New Perspectives in Science Education

The rapid advancement of generative AI is reshaping both industry [1]-[2] and higher education. While many institutions are still navigating how to respond, there is a timely opportunity to make small, strategic changes in curriculum design with long-term impact. This presentation proposes a practical approach to enriching Computer Science education by embedding AI tools across courses—forming an "AI track" similar to the existing academic skills track used in our computer science programs.

Building on prior work on academic literacy in computing education [3]-[4], this initiative highlights how AI-based tools—such as code-generation assistants, natural language processors, and AI-based project support—can be meaningfully integrated into learning activities. These integrations support not only tool literacy and ethical awareness but also prepare students for the changing expectations of the tech workforce.

Recent discussion [1] suggests that within just three years, the ability to program with an AI companion will be a key skill required by employers. As programming increasingly becomes a co-creative process between human and machine [5], educational institutions must prepare students to critically assess, refine, and collaborate with AI systems. The proposed AI track addresses this need by promoting early, guided exposure to AI-supported workflows throughout the Computer Science curriculum.

This presentation will share practical examples from Introduction to Computer Science, Fundamental Programming, more advanced Project-based, and Bachelor Thesis-level courses, demonstrating how AI can be used not to replace, but to enhance student learning and foster future-ready competencies—starting with minimal adjustments today.

Keywords:Computer Science Education, AI literacy and ethics, AI integration

References:

1. Eadicicco, L. (den 23 09 2025). cnn.com. Hämtat från Google says 90% of tech workers are now using AI at work: https://edition.cnn.com/2025/09/23/tech/google-study-90-percent-tech-jobs-ai

2. GitHubCopilot. (2025). GitHubCopilot. Hämtat från GitHubCopilot: https://github.com/features/copilot

3. Veletanlic, B., & Klonowska, K. (2015). Generella Kompetenser och Forskningsanknytning i Utbildningen - en Akademisk Slinga för Dataloger. Lärarlärdom, Växjö. doi:https://doi.org/10.15626/lld.201508

4. Klonowska, K., Teljega, M., & Einarson, D. (2023). A three-year academic track towards literacy in Sustainable Development: - A Computer Science Study Program Case. In SEFI (Ed.), European Society for Engineering Education: Engineering Education for Sustainability. Dublin, Ireland: SEFI. Retrieved from https://www.sefi2023.eu/

5. Sennersten, C., & Klonowska, K. (2025). Kandidatuppsats i Computer Science genererad av AI tools. Lärarlärdom. Karlskrona: BTH. Hämtat från https://www.bth.se/om-bth/sa-har-arbetar-vi/undervisning-och-larande/lararlardom/lararlardom-2025/program