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The relationship between learning styles and academic performance: consistency among multiple assessment methods in psychology and education students.

1. Introduction

1.1. learning styles: experiential learning theory, 1.2. assessment method, academic performance and learning dimensions, 1.3. present study, 2. materials and methods, 2.1. participants, 2.2. instruments.

• Multiple choice questions (MCQ). The contents were evaluated through multiple choice tests. Using this closed question method, students had to identify a single valid response among four alternatives. The following is an example of an MCQ used in the assessment: “The increase in explicit memory in children is associated with: (a) the autonomy of the child when learning to walk and handle objects; (b) an increase in the density of synapses at four months; (c) an increase in the density of synapses at eight months (correct answer); (d) the importance of holophrases in children to store memory”. A total of 30 MCQ were used with a final score of 0 to 10.
• Short questions (SQ). This method used short and closed questions. In this test, the student is given a statement in order to identify a concept. An example is given below: “Identify the developmental theory that states that the zone of proximal development refers to the distance between the actual level of development and the level of potential development”. In this case, the correct answer would be: Vygotsky’s Sociocultural Theory. A total of 10 SQ were used with a final score ranging from 0 to 10.
• Creation-elaboration questions (CEQ). In this open-ended question, students must create a practical activity based on the contents studied in the developmental psychology course. This method involves mainly a practical question. The CEQ used in the tests was: “Create an activity to work on the understanding other people’s emotions in a class of 5-year-olds”. With a score between 0 and 10 points, the structure of the activity, creativity, and suitability with the contents of the course were used as criteria to evaluate performance on the CEQ.
• Elaboration Questions on the Relationship between Theory and Practice (EQRTP). In this open-ended assessment question, students must link theoretical concepts to practical application. A video is used to illustrate a teaching-learning process between children and an expert, and various interactions between children. After watching the video, students must analyze its content using theoretical concepts. Below is the examination question and a link to the video used ( https://www.dropbox.com/s/xux6p9di5pj885m/Sustainability.mp4?dl=0 ) (accessed on 29 January 2021) [ 48 ] “Associate the following video with theoretical contents of the Developmental Psychology course”. The number of associations between practical aspects and theoretical contents, coherence between concepts, presentation of theory and clarity in the written composition were used as criteria to assess performance from 0 to 10.

2.3. Procedure

2.4. data analysis, 3.1. learning styles according to personal and educational dimensions, 3.2. assessment methods: academic performance and consistency and their relation to learning dimensions and styles, 3.3. influence of learning dimensions on performance consistency in the different assessment methods, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, acknowledgments, conflicts of interest.

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Maya, J.; Luesia, J.F.; Pérez-Padilla, J. The Relationship between Learning Styles and Academic Performance: Consistency among Multiple Assessment Methods in Psychology and Education Students. Sustainability 2021 , 13 , 3341. https://doi.org/10.3390/su13063341

Maya J, Luesia JF, Pérez-Padilla J. The Relationship between Learning Styles and Academic Performance: Consistency among Multiple Assessment Methods in Psychology and Education Students. Sustainability . 2021; 13(6):3341. https://doi.org/10.3390/su13063341

Maya, Jesús, Juan F. Luesia, and Javier Pérez-Padilla. 2021. "The Relationship between Learning Styles and Academic Performance: Consistency among Multiple Assessment Methods in Psychology and Education Students" Sustainability 13, no. 6: 3341. https://doi.org/10.3390/su13063341

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The Relationship Between the VARK Learning Styles and Academic Achievement in Dental Students

Hamid reza mozaffari.

1 Department of Oral and Maxillofacial Medicine, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran

Maryam Janatolmakan

2 Medical Surgical Nursing, Clinical Research Development Center, Imam Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran

Roohollah Sharifi

3 Department of Endodontic, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran

Fatemeh Ghandinejad

4 Kermanshah University of Medical Sciences, Kermanshah, Iran

Bahare Andayeshgar

5 Statistic, Clinical Research Development Center, Imam Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran

Alireza Khatony

6 Social Development and Health Promotion Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran

Learning style is a factor influencing academic achievement. There are contradictory results in studies on the relationship between learning styles and academic achievement. The current study aimed at investigating the relationship between learning styles and academic achievement in dental students.

