Doctoral Dissertations

Date of Award

8-2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major Professor

Dr. Gary Skolits

Committee Members

Jennifer Morrow, Louis Rocconi, Patrick Biddix

Abstract

The capacity for data analytical decision-making is not always optimal in institutions of higher education (Hawkins & Bailey, 2020). Data analytic decision making for this study is defined as any decision utilized to improve the process or outcome for any function of higher educational administration (Nguyen et al., 2020) including but not limited to: state appropriated funding (e.g. Campbell, 2018) improving graduation rates (e.g Moscoso-Zea, Saa & Luján-Mora, 2019), teacher instruction (e.g. Cai & Zhu, 2015), or student success (e.g. Foster & Francis, 2020). Many IR professionals still face obstacles pertaining to their ability to both utilize data analytical software as well as share data analytical findings across their respective clientele units outside of institutional research to impact institutional decision-making (Lehman, 2017). The literature is lacking concerning how IR professionals experience and navigate these critical aspects of data analytical decision-making support in higher educational institutions.

The purpose of this study was to address the gap in the research by assessing the perspectives of IR professionals regarding their ability to utilize data analytic systems (e.g., analyzing, interpreting, sharing of data) to impact and strengthen institutional decision-making. The purpose of this study was also to understand how institutional culture (e.g., policies, operational processes, relevancy, conduciveness) influences the ability of IR professionals to utilize data analytic systems when sharing data findings or collaborating across their respective institutions to enhance institutional decision-making. Recommendations based on the study findings included stronger data governance for dashboards and data visualizations, expanding predictive analytics to enhance student success, and data literacy training with both utilizing data analytics software and interpreting data findings according to the context of individual institutions.

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