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Mapping Common Errors in Entity Relationship Diagram Design of Novice Designers
Author(s) -
Rami Rashkovits,
Ilana Lavy
Publication year - 2021
Publication title -
international journal of database management systems
Language(s) - English
Resource type - Journals
eISSN - 0975-5985
pISSN - 0975-5705
DOI - 10.5121/ijdms.2021.13101
Subject(s) - computer science , entity–relationship model , schema (genetic algorithms) , database design , database schema , data science , data mining , database , information retrieval
Data modeling in the context of database design is a challenging task for any database designer, even more so for novice designers. A proper database schema is a key factor for the success of any information systems, hence conceptual data modeling that yields the database schema is an essential process of the system development. However, novice designers encounter difficulties in understanding and implementing such models. This study aims to identify the difficulties in understanding and implementing data models and explore the origins of these difficulties. This research examines the data model produced by students and maps the errors done by the students. The errors were classified using the SOLO taxonomy. The study also sheds light on the underlying reasons for the errors done during the design of the data model based on interviews conducted with a representative group of the study participants. We also suggest ways to improve novice designer's performances more effectively, so they can draw more accurate models and make use of advanced design constituents such as entity hierarchies, ternary relationships, aggregated entities, and alike. The research findings might enrich the data body research on data model design from the students' perspectives.

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