Faculty’s Digital Accessibility Assistant: Does Generative AI Write Accurate, Meaningful, and Useful Alternative Text for Course Images?

BACKGROUND: Alternative text (alt text) for images is critical for digital accessibility, but faculty often lack time or training to create it. Generative artificial intelligence (AI) offers a potential solution, although its effectiveness in education is underexplored. PURPOSE: The aim was to evaluate the quality of AI-generated alt text for course images from the perspective of nursing faculty. METHODS: Ten nursing faculty evaluated 43 alt descriptions generated by ChatGPT-4 for their course images using 5-point Likert scales (accuracy, meaningfulness, usefulness) and provided qualitative feedback. RESULTS: Faculty rated AI-generated text highly for accuracy (M = 4.44, 90.7% positive), meaningfulness (M = 4.30, 86.0% positive), and usefulness (M = 4.05, 76.7% positive). Three critique themes emerged: "accurate but..." (lacking pedagogical context), "not quite" (subtle semantic errors), and "too much" (excessive verbosity). CONCLUSIONS: Generative AI can produce high-quality alt text drafts that reduce faculty workload. However, subject-matter expert review remains necessary to correct errors, refine brevity, and incorporate pedagogical context.