Artificial Intelligence Driven Course Generation: A Case Study Using ChatGPT
Djaber ROUABHIA
Chahid Cheikh Laarbi Tebessi University, Tebessa, Algeria
djaber.rouabhia@univ-tebessa.dz
https://orcid.org/0000-0002-9805-3017
Abstract
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.
Keywords: Attitudes, digital literacy, EFL learners, information and communication technologies, university students
DOI:
https://doi.org/10.70091/atras/AI.18
How to Cite this Paper :
Rouabhia, D. (2024). Artificial Intelligence Driven Course Generation: A Case Study Using ChatGPT. Atras Journal, 5 (Special Issue), 287-302.
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