Mental Workload Impact of a Visual Language on Understanding SQL Queries
Resumo
Structured Query Language (SQL) is an essential topic in introductory database courses. Despite its declarative syntax, SQL query specification can be confusing. Visual Query Languages (VQLs) are an alternative to reduce this complexity. However, these VQLs do not cover many complex constructions. To overcome this limitation, we present the Diagrammatic SQL (DSQL). Because increased Mental Workload (MW) during task performance may increase fatigue and facilitate errors, our objective is to investigate the MW impact of DSQL on the understanding of SQL queries. In this experiment, we compare the accuracy, time, and ease-of-understanding complex queries using both languages. The results indicate that there is no significant difference.
Palavras-chave:
Mental Workload, Visual Language, SQL Queries
Referências
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Bakke, E. and Karger, D. R. (2016). Expressive query construction through direct manipulation of nested relational results. In Proceedings of the 2016 International Conference on Management of Data, SIGMOD’16, p. 1377–1392, New York, NY, USA. ACM.
Bloesch, A. C. and Halpin, T. A. (1997). Conceptual queries using conquer-ii. In International Conference on Conceptual Modeling, p. 113–126. Springer.
Brambilla, M., Cabot, J., and Wimmer, M. (2017). Model-Driven Software Engineering in Practice: Second Edition. Synthesis Lectures on Software Engineering, 3(1):1–207.
Cain, B. (2007). A review of the mental workload literature. Technical report, Defence Research And Development Toronto (Canada).
Catarci, T. and Santucci, G. (1995). Diagrammatic Vs Textual Query Languages: A Comparative Experiment, p. 69–83. Springer US, Boston, MA.
Cerullo, C. and Porta, M. (2007). A system for database visual querying and query visualization: Complementing text and graphics to increase expressiveness. In Inter. Workshop on Database and Expert Systems Applications, p. 109–113.
Czejdo, B. D., Tucci, R. P., Embley, D. W., and Liddle, S. W. (1993). Graphical query specification with participation constraints. In Computing and Information, 1993. Proceedings ICCI’93., Fifth International Conference on, p. 433–437.
Eitrheim, M. H. and Fernandes, A. (2016). The nasa task load index for rating workload acceptability. In Human Factors and User Needs in Transport, Control, and the Workplace.
El-Mahgary, S. and Soisalon-Soininen, E. (2015). A form-based query interface for complex queries. J. Vis. Lang. Comput., 29(C):15–53.
Gryz, J., Wang, Q., Qian, X., and Zuzarte, C. (2008). Sql queries with case expressions. In Foundations of Intelligent Systems, p. 351–360, Berlin, Heidelberg.
Hart, S. G. and Staveland, L. E. (1988). Development of nasa-tlx (task load index): Results of empirical and theoretical research. In Hancock, P. A. and Meshkati, N., editors, Human Mental Workload, volume 52 of Advances in Psychology, p. 139–183. North-Holland.
Hvorecký, J., Drlík, M., and Munk, M. (2010). The effect of visual query languages on the improvement of information retrieval skills. Procedia-Social and Behavioral Sciences, 2(2):717–723. Innovation and Creativity in Education.
Kawash, J. (2004). Complex quantification in structured query language (sql): A tutorial using relational calculus. Journal of Computers in Mathematics and Science Teaching, 23(2):169–190.
Kitchenham, B., Madeyski, L., Budgen, D., Keung, J., Brereton, P., Charters, S., Gibbs, S., and Pohthong, A. (2017). Robust statistical methods for empirical software engineering. Empirical Software Engineering, 22(2):579–630.
Longo, L. (2015). A defeasible reasoning framework for human mental workload representation and assessment. Behaviour & Information Technology, 34(8):758–786.
StackOverflow (2018). Stack Overflow developer survey results 2018. [link]. Accessed: 2018-12-14.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., Regnell, B., and Wesslén, A. (2012). Experimentation in software engineering. Springer Science & Business Media.
Zhang, G., Chu, W. W., Meng, F., and Kong, G. (1999). Query formulation from high-level concepts for relational databases. In Proc. User Interfaces to Data Intensive Systems.
