Abstract
Background:
Emergency medicine residency training requires rapid acquisition of diverse clinical competencies in high-pressure environments. Understanding residents’ learning preferences and curriculum satisfaction is essential for optimizing training outcomes, yet limited research exists on how demographic factors influence these variables in emergency medicine education, particularly in non-Western contexts.
Objectives:
This study aims to investigate the VARK (Visual, Aural, Reading/Writing, Kinesthetic) learning preferences of emergency medicine residents at multiple training centers in Riyadh, evaluate their satisfaction with the academic curriculum, and examine the influence of demographic factors including gender and residency year on both learning preferences and curriculum satisfaction.
Methods and materials:
A cross-sectional study was conducted with 121 emergency medicine residents from multiple training centers in Riyadh. Participants completed the validated VARK questionnaire (Version 8.01), which consists of 16 scenario-based items assessing four sensory modalities. Each item presents a learning situation with four response options corresponding to visual (e.g., diagrams, charts), aural (e.g., discussions, lectures), reading/writing (e.g., manuals, notes), and kinesthetic (e.g., hands-on practice) preferences. The questionnaire also identifies multimodal combinations (bimodal, trimodal, quadmodal). Additionally, residents completed a 4-item curriculum satisfaction survey using a 4-point Likert scale (1 = Disagree, 2 = Neutral, 3 = Agree, 4 = Strongly agree) evaluating key domains including simulation quality and clinical skill development.
Results:
Among 121 emergency medicine residents (61.2% male, 38.8% female), VARK preferences revealed near-universal use of visual (97.5%) and kinesthetic (96.7%) modes, with 68.6% preferring quadmodal (all four) learning. Residents predominantly relied on maps (74.4%) for navigation, videos (51.2%) for online learning, and hands-on practice (42.1%) for skill acquisition. Satisfaction with the curriculum was high: 79.4% (agreed/strongly agreed), and 71.9% (agreed/strongly agreed) endorsed simulation/practical sessions. However, no significant association existed between VARK preferences and satisfaction scores (p > 0.05). Males scored higher in kinesthetic preference than females (p = 0.005), but neither gender nor residency year significantly influenced satisfaction (p > 0.05).
Conclusion:
Emergency medicine residents demonstrate consistent visual-kinesthetic learning dominance throughout training, with gender-based differences in preference and satisfaction. These findings support curriculum redesigns emphasizing multimodal, hands-on teaching while addressing gender-specific needs. Future research should examine how these preferences correlate with clinical performance.
Introduction
Emergency medicine residency programs represent one of the most demanding and challenging training environments in medical education. Residents must rapidly assimilate vast amounts of clinical knowledge while developing the ability to make critical decisions under pressure, perform complex procedures, and adapt to unpredictable clinical scenarios with minimal supervision (; ). The dynamic nature of emergency medicine demands not only clinical competence but also resilience, adaptability, and efficient learning strategies (; ).
Medical education has increasingly recognized the importance of individualized learning approaches, as trainees often differ significantly in how they acquire, process, and retain information (; ; ). One of the most widely used frameworks for understanding these differences is the VARK model, which categorizes learning preferences into four sensory modalities: Visual (V), Aural (A), Reading/Writing (R), and Kinesthetic (K). Visual learners benefit from diagrams, flowcharts, and spatial representations; aural learners thrive through lectures, discussions, and auditory explanations; reading/writing learners prefer textual engagement, such as textbooks and notes; and kinesthetic learners excel with hands-on experience, simulation, and physical practice (; ). Learning preferences are integral to how individuals engage with new information and retain knowledge ().
In the context of emergency medicine—where training must balance theoretical knowledge with real-time clinical application—understanding residents' learning preferences could have profound implications for curriculum design. If educational strategies align with how residents learn best, knowledge retention, clinical performance, and confidence in high-acuity settings may improve. Conversely, a mismatch between teaching methods and learning preferences could lead to disengagement, frustration, or even gaps in competency (; ; ; ). Despite the potential impact of learning styles on emergency medicine training, few studies have explored VARK preferences specifically within emergency medicine residency programs, particularly in non-Western settings This gap in the literature limits the ability of educators to tailor curricula to the needs of their trainees.
Equally important is the concept of curriculum satisfaction —a critical factor in medical education that influences motivation, academic performance, and professional well-being (). A curriculum that resonates with learners fosters engagement, reduces burnout, and enhances long-term career satisfaction. In emergency medicine, where training intensity can contribute to stress and attrition, ensuring that residents are satisfied with their educational experience is paramount (). However, satisfaction is likely not uniform; it may depend on how well the curriculum accommodates individual learning preferences (). For example, a kinesthetic learner in a program overly reliant on didactic lectures may feel underserved, while a reading/writing learner in a simulation-heavy environment might struggle to retain information (; ; ). Despite the intuitive connection between learning preferences and curriculum satisfaction, this relationship remains underexplored in emergency medicine residency programs.
Furthermore, demographic variables may play a significant role in shaping both learning preferences and curriculum satisfaction. Prior research in general medical education suggests that gender can influence learning style tendencies, possibly due to cultural, societal, or cognitive differences (). For instance, some studies indicate that female learners may gravitate toward collaborative and discussion-based learning, while male learners may prefer independent or hands-on approaches—though such trends are not universal and require context-specific investigation (; ). Similarly, the year of residency likely impacts educational needs: junior residents may prioritize foundational knowledge and skill acquisition, whereas senior residents may focus on advanced decision-making, leadership, and nuanced clinical judgment. If curricula fail to adapt to these evolving needs, satisfaction and learning efficacy could decline over time (). Unfortunately, few studies have examined how these demographic factors interact with learning preferences and curriculum satisfaction in emergency medicine training.