In the current descriptive-analytical study, 184 dental students were selected by simple random sampling. The VARK questionnaire was used as the data collection tool. The grade point average (GPA) of previous semester was used as an indicator of academic achievement, and accordingly, students were divided into two groups of strong (GPA ≥15) and weak (GPA ≤14.99).

The most common learning styles in strong students were unimodal (n = 55, 42%) and bimodal (n = 41, 31.3%), while they were unimodal (n = 28, 47.2%) and bimodal (n = 24, 45.3%) in the weak students. There was no significant relationship between learning styles and academic achievement in the two groups of strong and weak students.

No significant relationship was found between learning style and academic achievement. Further studies with larger sample sizes are recommended. Further studies with larger sample sizes are recommended.

Introduction

Academic achievement is one of the most important parameters used to predict the future academic status of learners. 1 Learning styles are of the factors influencing academic achievement. 2 The learning style is defined as a combination of cognitive, emotional, and physiological traits that show how the learner perceives and responds to the learning environment. 3 Understanding learning style of learners can be effective in organizing and modifying the learning environment and teaching and learning process. 4 Each student has his/her own learning style. 5 There are several methods to measure learning styles and the VARK questionnaire developed by Fleming and Mills (1992) is the most widely used one. According to this questionnaire, learning styles comprises visual (V), aural (A), reading/writing (R), and kinesthetic (K) models. 6 Visual learners learn through watching videos, images, and figures. Aural learners learn through listening to lectures; reading-writing learners through reading texts and writing notes on them, and kinesthetic learners through touch and manipulation of objects. 6 , 7 According to the VARK model, one may apply multiple learning styles. 4 Various studies investigated the relationship between learning styles and academic achievement in students of different disciplines. In some of these studies, a significant relationship was found between learning style and academic achievement, 8 – 12 while in some others, no significant relationship reported. 13 , 14 The current study was designed and conducted in light of the importance of knowledge of teachers about learners’ learning styles, and contradictory results of different studies on the relationship between learning styles and academic achievement. The present study aimed at determining the relationship between type and number of learning styles based on the VARK model and academic achievement in dental students of Kermanshah University of Medical Sciences (KUMS).

Materials and Methods

Study design.

The current cross-sectional, descriptive-analytical study was performed on dental students.

Study Questions

We sought to answer the following questions: 1) What is the academic status of dental students?, 2) What is the frequency of learning styles among dental students?, and 3) What is the relationship between academic achievement and learning style in dental students?

Sample and Sampling Method

The study population included dental students of KUMS. The Cochran formula was used to determine the sample size; with a confidence of 95%, the sample size was 184. Inclusion criteria were willingness to participate in the study and studying in third semester and higher. Simple random sampling was used in the current study.

Measurement Instrument

Data collection tools included a demographic information sheet and the VARK questionnaire. The demographic information sheet included four items on age, gender, marital status, and the grade point average (GPA) of the two latter semesters. The VARK questionnaire is a standard tool, 15 which its validity and reliability were assessed and confirmed in a study by Zhu (2018). 16 The Persian version of the VARK questionnaire was psychometrically assessed by Mehdipour et al, (2018) in Iran. 17

The VARK questionnaire consists of 16 multiple-choice items and can be used to identify four types of learning styles. Each item is related to a particular style. The respondents should choose the options according to their preferences, and if one choice does not reflect the whole view, they can choose more options and leave items not happened yet. Higher scores in each learning style indicate the respondents’ greater desire for that style. If an individual gets equal scores in two or more styles, his/her learning style is considered “multimodal”. Total score in each item ranges from zero to 16. The GPA of the last two semesters was used to determine academic status. The students were divided into two groups of strong (GPA ≥15) and weak (GPA ≤14.99) based on their GPA.

Data Collection

First, the list of students studying in the third semester and above was taken from the Department of Education at the Faculty of Dentistry, and numbered. Then, using random number table, 184 students entered the study and the ones who agreed to participate, received a questionnaire.

