mlsanityData to 14 Oct 2026

Artificial Intelligence Driven Course Generation: A Case Study Using ChatGPT

arXiv 2411.01369 ↗First posted 2 Nov 2024cs.CL cs.CYcited by 0

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Abstract (arXiv)

This study explores Artificial Intelligence use, specifically ChatGPT, in creating educational content. The study aims to elaborate on using ChatGPT to create course materials. The main objective is to assess the efficiency, quality, and impact of AI-driven course generation, and to create a Multimedia Databases course as a case study. The study highlights the potential of AI to revolutionize educational content creation, making it more accessible, personalized, and efficient. The course content was generated in less than one day through iterative methods, using prompts for translation, content expansion, practical examples, assignments, supplementary materials, and LaTeX formatting. Each part was verified immediately after generation to ensure accuracy. Post-generation analysis with Detectia and Turnitin showed similarity rates of 8.7% and 13%, indicating high originality. Experts and university committees reviewed and approved the course, with English university teachers praising its language quality. ChatGPT also created a well-structured and diversified exam for the module. Key findings reveal significant time efficiency, comprehensive content coverage, and high flexibility. The study underscores AI's transformative potential in education, addressing challenges related to data privacy, technology dependence, content accuracy, and algorithmic biases. The conclusions emphasize the need for collaboration between educators, policymakers, and technology developers to harness AI's benefits in education fully.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 13 references that are in the map. First posted on arXiv 2 Nov 2024.

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References · 1

  1. 2023Analyzing ChatGPT's Aptitude in an Introductory Computer Engineering Coursecited by 5

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