Generating SQL-Query-Items Using Knowledge Graphs

Paul Christ, Torsten Munkelt, Jörg M. Haake

2025

Abstract

SQL is still one of the most popular languages used in todays industry across many fields. Poorly written SQL remains one of the root causes of performance issues. Thus, achieving a high level of mastery for SQL is important. Achieving mastery requires practicing with many SQL assessment items of varying complexity and content. The manual creation of such items is very labor-some and expensive. Automatic item generation reduces the cost of item creation. This paper proposes an approach for automatically generating SQL-query items of varying complexity, content, and human-like natural language problem statements (NLPS). The approach is evaluated by human raters regarding the complexity and plausibility of the generated SQL-queries and the preference between two alternative NLPS. The results show agreement on the plausibility of the generated SQL-queries, while the complexity and the NLPS preference show higher variance.

Paper Citation

in Harvard Style

Christ P., Munkelt T. and Haake J. (2025). Generating SQL-Query-Items Using Knowledge Graphs. In Proceedings of the 17th International Conference on Computer Supported Education - Volume 1: AIG; ISBN 978-989-758-746-7, SciTePress, pages 785-796. DOI: 10.5220/0013498300003932

in Bibtex Style

@conference{aig25,
author={Paul Christ and Torsten Munkelt and Jörg Haake},
title={Generating SQL-Query-Items Using Knowledge Graphs},
booktitle={Proceedings of the 17th International Conference on Computer Supported Education - Volume 1: AIG},
year={2025},
pages={785-796},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013498300003932},
isbn={978-989-758-746-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Computer Supported Education - Volume 1: AIG
TI - Generating SQL-Query-Items Using Knowledge Graphs
SN - 978-989-758-746-7
AU - Christ P.
AU - Munkelt T.
AU - Haake J.
PY - 2025
SP - 785
EP - 796
DO - 10.5220/0013498300003932
PB - SciTePress