Data Analysis

Data were analyzed by the SPSS v.18.0 software using descriptive and inferential statistics. First, the Kolmogorov–Smirnov test, showing abnormal distribution of GAP and learning style variables, was performed. Chi-Squared test was also utilized to determine the relationship between academic achievement and learning styles. The significance level was considered less than 0.05.

Ethical Considerations

The Ethics Committee of the University approved the study with the code: KUMS.REC.2017.627. Written informed consent was obtained from all students and they were assured of the confidentiality of their information.

According to the obtained results, most subjects were female (58.7%, n = 108) and single (63%, n = 116). Their mean age was 24±30 years. In the group of strong students, majority of the subjects were within the age range of 21–23 years, but in the weak students group, 24–27 years was the most frequent age group (41.5%, n = 22) ( Table 1 ).

Demographic Characteristics of Study Subjects (n=184)

Results showed that the majority of students (n = 131, 71%) were in the strong group. In addition, reading-writing (n = 87.66.4%) and kinesthetic (n = 22, 16.8%) were the most and least frequent learning styles, respectively, in the strong group. Also, in the weak students group, the reading-writing and kinesthetic learning styles had the highest (n = 30, 56.6%) and lowest (n = 7, 13.2%) frequencies, respectively. Regarding the learning style used, no significant difference was found between strong and weak students ( Table 2 ). In terms of the number of learning styles used by the strong students, the results showed that 42% (n = 55) of the subjects were unimodal and about one-third bimodal (n = 41, 31.3%). In the weak students group, the majority of subjects were unimodal (n = 28, 47.2%) and bimodal (n = 24, 45.3%). There was no significant difference in the number of learning styles used between the strong and weak student groups ( Table 3 ).

Relationship Between Types of Learning Styles and Academic Achievement in Study Subjects

Notes: *Grade Point Average. **Non-significant.

Relationship Between Number of Learning Styles and Academic Achievement Among Study Subjects

The current cross-sectional study aimed at determining the relationship between the type of learning style used and academic achievement in dental students. Findings showed that reading/writing style had the highest frequency in both groups of strong and weak students. In a study (2016) on the learning style of dental students in Saudi Arabia, kinesthetic (35.1%) and aura (35.1%) were the most common learning styles used. 6 Results of a study (2018) in Saudi Arabia on dental students showed that the most commonly used learning styles were aural and kinesthetic. 18 In a study in the USA on anatomy students (2018), the most common learning style was kinesthetic. 19 The results of the study by Habibpour et al (2016), in Iran on medical students showed that the most common learning style used was reading-writing. The results of the aforementioned studies show that students have various learning styles. The predominance of some particular learning styles in students can be related to their field of study, teaching methods, learning experiences, curriculum content, and volume of course content. Therefore, it is suggested that teachers pay more attention to the differences in learning styles among students when preparing the lesson plan.

In the current study, 42% of strong students and 47.2% of their weak peers were unimodal and in fact had a predominant learning style. The result was similar to those of the study by Zamani and Kaboodi (2017) on Iranian students, and Siddiqi et al (2012) and Haq et al (2012) in Pakistan. 3 But in studies by Moshabab (2016) and Al-Saud (2013) in Saudi Arabia, Murphy et al (2004) in the USA, and Tantawi (2009) in Egypt, the predominant learning style of most dental students was multimodal, 6 , 20 – 22 which is not in line with the result of the current study. The reasons for inconsistency between the results of the current study and the aforementioned studies may be differences in personal characteristics of the studied subjects and the teaching method of lecturers in the colleges.

The results showed no significant relationship between learning style and academic achievement. Almigbal et al (2015) in Saudi Arabia, Dobson et al (2010) and Dobson et al (2009) in the USA (2014), Urva et al in India (2014), and Mlambo et al (2011) in Jamaica also did not find a significant relationship between learning style and academic achievement, 13 , 23 – 26 but Samarakoon et al (2013) in Sri Lanka, and Habibpour et al (2016) and Panahi et al (2012) in Iran reported a significant relationship between learning style and academic achievement in students. 27 – 29 The relationship between learning style and academic achievement may vary in different situations. Choosing a teaching method based on the students’ learning style can increase the students’ interest in lessons and encourage their participation in the classroom, which can influence their academic achievement.

