Towards an Interoperable Model-driven Automated Assessment System for Computer Science Education

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Abstract

In recent years, the number of computer science students has steadily risen, but the time for educators to give feedback to the students remains the same. Because of this predicament, many systems for the automatic or semi-automatic assessment of student tasks were developed. A fundamental problem of this development is that most of these assessment systems deploy a different type of data representation, which leads to a lack of interoperability between the approaches. This hinders the reuse of teaching materials that need to match the targeted system, leading to situations in which instructors need to recreate their materials. In this work, we aim to close this gap by introducing a model-driven approach called Assisted Assessment. The approach uses a technology-independent assessment model to bridge instructors' and assessment systems' technical spaces, helping instructors to transform their material for various systems. We introduce Assisted Assessment by describing the scenario of an undergraduate course for software technology and how the approach can help to manage the different available assessment systems.

Details

OriginalspracheEnglisch
TitelMODELS Companion '24: Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems
ErscheinungsortLinz, Austria
Herausgeber (Verlag)Association for Computing Machinery
Seiten95-192
Seitenumfang8
ISBN (elektronisch)9798400706226
PublikationsstatusVeröffentlicht - 22 Sept. 2024
Peer-Review-StatusJa

Konferenz

Titel27th ACM / IEEE International Conference on Model Driven Engineering Languages and Systems
KurztitelMODELS 2024
Veranstaltungsnummer27
Dauer22 - 27 September 2024
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtJohannes Kepler Universität Linz
StadtLinz
LandÖsterreich

Externe IDs

ORCID /0000-0003-1537-7815/work/173054517
ORCID /0000-0002-3513-6448/work/173054767

Schlagworte

DFG-Fachsystematik nach Fachkollegium

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Schlagwörter

  • education, model-driven engineering, model-driven engineering, education, student assessment