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Project: Develop a metric to quantify query formulation problems in SQL


SQL has proven to be difficult for students to use effectively. Various papers have been written on the types and frequencies of SQL errors. However, this does not mean that all errors are equal. Some errors may inhibit query formulation much more than others.

To be able to argue more about which errors have what effect, we would like to quantify errors in query formulation. This means we want to give scores to errors (and perhaps to other types of struggles too). Then, if we aggregate over or plot all scores of a student, we can measure the extent to which they struggled. One suggestion comes from Poulsen et al., who suggest to develop an Error Quotient for SQL, based on the work by Jadud on programming.

In this project, you develop a metric to quantify novices’ struggles in SQL. This involves the analysis of query logs, the calculation of effects, and the creation of a model. This model can then be used by SQL teachers to identify problematic material, such that they know what they should be teaching in more detail.

Further reading:
  • Jadud, M. C. (2006). Methods and tools for exploring novice compilation behaviour. ICER 2006 - Proceedings of the 2nd International Computing Education Research Workshop, 2006, 73–84. source
  • Poulsen, S., Butler, L., Alawini, A., & Herman, G. L. (2020, June). Insights from student solutions to sql homework problems. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education(pp. 404-410). pdf
George Fletcher
Secondary supervisor
Daphne Miedema
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