“Josh has played a key role in expanding and refining the predictive models which we provide to the University  of Iowa concerning undergraduate student recruitment, retention, and academic success. He has worked with our team to not only predict these outcomes, but also with collaborators across the UI to make sure our models are useful for stakeholders. In this role, Josh has directly benefitted the UI’s planning efforts, as well as programs to help students succeed in their academic journey.” – Grant Brown, Assistant Professor, Biostatistics

• Hometown: Kapaʻau, Hawaiʻi
• Faculty mentor/advisor: Dr. Grant D. Brown, PhD and Dr. Knute D. Carter, PhD
• What is your degree program and expected graduate date? PhD Biostatistics, Spring 2023
• Please describe your research: My research pertains to the development and implementation of machine learning models that leverage data to both shape student enrollment and improve student success. Specific applications or goals of these models include supporting university recruitment efforts, forecasting total student enrollment to aid in financial/resource management, understanding the factors that promote or hinder a student’s likelihood of returning to college, and identifying factors which drive student persistence. Through collaboration with student success and retention professionals we are able to target interventions to support students in achieving their degrees.
• In simple terms, why does this research matter? According to the Education Data Initiative, 40% of undergraduate college students in the United States dropout of college. Dropping out of college adversely affects not only the student through loan debt, lower earning potential, and increased overall unemployment rate but also the broader economy through lower GDP and less potential tax revenue. By incorporating data driven solutions from the time when a student applies to when a student graduates, we hope to better equip college students with the tools necessary to realize their full potential and thus directly improve student outcomes and indirectly improve national outcomes.
• How soon after starting at the University of Iowa were you able to participate in research? I started this research project as soon as I began here at the university.
• How has being involved in research made you more successful at the University of Iowa? This research project has made me more successful by improving my ability to communicate statistical concepts to a non-technical audience, developing my programming and software development skills, and exposing me to advanced machine learning techniques.
• What are your career goals and/or plans after graduation? After graduating, I hope to continue developing impactful statistical/machine learning models as a professor.
• Does your research have connections to or implications for COVID-19? This research project is not directly connected to COVID-19 other than the fact that we will now have to anticipate and handle data quality implications due to COVID-19 which include but are certainly not limited to missing standardized test scores, the increase in student stress, and the impact of online courses versus in-person classes.

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