This study seeks to address these gaps by investigating the VARK learning preferences among emergency medicine residents at multiple training centers in Riyadh, assessing their satisfaction with the academic curriculum, and exploring how demographic factors - particularly gender and residency year - influence both learning preferences and curriculum satisfaction. By doing so, it aims to provide actionable insights for medical educators, enabling them to refine teaching methodologies, improve alignment between curriculum design and learner needs, and ultimately enhance both educational outcomes and resident well-being.
Methods and materials
Study design and participants
This cross-sectional study was conducted to assess the VARK learning preferences and academic curriculum satisfaction among Saudi emergency medicine residents. The study was conducted from May 8, 2024, to April 7, 2025, at the following training centers: King Khalid University Hospital (KKUH), King Abdulaziz Medical City (KAMC), Prince Sultan Military Medical City (PSMMC), Prince Mohammad bin Abdulaziz Hospital (PMAH), King Saud Medical City (KSMC), King Saud University Medical City (KSAMC), King Fahad Medical City (KFMC), and King Faisal Specialist Hospital (KFSH). A total of 121 residents participated, representing all four years of training (R1–R4).
Inclusion and exclusion criteria
The study included all actively enrolled emergency medicine residents (R1–R4) in training programs at the participating centers during the study period. Eligible participants were full-time trainees currently engaged in clinical duties. We excluded residents on extended leave and those who declined to provide consent.
Sample size calculation
The total number of emergency medicine residents across the selected training centers during the study period was approximately 403 residents. This number was obtained from the participating residency training programs and was used as the basis for the sample size calculation. Sample size was calculated with a 95% confidence level and 5% margin of error, yielding a target of 197 participants. However, due to limited availability of residents during academic activity days and competing clinical responsibilities, only 121 emergency medicine residents completed the study questionnaire and were included in the final analysis.
Procedure and data collection
A simple random sampling technique was employed to select participants. A list of emergency medicine residents from the different medical training centers was obtained. Participants were then randomly selected using a table of random numbers to minimize selection bias. Data were collected using an electronic, validated VARK questionnaire (Version 8.01) 2019, developed by VARK-Learn Limited (
). The questionnaire was distributed via Google Forms during residents' academic activity days to maximize response rates. The questionnaire comprised three sections:
- 1.
First section (Demographic Information): This section collected data on participants’ gender, medical center, and residency year, along with a consent statement for voluntary participation.
- 2.
Second section (Learning Preferences): This section contained the standardized 16-item VARK inventory, which assesses participants’ learning preferences across four distinct modalities: Visual (V), Aural (A), Reading/Writing (R), and Kinesthetic (K). Each item presented a scenario with four possible responses, and participants were asked to select the answer that best represented how they would approach the given situation. The responses correspond to one of the four learning styles.
Scoring and interpretation of learning preferences (section 2)
The scoring of the VARK inventory is designed to identify the participant's dominant learning preferences. Each of the 16 questions has four possible answers, each linked to one of the four categories (V, A, R, or K). After completing the questionnaire, the number of responses chosen for each modality (V, A, R, or K) is counted.
Visual (V): Answers associated with visual learning preferences, such as charts, diagrams, and other graphical representations.
Aural (A): Answers that reflect a preference for auditory learning, such as listening to lectures, discussions, or explanations.
Reading/Writing (R): Answers that reflect a preference for written materials, such as reading texts, writing notes, or reading instructions.
Kinesthetic (K): Answers related to physical, hands-on learning, such as learning by doing or using models.
Once responses are counted, the participant's learning preference profile is created using the official VARK scoring algorithm. The scoring chart in the VARK questionnaire assigns each answer to a specific modality. A specific algorithm is then applied to determine whether the participant has a single dominant preference or a multimodal preference (bimodal, trimodal, or quadmodal), rather than relying on simple dominant tallying. The final outcome is a profile that shows the participant's preferred learning style(s).
- 3.
Third Section (Satisfaction with the Academic Curriculum): This section aimed to measure participants’ satisfaction with their academic curriculum. It assessed their opinions on key aspects of the curriculum, such as overall satisfaction, how well the program meets their educational needs, and the effectiveness of simulation, practical sessions, and hands-on activities in enhancing their skills. This section consisted of four Likert scale items. Each item was scored from 1 to 4 (1 = Disagree, 2 = Neutral, 3 = Agree, 4 = Strongly agree), and the total satisfaction score was calculated as the sum of the four items (range 4–16). Participants were asked to rate their agreement with statements related to the integration of practical learning experiences, including simulations and hands-on activities, within the academic program. The responses provided insights into how well the curriculum aligns with the residents’ expectations and educational needs.
The consent form and study explanation were provided electronically by the research team through the Google Forms platform. Before accessing the questionnaire, participants were presented with an introductory section explaining the study objectives, confidentiality measures, the voluntary nature of participation, and the right to withdraw at any time without consequences. By proceeding to the questionnaire, participants provided informed consent.
Ethical considerations
This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, which ensures the protection of the rights, safety, and well-being of participants involved in clinical research. Ethical approval was granted by the Research Ethics Committee at King Saud University, College of Medicine, with the approval documented under the IRB log Number: 24/1303/ IRB. The confidentiality of participants' personal information was maintained, and all data were anonymized to protect privacy. Additionally, the data were stored electronically on password-protected computers in a secure office. Access was restricted and limited solely to the principal investigator (PI) to ensure confidentiality and data integrity. To avoid any potential coercion or authoritative influence on residents' participation decisions, no program directors, supervisors, or individuals in positions of authority were involved in recruitment or data collection. Participation was entirely voluntary.
Statistical analysis
Statistical analysis was conducted using SPSS software, version 28 (IBM Corp., Armonk, NY, USA). Numerical data were presented as the mean and standard deviation (SD) and analyzed using independent t-test or one-way ANOVA. Categorical data were presented as the frequency and percentage and analyzed using Chi-square test or exact test, as appropriate. A two tailed P-value <0.05 was considered statistically significant.