ACM/IEEE (2013). Computer Science Curricula 2013: Curriculum Guidelines for Undergraduate Degree Programs in Computer Science. ACM, NY, USA. 999133.
ACM/IEEE (2017). Information Technology Curricula 2017: Curriculum Guidelines for Baccalaureate Degree Programs in Information Technology. ACM, NY, USA.
Bakke, E. and Karger, D. R. (2016). Expressive query construction through direct manipulation of nested relational results. In Proceedings of the 2016 International Conference on Management of Data, SIGMOD’16, p. 1377–1392, New York, NY, USA. ACM.
Bloesch, A. C. and Halpin, T. A. (1997). Conceptual queries using conquer-ii. In International Conference on Conceptual Modeling, p. 113–126. Springer.
Brambilla, M., Cabot, J., and Wimmer, M. (2017). Model-Driven Software Engineering in Practice: Second Edition. Synthesis Lectures on Software Engineering, 3(1):1–207.
Cain, B. (2007). A review of the mental workload literature. Technical report, Defence Research And Development Toronto (Canada).
Catarci, T. and Santucci, G. (1995). Diagrammatic Vs Textual Query Languages: A Comparative Experiment, p. 69–83. Springer US, Boston, MA.
Cerullo, C. and Porta, M. (2007). A system for database visual querying and query visualization: Complementing text and graphics to increase expressiveness. In Inter. Workshop on Database and Expert Systems Applications, p. 109–113.
Czejdo, B. D., Tucci, R. P., Embley, D. W., and Liddle, S. W. (1993). Graphical query specification with participation constraints. In Computing and Information, 1993. Proceedings ICCI’93., Fifth International Conference on, p. 433–437.
Eitrheim, M. H. and Fernandes, A. (2016). The nasa task load index for rating workload acceptability. In Human Factors and User Needs in Transport, Control, and the Workplace.
El-Mahgary, S. and Soisalon-Soininen, E. (2015). A form-based query interface for complex queries. J. Vis. Lang. Comput., 29(C):15–53.
Gryz, J., Wang, Q., Qian, X., and Zuzarte, C. (2008). Sql queries with case expressions. In Foundations of Intelligent Systems, p. 351–360, Berlin, Heidelberg.
Hart, S. G. and Staveland, L. E. (1988). Development of nasa-tlx (task load index): Results of empirical and theoretical research. In Hancock, P. A. and Meshkati, N., editors, Human Mental Workload, volume 52 of Advances in Psychology, p. 139–183. North-Holland.
Hvorecký, J., Drlík, M., and Munk, M. (2010). The effect of visual query languages on the improvement of information retrieval skills. Procedia-Social and Behavioral Sciences, 2(2):717–723. Innovation and Creativity in Education.
Kawash, J. (2004). Complex quantification in structured query language (sql): A tutorial using relational calculus. Journal of Computers in Mathematics and Science Teaching, 23(2):169–190.
Kitchenham, B., Madeyski, L., Budgen, D., Keung, J., Brereton, P., Charters, S., Gibbs, S., and Pohthong, A. (2017). Robust statistical methods for empirical software engineering. Empirical Software Engineering, 22(2):579–630.
Longo, L. (2015). A defeasible reasoning framework for human mental workload representation and assessment. Behaviour & Information Technology, 34(8):758–786.
StackOverflow (2018). Stack Overflow developer survey results 2018. [link]. Accessed: 2018-12-14.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., Regnell, B., and Wesslén, A. (2012). Experimentation in software engineering. Springer Science & Business Media.
Zhang, G., Chu, W. W., Meng, F., and Kong, G. (1999). Query formulation from high-level concepts for relational databases. In Proc. User Interfaces to Data Intensive Systems.
Publicado
11/11/2019
Como Citar
SILVA, Edson A.; FRANCO, Natália M.; FERRO, Márcio R.; FIDALGO, Robson N..
Mental Workload Impact of a Visual Language on Understanding SQL Queries. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 30. , 2019, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 239-248.
DOI: https://doi.org/10.5753/cbie.sbie.2019.239.
