Understanding Conceptual Schemas: Exploring the Role of Application and IS Domain Knowledge

  • Authors:

  • Vijay Khatri;Iris Vessey;V. Ramesh;Paul Clay;Sung-Jin Park

  • Affiliations:

  • Kelley School of Business, Indiana University, 1309 East 10th Street, Bloomington, Indiana 47405;University of Queensland and Queensland University of Technology, Brisbane QLD 4000, Australia;Kelley School of Business, Indiana University, 1309 East 10th Street, Bloomington, Indiana 47405;Kelley School of Business, Indiana University, 1309 East 10th Street, Bloomington, Indiana 47405;School of Public and Environmental Affairs, Indiana University, Bloomington, Indiana 47405

  • Venue:
  • Information Systems Research
  • Year:
  • 2006

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Abstract

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.