. A better understanding of student preferences for particular instructional strategies can help educators, researchers, and policy makers deliberately tailor programmatic instructional structure to increase student persistence in the STEM pipeline. However, simply confirming the relationship between student preferences for science instructional strategies and their future career choices at a single time point is not sufficient to clarify our understanding of the relationship between instructional strategies and student persistence in the STEM pipeline, especially since preferences for instructional strategies are understood to vary over time. As such, we sought to develop a measure that invariantly captures student preference over a period of time: the Framework for Observing and Categorizing Instructional Strategies (FOCIS). We administered the FOCIS instrument over four semesters over two middle school grades to 1009 6th graders and 1021 7th graders and confirmed the longitudinal invariance of the FOCIS measure. This confirmation of longitudinal invariance will allow researchers to examine the relationship between student preference for certain instructional strategies and student persistence in the STEM pipeline.

This study examined a new form of pervasive gender inequality: the gender gap among high achievers in math and considered its implication for developing STEM talents. Using the cross-nation Programme for International Student Achievement (PISA) data from both 2003 and 2012, we examined the mathematics gender gap among 15-year-old high achievers across ten countries/regions. We showed a consistent male advantage among the top performers in mathematics. Follow-up regression analyses revealed that the gap was associated with some socio-demographic and schooling/attitudinal variables, even after controlling for the background variables. We argue that education communities should acknowledge and address this form of gender inequality, as it could have ramifications for the science, technology, engineering, and mathematics (STEM) education pipeline. Educators and society in general still face challenges in closing the gender gap among high achievers in math with an aim to develop a gender-balanced STEM talent pool.

Existing research has examined if undergraduate factors influence chemistry and physics, or physical science, doctoral degree entry and whether variables during PhD programs associate with graduation. Yet research on the transition from bachelor’s degree to doctoral degree entry (i.e., PhD entry in less than 6 months, attainment of a master’s degree prior to doctoral degree entry, or working in a science-related job for more than a year prior to doctoral degree entry) on PhD degree graduation remains scarce. Our study examines the transition from bachelor’s to doctoral degrees to see if experiences therein associate with female PhD graduation, after doctoral degree enrollment. Our logistic regression analysis, of female chemistry and physics doctorates ( n = 867), indicated that attainment of a master’s degree did not change the likelihood of graduation, when compared to direct entry into physical science doctoral programs. Meanwhile working in a science-related job for a year or more is associated with a significantly lower likelihood of physical science doctoral graduation when compared to women who entered directly into PhD programs or received a master’s degree prior to enrollment.

Recent research and public policy have indicated the need for increasing the physical science workforce through development of interest and engagement with informal and formal science, technology, engineering, and mathematics experiences. This study examines the association of family education and physical scientists’ informal experiences in science along with the association of informal family science experiences and early initial interest in science through multiple and logistic regression analyses. Research questions addressed are as follows: Controlling for demographic variables, do physical scientists parents’ level of education associate with participation in informal family science experiences? And which informal family science experiences are associated with physical scientists that report an initial personal interest in science by elementary school? These questions are analyzed with survey data from Project Crossover (N = 4,285), a sequential mixed-methods study that examines factors influencing ...

Mentors play important roles in determining the working environment of out-of-school-time clubs. On robotics teams, they provide guidance in hopes that their proteges progress through an engineering process. This study examined how mentors on one robotics team who defined their mentoring style as ‘let the students do the work’ navigated the challenges of a ‘build season’ and participation in regional competitions. What were some of the challenges faced by mentors and students? How did they cope when students played the largest role in team and design decisions? The mentor–student interactions captured in the research showed mentors playing supporting roles while students took command of all aspects of building the robot. The students on the team found themselves self-directing, learning, and gaining confidence by doing, and having fun with like-minded peers.

MD–PhD training takes, on average, 8 years to complete and involves two transitions, an MD-preclinical to PhD-research phase and a PhD-research to MD-clinical phase. There is a paucity of research about MD–PhD students’ experiences during each transition. This study examined transition experiences reported by 48 MD–PhD students who had experienced at least one of these transitions during their training. We purposefully sampled medical schools across the United States to recruit participants. Semistructured interviews were audio-recorded and transcribed for analysis; items focused on academic and social experiences within and outside their programs. Using a phenomenological approach and analytic induction, we examined students’ transition experiences during their MD–PhD programs. Five broad themes emerged centering on multiple needs: mentoring, facilitating integration with students in each phase, integrating the curriculum to foster mastery of skills needed for each phase, awareness of cultural differences between MD and PhD training, and support. None of the respondents attributed their transition experiences to gender or race/ethnicity. Students emphasized the need for mentoring by MD–PhD faculty and better institutional and program supports to mitigate feelings of isolation and help students relearn knowledge for clinical clerkships and ease re-entry into the hospital culture, which differs substantially from the research culture.

Do summer laboratory research apprenticeships during high school have an impact on entry to MD/PhD programs? This quantitative study (n= 236,432) examines the connection between laboratory research apprenticeship experience at the high school level and matriculation into one of the more rigorous educational programs for scientific research training., Do summer laboratory research apprenticeships during high school have an impact on entry into MD/PhD programs? Apart from the nearly decade-long span of time between high school and matriculation into an MD/PhD program, young people have many life-shaping experiences that presumably impact their education and career trajectories. This quantitative study (n = 236,432) examines the connection between early laboratory research apprenticeship experiences at the high school level and matriculation into one of the more rigorous educational programs for scientific research training. The span of time covered by this analysis reaches across more than a decade, examining the potential importance of research experiences during the precollege years in the educational trajectory of young people. Intertwined with this question on research experiences is a second major concern regarding diversity in the life sciences research corps. Diversity in this wide-ranging discipline refers specifically to the underrepresentation of Blacks/African Americans, Hispanics/Latino/as, and American Indians/Alaska Natives among the ranks of research scientists. Thus, this study includes analyses that specifically focus on research apprenticeships of Blacks/African Americans and Hispanics/Latino/as and their entrance into MD/PhD programs.