Results
The baseline characteristics of the participants are presented in Table 1. A total of 121 emergency medicine residents were included in the study, with 74 (61.2%) being male and 47 (38.8%) being female. Participants were recruited from various medical centers, with the highest representation from King Khalid University Hospital (KKUH) (30, 24.8%), followed by Prince Sultan Military Medical City (PSMMC) (23, 19.0%) and King Abdulaziz Medical City (KAMC) (17, 14.0%). Other centers included King Fahad Medical City (KFMC) (15, 12.4%), King Saud Medical City (KSMC) (13, 10.7%), King Faisal Specialist Hospital (KFSH) (12, 9.9%), Prince Mohammed bin Abdulaziz Hospital (PMAH) (10, 8.3%), and King Saud bin Abdulaziz Medical City (KSAMC) (1, 0.8%). Regarding the year of residency, 35 (28.9%) participants were in their first year, 30 (24.8%) in the second year, 32 (26.4%) in the third year, and 24 (19.8%) in the fourth year.
Table 1
| Item | N | % |
|---|---|---|
| Gender | ||
| Male | 74 | 61.2 |
|  Female | 47 | 38.8 |
| Center | ||
|  KKUH | 30 | 24.8 |
|  KAMC | 17 | 14.0 |
|  PSMMC | 23 | 19.0 |
|  PMAH | 10 | 8.3 |
|  KSMC | 13 | 10.7 |
|  KSAMC | 1 | .8 |
|  KFMC | 15 | 12.4 |
|  KFSH | 12 | 9.9 |
| Year of residency | ||
|  First | 35 | 28.9 |
|  Second | 30 | 24.8 |
|  Third | 32 | 26.4 |
|  Fourth | 24 | 19.8 |
The baseline characteristics of the participants (N = 121).
The learning methods preferred by participants are presented in Table 2. When finding a recommended shop, the majority (90, 74.4%) preferred using a map, while fewer participants relied on location-based memory (17, 14.0%), verbal directions (12, 9.9%), or written instructions (2, 1.7%). Regarding learning from a website with video content, 48 (39.7%) favored diagrams, followed by watching actions (34, 28.1%), listening (25, 20.7%), and reading (14, 11.6%). When seeking information about a tour, 47 (38.8%) preferred reading about highlights and activities, while 29 (24.0%) used maps, 25 (20.7%) read itineraries, and 20 (16.5%) preferred verbal discussions. In career selection, 54 (44.6%) valued real-world application, 32 (26.4%) preferred discussions, 23 (19.0%) favored design-based tasks, and 12 (9.9%) emphasized written communication. Regarding learning approaches, 40 (33.1%) preferred examples and applications, 38 (31.4%) identified patterns, 23 (19.0%) engaged in discussions, and 20 (16.5%) relied on reading. When making financial decisions, 38 (31.4%) reviewed personal examples, 30 (24.8%) consulted experts, 28 (23.1%) used graphs, and 25 (20.7%) read brochures. For learning new games, 42 (34.7%) observed others, 38 (31.4%) listened to explanations, 26 (21.5%) used diagrams, and 15 (12.4%) read instructions. When consulting a doctor about heart issues, most (58, 47.9%) preferred verbal descriptions, while others preferred models (30, 24.8%), diagrams (22, 18.2%), or reading materials (11, 9.1%). When learning to use new computer software, 51 (42.1%) preferred hands-on trial and error, 29 (24.0%) sought advice, 21 (17.4%) followed diagrams, and 20 (16.5%) read instructions. Learning from the Internet was most effective for 62 (51.2%) through videos, followed by written content (27, 22.3%), design features (18, 14.9%), and audio formats (14, 11.6%). For learning about new projects, 36 (29.8%) preferred diagrams or examples of successful applications, while others preferred written reports (29, 24.0%) or discussions (20, 16.5%). Regarding teaching methods, 44 (36.4%) favored demonstrations and practical sessions, while 35 (28.9%) preferred discussions, 31 (25.6%) relied on visual aids, and 11 (9.1%) used reading materials. When receiving feedback on tests, 36 (29.8%) preferred verbal discussions, 33 (27.3%) relied on examples, 30 (24.8%) used graphs, and 22 (18.2%) preferred written feedback. For property searches, 50 (41.3%) wanted video tours, while others preferred maps and floor plans (33, 27.3%), discussions (19, 15.7%), or printed descriptions (19, 15.7%). For assembling furniture, 39 (32.2%) preferred instructional videos, 38 (31.4%) followed diagrams, 24 (19.8%) read instructions, and 20 (16.5%) sought verbal guidance.
