The Promise and Paradox of AI in Doctoral Education.
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| Title: | The Promise and Paradox of AI in Doctoral Education. |
|---|---|
| Authors: | Brown, Kelly1, Shelton, Kaye2 |
| Source: | Online Learning. Jun2026, Vol. 30 Issue 2, p82-105. 24p. |
| Subject Terms: | *Artificial intelligence, *Doctoral degree, *Instructional systems, *Self-regulated learning, *Student development, Social psychology, Mentoring |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Online Learning is the property of Online Learning Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 194761187 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The Promise and Paradox of AI in Doctoral Education. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Brown%2C+Kelly%22">Brown, Kelly</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Shelton%2C+Kaye%22">Shelton, Kaye</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Online+Learning%22">Online Learning</searchLink>. Jun2026, Vol. 30 Issue 2, p82-105. 24p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Doctoral+degree%22">Doctoral degree</searchLink><br />*<searchLink fieldCode="DE" term="%22Instructional+systems%22">Instructional systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Self-regulated+learning%22">Self-regulated learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+development%22">Student development</searchLink><br /><searchLink fieldCode="DE" term="%22Social+psychology%22">Social psychology</searchLink><br /><searchLink fieldCode="DE" term="%22Mentoring%22">Mentoring</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Online Learning is the property of Online Learning Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=194761187 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.24059/olj.v30i2.5842 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 82 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Doctoral degree Type: general – SubjectFull: Instructional systems Type: general – SubjectFull: Self-regulated learning Type: general – SubjectFull: Student development Type: general – SubjectFull: Social psychology Type: general – SubjectFull: Mentoring Type: general Titles: – TitleFull: The Promise and Paradox of AI in Doctoral Education. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Brown, Kelly – PersonEntity: Name: NameFull: Shelton, Kaye IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 24725749 Numbering: – Type: volume Value: 30 – Type: issue Value: 2 Titles: – TitleFull: Online Learning Type: main |
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