AI for Continuous Improvement and Equity

• In Event: Artificial Intelligence as a Catalyst for Transforming Accreditation in Educator Preparation

Abstract

AI is not just a tool for compliance—it can be a catalyst for transformational change. This session explores how artificial intelligence can support continuous improvement and equity in educator preparation, aligning with accreditation standards that emphasize candidate success, program effectiveness, and responsiveness to diverse learner needs.

The presenter will begin by showing how AI can be used to identify patterns across candidate performance data, faculty feedback, and PK–12 partner input. For example, AI-powered data analysis can highlight disparities in clinical placement outcomes, track the retention of diverse teacher candidates, and uncover trends in employer satisfaction data. These insights enable EPPs to make more targeted, timely decisions to improve programs and address gaps in access or opportunity.

Participants will also learn how AI supports the creation of real-time feedback loops. AI-driven dashboards can provide up-to-date visuals of candidate progress, allowing program leaders to monitor key indicators like licensure exam pass rates, GPA trends, and clinical performance by subgroup. Predictive analytics can flag at-risk candidates earlier, enabling proactive support and advising interventions.

The session will spotlight several use cases where AI has advanced equity. For example, tools that disaggregate data by race, gender, or socioeconomic status can bring visibility to performance differences that might otherwise go unnoticed. AI can also assist in refining admissions models to ensure holistic candidate evaluation and reduce reliance on legacy criteria that disadvantage underrepresented applicants.

The presenter will emphasize that equity-focused AI use requires careful design, interpretation, and institutional commitment. Participants will discuss how to use AI outputs responsibly and ensure continuous improvement cycles include human reflection, community input, and validation of findings.

Interactive activities will help participants consider how AI tools can be mapped to their own institutional equity goals, program improvement plans, and strategic initiatives. Templates and planning tools will be provided to support integration.

Key takeaways include:

-How AI enables real-time feedback, early interventions, and trend analysis.

-Strategies for using AI to surface and address equity gaps in EPPs.

-Tools for embedding AI into ongoing cycles of program evaluation and improvement.

-Approaches for combining human insight with AI-driven evidence for better decision-making.

This session is geared toward program leaders, data teams, DEI officers, and assessment professionals committed to using technology not only to meet accreditation requirements, but to build more just, responsive, and effective educator preparation systems.

Author

• Beth W. Kubitskey, Eastern Michigan University