Depiction of Health. 2024;15(1): 27-38.
doi: 10.34172/doh.2024.03
  Abstract View: 350
  PDF Download: 194

Quality of Health Care Delivery

Original Article

Preferred Learning Methods among First-year Medical Students: A Cross-Sectional Descriptive Study

Gholamali Dehghani 1* ORCID logo

1 Department of Medical Education, Education Development Center, Tabriz University of Medical Sciences, Tabriz, Iran
*Corresponding Author: Email: dehghani_gholamali@yahoo.com


Background. Understanding how learners process and organize new experiences and acquire information is one of the critical factors affecting the effective teaching and learning. Therefore, the objective of this study was to investigate the perception and processing of information by first-year medical students.
Methods. In this cross-sectional study, the convenience sampling method was adopted to select and investigate 180 first-year medical students of Tabriz University of Medical Sciences in the 2nd semester of the academic year 2022-2023. Data were collected using a questionnaire consisting of two parts – demographic factors and Kolb's learning styles inventory (LSI). The collected data were analyzed using SPSS-25 and applying descriptive statistics, Chi-square (χ2), t-test, and one-way analysis of variance (ANOVA).
Results. According to the results, students preferred the learning method of Abstract Conceptualization (33.89 ± 7.44), followed by active experimentation (29.85 ± 9.77), reflective observation (29.77 ± 8.64), and concrete experience (26.49 ± 9.32). The predominant learning styles adopted by the students were assimilating (38.3%), converging (32.2%), diverging (22.8%), and accommodating (6.7%). No significant differences were found between students' preferred learning methods and demographic variables (i.e., gender, marital status, age, and residential status) (P>0.05).
Conclusion. It was concluded that the dominant learning style was not an exclusive factor in predicting educational achievement. It was recommended that the teachers should take their students' learning preferences into account when designing learning opportunities.

Extended Abstract

Learning style consists of the methods and conditions under which learners perceive, process, store, and retrieve what they have learned in a more efficient and effective manner. Several classifications of learning style have been proposed so far, one of which is a classification introduced by David A. Kolb based on his theory of experiential learning. According to Kolb, adult learning is the process of knowledge acquisition through the transformation of experience. He defines learning as a four-step process: first, the learner is exposed to a topic, content, or learning situation (i.e., concrete experience); then, the learner observes and reflects on it (i.e., reflective observation); next, the learner begins to think, comprehend, and synthesize his/her opinions and perceptions (i.e., abstract conceptualization); and finally, the learner begins to experiment (i.e., active experimentation). Kolb identifies four learning styles based on these learning orientations, namely Divergers, Assimilators, Convergers, and Accommodators.

Understanding how learners process and organize new experiences and acquire information is a critical step towards an effective teaching and learning. Thus, the purpose of this study was to identify the preferred learning methods of first-year medical students, with a focus on their perception and processing of information.


This cross-sectional study was conducted in Tabriz University of Medical Sciences, Faculty of Medicine, during the 2nd semester of academic year 2022-2023 to investigate all first-year medical students (N=345). The research sample consisted of 230 first-year medical students who were selected using convenience sampling method. As for inclusion criteria, all eligible students 1) enrolled in the medical school at the time of study, 2) determined as first-year medical students, and 3) agreed to participate in the study were included.

Data were collected using a two-part questionnaire. The first part of the questionnaire inquired about the contextual factors such as gender, age, marital status, and residential status. The second part of the questionnaire included Kolb's learning styles inventory (LSI) (version 3). The validity and reliability of the original questionnaire had been confirmed by Kolb and colleagues. In addition, the validity and reliability of the Persian version of the questionnaire had been acknowledged in several studies in Iran. The Kolb LSI consists of 12 statement sets of four items each. Each item in a set represents one of the four elements of the learning process (i.e., concrete experience, reflective observation, abstract conceptualization, and active experimentation). Participants were asked to rank the items in each set from one (the least like me) to four (the most like me) in terms of their fit with their learning styles. After receiving participants’ responses to each option, total score for each of them range from 12 to 48. A Cartesian graph was used to plot the difference between AE and RO on the x-axis (range, -28 to +28) as well as the difference between AC and CE on the y-axis (range, -28 to +28). This facilitated the categorization of participants into one of four learning styles, namely Convergence, Divergence, Assimilation, and Accommodation as described by Kolb. The collected data were analyzed using SPSS-25 through the application of descriptive statistics, Chi-squared (χ2), t-test, and one-way analysis of variance (ANOVA).


After the collection of 195 questionnaires out of a determined sample size of 230 persons, based on a statistical population of 345 persons, the information of 180 complete questionnaires was analyzed. There were 91 male participants (50.6%) and 89 female participants (49.4%) in the 18-39 age range, with a mean age of 20.28 ± 2.02 years. According to the results, majority of the participants (97.2%) were single and only few of them (2.8%) were married. About half of the participants (50%) lived with their families, 40% lived in university dormitories, 7.2% lived in individual homes, and 2.8% lived in private dormitories.

The results also showed that a learning method the students preferred the most was abstract conceptualization (33.89 ± 7.44), followed by active experimentation (29.85 ± 9.77), reflective observation (29.77 ± 8.64), and concrete experience (26.49 ± 9.32). Assimilators and convergers accounted for approximately 70.5% (assimilators: 38.3%; convergers: 32.2%), and the remainder was divergers (22.8%) and accommodators (6.7%).

There was no significant difference between the learning methods preferred by the first-year medical students (i.e., reflective observation, concrete experience, abstract conceptualization, and active experimentation) and the across demographic factors (i.e., age, gender, marital/residential status) (P>0.05). Furthermore, there was no significant relationship between learning style (i.e., converging, diverging, assimilating, and accommodating) and demographic factors of the participants (P>0.05).


In sum, a learning method the students preferred the most was the abstract conceptualization method, and the assimilative learning style was the dominant style of the first-year medical students. Knowledge of learning styles was found to have implications for both medical educators and students. Students were more likely to become lifelong, self-directed learners and maximize their true potential when they were given the chance to identify their learning preferences and use appropriate learning strategies. Teachers may have become aware of the learning styles of their students and, therefore, incorporated teaching and learning strategies tailored to the learning preferences of their students. This may have created an effective learning environment as well as motivated the students to achieve academic succeess. The dominant learning style, therefore, was not an exclusive factor for predicting the educational success. Rather, it was a pattern of students' learning preferences that the teachers could consider when designing the learning opportunities.

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Submitted: 15 Dec 2023
Revision: 25 Dec 2023
Accepted: 24 Feb 2024
ePublished: 27 Feb 2024
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