research-article

Open access

Engaging Databases for Data Systems Education

Authors:

Daphne Miedema,

Efthimia AivaloglouAuthors Info & Claims

ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1

Pages 334 - 340

https://doi.org/10.1145/3587102.3588804

Published: 30 June 2023 Publication History

Abstract

Querying a relational database is typically taught in practice by using an exercise database. Such databases may be simple toy examples or elaborate and complex schemas that mimic the real world. Which of these are preferable for students is yet unknown. Research has shown that while more complex exercise databases may hinder learning, they also benefit student engagement, as more complex databases are seen as more realistic. In our mixed-methods study, we explore what aspects of an exercise database contribute to student engagement in database education. To gain insight into what students would deem engaging, we asked 56 students to design, implement, and reflect on engaging databases for database education. The results imply that students are engaged by highly diverse yet easily understood database business domains, relatively simple database structures, and conceivable yet seemingly realistic amounts of data. The results challenge some previous study results while supporting approaches found in some textbooks, and provide guidelines and inspiration for educators designing exercise databases for querying and introducing relational database concepts.

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Cited By

Aerts WFletcher GMiedema D(2024)A Feasibility Study on Automated SQL Exercise Generation with ChatGPT-3.5Proceedings of the 3rd International Workshop on Data Systems Education: Bridging education practice with education research10.1145/3663649.3664368(13-19)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3663649.3664368
Miedema D(2023)Toward a Fundamental Understanding of SQL EducationProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 210.1145/3568812.3603454(64-68)Online publication date: 7-Aug-2023
https://dl.acm.org/doi/10.1145/3568812.3603454

Index Terms

Engaging Databases for Data Systems Education
1. Applied computing
  1. Education
2. Information systems
  1. Data management systems
    1. Data structures

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cover image ACM Conferences

ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1

June 2023

694 pages

ISBN:9798400701382

DOI:10.1145/3587102

General Chairs:
Mikko-Jussi Laakso
University of Turku, Finland
,
Mattia Monga
University of Milan, Italy
,
Program Chairs:
Simon
Unaffiliated, Australia
,
Judithe Sheard
Monash University, Australia

Copyright © 2023 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGCSE: ACM Special Interest Group on Computer Science Education

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Association for Computing Machinery

New York, NY, United States

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Published: 30 June 2023

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ITiCSE 2023: Innovation and Technology in Computer Science Education

July 7 - 12, 2023

Turku, Finland

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Cited By

Aerts WFletcher GMiedema D(2024)A Feasibility Study on Automated SQL Exercise Generation with ChatGPT-3.5Proceedings of the 3rd International Workshop on Data Systems Education: Bridging education practice with education research10.1145/3663649.3664368(13-19)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3663649.3664368
Miedema D(2023)Toward a Fundamental Understanding of SQL EducationProceedings of the 2023 ACM Conference on International Computing Education Research - Volume 210.1145/3568812.3603454(64-68)Online publication date: 7-Aug-2023
https://dl.acm.org/doi/10.1145/3568812.3603454

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