Relationships between Cognitive and Learning Styles of Premedical Students

Ahn, Sowon; Kim, Mi-Ra; Ahn, Duck Sun

doi:10.3946/kjme.2010.22.1.7

Cited by 11 publications

(6 citation statements)

References 12 publications

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“…Researchers hypothesize that a relation exists between the learning style and cognitive style. The outcomes of the existing research clearly shows that the information processing is linked to the preferred learning style of an individual (Ahn et al, 2010). Thus, the existing studies conclude that every individual has their own preferred learning style.…”

Section: Introductionmentioning

confidence: 99%

Classification of Visual and Non-visual Learners Using Electroencephalographic Alpha and Gamma Activities

Jawed

Amin

Malik³

et al. 2019

Front. Behav. Neurosci.

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This study analyzes the learning styles of subjects based on their electroencephalo-graphy (EEG) signals. The goal is to identify how the EEG features of a visual learner differ from those of a non-visual learner. The idea is to measure the students’ EEGs during the resting states (eyes open and eyes closed conditions) and when performing learning tasks. For this purpose, 34 healthy subjects are recruited. The subjects have no background knowledge of the animated learning content. The subjects are shown the animated learning content in a video format. The experiment consists of two sessions and each session comprises two parts: (1) Learning task: the subjects are shown the animated learning content for an 8–10 min duration. (2) Memory retrieval task The EEG signals are measured during the leaning task and memory retrieval task in two sessions. The retention time for the first session was 30 min, and 2 months for the second session. The analysis is performed for the EEG measured during the memory retrieval tasks. The study characterizes and differentiates the visual learners from the non-visual learners considering the extracted EEG features, such as the power spectral density (PSD), power spectral entropy (PSE), and discrete wavelet transform (DWT). The PSD and DWT features are analyzed. The EEG PSD and DWT features are computed for the recorded EEG in the alpha and gamma frequency bands over 128 scalp sites. The alpha and gamma frequency band for frontal, occipital, and parietal regions are analyzed as these regions are activated during learning. The extracted PSD and DWT features are then reduced to 8 and 15 optimum features using principal component analysis (PCA). The optimum features are then used as an input to the k -nearest neighbor ( k -NN) classifier using the Mahalanobis distance metric, with 10-fold cross validation and support vector machine (SVM) classifier using linear kernel, with 10-fold cross validation. The classification results showed 97% and 94% accuracies rate for the first session and 96% and 93% accuracies for the second session in the alpha and gamma bands for the visual learners and non-visual learners, respectively, for k -NN classifier for PSD features and 68% and 100% accuracies rate for first session and 100% accuracies rate for second session for DWT features using k -NN classifier for the second session in the alpha and gamma band. For PSD features 97% and 96% accuracies rate for the first session, 100% and 95% accuracies rate for second session using SVM classifier and 79% and 82% accuracy for first session and 56% and 74% accuracy for second session for DWT features using SVM classifier. The results showed that the PSDs in the alpha and gamma bands represent distinct and stable EEG signatures for visual learners and non-visual learners during the retrieval of the learned contents.

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Section: Introductionmentioning

confidence: 99%

Classification of Visual and Non-visual Learners Using Electroencephalographic Alpha and Gamma Activities

Jawed

Amin

Malik³

et al. 2019

Front. Behav. Neurosci.

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“…Data acquired from other published works (Fig. 3 ) have indicated that medical students have active, visual, sensing, and sequential LS priorities (except Nazarbayev and Taibah universities) [ 10 , 17 , 25 , 26 and 27 ]. Our clinical medical students’ learning styles were basically the same as those of the other medical students, but the active/reflective style was more balanced (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…According to the outcomes, students’ LS priorities were perceptual, sequential, and visual. Accordingly, as discussed in the literature, students majoring in the medical field prefer to master knowledge via demonstrations, photos, practice and familiarity with facts, diagrams, and algorithms sequentially and linearly [ 10 , 26 , 27 ]. Nevertheless, according to the analyses, no considerably significant differences were observed between priorities when continual active-reflective learning was a concern.…”