Table 2
| Item | N | % |
|---|---|---|
| I need to find the way to a shop that a friend has recommended. I would: | ||
| Find out where the shop is in relation to somewhere I know. | 17 | 14.0 |
| Ask my friend to tell me the directions. | 12 | 9.9 |
| Write down the street directions I need to remember. | 2 | 1.7 |
| Use a map. | 90 | 74.4 |
| A website has a video showing how to make a special graph or chart. There is a person speaking, some lists and words describing what to do and some diagrams. I would learn most from: | ||
| Seeing the diagrams. | 48 | 39.7 |
| Listening. | 25 | 20.7 |
| Reading the words. | 14 | 11.6 |
| Watching the actions. | 34 | 28.1 |
| I want to find out more about the tour that I am going on. I would: | ||
| Look at details about the highlights and activities on the tour. | 47 | 38.8 |
| Use a map and see where the places are. | 29 | 24.0 |
| Read about the tour on the itinerary. | 25 | 20.7 |
| Talk with the person who planned the tour or others who are going on the tour. | 20 | 16.5 |
| When choosing a career or area of study, these are important for me: | ||
| Applying my knowledge in real situations. | 54 | 44.6 |
| Communicating with others through discussion. | 32 | 26.4 |
| Working with designs, maps or charts. | 23 | 19.0 |
| Using words well in written communications. | 12 | 9.9 |
| When I am learning I: | ||
| Like to talk things through. | 23 | 19.0 |
| See patterns in things. | 38 | 31.4 |
| Use examples and applications. | 40 | 33.1 |
| Read books, articles and handouts. | 20 | 16.5 |
| I want to save more money and to decide between a range of options. I would: | ||
| Consider examples of each option using my financial information. | 38 | 31.4 |
| Read a print brochure that describes the options in detail. | 25 | 20.7 |
| Use graphs showing different options for different time periods. | 28 | 23.1 |
| Talk with an expert about the options. | 30 | 24.8 |
| I want to learn how to play a new board game or card game. I would: | ||
| Watch others play the game before joining in. | 42 | 34.7 |
| Listen to somebody explaining it and ask questions. | 38 | 31.4 |
| Use the diagrams that explain the various stages, moves and strategies in the game. | 26 | 21.5 |
| Read the instructions. | 15 | 12.4 |
| I have a problem with my heart. I would prefer that the doctor: | ||
| Gave me something to read to explain what was wrong. | 11 | 9.1 |
| Used a plastic model to show me what was wrong. | 30 | 24.8 |
| Described what was wrong. | 58 | 47.9 |
| Showed me a diagram of what was wrong. | 22 | 18.2 |
| I want to learn to do something new on a computer. I would: | ||
| Read the written instructions that came with the program. | 20 | 16.5 |
| Talk with people who know about the program. | 29 | 24.0 |
| Start using it and learn by trial and error. | 51 | 42.1 |
| Follow the diagrams in a book. | 21 | 17.4 |
| When learning from the Internet I like: | ||
| Videos showing how to do or make things. | 62 | 51.2 |
| Interesting design and visual features. | 18 | 14.9 |
| Interesting written descriptions, lists and explanations. | 27 | 22.3 |
| Audio channels where I can listen to podcasts or interviews. | 14 | 11.6 |
| I want to learn about a new project. I would ask for: | ||
| Diagrams to show the project stages with charts of benefits and costs. | 36 | 29.8 |
| A written report describing the main features of the project. | 29 | 24.0 |
| An opportunity to discuss the project. | 20 | 16.5 |
| Examples where the project has been used successfully. | 36 | 29.8 |
| I prefer a presenter or a teacher who uses: | ||
| Demonstrations, models or practical sessions. | 44 | 36.4 |
| Question and answer, talk, group discussion, or guest speakers. | 35 | 28.9 |
| Handouts, books, or readings. | 11 | 9.1 |
| Diagrams, charts, maps or graphs. | 31 | 25.6 |
| I have finished a competition or test and I would like some feedback. I would like to have feedback: | ||
| Using examples from what I have done. | 33 | 27.3 |
| Using a written description of my results. | 22 | 18.2 |
| From somebody who talks it through with me. | 36 | 29.8 |
| Using graphs showing what I achieved. | 30 | 24.8 |
| I want to find out about a house or an apartment. Before visiting it, I would want: | ||
| To view a video of the property. | 50 | 41.3 |
| A discussion with the owner. | 19 | 15.7 |
| A printed description of the rooms and features. | 19 | 15.7 |
| A plan showing the rooms and a map of the area. | 33 | 27.3 |
| I want to assemble a wooden table that came in parts (kitset). I would learn best from: | ||
| Diagrams showing each stage of the assembly. | 38 | 31.4 |
| Advice from someone who has done it before. | 20 | 16.5 |
| Written instructions that came with the parts for the table. | 24 | 19.8 |
| Watching a video of a person assembling a similar table. | 39 | 32.2 |
The learning methods preferred by participants.
The VARK learning preferences among participants are presented in Table 3. The most commonly preferred learning style was visual, reported by 118 participants (97.5%), followed closely by kinesthetic learning, which was preferred by 117 participants (96.7%). Aural learning was endorsed by 107 participants (88.4%), while reading/writing was the least common single-mode preference, reported by 93 participants (76.9%). Regarding multimodal learning preferences, 83 participants (68.6%) exhibited a quadmodal preference, utilizing all four learning styles. A trimodal preference was reported by 27 participants (22.3%), while 11 participants (9.1%) had a bimodal preference.
Table 3
| Item | N | % |
|---|---|---|
| Visual | 118 | 97.5 |
| Aural | 107 | 88.4 |
| Reading/writing | 93 | 76.9 |
| Kinesthetic | 117 | 96.7 |
| Bimodal | 11 | 9.1 |
| Trimodal | 27 | 22.3 |
| Quadmodal | 83 | 68.6 |
The VARK learning preferences among participants.
The satisfaction of participants with the academic curriculum is presented in Table 4. Overall, 75 participants (62.0%) agreed that they were satisfied with the academic program, while 21 (17.4%) strongly agreed. A neutral response was given by 19 participants (15.7%), and 6 (5.0%) disagreed. Regarding the program's ability to meet educational needs, 66 participants (54.5%) agreed, and 25 (20.7%) strongly agreed. A neutral stance was reported by 22 participants (18.2%), while 8 (6.6%) disagreed. For simulation and practical sessions, 55 participants (45.5%) agreed that these sessions effectively enhanced their skills, and 32 (26.4%) strongly agreed. Meanwhile, 29 participants (24.0%) remained neutral, and 5 (4.1%) disagreed. Regarding the integration of hands-on activities into the curriculum, 64 participants (52.9%) agreed, and 23 (19.0%) strongly agreed. A neutral response was given by 28 participants (23.1%), while 6 (5.0%) disagreed. Finally, the total satisfaction score had a mean of 15.61 ± 2.55.
