Having a diverse workforce in STEMM (science, technology, engineering, mathematics, and medicine) fields is essential for the United States to remain competitive in the global economy and to create a more just society. Faculty‐mentored undergraduate research experiences have been identified as a high‐impact practice for encouraging students from diverse backgrounds to pursue STEMM education and careers. Despite extensive research examining factors influencing the effectiveness of mentor−mentee relationships, there is still limited understanding of how differences or similarities in the social identities of mentors and mentees, which we term mentor−mentee discordance, impact undergraduates’ research experiences and outcomes. In this perspective, we propose that mentor−mentee discordance should be conceptualized as a multidimensional, continuous construct and suggest a global index to measure varying degrees of discordance in mentoring relationships. We also offer a conceptual model that incorporates the Discordance Index to systematize the understanding of the effects of discordant mentoring relationships on student development across social contexts and over time. Finally, we provide recommendations for future researchers, STEMM educators, and program directors who are interested in using the Discordance Index.
Mentoring across differences in science education: Applying a brokering framework
Mentoring relationships in academia have traditionally been described as a dyad between a mentor and a mentee. The mentor provides the mentee with both technical and psychosocial support to move toward obtaining their Ph.D. or gaining tenure and promotion. While there is an embedded assumption that mentoring is best suited when people of common background support each other, scholars must consider the impact of mentoring across differences. Given the lack of diversity among senior faculty members in science education, and given the increasing diversity represented among graduate students and early career scholars in science education, inevitably mentoring relationships will be formed across differences in identities (race, ethnicity, gender, sexuality, ability). In our essay, we focus on two focal points: we explore those aspects of mentoring relationships that research suggests are critical to the success of relationships built across differences, foregrounding lessons science education researchers can take from this literature and arguing that it is too much to expect one individual mentor to provide to any given mentee. Next, we propose a brokering framework, leveraging technological advances, to work toward more transformative mentoring outcomes at scale, particularly when mentoring across differences.
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- Award ID(s):
- 2029956
- NSF-PAR ID:
- 10331169
- Date Published:
- Journal Name:
- Science Education
- Volume:
- 106
- Issue:
- 5
- ISSN:
- 0036-8326
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Mentoring of graduate students and postdoctoral scholars is an integral part of training at research institutions. Mentoring scholarship has rapidly evolved over the last two decades, elucidating the need for shifts in mentor/mentee relationships, including the need for mentor training. The University of Maryland, Baltimore and the University of Maryland College Park combined mentoring workshops based on an established curriculum. Workshops were offered to faculty at different institutions in the Maryland system growing out of a need from the National Science Foundation Alliances for Graduate Education and the Professoriate (NSF AGEP) Promise Academy Alliance. The authors share the model they developed as well as the benefits and challenges of the inter-institutional approach.more » « less
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Mentoring of graduate students and postdoctoral scholars is an integral part of training at research institutions. Mentoring scholarship has rapidly evolved over the last two decades, elucidating the need for shifts in mentor/mentee relationships, including the need for mentor training. The University of Maryland, Baltimore and the University of Maryland College Park combined mentoring workshops based on an established curriculum. Workshops were offered to faculty at different institutions in the Maryland system growing out of a need from the National Science Foundation Alliances for Graduate Education and the Professoriate (NSF AGEP) Promise Academy Alliance. The authors share the model they developed as well as the benefits and challenges of the inter-institutional approach.more » « less
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Abstract This S_STEM project is designed to support the retention and graduation of high-achieving, low income students with demonstrated financial need at Baylor University. Over its five-year duration, this project will fund four-year scholarships to 22 students who are pursuing Bachelor degrees in Engineering, Electrical and Computer Engineering, Mechanical Engineering and Computer Science. Engineering and Computer Science (ECS) Scholars will participate in activities which include an orientation, a monthly seminar series and required faculty mentoring. Support services and activities for ECS Scholars build upon existing activities at Baylor and feature peer mentoring, study abroad opportunities, alumni mentoring, support and training for undergraduate research, professional development workshops, and tutoring support from the ECS Learning Resource Center. A distinguishing feature of the project is the use of EAB’s Navigate, a web-based software platform for tracking student progress, coordinating student care and employing predictive analytics. The expertise generated using a student dashboard capable of predictive analytics will have the broad impact of informing the STEM community of best practices for timely interventions, and improving retention and graduation rates. The Navigate platform is used for predictive analytics and to track and document ECS Scholar progress toward achieving benchmark goals in the areas of retention, graduation rates, internships, undergraduate research experiences, and job placement. The use of predictive analytics has significant potential for helping students arrive at successful outcomes. However, it is an assumption of this project that the successful use of predictive analytics should take into consideration not simply the accuracy in identifying students who are struggling but in the social attributions of success and perceptions of a “big data” tool that might be received alternatively with enthusiasm or suspicion. The focus of this paper will be to give an overview of our first-year results from the project. We were successful in recruiting the full first cohort that began in the Fall of 2020. For the first year, many of the engagement sessions with the students pivoted to a virtual experience, however, we were able to manage several events that fostered a sense of community among the ECS scholars. Our research partners from the Baylor School of Education were successful in conducting baseline qualitative research using detailed interviews with an initial focus on community fit, academic fit and faculty relationships. The paper will also summarize our use of the Navigate platform and the lessons learned in the areas of data capture and interventions.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/sce.21720
