DBSnap-Eval: Identifying Database Query Construction Patterns
Pages 131 - 137
Abstract
Learning to construct database queries can be a challenging task because students need to learn the specific query language syntax as well as properly understand the effect of each query operator and how multiple operators interact in a query. While some previous studies have looked into the types of database query errors students make and how the availability of expected query results can help to increase the success rate, there is very little that is known regarding the patterns that emerge while students are constructing a query. To be able to look into the process of constructing a query, in this paper we introduce DBSnap-Eval, a tool that supports tree-based queries (similar to SQL query plans) and a block-based querying interface to help separate the syntax and semantics of a query. DBSnap-Eval closely monitors the actions students take to construct a query such as adding a dataset or connecting a dataset with an operator. This paper presents an initial set of results about database query construction patterns using DBSnap-Eval. Particularly, it reports identified patterns in the process students follow to answer common database queries.
References
[1]
Alireza Ahadi, Vahid Behbood, Arto Vihavainen, Julia Prior, and Raymond Lister. 2016. Students' Syntactic Mistakes in Writing Seven Different Types of SQL Queries and Its Application to Predicting Students' Success. In ACM Technical Symposium on Computing Science Education (SIGCSE'16) (Memphis, TN). ACM, 401--406. https://doi.org/10.1145/2839509.2844640.
[2]
Alireza Ahadi, Julia Prior, Vahid Behbood, and Raymond Lister. 2016. Students' Semantic Mistakes in Writing Seven Different Types of SQL Queries. In ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE'16) (Arequipa, Peru). ACM, 272--277. https://doi.org/10.1145/2899415.2899464.
[3]
Jevri Tri Ardiansah, Aji Prasetya Wibawa, Triyanna Widyaningtyas, and Okazaki Yasuhisa. 2017. SQL Logic Error Detection by Using Start End Mid Algorithm. Knowledge Engineering and Data Science 1, 1 (2017), 33--38. https://doi.org/10.17977/um018v1i12018p33--38.
[4]
Anthony Kleerekoper and Andrew Schofield. 2018. SQL Tester: An Online SQL Assessment Tool and Its Impact. In ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE'2018) (Larnaca, Cyprus). ACM, 87--92. https://doi.org/10.1145/3197091.3197124.
[5]
Ana Paula Appel, Elaine Quintino da Silva, Caetano Traina Jr., and Agma J. M. Traina. 2004. iDFQL: a query-based tool to help the teaching process of the relational algebra. In World Congress on Engineering and Technology Education (WCETE). 179--184.
[6]
Adriano Lino, Álvaro Rocha, Luís Macedo, and Amanda Sizo. 2019. Application of clustering-based decision tree approach in SQL query error database. Future Generation Computer Systems 93 (2019), 392--406. https://doi.org/10.1016/j.future.2018.10.038.
[7]
Andrew Migler and Alex Dekhtyar. 2020. Mapping the SQL Learning Process in Introductory Database Courses. In ACM Technical Symposium on Computer Science Education (SIGCSE'20) (Portland, OR). ACM, 619--625. https://doi.org/10.1145/3328778.3366869.
[8]
George Obaido, Abejide Ade-Ibijola, and Hima Vadapalli. 2019. Generating SQL Queries from Visual Specifications. In ICT Education. Springer, 315--330. https://doi.org/10.1007/978--3-030-05813--5_21.
[9]
Nicolai Pöhner, Timo Schmidt, André Greubel, Martin Hennecke, and Matthias Ehmann. 2019. BlocklySQL: A New Block-Based Editor for SQL. In Workshop in Primary and Secondary Computing Education (WiPSCE'19) (Glasgow, Scotland). ACM. https://doi.org/10.1145/3361721.3362104.
[10]
Yasin N. Silva and Jaime Chon. 2015. DBSnap: Learning Database Queries by Snapping Blocks. In ACM Technical Symposium on Computer Science Education (SIGCSE'15) (Kansas City, MO). ACM, 179--184. https://doi.org/10.1145/2676723.2677220.
[11]
Yasin N. Silva and Jaime Chon. 2015. Querying databases by snapping blocks. In International Conference on Data Engineering (ICDE) (Seoul, South Korea). IEEE, 1472--1475. https://doi.org/10.1109/ICDE.2015.7113404.
[12]
Toni Taipalus and Piia Perälä. 2019. What to Expect and What to Focus on in SQL Query Teaching. In ACM Technical Symposium on Computer Science Education (SIGCSE'19) (Minneapolis, MN). ACM, 198--203. https://doi.org/10.1145/3287324.3287359.
[13]
UC Berkeley. 2013. Snap! Website. http://snap.berkeley.edu/.
[14]
Jason Gorman, Sebastian Gsell, and Chris Mayfield. 2014. Learning Relational Algebra by Snapping Blocks. In ACM Technical Symposium on Computer Science Education (SIGCSE'14) (Atlanta, GA). ACM, 73--78. https://doi.org/10.1145/2538862.2538961.
[15]
Moshé M. Zloof. 1975. Query by Example. In Proceedings of the National Computer Conference and Exposition (AFIPS'75) (Anaheim, CA). ACM, 431--438. https://doi.org/10.1145/1499949.1500034.
[16]
Eckart Modrow. 2018. SQLsnap!. Retrieved May 18, 2020 from http://snapextensions.uni-goettingen.de/.
[17]
Pritam Mitra. 2009. Relational Algebra Learning Tool. Technical Report, Dept. Computing, Imperial College London. Retrieved May 18, 2020 from https://www.doc.ic.ac.uk/~pjm/teaching/student_projects/pm105_report.pdf.
[18]
Blockly. 2012. Blockly: A JavaScript library for building visual programming editors. Retrieved from https://developers.google.com/blockly.
[19]
Yasin N. Silva, Anthony Nieuwenhuyse, Thomas G. Schenk, and Alaura Symons. 2018. DBSnap++: Creating Data-Driven Programs by Snapping Blocks. In ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE'2018) (Larnaca, Cyprus). ACM, 170--175. https://doi.org/10.1145/3197091.3197114.
[20]
Yasin N. Silva, Isadora Almeida, and Michell Queiroz. 2016. SQL: From Traditional Databases to Big Data. In ACM Technical Symposium on Computing Science Education (SIGCSE'16) (Memphis, Tennessee). ACM, 413--418. https://doi.org/10.1145/2839509.2844560.
[21]
Yasin N. Silva. 2022. DBSnap-Eval source-code. Retrieved from https://ysilva.cs.luc.edu/dbsnap/files/dbsnap-eval.zip.
Index Terms
- DBSnap-Eval: Identifying Database Query Construction Patterns
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ISBN:9781450392013
DOI:10.1145/3502718
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Published: 07 July 2022
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