Information Use in Solving a Well-Structured IS Problem: The Roles of IS and Application Domain Knowledge

1. Alexander, P.A.: Domain Knowledge: Evolving Themes and Emerging Concerns. Educational Psychologist 27(1), 33–51 (1992)

   Article  MathSciNet  Google Scholar 

2. Anderson, J.R.: Acquisition of Cognitive Skill. Psychological Review 89(4), 369–406 (1982)

   Article  Google Scholar 

3. Arisholm, E., Sjøberg, D.I.K.: Evaluating the Effect of a Delegated versus Centralized Control Style on the Maintainability of Object-Oriented Software. IEEE Transactions on Software Engineering 30(8), 521–534 (2004)

   Article  Google Scholar 

4. Blum, B.A.: A Paradigm for the 1990s Validated in the 1980s. In: Proceedings of the AIAA Conference 1989, pp. 502–511 (1989)

   Google Scholar 

5. Burton-Jones, A., Weber, R.: Understanding relationships with attributes in entity-relationship diagrams. In: Proceedings of the Twentieth International Conference on Information Systems, Charlotte, North Carolina, USA, pp. 214–228 (1999)

   Google Scholar 

6. Camerer, C.F., Johnson, E.J.: The process-performance paradox in expert judgment: How can experts know so much and predict so badly? In: Ericsson, K.A., Smith, J. (eds.) Towards a general theory of expertise: Prospects and limits, pp. 195–217. Cambridge Press, New York (1991)

   Google Scholar 

7. Chen, P.P.: The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions of Database Systems 1(1), 9–36 (1976)

   Article  Google Scholar 

8. Davies, I., Green, P., Rosemann, M., Indulska, M., Gallo, S.: How do practitioners use conceptual modeling in practice? Data & Knowledge Engineering 58(3), 358–380 (2006)

   Article  Google Scholar 

9. Dobing, B., Parsons, J.: How UML is used. Communications of the ACM 49(5), 109–113 (2006)

   Article  Google Scholar 

10. Elmasri, R., Navathe, S.B.: Fundamentals of Database Systems, 6th edn. Addison Wesley, Boston (2006)

    MATH  Google Scholar 

11. Ericsson, K.A., Simon, H.A.: Verbal reports as data. Psychological Review (87), 215–251 (1980)

    Google Scholar 

12. Hoffer, J.A., Prescott, M.B., McFadden, F.R.: Modern Database Management, 8th edn. Pearson/Prentice Hall, Upper Saddle River (2007)

    Google Scholar 

13. Khatri, V., Vessey, I.: Information Search Process for a Well-Structured IS Problem: The Role of IS and Application Domain Knowledge. In: 29th International Conference on Information Systems, Paris, France (2008)

    Google Scholar 

14. Khatri, V., Vessey, I., Ramesh, V., Clay, P., Kim, S.-J.: Understanding Conceptual Schemas: Exploring the Role of Application and IS Domain Knowledge. Information Systems Research 11(3), 81–99 (2006)

    Article  Google Scholar 

15. Kitchner, K.S.: Cognition, metacognition, and epistemic cognition: A three-level model of cognitive processing. Human Development (26), 222–232 (1983)

    Google Scholar 

16. Navon, D., Miller, J.: Role outcome conflict in dual-task interference. Journal of Experimental Psychology: Human Perception and Performance (13), 435–448 (1987)

    Google Scholar 

17. Nisbett, R.E., Wilson, T.D.: Telling more than we can know: verbal reports on mental processes. Psychological Review (84), 231–259 (1977)

    Google Scholar 

18. Purao, S., Rossi, M., Bush, A.: Toward an Understanding of the Use of Problem and Design Spaces During Object-Oriented System Development. Information and Organization (12), 249–281 (2002)

    Google Scholar 

19. Reitman, W.R.: Heuristic Decision Procedures: Open Constraints and the Structure of Ill-Defined Problems. In: Shelly, M.W., Bryan, G.L. (eds.) Human Judgments and Optimality, pp. 282–315. John Wiley, New York (1964)

    Google Scholar 

20. Shaft, T.M., Vessey, I.: The Relevance of Application Domain Knowledge: The Case of Computer Program Comprehension. Information Systems Research 6(3), 286–299 (1995)

    Article  Google Scholar 

21. Shaft, T.M., Vessey, I.: The Relevance of Application Domain Knowledge: Characterizing the Computer Program Comprehension Process. Journal of Management Information Systems 15(1), 51–78 (1998)

    Article  Google Scholar 

22. Shaft, T.M., Vessey, I.: The Role of Cognitive Fit in the Relationship Between Software Comprehension and Modification. MIS Quarterly 30(1), 29–55 (2006)

    Google Scholar 

23. Shanteau, J.: How Much Information Does An Expert Use? Is It Relevant? Acta Psychologica (81), 75–86 (1992)

    Google Scholar 

24. Spence, M.T., Brucks, M.: The Moderating Effects of Problem Characteristics on Experts’ and Novices’ Judgments. Journal of Marketing Research 34(2), 233–247 (1997)

    Article  Google Scholar 

25. Todd, P., Benbasat, I.: Process Tracing Methods in Decision Support Systems Research: Exploring the Black Box. MIS Quarterly 11(4), 493–512 (1987)

    Article  Google Scholar 

26. Vessey, I.: Cognitive Fit: A Theory-based Analysis of Graphs Vs. Tables Literature. Decision Sciences 22(2), 219–240 (1991)

    Article  Google Scholar 

27. Vessey, I.: The Effect of the Application Domain in IS Problem Solving: A Theoretical Analysis. In: Hart, D., Gregor, S. (eds.) Information Systems Foundations: Theory, Representation and Reality, pp. 25–48. ANU Press, Canberra (2006)

    Google Scholar 

28. Voss, J.F., Post, T.A.: On the solving of ill-structured problems. In: Chi, M.H., Glaser, R., Farr, M.J. (eds.) The nature of expertise, pp. 261–285. Lawrence Erlbaum Associates, Hillsdale (1988)

    Google Scholar 

29. Zhang, J.: The nature of external representations in problem solving. Cognitive Science 21(2), 179–217 (1997)

    Article  Google Scholar 

30. Zhang, J., Norman, D.A.: Representations in distributed cognitive tasks. Cognitive Science 18(1), 87–122 (1994)

    Article  Google Scholar 

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