Enhancing Software Modeling Learning with AI-Powered Scaffolding
Pasquale Ardimento, Mario Luca Bernardi, Marta Cimitile, Michele Scalera · 2024
This study introduces an innovative AI-powered scaffolding approach aimed at enhancing software modeling learning through UML diagrams. The focus of this research is on defining the principles and functions comprising the scaffolding. Leveraging recent advancements in generative AI, our approach provides a structured educational framework to improve comprehension and proficiency in modeling concepts. We present the initial implementation of the scaffolding, specifically highlighting the feedback function. By integrating theoretical insights with practical applications, this study seeks to advance Model-Driven Software Engineering education and underscores the potential of AI in enhancing instructional methodologies.