How Artificial Intelligence Is Taught Today: A Mixed-Methods Analysis of Introductory AI Courses

To gain a better understanding about how the rapidly growing field of artificial intelligence is currently being taught in universities, 45 introductory AI course syllabi were analyzed. A mixed-methods strategy using quantitative frequency count analysis and qualitative thematic coding analysis was primarily utilized. Among other findings, the results showed that machine learning was the most taught topic across courses, followed by neural networks and large language models. The most common pedagogy utilized across the various disciplines was lecture-heavy instruction. Ethics-related content was present in many syllabi but varied widely in depth and structure. These findings highlight the key trends and patterns in how AI is taught in universities and the growing need for AI-related skills.