Automatic, Configurable and Partial Assessment of Student SQL Queries with Joins and Groupings

Many papers exist that research semiautomated or fully-automated assessment of SQL queries in the context of high education, as this approach promises less load on teachers, more consistent assessment across all students and faster feedback to students. Instead of assessment process that results either in all or none marks awarded for a query, high education standards are more in favor of providing partial marks. This, and the fact that there should be an easy way for a teacher to customize assessment rules to adapt them to institution standards, makes assessment process more complex so many currently available tools fall short. This paper presents a newly developed fully-automated assessment model and an information system that implements it system and explores the possibilities of using it for partial assessment in higher education. This assessment model is designed to support complex joins and groupings, making it more applicable for real students' assignments and resulting queries. Students also get the immediate results and a list of found issues with their queries, which is very important for them in process of learning. In this paper, built system is compared with manual assessments of the same student queries and its shows promising results, even for very complex joins and groupings.