SQL pattern design, development & evaluation of its efficacy

Al-Shuaily, Huda (2013) SQL pattern design, development & evaluation of its efficacy. PhD thesis, University of Glasgow.

Abstract

Databases provide the foundation of most software systems. This means that system developers will inevitably need to write code to query these databases. The de facto language for querying is SQL and this, consequently, is the language primarily taught by higher education institutions. There is some evidence that learners find it hard to master SQL.
These issues and concerns were confirmed by reviewing the literature and establishing the scope and context. The literature review allowed extraction of the common issues in impacting SQL acquisition. The identified issues were confirmed and justified by empirical evidence as reported here. A model of SQL learning was derived. This framework or model involves SQL learning taxonomy, a model of SQL problem solving and incorporates cross-cutting factors.
The framework is used as map to the design of a proposed instructional design. The design employed pattern concepts and the related research to structure SQL knowledge as SQL patterns. Also presented are details on how SQL patterns could be organized and presented. A strong theoretical background (checklist, component-level design) was employed to organize, present and facilitated SQL pattern collection.
The evaluation of the SQL patterns yielded new insight such as novice problem solving strategies and the types of errors students made in attempting to solve SQL problems.
SQL patterns, as proposed as a result of this research, yielded statistically significant important in novice performance in writing SQL queries.
A longitudinal field study with a large number of learners in a flexible environment should be conducted to confirm the findings of this research.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Keywords: SQL, Pattern, Learning
• Subjects: Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
• Colleges/Schools: College of Science and Engineering > School of Computing Science
• Supervisor's Name: Renaud, Mrs. Karen
• Date of Award: 2013
• Depositing User: Mrs huda Al-shuaily
• Unique ID: glathesis:2013-4632
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 11 Oct 2013 11:25
• Last Modified: 11 Oct 2013 11:25
• URI: https://theses.gla.ac.uk/id/eprint/4632