Title:	DATA MODEL DESIGN - THE CASE OF THREESOME
Author(s):	Rami Rashkovits and Ilana Lavy
ISBN:	978-989-8533-87-6
Editors:	Miguel Baptista Nunes, Pedro Isaías, Philip Powell, Pascal Ravesteijn and Guido Ongena
Year:	2019
Edition:	Single
Keywords:	Data Model Design, Ternary Relationships, Abstract Thinking Abilities
Type:	Full Paper
First Page:	67
Last Page:	74
Language:	English
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Paper Abstract:	Information systems students encounter difficulties in understanding and implementing ternary relationships when designing a data model. The aim of this study is to explore the origins of these difficulties and to suggest didactical guidelines to overcome these difficulties. This research examines the data model produced by students in which a ternary relationship is required, and looks for errors. The students reflect on their solution via open interview and unfold the underlying reasons to their erroneous design. The issue is analysed using the cognitive complexity theory. The data of this research includes the students' responses to a questionnaire with a design problem and the transcripts of open interviews conducted with representative group of the study participants. The obtained data was analysed using content and inductive analysis methods. The research is qualitative yet some quantitative data are presented as well. The study shed light on the underlying reasons causing erroneous data model design by novice data modelers, referring to ternary relationships, and suggest ways to teach the issues involved more effectively. The findings are used to classify the difficulties involved in designing ternary relationships and the underlying reasons, which lead novice data modelers to err. The insights gained from the research findings enabled us to come with useful didactical suggestions for educators that might help them improve their teaching as regards to the ternary relationships modeling. The research findings might enrich the data body research on data model design from the students' perspective. Novice data modelers may perform better and avoid beginners' errors, which perhaps lead to better information systems quality.
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