Author Tan, Anthony Chin Lok
Title Cognitive patterns of engineering an nursing students: perception, processing and hemisphericity.
Institute Thesis (M.Ed.) National Institute of Education, Nanyang Technological University
Year 1999
Supervisor Yeap, Lay Leng
Call no. LB1060 Tan
 
Summary
The aim of this study is to identify and explain the characteristic cognitive patterns of polytechnic engineering and nursing students in the dimension of perception, processing and brain dominance.  It hopes to show a link between the cognitive profiles of engineering and nursing students, and their choice of an engineering and nursing course at Nanyang Polytechnic, in preparing them for an engineering and nursing profession.

Such an understanding of the cognitive patterns would enable us to attract like-minded students to pursue a course in engineering or nursing based on their cognitive profile.  At the same time, it will also help to address the shortage of engineers and nurses in Singapore.

The study focused on the cognitive profiles of third-year polytechnic students comprising 138 electronic engineering and 123 nursing students.  Their profiles were identified using the Learning Style Inventory, LSI (Kolb, 1985a) and the Hemispheric Mode Indicator, HMI (McCarthy, 1998a).  Their commonalities and differences in their background were identified using the Demographic Data Inventory (Tan, 1998).

This study aims to investigate :

(1) Whether the cognitive profiles in relation to the cognitive dimension of perception and information processing could distinguish the engineering and nursing students, and their choice of an engineering or nursing course at Nanyang Polytechnic.

(2) The learning styles namely, diverger, assimilator, converger and accommodator types that distinguish the engineering and nursing students.

(3) If choices that lead to a career in engineering and nursing are related to hemispheric preferences, namely left-brained, whole-brained and right-brained.

(4) The relationship between the learning styles identified by the Learning Style Inventory, LSI (Kolb, 1985a) as divergers, assimilators, convergers and accommodators, with the hemispheric preferences identified by the Hemispheric Mode Indicator, HMI (McCarthy, 1998a) as left-brained, whole-brained, and right-brained.

Data was collected and analysed using descriptive statistics, independent t-tests, chi-square test of significance and independence.

Analysis of the data suggests the following conclusions:

(1) In the perception dimension with the learning modes of Concrete Experience and Abstract Conceptualisation, there was no significant difference between engineering and nursing students.  Both groups tend to perceive information in the same way, namely in a concrete and abstract manner.  However, both groups were more abstract than concrete with the engineering students having a greater emphasis for abstract over concrete compared to the nursing students.

(2) In the processing dimension with the learning modes of Reflective Observation and Active Experimentation, there was no significant difference between engineering and nursing students.  Both groups tend to process information in the same way, namely in an active and reflective manner.  However, both groups were more active than reflective with the nursing students having a greater emphasis for active over reflective compared to the engineering students.

(3) There was no significant difference in the learning styles (divergers, assimilators, convergers and accommodators) between engineering and nursing students.  Both groups were predominantly assimilators, followed by divergers.  The nursing group had more divergers and convergers than the engineering group.

(4) There was significant difference in the hemispheric preferences (left-brained, whole-brained and right-brained) between engineering and nursing students.  The engineering students showed a tendency for left brain functioning while nursing students showed a tendency towards right brain functioning.

(5) There was significant difference in the relationship between the learning styles as diagnosed by the Learning Style Inventory, LSI (Kolb, 1985a) and the hemispheric preferences as diagnosed by the Hemispheric Mode Indicator, HMI (McCarthy, 1998a).  Engineering and nursing groups with an assimilator learning style had a tendency for left brain functioning.  The divergers in both groups had a tendency for right brain functioning.  The study also revealed that accommodators and convergers in the engineering group showed a tendency towards left brain functioning while those in the nursing group showed a tendency towards right brain functioning.

In summary, engineering students were found to be more abstract rather than concrete, had an assimilator or diverger learning style and exhibit a tendency for left brain functioning.  As for nursing students, they were more active rather than reflective, had an assimilator or diverger learning style and exhibit a tendency for right brain functioning.  It was noted that the primarily difference between engineering and nursing students lies in their brain functioning.  Findings from this study should prove helpful in attracting secondary students with like-minded cognitive profiles to pursue an engineering or nursing course.  This will in no doubt help address the shortage of engineers and nurses in Singapore by fitting the right person to the job rather than modifying the job to suit the person.