Abstract
In computer science as in many fields, practice activities are essential to facilitate skill acquisition. Nevertheless, developing and correcting questions are time consuming tasks. That is the case, in particular, for traditional and online SQL courses which include many SQL questions to be created and corrected. SQL learners need to practice more writing SQL statements in order to better understand and correct their syntactic and semantic errors. To overcome the difficulty of creating questions from scratch, research proposes to automatically generate such questions.
In this work, we propose a system that teachers can use to automatically produce SQL questions sorted by difficulty level. Instead of creating SQL questions, teachers only propose a database schema. Learners can also use the system to answer SQL questions and get appropriate feedback to improve their skills.
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Basse, A., Diatta, B., Ouya, S. (2021). Ontology-Based System for Automatic SQL Exercises Generation. In: Auer, M.E., Tsiatsos, T. (eds) Internet of Things, Infrastructures and Mobile Applications. IMCL 2019. Advances in Intelligent Systems and Computing, vol 1192. Springer, Cham. https://doi.org/10.1007/978-3-030-49932-7_69
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DOI: https://doi.org/10.1007/978-3-030-49932-7_69
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