Validation of learning style measures: implications for medical education practice.
BACKGROUND
It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners.


OBJECTIVE
This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula.


METHODS
Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales.


RESULTS
A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent.


CONCLUSIONS
Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.
Chapman
Dane M
DM
University of Colorado School of Medicine, Denver, Colorado, USA.
Calhoun
Judith G
JG
D003071:Cognition; D003194:Computer-Assisted Instruction; D003430:Cross-Sectional Studies; D003479:Curriculum; D004503:Education, Medical, Graduate / Q000379:methods*; D005260:Female; D006801:Humans; D007858:Learning; D008297:Male; D010551:Personality; D013337:Students, Medical / Q000523:psychology*; D013663:Teaching / Q000379:methods*