Applying Cognitive Theories to Evaluate Conceptual Models in Systems Analysis

Applying Cognitive Theories to Evaluate Conceptual Models in Systems Analysis

Stephen Rockwell (University of Tulsa, USA) and Akhilesh Bajaj (University of Tulsa, USA)
Copyright: © 2010 |Pages: 18
DOI: 10.4018/jitr.2010010105
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Abstract

Conceptual models have been evaluated along the dimensions of modeling complexity (how easy is it to create schemas given requirements?) and readability (how easy is it to understand the requirements by reading the model schema?). In this work, we update COGEVAL, a propositional framework based on cognitive theories to evaluate conceptual models. We synthesize work from cognitive literature to develop the framework, and show how it can be used to explain earlier empirical results as well as existing theoretical frameworks. We illustrate how COGEVAL can be used as a theoretical basis to design an empirical test of readability of a conceptual model. Unlike much of the earlier empirical work on readability, our approach isolates the effect of a model-independent variable (degree of fragmentation) on readability. From a practical perspective, our findings will have implications for both creators of new models and practitioners who use currently available models to create schemas.
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Introduction

Conceptual models1 are important in the area of information systems (IS) development. Essentially, a conceptual model is a method of documenting elements of an underlying reality. Model schemas may be used as: a) a method of either informally or formally documenting end-user requirements, which are initially articulated in a natural language like English; and/or b) a method of optimally designing the subsequent IS. A commonly used example of both a) and b) is the use of the Entity Relationship Model (ERM) (Chen, 1976) to capture end-user requirements for constructing a relational database application. Once the requirements are documented in an ERM schema, the ERM schema can then be mapped, using well-known rules, to a measurably good relational schema design. Over a hundred conceptual models have been proposed for requirements modeling (Olle, 1986), with over 1000 brand name methodologies utilizing these models (Jayaratna, 1994).

Several desirable attributes of modeling methods have been proposed in earlier work. These include: a) the adequacy or completeness of the modeling method in being able to represent the underlying reality (Amberg, 1996; Bajaj & Ram, 1996; Brosey & Schneiderman, 1978; Erickson & Siau, 2007; Kramer & Luqi, 1991; Mantha, 1987; Moynihan, 1996), b) the readability of the modeling method’s schemas (Aquirre-Urreta & Marakas, 2008; Hardgrave & Dalal, 1995; Shoval & Frummerman, 1994), and c) how easy it is to use the modeling method to represent requirements (Bajaj, 2006; Bock & Ryan, 1993; Kim & March, 1995; Kramer & Luqi, 1991; Shoval & Even-Chaime, 1987; Siau & Cao, 2001). Many earlier works consider both the effectiveness and the efficiency aspects of a) and b) (Bajaj, 2002; Wand & Weber, 2002). Modeling effectiveness is the degree to which modelers can correctly create the schema of a model, for a given requirements case. Modeling efficiency is the amount of effort expended to create the schema. Similarly, readability effectiveness is the degree to which readers of schema can correctly recreate the underlying requirements. Readability efficiency is the amount of effort taken by readers of a model schema to recreate the requirements.

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