Table 4
| Item | N | % |
|---|---|---|
| I am satisfied with the overall academic program. | ||
|  Disagree | 6 | 5.0 |
|  Neutral | 19 | 15.7 |
|  Agree | 75 | 62.0 |
|  Strongly agree | 21 | 17.4 |
| The program meets my educational needs. | ||
|  Disagree | 8 | 6.6 |
|  Neutral | 22 | 18.2 |
|  Agree | 66 | 54.5 |
|  Strongly agree | 25 | 20.7 |
| Simulation and practical sessions effectively enhance my skills. | ||
|  Disagree | 5 | 4.1 |
|  Neutral | 29 | 24.0 |
|  Agree | 55 | 45.5 |
|  Strongly agree | 32 | 26.4 |
| Hands-on activities are well integrated into the curriculum. | ||
|  Disagree | 6 | 5.0 |
|  Neutral | 28 | 23.1 |
|  Agree | 64 | 52.9 |
| Strongly agree | 23 | 19.0 |
| Total score | ||
| Mean ± SD | 15.61 ± 2.55 | |
The satisfaction of participants with the academic curriculum.
The relation between VARK learning preferences of participants and satisfaction with the academic curriculum is presented in Table 5. For the visual learning preference, participants who preferred visual learning reported a satisfaction score of 15.63 ± 2.58, compared to 15 ± 1 for those who did not prefer visual learning. The difference was not statistically significant (p = 0.676). Regarding the aural learning preference, participants who preferred aural learning had a satisfaction score of 15.73 ± 2.44, while those who did not prefer aural learning had a score of 14.71 ± 3.22. The difference was not statistically significant (p = 0.163). For the reading/writing preference, the satisfaction score was 15.61 ± 2.85 for participants who did not prefer reading/writing, and 15.61 ± 2.47 for those who did. The difference was not statistically significant (p = 0.992). In terms of kinesthetic learning preference, participants who preferred kinesthetic learning had a satisfaction score of 15.66 ± 2.57, while those who did not preferred kinesthetic learning had a score of 14.25 ± 1.26. The difference was not statistically significant (p = 0.279). For combined learning preferences, bimodal learners had a satisfaction score of 14.64 ± 2.54, trimodal learners had 15.67 ± 2.97, and quadmodal learners had 15.72 ± 2.41. The differences across these groups were not statistically significant (p = 0.414).
Table 5
| Item | Satisfaction score | P-value |
|---|---|---|
| Visual | ||
|  No | 15 ± 1 | 0.676 |
|  Yes | 15.63 ± 2.58 | |
| Aural | ||
|  No | 14.71 ± 3.22 | 0.163 |
|  Yes | 15.73 ± 2.44 | |
| Reading/writing | ||
|  No | 15.61 ± 2.85 | 0.992 |
|  Yes | 15.61 ± 2.47 | |
| Kinesthetic | ||
|  No | 14.25 ± 1.26 | 0.279 |
|  Yes | 15.66 ± 2.57 | |
| Combined | ||
|  Bimodal | 14.64 ± 2.54 | 0.414 |
|  Trimodal | 15.67 ± 2.97 | |
|  Quadmodal | 15.72 ± 2.41 | |
The relation between VARK learning preferences of participants and satisfaction with the academic curriculum.
Numerical data are presented as mean ± SD and categorical data are presented as frequency (%), statistical significance at P-value < 0.05.
The relation between gender and VARK learning preference scores is presented in Table 6. For the visual learning preference, male participants scored 3.93 ± 2.33, while female participants scored 4.68 ± 2.47. The difference between genders was not statistically significant (p = 0.095). Regarding the aural learning preference, male participants had a score of 3.32 ± 2.11, and female participants scored 3.51 ± 2.96. The difference was not statistically significant (p = 0.687). For the reading/writing preference, male participants scored 2.12 ± 2.16, while female participants scored 2.53 ± 2.45. The difference was not statistically significant (p = 0.335). In terms of kinesthetic learning preference, male participants scored 5.62 ± 2.63, while female participants scored 4.28 ± 2.37. The difference was statistically significant (p = 0.005), with males scoring higher than females in kinesthetic learning preference
Table 6
| Item | Male (n = 74) | Female (n = 47) | P-value |
|---|---|---|---|
| Visual | 3.93 ± 2.33 | 4.68 ± 2.47 | 0.095 |
| Aural | 3.32 ± 2.11 | 3.51 ± 2.96 | 0.687 |
| Reading/writing | 2.12 ± 2.16 | 2.53 ± 2.45 | 0.335 |
| Kinesthetic | 5.62 ± 2.63 | 4.28 ± 2.37 | 0.005 |
The relation between gender and VARK learning preference scores.
Numerical data are presented as mean ± SD and categorical data are presented as frequency (%), Statistical significance at P-value < 0.05.
The relation between the year of residency and VARK learning preference scores is presented in Table 7. For the visual learning preference, the first-year residents scored 3.94 ± 2.06, the second-year residents scored 4.8 ± 2.81, the third-year residents scored 4.13 ± 2.35, and the fourth-year residents scored 4.04 ± 2.42. The difference between the groups was not statistically significant (p = 0.499). Regarding the aural learning preference, first-year residents scored 3.43 ± 2.36, second-year residents scored 3.23 ± 2.86, third-year residents scored 3.38 ± 2.28, and fourth-year residents scored 3.58 ± 2.45. The difference was not statistically significant (p = 0.965). For the reading/writing preference, first-year residents scored 2.2 ± 1.66, second-year residents scored 2.27 ± 1.96, third-year residents scored 2.53 ± 3.2, and fourth-year residents scored 2.08 ± 2.02. The difference was not statistically significant (p = 0.896). In terms of kinesthetic learning preference, first-year residents scored 5.43 ± 2.48, second-year residents scored 4.7 ± 2.6, third-year residents scored 4.97 ± 2.78, and fourth-year residents scored 5.29 ± 2.66. The difference was not statistically significant (p = 0.694).
