Getting Things Done in Data-Intensive Inter-campus Research Initiatives: A Social Network Analysis Approach to Understanding and Building Effective Relationships between Researchers and Other University Employees

Lisa Kaczmarczyk; Daniel Pinedo

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Conference: 2021 ASEE Virtual Annual Conference Content Access
Location: Virtual Conference
Publication Date: July 26, 2021
Start Date: July 26, 2021
End Date: July 19, 2022
Conference Session: NSF Grantees Poster Session
Tagged Topic: NSF Grantees Poster Session
Page Count: 9
DOI: 10.18260/1-2--37224
Permanent URL: https://peer.asee.org/37224
Download Count: 312

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Paper Authors

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Lisa Kaczmarczyk Lisa Kaczmarczyk PhD Consulting, LLC

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Lisa Kaczmarczyk is the owner of a program evaluation business that specializes in computer science and engineering education, and an Adjunct Professor of Computer Science at Harvey Mudd College. Dr. Kaczmarczyk has extensive experience evaluating NSF funded STEM projects at the primary, secondary and post-secondary levels and has served as project PI. Her expertise is in interdisciplinary computing and engineering education, outreach to women, girls and other under-represented groups, and computing for social good. Dr. Kaczmarczyk currently serves as Vice-Chair of the ACM special interest group on Computers and Society. Dr. Kaczmarczyk was awarded her PhD at the University of Texas at Austin where her research wove together computer science, science education and psychology. Dr. Kaczmarczyk was lead author on the 2014 ACM Education Policy Committee report “Rebooting the Pathway to Success: Preparing Students for Computing Workforce Needs in the United States”. In 2019 her paper “Identifying student misconceptions of programming” was awarded the “Top Ranked SIGCSE Symposium Paper of All Time”.

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Daniel Pinedo Lisa Kaczmarczyk PhD Consulting, LLC orcid.org/0000-0002-1864-1303

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Daniel is a statistician with MA degrees in Organizational Behavior and Evaluation from Claremont Graduate University, and Clinical Psychology from Sofia University in Palo Alto, CA. His research areas encompass statistical methods for the myriad disciplines in the social sciences, and applications of organizational culture research. Daniel has held various roles including working as a Global HR consultant at Accenture Plc., as a university lecturer in the psychology department at Mount Saint Mary’s University in Los Angeles, CA, and as a mental health clinician. He is currently the Principal at Kinesis Consulting (https://kinesis.consulting) in Phoenixville, PA

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Abstract

Three large United States universities with different profiles and institutional missions are collaborating on a large grant project funded by NSF DUE examining how non-cognitive and affective (NCA) factors affect student academic success in Engineering and Computer Science. A unique aspect of this project is the stated intent to form partnerships between Engineering / Computer Science faculty PIs and Student Affairs personnel on their respective campuses. These relationships are a potential way to leverage the multiplicity of experience and perspectives to deploy effective student success initiatives. The project’s external evaluation focuses on how critical relationships develop between the project PIs and other campus personnel who support the project. This poster and accompanying paper focus on key aspects of these relationships.

When the project started the PIs began gathering a broad array of institutional student data housed across several offices and divisions. Securing authorizations and obtaining access to confidential student data proved more complex and time consuming than anticipated. Much time was spent learning which personnel to work with and what procedures to follow. In Spring 2019 the PIs completed a survey of their perceptions of the trust and common understanding between themselves and campus personnel they were communicating with about the project. This survey asked whom they had communicated with regarding the project in the past several months (“critical personnel” or “CPs”). The survey explored the strength of PIs’ trust in CPs, and perceptions of common understanding between themselves and CPs about the project. The survey results were used to create a series of actor-event social network analysis graphs that displayed communication patterns among PIs and CPs, with strengths and weaknesses related to trust and common understanding from the PI perspective.

