Informational and computational equivalence in comparing information modeling methods

Information modeling methods are key to the success of IS development projects. The problem in the software engineering field is not the lack of modeling methods, but the proliferation of modeling methods with little theoretical foundation and empirical evidence to support their usefulness. Evaluati...

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Main Author: SIAU, Keng
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2004
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Online Access:https://ink.library.smu.edu.sg/sis_research/9633
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-106332024-11-23T15:18:03Z Informational and computational equivalence in comparing information modeling methods SIAU, Keng Information modeling methods are key to the success of IS development projects. The problem in the software engineering field is not the lack of modeling methods, but the proliferation of modeling methods with little theoretical foundation and empirical evidence to support their usefulness. Evaluation techniques are, therefore, necessary to compare and contrast these modeling methods. In this paper, we suggest an evaluation approach based on the human information processing paradigm and the theory of equivalence of representations. This evaluation approach proposes that modeling methods can be evaluated and compared using two criteria: informational and computational equivalence. 2004-10-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/9633 info:doi/10.4018/jdm.2004010103 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Cognitive psychology Computational equivalence Evaluation technique Human factors Informational equivalence Modeling methods Unified modeling language (UML) Databases and Information Systems Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Cognitive psychology
Computational equivalence
Evaluation technique
Human factors
Informational equivalence
Modeling methods
Unified modeling language (UML)
Databases and Information Systems
Software Engineering
spellingShingle Cognitive psychology
Computational equivalence
Evaluation technique
Human factors
Informational equivalence
Modeling methods
Unified modeling language (UML)
Databases and Information Systems
Software Engineering
SIAU, Keng
Informational and computational equivalence in comparing information modeling methods
description Information modeling methods are key to the success of IS development projects. The problem in the software engineering field is not the lack of modeling methods, but the proliferation of modeling methods with little theoretical foundation and empirical evidence to support their usefulness. Evaluation techniques are, therefore, necessary to compare and contrast these modeling methods. In this paper, we suggest an evaluation approach based on the human information processing paradigm and the theory of equivalence of representations. This evaluation approach proposes that modeling methods can be evaluated and compared using two criteria: informational and computational equivalence.
format text
author SIAU, Keng
author_facet SIAU, Keng
author_sort SIAU, Keng
title Informational and computational equivalence in comparing information modeling methods
title_short Informational and computational equivalence in comparing information modeling methods
title_full Informational and computational equivalence in comparing information modeling methods
title_fullStr Informational and computational equivalence in comparing information modeling methods
title_full_unstemmed Informational and computational equivalence in comparing information modeling methods
title_sort informational and computational equivalence in comparing information modeling methods
publisher Institutional Knowledge at Singapore Management University
publishDate 2004
url https://ink.library.smu.edu.sg/sis_research/9633
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