AI-Powered Support for Enhancing Independent Research Studies in Doctoral Education

Alternative Title

Artificial Intelligence (AI)-Powered Support for Enhancing Independent Research Studies in Doctoral Education

Contributor

University of Central Florida. Faculty Center for Teaching and Learning; University of Central Florida. Division of Digital Learning; Teaching and Learning with AI Conference (2025 : Orlando, Fla.)

Location

Universal Center

Start Date

29-5-2025 4:00 PM

End Date

29-5-2025 5:00 PM

Publisher

University of Central Florida Libraries

Keywords:

AI tools; Doctoral education; Independent research; Dissertation support; Course design

Subjects

Artificial intelligence--Study and teaching (Higher); Artificial intelligence--Educational applications; Graduate students--Research; Educational technology--Study and teaching (Graduate); Research--Methodology--Computer-assisted instruction

Description

This presentation explores the innovative use of AI to support doctoral students in developing independent research studies aligned with their dissertation topics. By leveraging AI tools to design a structured course shell in Canvas, this approach streamlines the process for both students and faculty. The framework allows students to generate pilot study material, providing a foundation for their dissertation research. While findings are still emerging, this session will detail the implementation process, its benefits for doctoral programs, and its potential to reduce faculty workload. Attendees will gain practical insights into replicating this model in their own teaching and research contexts.

Language

eng

Type

Presentation

Rights Statement

All Rights Reserved

Audience

Faculty; Doctoral Students

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May 29th, 4:00 PM May 29th, 5:00 PM

AI-Powered Support for Enhancing Independent Research Studies in Doctoral Education

Universal Center

This presentation explores the innovative use of AI to support doctoral students in developing independent research studies aligned with their dissertation topics. By leveraging AI tools to design a structured course shell in Canvas, this approach streamlines the process for both students and faculty. The framework allows students to generate pilot study material, providing a foundation for their dissertation research. While findings are still emerging, this session will detail the implementation process, its benefits for doctoral programs, and its potential to reduce faculty workload. Attendees will gain practical insights into replicating this model in their own teaching and research contexts.