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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

USING ORACLE QUERY PLAN FOR AUTOMATED ASSESSMENT OF SQL

Nelson, David, McGarry, Kenneth and Proud, Mark (2023) USING ORACLE QUERY PLAN FOR AUTOMATED ASSESSMENT OF SQL. In: 17th International Technology, Education and Development Conference, 6-8 March 2023, Valencia, Spain.

Item Type: Conference or Workshop Item (Paper)

Abstract

In our second-year undergraduate database foundations module students are exposed to using the Oracle cloud environment for developing SQL (Structured Query Language) queries. Their first summative assessment for the module is of a problem-solving nature, whereby they are expected to repair a partially developed SQL schema for a given scenario, before subsequently developing SQL queries based on the scenario. Marking this work can be laborious, error prone and time consuming, as well as requiring multiple sample solutions for each query which cater for all potential solutions that the students could produce. The aim of this paper is therefore to describe an early-stage prototype automated assessment system for marking the SQL queries developed by the students.

[img] Microsoft Word (Finalised copy of paper submitted to INTED 2023)
1296 Final Paper V2.docx - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

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More Information

Additional Information: Extended abstract was accepted and referred. Document uploaded is final submitted version.
Uncontrolled Keywords: SQL, automated marking, assessment
Related URLs:
Depositing User: David Nelson

Identifiers

Item ID: 15882
URI: http://sure.sunderland.ac.uk/id/eprint/15882
Official URL: https://iated.org/inted/

Users with ORCIDS

ORCID for David Nelson: ORCID iD orcid.org/0000-0002-0868-9100
ORCID for Kenneth McGarry: ORCID iD orcid.org/0000-0002-9329-9835

Catalogue record

Date Deposited: 03 Apr 2023 12:52
Last Modified: 11 Apr 2023 08:24

Contributors

Author: David Nelson ORCID iD
Author: Kenneth McGarry ORCID iD
Author: Mark Proud

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Computing > Databases
Education > Learning Technology

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