A Unified Teaching Platform for (No)SQL Databases

Vanessa Meyer, Lena Wiese, Ahmed Al-Ghezi

2024

Abstract

Databases form the basic backend for information systems. This paper describes the development of a digital learning tool to promote learning of (No)SQL databases like PostgreSQL, Cassandra, Neo4J and MongoDB and the underlying data models using the React library. The learning tool will be uniformly connected to each of the mentioned databases. Thus, students can enter and execute their database queries, which are needed to solve tasks for a given example scenario, directly in our learning tool. This allows students to fully concentrate on learning the respective query languages. In this study, we present the web application’s architecture and front-end design, which will be continuously extended with additional components, such as a learning analytics dashboard. With this approach we want to contribute to the improvement of teaching methods in the field of databases and create a basis for the further development of interactive learning tools.

Paper Citation

in Harvard Style

Meyer V., Wiese L. and Al-Ghezi A. (2024). A Unified Teaching Platform for (No)SQL Databases. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 374-381. DOI: 10.5220/0012724300003690

in Bibtex Style

@conference{iceis24,
author={Vanessa Meyer and Lena Wiese and Ahmed Al-Ghezi},
title={A Unified Teaching Platform for (No)SQL Databases},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={374-381},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012724300003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - A Unified Teaching Platform for (No)SQL Databases
SN - 978-989-758-692-7
AU - Meyer V.
AU - Wiese L.
AU - Al-Ghezi A.
PY - 2024
SP - 374
EP - 381
DO - 10.5220/0012724300003690
PB - SciTePress