تقييم الطلاب لأنماط التعلم المفضلة لديهم في كلية التربية والآداب بجامعة تبوك وعلاقة ذلك ببعض المتغيرات الديموغرافية

Assessment of students’ learning styles preferences in the faculty of science, Tishreen University, Syria

This study explored the learning styles prevalent among high and low achievers in 14 public and independent senior secondary schools in Lagos State, Nigeria. The study utilised a survey design to elicit information from 414 participants across three local government areas of the state, using a random sampling technique and the English Language Achievement Test (ELAT) instrument. The collected data were analysed using t-test analysis. The findings showed no significant difference in the learning style preferences of high and low achieving students in secondary schools for visual and auditory styles, while there was a significant difference in tactile learning style. Low achievers had a higher preference for the tactile learning style (M = 17.96) than high achievers (M = 16.24). The study also revealed that the most prevalent learning style among high and low achieving students in public and independent secondary schools is visual, followed by auditory, while tactile/kinesthetic is the least prevalent learning style. Based on the findings in this study, a number of recommendations were articulated for teachers, curriculum developers and learners.

On Learning Styles, Academic Performance and Innovative Teaching Practices: Empirical Evidence from Post-Graduate Students at Department of Commerce, University of Delhi

Recognizing students’ preferred learning styles can inform instructional design and support academic success, yet the linkage between learning-style models and teaching practice is often overlooked. In this paper, the interactions between prominent learning style models and both the cognitive and teaching styles are discussed and presented in a novel visual way. Additionally, two courses shared by Electrical Engineering (EE) and Mechanical Engineering (ME) students, and taught by two professors with contrasting teaching styles, are used to assess how instructional approaches interact with learner preferences and outcomes. This research aims to raise two research questions: 1) Should instructors adjust their teaching style based on students’ discipline? 2) Is there a correlation between students’ learning style and their choice of field of study? Four case studies are used to evaluate the impact of teaching styles on the learning of ME and EE students. Results indicate a discipline-specific pattern: EE students predominately display abstract, intuitive, and aural preferences and perform well in theory-oriented settings, whereas ME students more often exhibit concrete, sensing, and kinesthetic preferences and benefit from real-world, hands-on examples to grasp theoretical concepts. These divergent preferences may influence disciplinary orientation and have clear implications for curriculum and pedagogy. While the limited sample precludes definitive conclusions, the observed trends suggest that combining abstract exposition with applied, experiential learning could better accommodate diverse engineering learners.

This study investigated the effect of rhythm based computer-assisted music instruction designed for individual learning style preferences. Participants were undergraduate preservice elementary education majors (N = 82) enrolled in Fundamentals of Music. The Perceptual Learning Style Preferences Survey and the Diablo Valley College Learning Style Survey were used to measure learning preferences. Two content knowledge assessments were administered as pre and posttest: (a) Music Achievement Test (MAT) Test 2-Part 3-Auditory and Visual Discrimination subtest b and (b) Researcher-Developed Rhythm Test (RDRT). Researcher-developed software programs were constructed, teaching participants the basic elements of rhythm based on learning style preferences. Forty-three of the participants (13 auditory, 13 visual, and 17 tactile/kinesthetic) completed software programs designed for their individual learning preferences. A stratified randomly selected group (11 auditory, 10 visual, and 18 tactile/kinesthetic) was assigned software that addressed all learning style strategies (n = 39) to complete the rhythm unit. A repeated measures multivariate analysis of variance (MANOVA) conducted to determine the effect of three types of learning style strategies and two treatments (learner specific and all learning styles) on the two dependent variables (MAT and RDRT) revealed significant differences between the dependent measures. Two separate three-way repeated measures ANOVAs calculated on the MAT and RDRT found significant differences from pretest to posttest, indicating a significant increase in skill level on both measures. MAT scores revealed no significant differences with regards to treatment or learning style preferences. A significant two-way interaction between treatment and pretest to posttest was found for the RDRT. Both groups made significant gains due to treatment from pretest to posttest. The gain was greater for participants who used all learning styles software than for those who used individualized learning styles software. A significant two-way interaction among learning style strategies, RDRT pretest to posttest, was revealed. All participants made large gains due to treatment; tactile/kinesthetic learners gained noticeably less than aural and visual learners. Participants with the highest and lowest posttest scores (n = 23) from each learning style preference were selected for interviews. Overlapping themes indicated positive acceptance of the program, superior educational value, and creative program design.

