Comprehending object and process models: An empirical study

Although prior research has compared modeling performance using different systems development methods, there has been little research examining the comprehensibility of models generated by those methods. in this paper, we report the results of an empirical study comparing user comprehension of object-oriented (OO) and process-oriented (PO) models. The fundamental difference is that while OO models tend to focus on structure, PO models tend to emphasize behavior or processes. Proponents of the OO modeling approach argue that it lends itself naturally to the way humans think. However, evidence from research in cognitive psychology and human factors suggests that human problem solving is innately procedural. Given these conflicting viewpoints, we investigate empirically if OO models are in fact easier to understand than PO models. But, as suggested by the theory of cognitive fit, model comprehension may be influenced by task-specific characteristics. We, therefore, compare OO and PO models based on whether the comprehension activity involves: 1) only structural aspects, 2) only behavioral aspects, or 3) a combination of structural and behavioral aspects. We measure comprehension through subjects' responses to questions designed along these three dimensions. Two experiments were conducted, each with a different application and a different group of subjects. Each subject was first trained in both methods, and then participated in one of the two experiments, answering several questions relating to his or her comprehension of an OO or a PO model of a business application. The comprehension questions ranged in complexity from relatively simple (addressing either structural or behavioral aspects) to more complex ones (addressing both structural and behavioral aspects). Results show that for most of the simple questions, no significant difference was observed insofar as model comprehension is concerned. For most of the complex questions, however, the PO model was found to be easier to understand than the OO model. In addition to describing the process and the outcomes of the experiments, we present the experimental method employed as a viable approach for conducting research into various phenomena related to the efficacy of alternative systems analysis and design methods. We also identify areas where future research is necessary, along with a recommendation of appropriate research methods for empirical examination.