SQL Education

Abstract

Structured Query Language (SQL) skills are crucial in software engineering and computer science. However, teaching SQL effectively requires both pedagogical skill and considerable knowledge of the language. Educators and scholars have proposed numerous considerations for the betterment of SQL education, yet these considerations may be too numerous and scattered among different fora for educators to find and internalize, as no systematic mappings or literature reviews regarding SQL education have been conducted. The two main goals of this mapping study are to provide an overview of educational SQL research topics, research types and publication fora, and to collect and propagate SQL teaching practices for educators to utilize. Additionally, we present a short future research agenda based on insights from the mapping process. We conducted a systematic mapping study complemented by snowballing techniques to identify applicable primary studies. We classified the primary studies according to research type, and utilized directed content analysis to classify the primary studies by their topic. Out of our selected 89 primary studies, we identified six recurring topics: (i) student errors in query formulation; (ii) characteristics and presentation of the exercise database; (iii) specific and (iv) non-specific teaching approach suggestions; (v) patterns and visualization; and (vi) easing teacher workload. We list 66 teaching approaches the primary studies argued for (and in some cases against). For researchers, we provide a systematic map of educational SQL research, and future research agenda. For educators, we present an aggregated body of knowledge on teaching practices in SQL education over a time frame of 30 years. In conclusion, we suggest that replication studies, studies on advanced SQL concepts, and studies on aspects other than data retrieval are needed to further educational SQL research.

Data-Driven Analysis of Student Engagement in Time-Limited Computer Laboratories

“…Due to the overwhelming diffusion of relational Database Management Systems, in software engineering and computer science education, Structured Query Language (SQL) skills are deemed to be fundamental. A systematic review of SQL education is given by [14]. In the early 2000s, most research works related to SQL education were focused on proposing ad hoc tools to support laboratory sessions on SQL query writing (e.g., [19][20][21]).…”

“…Teaching SQL is widespread in university-level database courses. Computer laboratories are particularly suitable for SQL education because learners can type the queries solving a list of exercises, progressively submit the draft solutions, and eventually fix them by adopting a trial-and-error approach [14]. We present a case study that we performed in our university, where we set up the laboratory environment and acquired learner-generated data.…”

Explaining Causes Behind SQL Query Formulation Errors

“…In terms of educational research, prevalent SQL research topics are different learning environments [12] [13] [14], various teaching approach propositions [15] [16] [17], and understanding novice errors [8] [9]. Although SQL is a versatile language, both SQL education and research usually focus on data retrieval, i.e., SELECT statements [5]. Much of the research seem to agree that students should learn SQL in practice in addition to learning theoretical foundations [18] [19].…”

“…In industry, SQL remains the de facto language to query data from databases. Even though programming languages have received ample attention in educational research [4], SQL, in comparison, has largely remained in the sidelines [5]. Although it can be argued that studies concerning programming languages can be generalized to cover SQL as well, SQL is not a programming language, and the paradigm behind SQL is declarative, as opposed to the imperative nature of many programming languages studied [6].…”

“…Furthermore, as we are beginning to understand what errors novices commit, we are able to move towards why these errors occur, and start to mitigate them. However, research explaining causes behind errors is both scarce, and in some cases, possibly obsolete [5] due to additional features introduced in the SQL language. To that end, we conducted a quantitative study to find out which persistent (i.e., never corrected) errors are most common in certain types of queries, and mapped these errors to cognitive explanations introduced previously [11].…”