Table 7
| Item | 1st year (n = 35) | 2nd year (n = 30) | 3rd year (n = 32) | 4th year (n = 24) | P-value |
|---|---|---|---|---|---|
| Visual | 3.94 ± 2.06 | 4.8 ± 2.81 | 4.13 ± 2.35 | 4.04 ± 2.42 | 0.499 |
| Aural | 3.43 ± 2.36 | 3.23 ± 2.86 | 3.38 ± 2.28 | 3.58 ± 2.45 | 0.965 |
| Reading/writing | 2.2 ± 1.66 | 2.27 ± 1.96 | 2.53 ± 3.2 | 2.08 ± 2.02 | 0.896 |
| Kinesthetic | 5.43 ± 2.48 | 4.7 ± 2.6 | 4.97 ± 2.78 | 5.29 ± 2.66 | 0.694 |
The relation between the year of residency and VARK learning preference scores.
Numerical data are presented as mean ± SD and categorical data are presented as frequency (%), statistical significance at P-value < 0.05.
The relation between gender, year of residency, and satisfaction with the academic curriculum is presented in Table 8. For gender, male participants reported a satisfaction score of 15.96 ± 2.79, while female participants reported a score of 15.06 ± 2.04. The difference in satisfaction scores between males and females was not statistically significant (p = 0.059). Regarding years of residency, first-year residents had a satisfaction score of 15.46 ± 2.87, second-year residents scored 15.43 ± 2.4, third-year residents scored 15.53 ± 2.37, and fourth-year residents scored 16.17 ± 2.55. The difference in satisfaction scores across the years of residency was not statistically significant (p = 0.700).
Table 8
| Item | Satisfaction score | P-value |
|---|---|---|
| Gender | ||
|  Male | 15.96 ± 2.79 | 0.059 |
|  Female | 15.06 ± 2.04 | |
| Years of residency | ||
|  First | 15.46 ± 2.87 | 0.700 |
|  Second | 15.43 ± 2.4 | |
|  Third | 15.53 ± 2.37 | |
|  Fourth | 16.17 ± 2.55 | |
The relation between gender, year of residency, and satisfaction with the academic curriculum.
Numerical data are presented as mean ± SD and categorical data are presented as frequency (%), statistical significance at P-value < 0.05.
Discussion
Emergency medicine residency training represents a uniquely challenging educational environment that demands mastery of both cognitive and procedural skills under time-sensitive conditions. This study sought to investigate the learning preferences of emergency medicine residents using the VARK framework, evaluate their satisfaction with the current academic curriculum, and examine how demographic factors influence these educational experiences. Our findings reveal several fundamental insights about EM education. We discovered an overwhelming predominance of visual and kinesthetic learning preferences among residents, with most utilizing multiple modalities simultaneously, while reading/writing approaches were significantly less common. Residents showed particularly strong reliance on spatial, visual, and hands-on learning methods across various educational contexts. Satisfaction with the curriculum was generally positive, especially for simulation-based components, though learning preferences did not directly correlate with satisfaction levels. While some gender-based differences in learning approaches emerged, neither gender nor training year significantly influenced overall satisfaction with the program.
The near-universal preference for visual (97.5%) and kinesthetic (96.7%) learning among emergency medicine residents reflects the specialty's unique cognitive-procedural demands, which supports recent findings by demonstrating residents consistently favored visual methods for pathophysiology and kinesthetic approaches for clinical knowledge (). This pattern aligns with emergency medicine's characteristic dependence on both hands-on procedural tasks like intubation and visual diagnostics such as trauma imaging, while contrasting sharply with broader medical education trends where found only 33% of general medical students preferred visual learning as their primary style (). Notably, observed PGY1 residents showed stronger kinesthetic preference, whereas senior residents increasingly utilized visual and reading methods, suggesting learning styles evolve with clinical experience toward more diagnostic-focused modalities (). These findings carry critical implications for curriculum design, where high-fidelity simulation should be prioritized for kinesthetic skill development alongside visual case-based learning for diagnostic training, while deliberately incorporating reading/writing components to ensure balanced competency development. The absence of gender differences in learning preferences () further reinforces that emergency medicine's procedural demands standardize educational needs across demographics, though programs should remain vigilant against potential marginalization of auditory learners. When compared with findings of 90.5% kinesthetic preference in problem-based learning curricula (), our results suggest emergency medicine's clinical environment may intensify multimodal learning demands beyond even other active-learning medical education models.
The high rate of quadmodal preference (68.6%) among emergency medicine residents significantly exceeds rates observed in health sciences programs where quadmodal preferences remain rare (), underscoring emergency medicine's distinctive need for integrated learning approaches. This pattern likely stems from multiple interdependent factors: the procedural nature of emergency medicine demands rapid processing of spatial information and technical skill performance under pressure, naturally favoring visual/kinesthetic modes, while cognitive load theory () explains residents' default to these modalities for efficient information processing in high-acuity environments. Supporting this, demonstrated how kinesthetic learners in medical education actively employ multimodal strategies like 3D modeling to master complex anatomical relationships, mirroring emergency medicine residents’ adaptive blending of learning styles (). The substantial gap between emergency medicine's quadmodal prevalence and the 32% rate in preclinical medical students () further suggests self-selection bias may occur as trainees with visual/kinesthetic strengths gravitate toward procedural specialties. These findings carry important implications for curriculum design, where high-fidelity simulation should remain central while deliberately incorporating read/write components for documentation training and auditory elements for communication skills, ensuring comprehensive skills development. Notably, Gangadharan et al.'s finding that multimodal learners achieve higher academic performance reinforces the pedagogical value of this approach in emergency medicine training ().
