Intellectual Style Inventory (ISI): Learning Style Assessment after Cortical Functional Specialization
Mai S. Saleh, Zeinab M. Monir, Amal Saad-Hussein, Sally S. Mustafa
Journal of Education, Society and Behavioural Science · pp. 987–1005 · Published 28 Mar 2014
10.9734/BJESBS/2014/8751Abstract
Background: Many criticisms face theoretical bases and measurement tools used for identifying learning styles. The Intellectual Style Inventory (ISI) introduced in this work provides a new approach for learning style assessment based on cortical functional specialization. The ISI emphasizes the distinct characteristic processes of thinking and perception in each cortical lobe. It adds that the lobe indicating an individual's first preference in thinking may differ from his lobe of first preference in perception. Knowing an individual's preferred cortical lobe in thinking and in perception could help identify his learning style according to his predominant intellectual processes. Aims: The aim of the present study was to investigate the theoretical assumption after the ISI, and the appropriateness of the tool. Methodology: Study sample was composed of 203 volunteers of both sexes with mean age of 33.2 years. The subjects completed the ISI and demographic data were also collected. One month later, 19 of the study sample retook the ISI. Results: Content validity coefficient (V) and homogeneity reliability coefficient (H) for all items and sets of items of the inventory exceeded 0.71. Likelihood ratio comparing first preferences in thinking and perception showed non-significant results. No significant difference was found between test and retest. Conclusion: In conclusion, it could be suggested that for the same individual; there is no relationship between the first preference concerning each of the two intellectual functions; thinking and perception: two distinct faculties describing learning. ISI is a potential reliable tool for learning style assessment under the concept of cortical function specialization.
Cited by 2
Mai Saleh, Osama El-Sharkawy · 2020 21st International Arab Conference on Information Technology (ACIT) · 2020
Mai Sabry Sale, Yasser Zakaria Za · Journal of Artificial Intelligence · 2017
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