TENNAIR 2026

Effective academic program review is often assumed to rest primarily on the quality of program level responses. However, experience suggests that the success of program review is largely shaped long before programs begin writing, by the administrative structures, tools, timelines, and guidance that frame the process. When intentionally designed, this infrastructure can reduce rework and confusion, improve consistency and clarity across submissions, and better support data informed reflection and continuous improvement.

This session offers an administrator centered perspective common to institutional research, assessment, and planning roles, exploring how responsibilities shift when administrators act as translators of external expectations, designers of coherent review systems, and coaches supporting faculty and program leaders. Using examples aligned with Tennessee Higher Education Commission (THEC) expectations, the presenter will share practical strategies such as guided self-study templates, standardized site visit itineraries, clear review timelines, and observer roles to build institutional capacity. These approaches have contributed to stronger narratives, fewer clarification cycles, and clearer links between review findings, decision making, and improvement planning.

The session also addresses the emerging use of artificial intelligence as an administrative support strategy within program review workflows. Rather than replacing professional judgment or program ownership, AI is positioned as a tool for improving clarity, identifying cross cutting themes, and generating reflective prompts, with clear guardrails emphasizing transparency and human review.

Participants will reflect on pain points in their own program review processes, consider where assumptions or inconsistent guidance create unnecessary burden, and identify administrative adjustments that could strengthen existing systems. Attendees will leave with transferable, scalable strategies that can be adapted across institution types to support more meaningful program review, without overhauling current models.