The pronounced dominance of maps (74.4%) and videos (51.2%) for navigation and online learning in emergency medicine contrasts with text-reliant non-procedural specialties, a dichotomy that reflects emergency medicine's unique spatial intelligence demands and time-sensitive decision-making requirements. This preference aligns with emerging evidence that millennial emergency medicine residents demonstrate significant knowledge gains through online platforms (), particularly for just-in-time learning of complex concepts. The strong preference for hands-on practice (42.1%) not only parallels medicine's experiential learning paradigms but also finds support in contemporary virtual training research, where blended approaches combining virtual reality tutorials with practical scenarios show particular promise for emergency medicine skill acquisition (). These multimodal preferences likely stem from emergency medicine's dual need for rapid skill assimilation and continuous mental mapping of dynamic clinical environments, as evidenced by the successful application of virtual tools for spatial learning in point-of-care ultrasound training (). While this orientation ensures clinical efficiency, it risks creating competency gaps in documentation and evidence synthesis, necessitating deliberate curricular counterbalances like structured note-writing drills integrated with procedural training. The COVID-19 pandemic's forced virtualization of emergency medicine education unexpectedly validated the durability of these visual-spatial learning preferences while revealing opportunities to enhance virtual platforms for procedural training (). Spatial learning strengths evident in map preference could be further cultivated through next-generation 3D anatomy tools and virtual ER navigation simulations, building on demonstrated successes of VR familiarization in emergency scenarios ().
The high curriculum satisfaction (79.4%), with particularly strong endorsement of simulation training (71.9%), aligns with global emergency medicine educational benchmarks and is substantiated by multiple contemporary studies demonstrating the effectiveness of experiential learning modalities in emergency medicine education. This satisfaction persists despite the lack of significant association between VARK preferences and satisfaction scores (p > 0.05), suggesting either that current emergency medicine curricula successfully accommodate diverse learning styles through their multimodal design - as evidenced by the net positive satisfaction with simulation curricula like emergency medicine ReSCu Peds () - or that satisfaction reflects competency achievement rather than academic alignment, a phenomenon observed in both 3-year and 4-year residency programs (). The universal effectiveness of simulation-based training modalities, from disaster medicine competitions () to emergency medicine boot camps (), further supports that satisfaction may be more strongly tied to clinical skill acquisition than to individual learning preferences. Programs should therefore maintain diverse teaching methods while implementing robust competency tracking systems, particularly given the demonstrated capacity of simulation training to maintain educational quality even during disruptions like COVID-19 (Zargaran et al., 2022). The consistency of these findings across different training levels and program structures suggests that emergency medicine's competency-focused culture creates a satisfaction baseline that transcends individual learning style differences, though ongoing monitoring remains essential to ensure all learner needs are met as educational technologies evolve.
The observed gender difference in kinesthetic preference (males scoring higher; p = 0.005) aligns with broader medical education trends, where multiple studies demonstrate consistent male-leaning kinesthetic preferences across disciplines - from preclinical anatomy students () to Iranian medical trainees (). This pattern likely reflects early socialization toward physical-risk tasks, as suggested by findings that male physiotherapy students maintained stronger kinesthetic leanings throughout undergraduate training compared to their female peers' visual/read-write preferences (). Crucially, however, the non-significant satisfaction difference between genders in our study suggests that current emergency medicine training may be associated with neutralizing these baseline disparities, possibly through standardized competency assessments, mirroring Khanal et al.'s observation that learning style differences need not translate to academic performance gaps when robust evaluation systems exist (). These collective findings strongly support maintaining competency-based evaluation frameworks while implementing two key safeguards: (1) proactive monitoring of procedural opportunity distribution to ensure equitable hands-on experience across genders, and (2) targeted faculty development to recognize and counter unconscious biases in clinical teaching assignments. The consistency of these gender-based learning patterns across international contexts (Nepal, Iran, India) and educational levels (preclinical to residency) suggests emergency medicine programs should view this as an endemic pedagogical consideration rather than a local phenomenon.
The absence of significant association between VARK preferences and curriculum satisfaction scores (p > 0.05) challenges conventional assumptions about learning style alignment in medical education. This finding contrasts with neurology clerkship research where learning preferences directly correlate with satisfaction (), suggesting emergency medicine's educational ecosystem operates under distinct dynamics. Rather than indicating ineffective education, the null association likely stems from emergency medicine's robust multimodal curriculum—combining didactics, simulation, and clinical immersion—which appears to universally support diverse learners through multiple concurrent pathways. Furthermore, the specialty's competency-driven culture prioritizes clinical skill mastery during satisfaction evaluations, potentially overshadowing individual educational preferences that dominate in less procedurally intensive disciplines. Notably, the near-universal visual (97.5%) and kinesthetic (96.7%) preferences among residents creates a homogeneity that statistically minimizes detectable associations, though this very consistency confirms the curriculum's alignment with emergency medicine's clinical demands. Consequently, these findings advocate for sustaining multimodal teaching frameworks while vigilantly monitoring equitable access across learning modalities, rather than pursuing resource-intensive individualization strategies. The divergence from neurology's pattern particularly underscores how emergency medicine's high-acuity environment may fundamentally reshape traditional relationships between learning preferences and educational satisfaction.
