Alternative Title

Developing an Artificial Intelligence (AI)-Agent to Help Students Research: An Exploratory Study

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 (2024 : Orlando, Fla.)

Location

Mangrove

Start Date

24-7-2024 9:00 AM

End Date

24-7-2024 10:00 AM

Publisher

University of Central Florida Libraries

Keywords:

AI assistant; Prompt engineering; Generative AI; Pedagogical challenges; Research assignment

Subjects

Artificial intelligence--Educational applications; Artificial intelligence--Research; Students--Research; Research--Computer-assisted instruction; Artificial intelligence--Study and teaching (Higher)

Description

This session will describe the results of an exploratory action research project to develop an AI-assistant to help first-year undergraduates perform their first research assignment in college. The different prompt engineering techniques used to develop this AI agent will be discussed (multi-shot, TRACI structure, etc.). Additionally, the viability and pragmatic challenges of creating such an AI-assistant will be discussed, with particular emphasis on the challenges of assessing generative AI outputs in a pedagogical context.

Language

eng

Type

Presentation

Format

application/pdf

Rights Statement

All Rights Reserved

Audience

Faculty, Students, Instructional designers

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Jul 24th, 9:00 AM Jul 24th, 10:00 AM

Developing an AI-Agent to Help Students Research: An Exploratory Study

Mangrove

This session will describe the results of an exploratory action research project to develop an AI-assistant to help first-year undergraduates perform their first research assignment in college. The different prompt engineering techniques used to develop this AI agent will be discussed (multi-shot, TRACI structure, etc.). Additionally, the viability and pragmatic challenges of creating such an AI-assistant will be discussed, with particular emphasis on the challenges of assessing generative AI outputs in a pedagogical context.

Accessibility Statement

This item was created or digitized prior to April 24, 2027, or is a reproduction of legacy media created before that date. It is preserved in its original, unmodified state specifically for research, reference, or historical recordkeeping. In accordance with the ADA Title II Final Rule, the University Libraries provides accessible versions of archival materials upon request. To request an accommodation for this item, please submit an accessibility request form.