Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success

Alireza Ahadi; Vahid Behbood; Arto Vihavainen; Julia Prior; Raymond Lister

doi:10.1145/2839509.2844640

Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success

Alireza Ahadi, Vahid Behbood, Arto Vihavainen, Julia Prior, Raymond Lister

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

68 Citations (Scopus)

Abstract

The computing education community has studied extensively the errors of novice programmers. In contrast, little attention has been given to student's mistake in writing SQL statements. This paper represents the first large scale quantitative analysis of the student's syntactic mistakes in writing different types of SQL queries. Over 160 thousand snapshots of SQL queries were collected from over 2000 students across eight years. We describe the most common types of syntactic errors that students make. We also describe our development of an automatic classifier with an overall accuracy of 0.78 for predicting student performance in writing SQL queries.

Original language	English
Title of host publication	SIGCSE 2016
Subtitle of host publication	Proceedings of the 47th ACM Technical Symposium on Computing Science Education
Place of Publication	New York, NY
Publisher	Association for Computing Machinery, Inc
Pages	401-406
Number of pages	6
ISBN (Electronic)	9781450338561
ISBN (Print)	9781450336857
DOIs	https://doi.org/10.1145/2839509.2844640
Publication status	Published - 2016
Externally published	Yes
Event	ACM Technical Symposium on Computing Science Education (47th : 2016) - Memphis, United States Duration: 2 Mar 2016 → 5 Mar 2016

Conference

Conference	ACM Technical Symposium on Computing Science Education (47th : 2016)
Abbreviated title	SIGCSE 2016
Country/Territory	United States
City	Memphis
Period	2/03/16 → 5/03/16

Keywords

online assessment
databases
SQL queries
machine learning

Access to Document

10.1145/2839509.2844640

Cite this

Ahadi, A., Behbood, V., Vihavainen, A., Prior, J., & Lister, R. (2016). Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success. In SIGCSE 2016: Proceedings of the 47th ACM Technical Symposium on Computing Science Education (pp. 401-406). Association for Computing Machinery, Inc. https://doi.org/10.1145/2839509.2844640

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title = "Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success",

abstract = "The computing education community has studied extensively the errors of novice programmers. In contrast, little attention has been given to student's mistake in writing SQL statements. This paper represents the first large scale quantitative analysis of the student's syntactic mistakes in writing different types of SQL queries. Over 160 thousand snapshots of SQL queries were collected from over 2000 students across eight years. We describe the most common types of syntactic errors that students make. We also describe our development of an automatic classifier with an overall accuracy of 0.78 for predicting student performance in writing SQL queries.",

keywords = "online assessment, databases, SQL queries, machine learning",

author = "Alireza Ahadi and Vahid Behbood and Arto Vihavainen and Julia Prior and Raymond Lister",

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doi = "10.1145/2839509.2844640",

language = "English",

isbn = "9781450336857",

pages = "401--406",

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publisher = "Association for Computing Machinery, Inc",

note = "ACM Technical Symposium on Computing Science Education (47th : 2016), SIGCSE 2016 ; Conference date: 02-03-2016 Through 05-03-2016",

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Ahadi, A, Behbood, V, Vihavainen, A, Prior, J & Lister, R 2016, Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success. in SIGCSE 2016: Proceedings of the 47th ACM Technical Symposium on Computing Science Education. Association for Computing Machinery, Inc, New York, NY, pp. 401-406, ACM Technical Symposium on Computing Science Education (47th : 2016), Memphis, United States, 2/03/16. https://doi.org/10.1145/2839509.2844640

Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success. / Ahadi, Alireza; Behbood, Vahid; Vihavainen, Arto et al.
SIGCSE 2016: Proceedings of the 47th ACM Technical Symposium on Computing Science Education. New York, NY: Association for Computing Machinery, Inc, 2016. p. 401-406.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Prior, Julia

AU - Lister, Raymond

PY - 2016

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AB - The computing education community has studied extensively the errors of novice programmers. In contrast, little attention has been given to student's mistake in writing SQL statements. This paper represents the first large scale quantitative analysis of the student's syntactic mistakes in writing different types of SQL queries. Over 160 thousand snapshots of SQL queries were collected from over 2000 students across eight years. We describe the most common types of syntactic errors that students make. We also describe our development of an automatic classifier with an overall accuracy of 0.78 for predicting student performance in writing SQL queries.

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KW - databases

KW - SQL queries

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EP - 406

BT - SIGCSE 2016

PB - Association for Computing Machinery, Inc

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T2 - ACM Technical Symposium on Computing Science Education (47th : 2016)

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Ahadi A, Behbood V, Vihavainen A, Prior J, Lister R. Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success. In SIGCSE 2016: Proceedings of the 47th ACM Technical Symposium on Computing Science Education. New York, NY: Association for Computing Machinery, Inc. 2016. p. 401-406 doi: 10.1145/2839509.2844640

Students' syntactic mistakes in writing seven different types of SQL queries and its application to predicting students' success

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