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International Journal of Human-Computer Studies
Volume 61, Issue 4, October 2004, Pages 397-419
 
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doi:10.1016/j.ijhcs.2003.12.019    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2004 Elsevier Ltd All rights reserved.

Comparing a rule-based approach with a pattern-based approach at different levels of complexity of conceptual data modelling tasks

Dinesh BatraCorresponding Author Contact Information, E-mail The Corresponding Author and Nicole A. Wishart

Decision Sciences and Information Systems, College of Business Administration, Florida International University, 11200 S.W. 8th street, University Park, Miami, FL 33199, USA

Received 16 June 2003; 
accepted 5 December 2003. 
Available online 6 August 2004.

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Abstract

It is well known that conceptual database design is an unusually difficult and error-prone task for novice designers. To address the problem, at least two training approaches—rule-based and pattern-based—have been suggested. A rule-based approach prescribes a sequence in modelling the conceptual modelling constructs, and the action to be taken at each stage. A pattern-based approach presents data modelling structures that occur frequently in practice, and prescribes guidelines on how to recognize these structures. This paper describes the conceptual framework, experimental design, and results of a laboratory study that employed novice designers to compare the effectiveness of the two training approaches (between-subjects) at three levels of task complexity (within subjects). Results indicate an interaction effect between treatment and task complexity. The rule-based approach was significantly better in the low-complexity and the high-complexity cases; there was no statistical difference in the medium-complexity case. Designer performance fell significantly as complexity increased. Overall, although the rule-based approach was not significantly superior to the pattern-based approach, the study still recommends the rule-based approach for novice designers given the significantly better performance at two out of three complexity levels.

Article Outline

1. Introduction
2. Complexity in conceptual data modelling
3. Rules and patterns
4. Research framework and hypotheses
5. Research methodology
5.1. Tasks
5.2. Training sessions
5.3. Grading scheme
6. Results
7. Discussion of results
8. Conclusion
Appendix A. Partial illustration of the rule-based approach
Appendix B. Partial illustration of the pattern-based approach
B.1. Pattern 1: generic transaction pattern
Appendix C. Experimental tasks
Appendix D: Task solutions
Appendix E: Grading scheme
References







 
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