Comparative Analysis Vision of Worldwide AI Courses
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Abstract (arXiv)
This research investigates the curriculum structures of undergraduate Artificial Intelligence (AI) education across universities worldwide. By examining the curricula of leading universities, the research seeks to contribute to a deeper understanding of AI education on a global scale, facilitating the alignment of educational practices with the evolving needs of the AI landscape. This research delves into the diverse course structures of leading universities, exploring contemporary trends and priorities to reveal the nuanced approaches in AI education. It also investigates the core AI topics and learning contents frequently taught, comparing them with the CS2023 curriculum guidance to identify convergence and divergence. Additionally, it examines how universities across different countries approach AI education, analyzing educational objectives, priorities, potential careers, and methodologies to understand the global landscape and implications of AI pedagogy.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 4 Jun 2024.
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2 of 15 references.
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Citing papers per year: 2026: 1.
1 paper.