A comparative analysis of student SQL and relational database knowledge using automated grading tools

BOISVERT, Charles, DOMDOUZIS, Konstantinos and LICENSE, Joshua (2018). A comparative analysis of student SQL and relational database knowledge using automated grading tools. In: Proceedings of the international symposium on computers in education (SIIE) 2018. IEEE.

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Official URL: https://ieeexplore.ieee.org/document/8586684
Link to published version:: https://doi.org/10.1109/SIIE.2018.8586684

Abstract

This paper evaluates a blended learning methodology for Relational Database Systems. Our module offers students a range of interconnected tools and teaching resources. Among them is \testsql, a query tool giving the students automated feedback on SQL query exercises; but we do not use it to assess the students. Instead assessment is through a range of questions which test not only SQL writing skills, but also other aspects of the field, including questions on optimisation, physical modelling, PL/SQL, and indirect questions on SQL knowledge, such as processing order. The effectiveness of the approach is investigated through a survey of student attitudes', and assessment data. Our analysis shows, unsurprisingly, that the students' use of more resources correlates significantly with better results; but also that success at the different sub-topics tested is not at all well correlated, which shows that students can master some topics while remaining weak at others; and finally, that indirect SQL questions is best predictor of success at each of the other sub-topics. This last result confirms our choice to broaden the testing of SQL skills, and has implications for the use automated SQL assessment tools: we recommend that in automated testing for Database Systems, SQL writing tests be complemented with indirect questions on keyword use, parsing, or error recognition aimed at revealing broader abilities of learners.

Item Type: Book Section
Additional Information: Proceedings of SIIE 2018, Cadiz, Spain, 19-21 September 2018
Uncontrolled Keywords: Computer Science Education, Structured Query Language, Automated assessment, Relational Databases
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.1109/SIIE.2018.8586684
Depositing User: Charles Boisvert
Date Deposited: 24 Aug 2018 08:31
Last Modified: 04 Jan 2019 09:32
URI: http://shura.shu.ac.uk/id/eprint/22250

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