Preparing Students for AI-Driven Agile Development: A Project-Based AI Engineering Curriculum
Andreas Rausch, Stefan Wittek, Tobias Geger, David Inkermann

TL;DR
This paper introduces a project-based AI Engineering curriculum that integrates AI tools with agile practices to better prepare students for AI-driven software development, supported by a case study and early evaluation.
Contribution
It presents a novel curriculum design combining agile methods and AI competencies, along with a case study and initial evidence of its effectiveness.
Findings
AI tools enhance hands-on learning in agile projects
Curriculum supports interdisciplinary, AI-enabled student projects
Adaptations are needed for teaching agility with evolving AI tools
Abstract
Generative AI and agentic tools are reshaping agile software development, yet many engineering curricula still teach agile methods and AI competencies separately and largely lecture-based. This paper presents a project-based AI Engineering curriculum designed to prepare students for AI-driven agile development by integrating agile practices and AI-enabled engineering throughout the program. We contribute (1) the curriculum concept and guiding principles, (2) a case study of interdisciplinary, AI-enabled agile student projects, and (3) early evidence from a mixed-methods evaluation. In our case study, second-semester bachelor students work in teams over seven two-week sprints on a realistic software product. AI tools are embedded into everyday agile engineering tasks - requirements clarification, backlog refinement, architectural reasoning, coding support, testing, and documentation -…
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Teaching and Learning Programming · Ethics and Social Impacts of AI
