Students semantic mistakes in writing seven different types of SQL queries

Alireza Ahadi, Julia Prior, Vahid Behbood, Raymond Lister

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

50 Citations (Scopus)

Abstract

Computer science researchers have studied extensively the mistakes of novice programmers. In comparison, little attention has been given to studying the mistakes of people who are novices at writing database queries. This paper represents the first large scale analysis of students' semantic mistakes in writing different types of SQL SELECT statements. Over 160 thousand snapshots of SQL queries were collected from over 2300 students across nine years. We describe the most common semantic mistakes that these students made when writing different types of SQL statements, and suggest reasons behind those mistakes. We mapped the semantic mistakes we identified in our data to different semantic categories found in the literature. Our findings show that the majority of semantic mistakes are of the type "omission". Most of these omissions happen in queries that require a JOIN, a subquery, or a GROUP BY operator. We conclude that it is important to explicitly teach students techniques for choosing the appropriate type of query when designing a SQL query.

Original languageEnglish
Title of host publicationITiCSE 2016
Subtitle of host publicationProceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
Pages272-277
Number of pages6
ISBN (Electronic)9781450342315
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event2016 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2016 - Arequipa, Peru
Duration: 11 Jul 201613 Jul 2016

Conference

Conference2016 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2016
Country/TerritoryPeru
CityArequipa
Period11/07/1613/07/16

Keywords

  • online assessment
  • databases
  • SQL queries

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