AI-Enhanced Lean Six Sigma Framework for Building Software Sector Quality Competencies in Engineering
DOI:
https://doi.org/10.16920/jeet/2026/v39is2/26064Keywords:
AI in Education; DMAIC; Lean Six Sigma; Software Sector; Engineering Education; Quality Competencies.Abstract
The goal of this study is to use an AI-enhanced framework to systematically add Lean Six Sigma (LSS) ideas to software engineering project-based courses. The goal is to help software engineering students do better work that is useful to the industry. The framework's goal is to include process thinking and an emphasis on quality to the undergraduate engineering curriculum. It employs a Design-Based Research (DBR) method to put the DMAIC (Define-Measure-Analyze-Improve-Control) quality improvement model into action. AI agents allow for continual improvement by using contextual feedback loops, fault grouping, documentation scaffolding, and real-time reflective analytics. Results from empirical validation across the two semesters demonstrate significant enhancement in both technical and process-oriented learning, evidenced by a 35% reduction in software faults and a 42% increase in DMAIC documentation completeness. This research explains why the framework was created, how AI fits into it, how it is used in the classroom, and how it affects student success. The primary objective of the intervention and its results, which are components of a broader research initiative, is to enhance software engineering education by establishing more structured and quality-focused learning environments.
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