CLIMBS UP 2: A Longitudinal & Mixed-Methods Extension
The CLIMBS UP 2 project, funded by the National Science Foundation*, builds on CLIMBS UP 1 to examine how a positive academic climate affects longitudinal academic STEM career outcomes, particularly for early-career individuals from historically underrepresented groups.
The overarching goal of CLIMBS UP 2 is to increase understanding of the longitudinal effects of early-career climates and the COVID 19 pandemic on STEM career outcomes (productivity and attitudes) and professional pathways. We are particularly interested in better understanding the differential longitudinal effects of climate and the CV19 pandemic on scholars from historically underrepresented groups, as compared with their more privileged peers.
We will use mixed methods data collection at two time points (Figure 2) to build upon our CLIMBS UP 1 (T1) survey. We first conducted a longitudinal follow-up survey (T2) of the scholars in our T1 data set during Fall 2024 (n = 1,365) to examine the effects of academic climates and CV19 on career outcomes and professional pathways through time. Next, we will conduct one-on-one interviews (T3) with a diverse subsample (n = 80) of participants who completed the T2 survey. These interviews will enable us to gain deep understanding of how scholars make sense of, navigate, and shape their academic climates, and how multiple levels of academic climate interact with each other and with disruptions caused by CV19 to shape professional pathways.
Results and recommendations from CLIMBS-UP 1 can be accessed in the "Resources" tab above. As results from this phase of the project become available, we will update the resources page.
The overarching goal of CLIMBS UP 2 is to increase understanding of the longitudinal effects of early-career climates and the COVID 19 pandemic on STEM career outcomes (productivity and attitudes) and professional pathways. We are particularly interested in better understanding the differential longitudinal effects of climate and the CV19 pandemic on scholars from historically underrepresented groups, as compared with their more privileged peers.
We will use mixed methods data collection at two time points (Figure 2) to build upon our CLIMBS UP 1 (T1) survey. We first conducted a longitudinal follow-up survey (T2) of the scholars in our T1 data set during Fall 2024 (n = 1,365) to examine the effects of academic climates and CV19 on career outcomes and professional pathways through time. Next, we will conduct one-on-one interviews (T3) with a diverse subsample (n = 80) of participants who completed the T2 survey. These interviews will enable us to gain deep understanding of how scholars make sense of, navigate, and shape their academic climates, and how multiple levels of academic climate interact with each other and with disruptions caused by CV19 to shape professional pathways.
Results and recommendations from CLIMBS-UP 1 can be accessed in the "Resources" tab above. As results from this phase of the project become available, we will update the resources page.
Meet the Team
The team is comprised of a diverse group of scholars from multiple disciplines, institutions, and demographic backgrounds.
PIs |
Collaborators |
Past Collaborators |
|
Kendra Spence Cheruvelil, PhD, Professor of Freshwater Ecology and Biology, Michigan State University
Kevin Elliott, PhD, Professor of Philosophy, Michigan State University Georgina Montgomery, PhD, Professor of History, Michigan State University Isis Settles, PhD, Professor of Psychology and Afro American Studies, University of Michigan Erin Cech, PhD, Associate Professor of Sociology, University of Michigan Leslie D. Gonzales, EdD, Professor of Higher Education, University of Arizona |
Guizhen M a, PhD, Delta State University
Josiah Rosario, PhD, University of Michigan Danielle Parra, University of Michigan Eman Khan, Michigan State University |
Hannah Douglas, PhD, University of Michigan
Tangier Davis, PhD, University of Michigan Hady Omar, Michigan State University |
Acknowledgements
* This material is based upon work supported by the National Science Foundation under Grants #2300709 (UM NSF Award) and #2300710 (MSU NSF Award).
