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What to Expect and What to Focus on in SQL Query Teaching

Published: 22 February 2019 Publication History

Abstract

In the process of learning a new computer language, writing erroneous statements is part of the learning experience. However, some errors persist throughout the query writing process and are never corrected. Structured Query Language (SQL) consists of a number of different concepts such as expressions, joins, grouping and ordering, all of which by nature invite different possible errors in the query writing process. Furthermore, some of these errors are relatively easy for a student to fix when compared to others. Using a data set from three student cohorts with the total of 744 students, we set out to explore which types of errors are persistent, i.e., more likely to be left uncorrected by the students. Additionally, based on the results, we contemplate which types of errors different query concepts seem to invite. The results show that syntax and semantic errors are less likely to persist than logical errors and complications. We expect that the results will help us understand which kind of errors students struggle with, and e.g., help teachers generate or choose more appropriate data for students to use when learning SQL.

References

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Alireza Ahadi, Vahid Behbood, Arto Vihavainen, Julia Prior, and Raymond Lister. 2016a. Students' Syntactic Mistakes in Writing Seven Different Types of SQL Queries and its Application to Predicting Students' Success. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education (SIGCSE '16) . ACM Press, New York, New York, USA, 401--406.
[2]
Alireza Ahadi, Julia Prior, Vahid Behbood, and Raymond Lister. 2015. A Quantitative Study of the Relative Difficulty for Novices of Writing Seven Different Types of SQL Queries. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '15) . ACM Press, New York, New York, USA, 201--206.
[3]
Alireza Ahadi, Julia Prior, Vahid Behbood, and Raymond Lister. 2016b. Students' Semantic Mistakes in Writing Seven Different Types of SQL Queries. In Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education (SIGCSE '16). 272--277.
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Stefan Brass and Christian Goldberg. 2005. Semantic errors in SQL queries: A quite complete list. Journal of Systems and Software, Vol. 79, 5 (2005), 630--644.
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Luca Cagliero, Luigi De Russis, Laura Farinetti, and Teodoro Montanaro. 2018. Improving the Effectiveness of SQL Learning Practice: A Data-Driven Approach. In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Vol. 01. 980--989.
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cover image ACM Conferences
SIGCSE '19: Proceedings of the 50th ACM Technical Symposium on Computer Science Education
February 2019
1364 pages
ISBN:9781450358903
DOI:10.1145/3287324
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 22 February 2019

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Author Tags

  1. database education
  2. error
  3. query language
  4. relational database
  5. sql

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SIGCSE '19 Paper Acceptance Rate 169 of 526 submissions, 32%;
Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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  • (2024)LEARNDB: A Comprehensive Toolkit for Database EducationProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635526(1861-1862)Online publication date: 14-Mar-2024
  • (2024)FROM Syntax to Semantics: An OER-Powered SQL Learning and Visualisation Tool2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC61105.2024.00219(1522-1523)Online publication date: 2-Jul-2024
  • (2023)“There is no ambiguity on what to return”: Investigating the Prevalence of SQL MisconceptionsProceedings of the 23rd Koli Calling International Conference on Computing Education Research10.1145/3631802.3631821(1-12)Online publication date: 13-Nov-2023
  • (2023)Framework for SQL Error Message Design: A Data-Driven ApproachACM Transactions on Software Engineering and Methodology10.1145/360718033:1(1-50)Online publication date: 23-Nov-2023
  • (2023)Student's Learning Challenges with Relational, Document, and Graph Query LanguagesProceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research10.1145/3596673.3596976(30-36)Online publication date: 23-Jun-2023
  • (2023)Mining SQL Problem Solving Patterns using Advanced Sequence Processing AlgorithmsProceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research10.1145/3596673.3596973(37-43)Online publication date: 23-Jun-2023
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  • (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
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