Self-study, assessment and evidence systems built by someone who has sat on both sides of the review. Including how to document AI decisions so they strengthen your next review instead of complicating it.
By Eric Goodman, Ph.D., former chief academic officer · Updated October 2026
Eric Goodman, Ph.D., served as an HLC Peer Reviewer from 2006 to 2011. He led a multi-state college through its transition to a university system and its 10-year SACSCOC reaffirmation with no academic findings.
His accreditation work spans SACSCOC, HLC and NCA: regional reaffirmations, HLC Candidacy, HLC approval of new master’s programs, and programmatic accreditation including ABET and CAPTE.
Planning and writing support for reaffirmation and candidacy self-studies.
Assessment systems that show what students learn, program by program.
Evidence collection that runs all year instead of the semester before a visit.
Documenting AI policy, training and outcomes as evidence reviewers can follow.
Increasingly, yes. Accreditors look for evidence that an institution governs new technology, protects academic integrity and assesses learning outcomes. Your AI policy, training records and outcomes data become evidence in a review.
AI touches several standards at once: academic integrity, faculty qualifications and development, assessment of student learning, and data governance. Documenting AI decisions now makes the next self-study easier.
Regional accreditors including SACSCOC, HLC and NCA, covering reaffirmations, HLC Candidacy and HLC approval of new master’s programs, plus programmatic accreditation including ABET and CAPTE.
In a 60-minute Executive Briefing, you’ll get a clear picture of where your institution stands on AI and a written summary to share with your cabinet.