# Synthesis of SQL Queries from South African Local Language Narrations Source: [Synthesis of SQL Queries from South African Local Language Narrations]() Collection index: [llms.txt]() Data updated: 2025-10-25T22:45:52.748Z Authors: George Obaido, Abejide Ade-Ibijola, Hima Vadapalli Published: 2020-11-14T19:38:08.000Z ## Abstract English remains the language of choice for database courses and widely used for instruction in nearly all South African universities, and also in many countries. Novice programmers of native origins are mostly taught Structured Query Language (SQL) through English as the medium of instruction. Consequently, this creates a myriad of problems in understanding the syntax of SQL as most native learners are not too proficient in English. This could affect a learner's ability in comprehending SQL syntaxes. To resolve this problem, this work proposes a tool called local language narrations (Local-Nar-SQL) to SQL that uses a type of Finite Machine, such as a Jumping Finite Automaton to translate local language narratives into SQL queries. Further, the generated query extracts information from a sample database and presents output to the learner. This paper is an extension of work originally presented in a previous study in this field. A survey involving 145 participants concluded that the majority found Local-Nar-SQL to be helpful in understanding SQL queries from local languages. If the proposed tool is used as a learning aid, native learners will find it easier to work with SQL, which will eliminate many of the barriers faced with English proficiencies in programming pedagogies. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()