MODELS 2024
Sun 22 - Fri 27 September 2024 Linz, Austria

Domain modeling is an essential component in many software engineering courses since it serves as a way to represent and understand the concepts and relationships in a problem domain. Course instructors evaluate student-generated diagrams manually, comparing them against a reference solution and providing feedback. However, as enrollment in software engineering courses continues to rise, manual grading of a large number of student submissions becomes an overwhelming and time-intensive task for instructors.Hence, there is a need for automated assessment of domain models which assists course instructors during the grading process. In this paper, we propose a novel text embedding-based approach that automatizes the assessment of domain models expressed in a textual domain-specific language, against reference solutions created by modeling experts. Our algorithm showcases remarkable proficiency in matching model elements across domain models, achieving an F1-score of 0.82 for class matching, 0.75 for attribute matching, and 0.80 for relation matching. Our algorithm also yields grades highly correlated with human grader assessments, with correlations exceeding 0.8 and mean absolute errors below 0.05.

Tue 24 Sep

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

11:00 - 12:30
Session 2: Low-Code, Executable Objects and EmbeddingsEducators Symposium at T - Super Mario Bros
Chair(s): Eugene Syriani Université de Montréal
11:00
30m
Talk
UML++: Enhancing Student Learning of Object-Oriented Modeling through Executable Objects
Educators Symposium
Pierre Maier University of Duisburg-Essen, Tobias Schwarz University of Duisburg-Essen
DOI File Attached
11:30
30m
Talk
Teaching Model-Driven Low-Code Development Platforms
Educators Symposium
Joel Charles RWTH Aachen University, Judith Michael RWTH Aachen University, Lukas Netz RWTH Aachen University, Bernhard Rumpe RWTH Aachen University
File Attached
12:00
30m
Talk
Embedding-based Automated Assessment of Domain Models
Educators Symposium
Kua Chen , Boqi Chen McGill University, Yujing Yang McGill University, Gunter Mussbacher McGill University, Daniel Varro Linköping University / McGill University
File Attached