This study investigated the learning styles of collegiate aviation students. The results of this investigation were compared to the learning styles of qualified pilots in the United States Air Force, as identified in a previous study. Using the Kolb Learning Style Inventory, the objectives were to identify the learning styles of collegiate aviation students, determine if there was a difference in learning style among the grade levels of the college students, and to note the similarities and/or differences in learning styles between the collegiate aviation students and the United States Air Force pilots. The demographic survey used in the previous study was tailored to reflect the disparity of experiences between college students and active pilots in the United States Air Force. The population for this study consisted of students enrolled in the aviation programs at Oklahoma State University-Stillwater campus, Oklahoma State University-Tulsa campus, and Southeastern Oklahoma State University on the Durant campus and at Tinker Air Force Base. Using the results of this study to identify a preferred learning style among college aviation students can provide information about the students’ cognitive mapping. This mapping can be used as a tool so that courses can be more effectively designed. Modifications to this main theme can then be made for those students who have different learning styles. An ideal learning style, due to the predictive nature of Kolb’s Learning Style Inventory, can also identify aviation students as a discrete group from other degree programs on campus.

A study was conducted to compare and evaluate the different learning styles of students in Bangladesh and the United States. The objective was to identify the similarities and differences among individual student learning styles using the Fielder-Silverman model and an index of learning styles, which was compiled using student response data from two universities in Bangladesh and one American university. Statistical analysis was performed to identify the factors affecting learning style, such as the number of years spent in school, cultural background, and academic major. Altogether, eight dimensions were used to study the students’ differences in learning preference. The analysis concluded there was no difference between the learning styles of American and Bangladeshi engineering students. However, the results showed a difference between first year (freshmen) and final year (senior) engineering students on the sensing/intuitive dimension. Differences in learning style were also observed between students from different academic majors on the sensing/intuitive and visual/verbal dimensions.

This study aimed to investigate the preferred learning styles of sports students in higher education in Algeria. Using the Felder-Silverman model, which categorizes learning styles into four dimensions: active-reflective, visual-verbal, sensing-intuitive, and sequential-global, the research also examined differences in learning styles based on specialization, academic level, and diploma. The research involved 268 students from the Sports Institute in Setif, and the data were analyzed using SPSS version 28. The findings revealed a predominant preference for the visual learning style, followed by the sensing and sequential styles. No significant differences were found in learning styles according to specialization. However, significant differences were observed between groups based on academic level and diploma, and the study recommended creating training courses for teachers that adopt modern methods and encourage them to consider the learning styles of each student.

In a student-centered teaching and learning environment, students' needs, potentials, and learning styles are considered crucial. Therefore, teachers need to understand what learning styles students prefer to teach effectively. In the current study, a quantitative research approach has been adopted in this study within it descriptive research designed was used. To determine the preferred learning styles of B.Ed. students, VARK (Visual, Aural, Read/Write, and Kinesthetic) learning style model has been used. Since the data was collected using the VARK questionnaire, simple random sampling techniques were used. The reliability of the instrument was calculated through Cronbach α= 0.75. The sample of the study consists of 140 Bachelor of Education (B.Ed.) students of a Public Sector University located in Northern Sindh, Pakistan. The data were analyzed through descriptive statistics (percentages mean and standard deviation) to determine the most preferred style of learning of students. The results of the study revealed that 27.93% of the B.Ed. students have preferred aural learning style, 25.13% kinaesthetic learning style, 22.65% visual style of learning and 21.09% preferred read/write learning style respectively. To conclude that the majority of the B.Ed. students preferred aural learning style and the least preferred style of learning was read/write. Hence, B.Ed. students were driven towards an aural learning style. This study suggests that students learning styles are influenced by the teacher’s teaching style. Therefore, the teacher can determine his/her teaching style by using the score of the VARK questionnaire. The study recommends that another study can be conducted by the teachers to learn about the larger number of students’ preferred learning styles. The teacher can also address a mixture of learning styles. In the classroom, there are always diverse learners. In that case, the teacher can use integrated teaching style which can address all learners preferred teaching style.

