Computational Thinking with Computer Vision: Developing AI Competency in an Introductory Computer Science Course

AI ethics can be taught effectively at introductory levels: The course demonstrated that students in beginner computer science classes can engage in "deep engagement with the complex challenges in today's AI landscape" through reading discussions, suggesting that ethical considerations shouldn't be reserved only for advanced AI courses.

Hands-on AI projects boost student confidence and belonging: The study found "improved sense of belonging, self-efficacy, and AI ethics awareness among students," with student-selected projects particularly supporting self-efficacy, indicating that practical experience with real AI applications helps beginners feel more capable and included in computer science.

Computer vision provides an accessible entry point to AI: Using computer vision as an application context allowed introductory students to develop both computational thinking skills and critical thinking about AI's societal implications, suggesting that concrete, visual AI applications may be more approachable for beginners than abstract AI concepts.

Early AI exposure improves career readiness: The research indicates that "an AI-focused context can enhance participation and employability," meaning students who learn AI fundamentals early in their CS education may have better job prospects as AI becomes increasingly central to the field.

Balancing technical and ethical AI education is feasible: The course successfully combined technical learning with critical thinking about AI's societal implications through "experiential activities such as individual projects and reading discussions," demonstrating that responsible AI education doesn't require choosing between technical competency and ethical awareness.