One significant outcome of the graph findings was the reflective conversations they spurred among the PIs. These discussions led to insights connecting the common understanding graphs to their understanding of challenges and successes of data collection relative to campus culture. For example, the common understanding (CU) graphs showed a contrast between campuses for actor-event relationship patterns, with corresponding contrasts related to communication patterns. The PIs reflected on the amount of time spent learning how to obtain the student data required for their research, and how much they now know about the people and processes involved. They recognized how this new understanding will make upcoming stages of their collaborative research progress more smoothly. Ultimately, the PIs understood the importance of deeply understanding how campus culture impacts the implementation of complex inter-campus research initiatives.

Engineering Education researchers conducting inter-campus research may benefit from using this methodology in the planning stages of projects to understand the people and processes related to “how things get done” on their campuses. Potential benefits include reducing the amount of time spent collecting needed data and helping build stronger relationships with campus partners. More broadly, this methodology may help researchers understand and effectively manage complexities of working with large amounts of people and data.

Citation
Format

Kaczmarczyk, L., & Pinedo, D. (2021, July), Getting Things Done in Data-Intensive Inter-campus Research Initiatives: A Social Network Analysis Approach to Understanding and Building Effective Relationships between Researchers and Other University Employees Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37224

TY - CPAPER
AB - Three large United States universities with different profiles and institutional missions are collaborating on a large grant project funded by NSF DUE examining how non-cognitive and affective (NCA) factors affect student academic success in Engineering and Computer Science. A unique aspect of this project is the stated intent to form partnerships between Engineering / Computer Science faculty PIs and Student Affairs personnel on their respective campuses. These relationships are a potential way to leverage the multiplicity of experience and perspectives to deploy effective student success initiatives. The project’s external evaluation focuses on how critical relationships develop between the project PIs and other campus personnel who support the project. This poster and accompanying paper focus on key aspects of these relationships.

When the project started the PIs began gathering a broad array of institutional student data housed across several offices and divisions. Securing authorizations and obtaining access to confidential student data proved more complex and time consuming than anticipated. Much time was spent learning which personnel to work with and what procedures to follow. In Spring 2019 the PIs completed a survey of their perceptions of the trust and common understanding between themselves and campus personnel they were communicating with about the project. This survey asked whom they had communicated with regarding the project in the past several months (“critical personnel” or “CPs”). The survey explored the strength of PIs’ trust in CPs, and perceptions of common understanding between themselves and CPs about the project. The survey results were used to create a series of actor-event social network analysis graphs that displayed communication patterns among PIs and CPs, with strengths and weaknesses related to trust and common understanding from the PI perspective.

One significant outcome of the graph findings was the reflective conversations they spurred among the PIs. These discussions led to insights connecting the common understanding graphs to their understanding of challenges and successes of data collection relative to campus culture. For example, the common understanding (CU) graphs showed a contrast between campuses for actor-event relationship patterns, with corresponding contrasts related to communication patterns. The PIs reflected on the amount of time spent learning how to obtain the student data required for their research, and how much they now know about the people and processes involved. They recognized how this new understanding will make upcoming stages of their collaborative research progress more smoothly. Ultimately, the PIs understood the importance of deeply understanding how campus culture impacts the implementation of complex inter-campus research initiatives.

Engineering Education researchers conducting inter-campus research may benefit from using this methodology in the planning stages of projects to understand the people and processes related to “how things get done” on their campuses. Potential benefits include reducing the amount of time spent collecting needed data and helping build stronger relationships with campus partners. More broadly, this methodology may help researchers understand and effectively manage complexities of working with large amounts of people and data.

AU - Lisa Kaczmarczyk
AU - Daniel Pinedo
CY - Virtual Conference
DA - 2021/07/26
PB - ASEE Conferences
TI - Getting Things Done in Data-Intensive Inter-campus Research Initiatives: A Social Network Analysis Approach to Understanding and Building Effective Relationships between Researchers and Other University Employees
UR - https://peer.asee.org/37224
DO - 10.18260/1-2--37224
ER -