An alternative Fit through Problem Representation in Cognitive Fit Theory

Hock Chuan Chan, Suparna Goswami, Hee Woong Kim

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


This paper uses cognitive fit theory to analyze the problem solving process in spreadsheet analyses. Cognitive fit theory proposes the formation of mental representation as a part of the problem solving process. However, there is little research examining mental representation, which is a key concept in cognitive fit theory. This study examines the formation of mental representation and proposes an alternative mechanism of cognitive fit between different problem representations and their corresponding mental representations when the task is invariant, but the problem representation changes. Mental representation is then empirically assessed based on the application of Hick's law, which states that the response time of users making a choice varies with the logarithm of the number of possible choices. Therefore, this study contributes to research on cognitive fit theory by proposing an alternative fit and by demonstrating a feasible approach for identifying mental representations. It contributes to spreadsheet research by showing how problem representations affect task performance in the case of spreadsheet error correction.

Original languageEnglish
Pages (from-to)22-43
Number of pages22
JournalJournal of Database Management
Issue number2
Publication statusPublished - 2012 Apr

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture


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