The relationship between personality traits and learning styles in medical education students at Iran University of Medical Sciences: A cross‑sectional study
Volume 13, Issue 1, Winter 2023, Pages 1-6
. Zohreh Sohrabi, . Shoaleh Bigdeli, . Shabnam Nadjafi
Abstract BACKGROUND: The relationship between personality traits and learning styles is an attractive
subject for researchers. “Learning Style” indicates on a method of education for effective studying. The
Kolb’s Learning Style is a known theory in the field of learning style. The Kolb’s four learning styles
include: Divergent, convergent, assimilating, and accommodating. Furthermore, personality, known
as relatively fixed and durable characteristics that distinguish people from each other, and personality
contains five broad identified traits of extraversion, agreeableness, openness, conscientiousness,
and neuroticism. In this study, we intended to evaluate the relationship between personality traits
and learning styles in medical education students.
MATERIALS AND METHODS: This research was an observational analytic cross‑sectional study
that was conducted on medical education students at Iran University of Medical Sciences, between
2018 and 2019, and 31 students were participated as volunteers. NEO Five‑Factor Inventory and
the Kolb’s learning style inventory (version 3.1) were used to evaluate the students’ personality traits
and learning styles, respectively. The simple and multiple analysis of multinomial logistic regression
were used for statistical analysis.
RESULTS: The results indicated that if one unit would be added to the score of the “Extraversion”
personality trait, the estimated odds, by which the student’s learning style would become
“Accommodating” rather than “Assimilating,” is 1.3 times more than the basic condition, in which
“Extraversion” score would be remained unchanged (P = 0.035).
CONCLUSION: It seems that “Accommodating” learning style might be related to “Extraversion”
personality trait in medical education students. However, researches with a larger population are
suggested.