Section: Discussionmentioning

confidence: 99%

“…According to our outcomes, the dominant LSs for Chinese medical students were perceptual and visual, in line with the previously obtained outcomes. In addition, although some works have reflected medical students’ positive learning style priorities [ 17 , 26 ], others have indicated that reflective or active information processing is an insignificant priority [ 12 ]. The obtained outcomes reflect more balance in the dimension of active/reflective learning and the dominance of the sequential learning style, which is compatible with the LS of King Edward Medical University MSs.…”

Section: Discussionmentioning

confidence: 99%

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Learning styles of medical students from a university in China

Liu

Liu²

2023

BMC Med Educ

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Background Investigating students’ learning styles can generate useful information that can improve curriculum design. This study adopts diverse measures to identify the learning styles of students despite limited literature related to clinical medical students in China. We utilized Felder’s Index of Learning Styles to examine the learning style characteristics of clinical medical students at Inner Mongolia Minzu University. Methods Cluster sampling (probability sampling) was used. This cross-sectional study investigated clinical medicine students with regard to their learning style preference and the difference across genders. This study also analysed data collected from other published studies. A total of 411 students from the medical school at Inner Mongolia Minzu University completed the Index of Learning Styles Questionnaire. The questionnaire assessed the learning styles of students in four dimensions: visual-verbal learning, sequential-global learning, active-reflective leaning, and sensing-intuitive learning. Results The analysis results show that clinical medicine students choose to receive visual information (73.97% of the student sample) instead of verbal information. These students prioritize sensory information (67.15%) rather than intuitive information and process reflective information (51.82%) rather than active information. They prefer to process information sequentially (59.85%) instead of globally. Our results also show that male students present a higher preference for an active learning style over a reflective learning style, while female students seem to present a higher preference for a reflective learning style over an active learning style. These preferences vary between cohorts (gender), but the difference is not statistically significant. Compared to data collected from other published studies, active, visual, sensing, and sequential are the most popular styles of learning adopted by medical science students. Conclusions The identification of medical students’ learning style in China provides information that medical educators and others can use to make informed choices about modification, development and strengthening of medical educational programs. Our outcomes may potentially improve motivation, engagement and deep learning in medical education when used as a supplement to teaching/learning activities.

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“…Mayer and Massa [6] suggested a standard that can differentiate learning style, cognitive style, and cognitive ability as follows: cognitive ability is an ability to do something; cognitive style involves a method that people use to process and represent information; and learning style refers to the style of information presentation that people prefer. Moreover, An et al [7] reported that there is a correlation between visual-verbal aspects of cognitive style and learning style. Summing up Mayer and Massa's and An et al's results, we can see that the type of information that a learner prefers is related to the way he/she processes and represents that information.…”

Section: Introductionmentioning

confidence: 99%

An EEG Study on Visual Learners’ Performance a Scientific Classifying Task Composed of Pictures and Words

Kim¹,

Ilho²,

Lim³

2015

Advanced Science and Technology Letters

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The purpose of this study is to examine how brain waves differ when a visual learner performs a classifying task that conforms to her learning style compared to a classifying task that does not. For this purpose, we measured the brain waves of seven visual learners while they were conducting scientific classifying tasks that are composed of pictures and words to compare the relative power spectrum. According to the results, the average relative power of EEG theta waves decreased and the average relative power of EEG beta waves increased when they performed a picture classifying task rather than a word classifying task. Moreover, in the case of the word classifying task, not only the Wernicke's area of the left hemisphere, but also the temporal lobe of the right hemisphere showed the strong relative power spectrum of gamma waves.

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Relationships between Cognitive and Learning Styles of Premedical Students

Abstract: In the visual (imagery)-verbal dimension, there was some correlation between cognitive and learning styles.

Cited by 11 publications

References 12 publications

Classification of Visual and Non-visual Learners Using Electroencephalographic Alpha and Gamma Activities

Classification of Visual and Non-visual Learners Using Electroencephalographic Alpha and Gamma Activities

Learning styles of medical students from a university in China

An EEG Study on Visual Learners’ Performance a Scientific Classifying Task Composed of Pictures and Words

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