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SQLVis: Visual Query Representations for Supporting SQL Learners

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Abstract

SQL is a typical query language for performing data analytics. Although its usage is ubiquitous, learners experience that query formulation in SQL is error-prone and time-consuming. Prior research has shown that this is due to low expressive ease, extensive training requirements and high cognitive load, all of which present a significant burden for SQL learners. Visual representations can assist learners to significantly lower this burden. The current dominant paradigm aims to facilitate SQL querying by helping users to avoid the syntax of SQL. Such Visual Querying Systems (VQS), however, are not effective for SQL learners as they hide the syntax of the language during query formulation, rather than assisting learners to write correct queries in SQL. Furthermore, training with VQSs is system specific, which leads to system dependency for learners. We argue that novices need support from Visual Query Representation (VQR) solutions which, instead, help them in learning how to write correct and portable SQL queries. In this paper we present SQLVis, a VQR to support novice SQL users in query writing. Our system represents the query as written in SQL by the user, which can improve the SQL writing proficiency of its users. Results of an in depth empirical study demonstrate the significant value of SQLVis for learners.
Original languageEnglish
Title of host publicationProceedings - 2021 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2021
EditorsKyle Harms, Jácome Cunha, Steve Oney, Caitlin Kelleher
PublisherInstitute of Electrical and Electronics Engineers
Number of pages9
ISBN (Electronic)978-1-6654-4592-4
DOIs
Publication statusPublished - 29 Oct 2021
EventIEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2021 - St. Louis, United States
Duration: 10 Oct 202113 Oct 2021

Conference

ConferenceIEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2021
Abbreviated titleVL/HCC 2021
Country/TerritoryUnited States
CitySt. Louis
Period10/10/2113/10/21

Keywords

  • Query language
  • Visualization techniques
  • Computer science education
  • Structured Query Language
  • Computer Science education
  • Query languages
  • Visualization techniques and methodologies

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