The present study investigates gender-based differences in learning styles among IX standard students. Recognizing individual learning preferences, especially in relation to gender, is crucial for enhancing instructional effectiveness during adolescence a stage of cognitive and emotional development. Using a survey method, data were collected from 300 students across six schools using the standardized Learning Style Inventory by J.M. Reid. Statistical analysis, including descriptive statistics and the two-tailed t-test, revealed no significant difference in learning styles between boys and girls. These findings align with previous studies, indicating that while learning preferences may vary, gender alone does not significantly impact learning style. The study underscores the importance of adopting diverse, learner-centered teaching strategies that address varied learning needs, thereby promoting inclusive and effective classroom practices.

INTRODUCTION: Learning styles refer to the ways an individual processes and retain new information and skills. Knowledge about preferred learning styles can assist in developing effective pedagogies and enhance classroom–learning experiences. Optimal learning environments consider how students learn and utilize various teaching methods for curriculum delivery to match specified student learning preferences. METHODS: This cross-sectional study presents the findings of the preferred learning style of 97 physiotherapy students studying in JSS College of Physiotherapy, Mysuru, using a self-administered questionnaire developed by Victoria Chislett and Alan Chapman, 2005. Data were collected using the survey method through Google Forms. RESULTS: We found equal distribution of unimodal and multimodal learning style. Among the unimodal style of learning, 20.6% of participants had predominantly auditory learning style. 15.46% of participants had predominantly visual learning style. 10.3% of participants had predominantly kinesthetic learning style. In multimodal style of learning, 21.6% of participants had predominantly visual and auditory learning styles. 15.46% of participants had predominantly visual and kinesthetic learning style. 12.37% of participants had predominantly auditory and kinesthetic learning style and only 1% of participants had visual, auditory, and kinesthetic learning style. CONCLUSION: The most preferred unimodal learning style among physiotherapy students was auditory followed by visual and kinesthetic. The most preferred multimodal style of learning was visual and auditory, followed by visual and kinesthetic.

PowerPoint presentations (PPTs) have become routine in medical colleges because of their flexible and varied presentation capabilities. Research indicates that students prefer PPTs over the chalk-and-talk method, and there is a lot of debate over advantages and disadvantages of PPTs. However, there is no clear evidence that PPTs improve student learning/performance. Furthermore, there are a variety of learning styles with sex differences in classrooms. It is the responsibility of teacher/facilitator and student to be aware of learning style preferences to improve learning. The present study asked the following research question: do PPTs equally affect the learning of students with different learning styles in a mixed sex classroom? After we assessed students' predominant learning style according to the sensory modality that one most prefers to use when learning, a test was conducted before and after a PPT to assess student performance. The results were analyzed using Student's t-test and ANOVA with a Bonferroni post hoc test. A z-test showed no sex differences in preferred learning styles. There was significant increase in posttest performance compared with that of the pretest in all types of learners of both sexes. There was also a nonsignificant relationship among sex, learning style, and performance after the PPT. A PPT is equally effective for students with different learning style preferences and supports mixed sex classrooms.

“From the classroom to Dr. YouTube”: nursing students' experiences of learning and teaching styles in Jordan

The study aimed at determining the learning styles of students pursuing master's degree programmes in engineering. Index of Learning Style was administered to 175 students. The findings reveal that there exist differences in learning styles of students pursuing master's degree in computer science and engineering, civil engineering, electrical engineering, electronics and communication engineering and mechanical engineering.Majority of the students of various branches except of mechanical engineering prefer active, sensing, visual and sequential learning styles but very few of them have strong preference for a particular learning style.

Learning styles play an important role in determining the most effective teaching strategies by aligning instructional methods with students’ individual preferences in receiving, processing, and understanding information. However, classroom teaching is often applied uniformly, disregarding the differences in learning styles among students. This can hinder the effectiveness of the learning process. This research aims to develop a web-based expert system using the Euclidean Probability method to identify the dominant learning styles of students at SMK Negeri 3 Lhokseumawe. The system processes input data representing student characteristics and calculates the proximity to each learning style category using the Euclidean distance formula. A total of 110 student data entries were analyzed, revealing that 32 students (29.09%) had a Visual learning style, 26 students (23.64%) were Auditory, 16 students (14.55%) were Read/Write, and 36 students (32.73%) were Kinesthetic learners. The results showed that the Kinesthetic learning style was the most dominant among students. Therefore, this expert system can efficiently assist in determining students' learning styles, allowing for quick and accurate identification of their learning preferences. This supports the development of more personalized and adaptive learning strategies, which are expected to enhance student engagement and learning outcomes.