Cognitive Fit in Requirements Modeling: A Study of Object and Process Methodologies

Abstract:

Requirements modeling constitutes one of the most important phases of the systems development life cycle. Despite the proliferation of methodologies and models for requirements analysis, empirical work examining their relative efficacy is limited. This paper presents an empirical examination of object-oriented and process-oriented methodologies as applied to object-oriented and process-oriented tasks. The conceptual basis of the research model is derived from the theory of cognitive fit, which posits that superior problem-solving performance will result when the problemsolving task and the problem-solving tool emphasize the same type of information. Two groups of subjects participated in an experiment that required them to construct solutions to two requirements-modeling tasks, one process-oriented and the other object-oriented. One group employed the object-oriented tool while the other used the process-oriented tool. As predicted by the theory of cognitive fit, superior performance was observed when the process-oriented tool was applied to the process-oriented task. For the object-oriented task, however, the performance effects of cognitive fit require further investigation since there was no difference in subject performance across the two tools.

Key Words and Phrases:

• cognitive fit
• human factors
• object-oriented analysis
• process-oriented analysis
• requirements modeling

Additional information

Notes on contributors

Ritu Agarwal

Ritu Agarwal is an Associate Professor of MIS at the University of Dayton. She received her Ph.D. in management information systems and M.S. in computer science from Syracuse University in 1988. Professor Agarwal’s articles have appeared in Journal of Management Information Systems, Information and Management, OMEGA, Decision Support Systems, Knowledge-Based Systems, International Journal of Man-Machine Studies, Behavior and Information Technology, Knowledge Acquisition, among other publications, and she has presented papers at several national and international meetings. She serves as an Associate Editor for the International Journal of Human-Computer Studies. Her current research focuses on individual learning and organizational diffusion of new technologies, business process reengineering, and object-oriented technologies.

Atish P. Sinha

Atish P. Sinha is an Assistant Professor of MIS in the School of Business Administration at the University of Dayton. He received his Ph.D. in business with a concentration in artifical intelligence from the University of Pittsburgh. His current research interests are case-based reasoning, expert systems, object-oriented modeling, and human factors in software engineering.

Mohan Tanniru

Mohan Tanniru is an Associate Professor of MIS in the School of Management at Syracuse University. He received his Ph.D. in MIS from Northwestern University. He has published in a number of journals and presented papers at various meetings. Dr. Tanniru has consulted with several corporations in the area of expert and knowledge-based systems and technology management, including the Carrier Corporation, Bristol-Myers, and Tata Consultancy Services. His current research interests are systems analysis and design, decision support systems, and expert systems.