The Promise and Paradox of AI in Doctoral Education

Authors

  • Dr. Kelly Brown Texas A&M University-Corpus Christi
  • Dr. Kaye Shelton Lamar University

DOI:

https://doi.org/10.24059/olj.v30i2.5842

Keywords:

Adaptive artificial intelligence (AI), support for doctoral students, doctoral programs, artificial intelligence and doctoral education, doctoral student attrition, online doctoral programs

Abstract

This paper proposes a conceptual model of adaptive artificial intelligence (AI) support for doctoral education that operationalizes supported autonomy across three interconnected dimensions of doctoral student development: cognitive, affective, and social. Each dimension represents a distinct but overlapping area where AI can provide responsive scaffolding while preserving student agency and intellectual ownership. This framework provides a structured approach to understanding how AI tools can enhance rather than diminish doctoral development when thoughtfully integrated into mentorship and supervision structures. Challenges and ethical use are addressed along with implications for doctoral programs. We suggest a balanced use of AI, a clear framework or guidelines for ethical use, and doctoral student supervision (dissertation chair) to reduce feelings of isolation, student attrition, and use of students’ time.

Author Biographies

Dr. Kelly Brown, Texas A&M University-Corpus Christi

Associate Professor, Educational Leadership

Dr. Kaye Shelton, Lamar University

Professor, Educational Leadership

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Published

2026-06-01

How to Cite

Brown, K., & Shelton, K. (2026). The Promise and Paradox of AI in Doctoral Education. Online Learning, 30(2), 82–105. https://doi.org/10.24059/olj.v30i2.5842

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Higher Education in an AI-Transformed World