DigitalCommons@Kennesaw State University - C-Day Computing Showcase: GRM-041 AI-Driven Analysis of OpenALG Curriculum: Mapping AI Competencies Across Georgia’s Higher Education Landscape

 

Location

https://www.kennesaw.edu/ccse/events/computing-showcase/sp25-cday-program.php

Streaming Media

Document Type

Event

Start Date

15-4-2025 4:00 PM

Description

This project investigates the presence of artificial intelligence (AI) competencies across Georgia’s higher education curriculum using university course catalogs as the primary data source, supplemented by OpenALG materials. We applied large language models, including OpenAI’s ChatGPT and embedding APIs, to analyze over 34,000 courses summarizing content, classifying AI relevance, and mapping to global frameworks (AI4K12 and UNESCO). Techniques such as topic clustering, semantic similarity analysis, and geographic distribution mapping were used to uncover patterns in AI integration. Findings reveal that AI content is concentrated in computing disciplines and research universities, with limited coverage in community colleges, MSIs, and non-technical fields. The results highlight the need for more equitable and interdisciplinary AI education across Georgia’s institutions.

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Apr 15th, 4:00 PM

GRM-041 AI-Driven Analysis of OpenALG Curriculum: Mapping AI Competencies Across Georgia’s Higher Education Landscape

https://www.kennesaw.edu/ccse/events/computing-showcase/sp25-cday-program.php

This project investigates the presence of artificial intelligence (AI) competencies across Georgia’s higher education curriculum using university course catalogs as the primary data source, supplemented by OpenALG materials. We applied large language models, including OpenAI’s ChatGPT and embedding APIs, to analyze over 34,000 courses summarizing content, classifying AI relevance, and mapping to global frameworks (AI4K12 and UNESCO). Techniques such as topic clustering, semantic similarity analysis, and geographic distribution mapping were used to uncover patterns in AI integration. Findings reveal that AI content is concentrated in computing disciplines and research universities, with limited coverage in community colleges, MSIs, and non-technical fields. The results highlight the need for more equitable and interdisciplinary AI education across Georgia’s institutions.