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Title:
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IMPROVING RELATIONAL DATA MODELLING THROUGH LEARNING FROM ERRORS |
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Author(s):
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Adi Katz, Ronit Shmallo |
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ISBN:
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978-989-8533-39-5 |
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Editors:
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Ajith P. Abraham, Antonio Palma dos Reis and Jörg Roth |
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Year:
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2015 |
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Edition:
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Single |
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Keywords:
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Conceptual Data Modelling, Databases, Learning from Errors, Normalization. |
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Type:
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Short Paper |
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First Page:
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198 |
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Last Page:
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202 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This research focuses on improving relational databases design of novice designers. Teaching conceptual data modelling is a challenge to Information Systems educators. Our goal is to test the effectiveness of the learning from errors approach in the area of conceptual data modelling of relational databases. For understanding the difficulties that novice designers encounter in the activity of conceptual modelling, we analyzed students' solutions to a course exercise, in the form of a textual scenario, and mapped their errors into categories. At the next phase we intend to design learning lessons and activities that utilize these errors for the learning process. We will then design an experiment that compares between the traditional database teaching approach and a combination of the traditional approach with the learning from errors approach to test the effectiveness of the latter. |
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