Recommender system for learning SQL using hints

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.

KEYWORDS:

• Intelligent Tutoring Systems
• improving classroom teaching
• interactive learning environments
• programming and programming languages
• recommender system
• SQL learning

Notes on contributors

Dejan Lavbič received his PhD degree in 2010 and is currently employed at Laboratory for Data Technologies, Faculty of Computer and Information Science, University of Ljubljana as Assistant Professor. His research interests are intelligent agents, knowledge management, social network analysis, Semantic Web, Information Quality and Intelligent tutoring systems. He is a reviewer, member of program board of several international conferences and author of more than 40 journal papers and papers presented at international conferences.

Tadej Matek received his BSc degree in 2015 from the Faculty of Computer and Information Science, University of Ljubljana. He is currently applying for a MSc in Computer and Information Science at the same institution. His research interests include machine learning, network analysis, intelligent tutoring systems and data management systems.

Aljaž Zrnec received his PhD degree in 2006 from the Faculty of Computer and Information Science, University of Ljubljana. He works in the Laboratory for data technologies as a lecturer and assistant in the field of databases. His research is focused on database management systems, methods for plagiarism detection and intelligent tutoring systems. He is the author or coauthor of numerous articles in professional and scientific publications.

ORCiD

Dejan Lavbič http://orcid.org/0000-0003-2390-4160