The lack of significant curriculum satisfaction differences by gender or residency year (p > 0.05) reveals critical strengths in emergency medicine's training paradigm, particularly when contrasted with specialties documenting demographic disparities in educational experiences. Unlike family medicine where training duration impacts satisfaction (), emergency medicine's consistency likely stems from its dual emphasis on standardized competency assessments and team-based performance culture, which collectively minimize subjective evaluation biases. This equitable pattern aligns with Chuented et al.'s findings that structured learning environments enhance resident well-being across demographics (), while diverging from Venkatesh's blended learning study where gender predicted satisfaction differences in preclinical training (). The absence of a decline in engagement or performance among senior residents across residency years further suggests the curriculum adapts effectively to learners' evolving needs, mirroring the high satisfaction rates seen in mandatory research years when support systems are robust ().These findings collectively validate emergency medicine's current assessment frameworks while underscoring the need for continued qualitative monitoring to capture nuanced experiences beyond survey metrics. Importantly, they demonstrate how competency-focused cultures can neutralize demographic variables that influence satisfaction in other training contexts, providing a model for maintaining equity in high-stakes medical education.
Strengths and limitations
This study can be evaluated in light of its strengths and limitations. Among its key strengths is the use of a validated VARK questionnaire (Version 8.01) to reliably assess learning preferences. Another significant strength is the inclusion of emergency medicine residents from eight major tertiary care centers across Riyadh, which enhances the generalizability of findings within the Saudi context. In addition, the standardized data collection through electronic surveys during academic days, combined with simple random sampling, strengthened methodological rigor while minimizing selection bias. Furthermore, the examination of demographic influences, particularly gender and residency year, provided valuable insights into how training progression and sociocultural factors may shape educational experiences. However, several limitations warrant consideration. The final sample size of 121 residents fell short of the calculated target of 197 due to recruitment challenges and response availability during the study period. This reduction may have lowered the statistical power of the study and limited the ability to detect smaller associations between learning preferences and curriculum satisfaction. Additionally, the reduced sample size may affect the precision of estimates for less dominant learning preferences. The exclusive focus on Riyadh-based centers may not fully capture regional variations in training approaches, while the cross-sectional design precludes assessment of how learning preferences evolve over time. Moreover, self-reporting biases and potential non-response patterns may have influenced results, as well as the study's quantitative nature did not explore the underlying reasons behind residents' preferences and satisfaction levels. Furthermore, the curriculum satisfaction survey used in this study was developed by the research team and reviewed by faculty for content relevance, but it was not formally validated. No psychometric properties (e.g., Cronbach's alpha, construct validity) were assessed prior to implementation. Also, the survey was designed to assess overall satisfaction rather than modality-specific satisfaction; it did not include items targeting each VARK domain separately (e.g., no specific item on adequacy of lecture sessions for aural learners). This may have limited the ability to fully capture the correlation between individual learning preferences and satisfaction with corresponding teaching methods. These limitations highlight opportunities for future multi-center longitudinal studies incorporating qualitative methods to provide deeper understanding of curriculum optimization in emergency medicine education.
Conclusion
These findings offer valuable insights for optimizing emergency medicine training programs. The demonstrated alignment between residents' learning preferences and the specialty's procedural demands supports the continued emphasis on multimodal teaching strategies in emergency medicine education. The results reinforce the importance of maintaining flexible, learner-centered approaches that accommodate diverse styles while upholding rigorous competency standards. This study also provides essential baseline data from a non-Western setting, addressing a gap in the literature. These findings support the need for further regional research to confirm whether such patterns generalize across different cultural and educational contexts.
Future recommendations
Building on these findings, several directions emerge for research and curricular development. Future studies should explore how learning preferences evolve during residency and whether specific instructional methods enhance competency for less common learning styles. Mixed-methods research combining quantitative assessments with qualitative interviews would better capture how residents perceive different teaching approaches.
At the curricular level, periodic assessment of learning preferences could identify gaps in instructional methods while maintaining multimodal teaching. Targeted interventions for less dominant styles, such as structured reading/writing components for evidence-based medicine, would ensure balanced support. Faculty development should emphasize awareness of diverse learning needs to create inclusive environments without compromising standardization.
Longitudinal and multi-center studies across different institutions and training models would help determine whether these findings represent consistent patterns in emergency medicine education. By pursuing these directions, the field can continue refining evidence-based training that supports all learners while maintaining high practice standards.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Ethics statement
This study was performed in line with the principles of the Declaration of Helsinki. Ethical approval was obtained under IRB log Number: 24/1303/ IRB from the research ethics committee at the College of Medicine, King Saud University, Riyadh, Saudi Arabia. Written informed consent was obtained from the participants to this study.
Author contributions
FA: Conceptualization, Methodology, Supervision, Validation, Writing – review & editing. HA: Conceptualization, Methodology, Supervision, Validation, Writing – review & editing. GA: Formal analysis, Writing – original draft, Writing – review & editing. NA: Conceptualization, Data curation, Methodology, Project administration, Resources, Writing – review & editing. TA: Conceptualization, Data curation, Methodology, Project administration, Resources, Writing – review & editing.
Funding
The author(s) declared that financial support was not received for this work and/or its publication.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
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Summary
Keywords
curriculum satisfaction, demographic factors, emergency medicine residents, learning preferences, medical education, teaching methods, VARK model
Citation
Abuguyan F, Alhashem HM, Alsaleh GS, Alsalame N and Alnasser T (2026) Exploring VARK learning preferences, curriculum satisfaction, and the impact of demographic factors among emergency medicine residents at multiple training centers in Riyadh. Front. Educ. 11:1823232. doi: 10.3389/feduc.2026.1823232
Received
04 March 2026
Revised
21 May 2026
Accepted
25 May 2026
Published
10 June 2026
Volume
11 - 2026
Edited by
Korakot Apiratwarakul, Khon Kaen University, Thailand
Reviewed by
Nilnetre Mahathanaruk, Mahidol University, Thailand
Kasamon Aramvanitch, Mahidol University, Thailand
Updates
Copyright
© 2026 Abuguyan, Alhashem, Alsaleh, Alsalame and Alnasser.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ghadah Alsaleh Ghadah-alsaleh@hotmail.com
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.