Enhancing Software Modeling Learning with AI-Powered Scaffolding

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.

Authors

Institutions

Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1145/3652620.3687776
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Software Modeling Learning with AI-Powered Scaffolding

Marta Cimitile, Mario Luca Bernardi, Michele Scalera, Pasquale Ardimento
Software Engineering Techniques and Practices
article

Enhancing Software Modeling Learning with AI-Powered Scaffolding

Marta Cimitile, Mario Luca Bernardi, Michele Scalera, Pasquale Ardimento
article en

Abstract

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.

University of Sannio (IT), Unitelma Sapienza University (IT), University of Bari Aldo Moro (IT)
Openalex Percentile: Top 70%
Software Engineering Techniques and Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enhancing Software Modeling Learning with AI-Powered Scaffolding — Marta Cimitile, Mario Luca Bernardi, et al. · (2024) | TGRS Research Map | TGRS