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Social and Administrative Sciences

(233) Investing in Student Success Through the Use of Artificial Intelligence

    Primary Author(s)

  • Maryann Wu, EdD (she/her/hers)

    Assistant Dean for Assessment and Assistant Professor of Clinical Pharmacy
    University of Southern California
    Los Angeles, California, United States

    • Co-Author(s)

  • Ying Wang, PharmD, APh

    Director, Professional Experience Programs and Assistant Professor of Clinical Pharmacy
    University of Southern California
    Los Angeles, California, United States

  • Ian S. Haworth, PhD

    Vice Chair and Associate Professor of Pharmacology and Pharmaceutical Sciences
    University of Southern California
    Los Angeles, California, United States

Objective : Use of artificial intelligence (AI) may help to align education to meet societal needs, while also maximizing students’ chances of success, including matching for postgraduate training, or finding a full-time job in their desired field.

Methods: We have started to build a model called AI-SiPS (Success in Pharmacy School) to identify activities that lead to success upon graduation. The model includes data collected at multiple stages of the PharmD program, with the purpose of identifying key factors for success. Outcomes are divided into broad categories of “Residency”, “Industry”, “Community/Hospital” (RICH). AI-SiPS is implemented on the KNIME (ver. 4.5.1) platform.

Results: Analysis indicated: 1) an early Acute Care APPE led to a higher residency match rate than a late Acute Care APPE (70.2% vs. 58.0%), 2) students who performed well in certain therapeutic didactic courses, such as cardiology, had a higher chance of matching for residency than those who did not perform well (77.8% vs. 51.7%), and 3) students who felt confident about starting their APPEs had a higher chance of matching for residency than those who reported not feeling confident (77.1% vs. 66.7%). Earlier didactic courses focused on practical application of knowledge also showed an impact on self-perceived confidence. Lastly, APPE confidence may also relate to pursuit of a career in industry.

Conclusions: The AI-SiPS model represents our conceptual approach based on preliminary analyses of important data leading to RICH post-graduation outcomes. Future plans are to provide KNIME workflows to other institutions interested in using AI to support student success, including student recruitment and advisement that are consistent with the changing needs of society.