Decoding AI: Insights into Answer Variability Using Text Analytics 4:00

Alternative Title

Decoding Artificial Intelligence (AI): Insights into Answer Variability Using Text Analytics 4:00

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:

Generative AI; Text analytics; Answer variability; Education technology; Shiny App

Subjects

Artificial intelligence--Educational applications; Artificial intelligence--Computer-assisted instruction; Artificial intelligence--Statistical methods; Artificial intelligence--Study and teaching; Artificial intelligence--Research

Description

Many believe that generative AI platforms have the potential to revolutionize education by providing a personalized supplement to traditional education. Therefore, it is important to investigate the accuracy of output from generative AI platforms and the variations in results from the same prompt on different platforms. We examined differences in answers to statistics questions among several commonly used AI platforms employing text analytics, such as reading level evaluation, word counts, topic modeling, and sentiment analysis. In this session, we will introduce a Shiny App to perform these analytics for output from any generative AI platform.

Language

eng

Type

Presentation

Rights Statement

All Rights Reserved

Audience

Faculty; Students

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

Decoding AI: Insights into Answer Variability Using Text Analytics 4:00

Universal Center

Many believe that generative AI platforms have the potential to revolutionize education by providing a personalized supplement to traditional education. Therefore, it is important to investigate the accuracy of output from generative AI platforms and the variations in results from the same prompt on different platforms. We examined differences in answers to statistics questions among several commonly used AI platforms employing text analytics, such as reading level evaluation, word counts, topic modeling, and sentiment analysis. In this session, we will introduce a Shiny App to perform these analytics for output from any generative AI platform.