Recommender system for learning SQL using hints. Issue 8 (17th November 2017)

• Record Type: Journal Article
• Authors: Lavbič, Dejan; Matek, Tadej; Zrnec, Aljaž
• Is Part Of: Interactive learning environments. Volume 25:Issue 8(2017)
• Page Start: 1048
• Page End: 1064
• Publication Date: 2017-11-17
• Subjects: Intelligent Tutoring Systems -- improving classroom teaching -- interactive learning environments -- programming and programming languages -- recommender system -- SQL learning; Educational technology -- United States -- Periodicals; 371.33
• DOI: 10.1080/10494820.2016.1244084
• Languages: English
• ISSNs: 1049-4820

Abstract

ABSTRACT: Today's software industry requires individuals who are proficient in as many programming languages as possible. Structured query language (SQL), as an adopted standard, is no exception, as it is the most widely used query language to retrieve and manipulate data. However, the process of learning SQL turns out to be challenging. The need for a computer-aided solution to help users learn SQL and improve their proficiency is vital. In this study, we present a new approach to help users conceptualize basic building blocks of the language faster and more efficiently. The adaptive design of the proposed approach aids users in learning SQL by supporting their own path to the solution and employing successful previous attempts, while not enforcing the ideal solution provided by the instructor. Furthermore, we perform an empirical evaluation with 93 participants and demonstrate that the employment of hints is successful, being especially beneficial for users with lower prior knowledge.