PREFERENCE FOR INTUITION AND DELIBERATION AND ITS RELATIONSHIP WITH LEARNING OUTCOMES

Learning styles are useful tools when measuring way and output of someone’s learning (Kozhevnikov, 2007). Cognitive styles on the other hand were designed to measure humans’ cognition and its relation with learning is still not established. Therefore, the aim of this study is to study relationship between cognitive style measured by PID inventory (Betsch, 2004) and different learning outputs evaluated by a teacher. PID inventory consist of two subscales (PID deliberation, PID intuition). We divided respondents into four groups: deliberative (above mean in deliberation, below mean in intuition); intuitive (vice versa), indifferent (both below mean in deliberation and intuition) and mixed (above mean in both subscales).

75 students of University of Economics in Slovakia were tested in their fifth semester of bachelor study in the course Managerial Informatics. They had to pass four tasks for credit during semester together with final exam based on memorizing. Two tasks measured how well students understood and learned to properly use the accounting software (Alpha and Omega from Kros Corporation). To demonstrate their knowledge they had to solve successfully and properly a complex case task consisting of several subtasks. Third task measured an ability to search in internet, compare data and answer 30 questions about ERP software. Fourth task was a case study of a real specific company. To successfully solve the task students had to examine and analyse IT status of the company, and bring solutions for improving current status. Last task was measured the ability to memorize data for final exam in Managerial Informatics.

PID deliberation scale did not correlate significantly with any of those five tasks, in fact there was no relationship between them (for example PID deliberation and final exam, r = .069; p = .559). The similar results were found for PID intuition scale. The strongest of those insignificant relationships was between both PID subscales and ERP task which was software information searching, comparing and answering. As insignificant, neither of the scales could be used as predictors. As expected, analysis of relationships between five tasks revealed that they all measure different learning capacities and do not correlate together. Only relationship between tasks Alpha and Omega tasks were very close to significance (r = .22; p = .056), which was expected because they are based on the same principle. Four groups of students according their score in PID did not significantly differ between themselves in five tasks except task Alpha software case study (Kruskal –Wallis showed significant difference H(3) = 8.02; p = .046).
Cognitive style inventory PID, designed for measuring deliberation and affective intuition measures human cognition but is not useful for measuring or predicting students´ performance in learning. It is not able differentiate between any of five different tasks based on four different principles (case study, memorizing, searching and analysing, learning new software) except task Alpha software, where results are close to insignificance.