Document Type
Article
Publication Date
7-2022
Publication Title
ITiCSE '22: Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education
Volume
1
Pages
131 - 137
Publisher Name
ACM
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.
Identifier
ISBN 978-1-4503-9201-3/22/07
Recommended Citation
Y. N. Silva, A. Loza, H. Razente. DBSnap-Eval: Identifying Database Query Construction Patterns. The 27th ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), Dublin, Ireland, 2022.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Copyright Statement
© Yasin N Silva , Alexis Loza , Humberto Razente, 2022.
Comments
Author Posting. © Yasin N Silva , Alexis Loza , Humberto Razente, 2022. This is the author's version of the work. It is posted here by permission of Association for Computing Machinery for personal use, not for redistribution. The definitive version will be published in Proceedings of 27th ACM Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), June 2022,https://doi.org/10.1145/3502718.3524822