Faculty, Staff and Student Publications

Language

English

Publication Date

1-1-2026

Journal

Frontiers in Digital Health

DOI

0.3389/fdgth.2026.1786363

PMID

42339004

PMCID

PMC13284074

PubMedCentral® Posted Date

6-8-2026

PubMedCentral® Full Text Version

Post-print

Abstract

Introduction: The adoption of artificial intelligence (AI) in higher education presents opportunities and challenges for dental education. This study explores the use of Large Language Model (LLM) based AI tools, including ChatGPT and Grammarly AI, among faculty and students at the UTHealth School of Dentistry in Houston (UTSDH). This research assessed usage patterns, perceived benefits and concerns, and AI training demand.

Methods: A piloted, cross-sectional survey was administered via email. The survey included Likert-scale, multiple-choice, and open-ended questions. Respondents provided demographics and rated their LLM-based AI tools for use and perceptions in educational, clinical, and research contexts. Data was analyzed using Kruskal-Wallis and Tukey-Kramer-Nemenyi tests. Qualitative responses were analyzed thematically.

Results: Among 243 respondents, 66% of faculty and 73% of students reported using LLM-based AI tools, primarily for writing and educational tasks. Students were more likely to perceive LLM-based AI tools as beneficial (p < 0.01), while faculty showed stronger demand for AI training (p < 0.05). Gender differences were significant, with males were more supportive of AI in research tasks (p < 0.05). User experience ratings differed, with students rating ChatGPT more favorably across all categories.

Discussion: LLM-based AI tools (e.g., ChatGPT and Grammarly AI) are becoming increasingly relevant in dental education, particularly in academic writing and concept learning. While students are leading early adoption, faculty expressed a strong need for structured AI training, highlighting fertile ground for development programs. Clinical and research applications remain underdeveloped but promising. Addressing these gaps through tailored education, ethical guidelines, and institutional support will be essential for optimizing AI's potential across dental education and practice.

Keywords

artificial intelligence, attitude of health personnel, dental, education, educational technology

Published Open-Access

yes

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