The present study also had some limitations. Since the current study had a cross-sectional design, it was not possible to investigate the likelihood of a cause-and-effect relationship between learning style and academic achievement. The self-report method used to collect data in the current study might affect the accuracy of the results. The individuality of learning style used can also influence the generalizability of the results. Since students from third vs last grade may present differences due to acquired experience and maturity, the results might be affected when comparing students from different grades.

The most common learning style in strong and weak students was the reading-writing model. Most of the strong and weak students were unimodal and, in fact, had the same learning style preferences. No significant relationship was found between type and number of learning styles and academic achievement. Further studies with larger sample sizes are recommended in other dental schools.

Acknowledgments

This article was drawn from a research project (No 95563) sponsored by deputy of research and technology of Kermanshah University of Medical Sciences. We would like to express our sincere gratitude to all the students who participated in this research. We highly appreciate the Clinical Research Development Center of Imam Reza Hospital for their wise advices.

Funding Statement

This study was drawn from a research project (No 95563) sponsored by deputy of research and technology of Kermanshah University of Medical Sciences.

The authors report no conflicts of interest in this work.

• Research article
• Open access
• Published: 04 December 2018

The relationship between learning styles and academic performance in TURKISH physiotherapy students

• Nursen İlçin   ORCID: orcid.org/0000-0003-0174-8224 1 ,
• Murat Tomruk 1 ,
• Sevgi Sevi Yeşilyaprak 1 ,
• Didem Karadibak 1 &
• Sema Savcı 1  

BMC Medical Education volume  18 , Article number:  291 ( 2018 ) Cite this article

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Learning style refers to the unique ways an individual processes and retains new information and skills. In this study, we aimed to identify the learning styles of Turkish physiotherapy students and investigate the relationship between academic performance and learning style subscale scores in order to determine whether the learning styles of physiotherapy students could influence academic performance.

The learning styles of 184 physiotherapy students were determined using the Grasha-Riechmann Student Learning Style Scales. Cumulative grade point average was accepted as a measure of academic performance. The Kruskal-Wallis test was conducted to compare academic performance among the six learning style groups (Independent, Dependent, Competitive, Collaborative, Avoidant, and Participant).

The most common learning style was Collaborative (34.8%). Academic performance was negatively correlated with Avoidant score ( p  < 0.001, r  = − 0.317) and positively correlated with Participant score ( p  < 0.001, r  = 0.400). The academic performance of the Participant learning style group was significantly higher than that of all the other groups ( p  < 0.003).

Conclusions

Although Turkish physiotherapy students most commonly exhibited a Collaborative learning style, the Participant learning style was associated with significantly higher academic performance. Teaching strategies that encourage more participant-style learning may be effective in increasing academic performance among Turkish physiotherapy students.

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Learning can be defined as permanent changes in behavior induced by life [ 1 ]. According to experiential learning theory, learning is “the process whereby knowledge is created through the transformation of experience” [ 2 , 3 ].

Facilitating the learning process is the primary aim of teaching [ 4 ]. Understanding the learning behavior of students is considered to be a part of this process [ 5 ]. Therefore, the concept of learning styles has become a popular topic in recent literature, with many theories about learning styles put forward to better understand the dynamic process of learning [ 2 , 3 ].

Learning style refers to an individual’s preferred way of processing new information for efficient learning [ 6 ]. Rita Dunn described the concept of learning style as “a unique way developed by students when he/she was learning new and difficult knowledge” [ 7 ]. Learning style is about how students learn rather than what they learn [ 1 ]. The learning process is different for each individual; even in the same educational environment, learning does not occur in all students at the same level and quality [ 8 ]. Research has shown that individuals exhibit different approaches in the learning process and a single strategy or approach was unable to provide optimal learning conditions for all individuals [ 9 ]. This may be related to students’ different backgrounds, strengths, weaknesses, interests, ambitions, levels of motivation, and approaches to studying [ 10 ]. To improve undergraduate education, educators should become more aware of these diverse approaches [ 11 ]. Learning styles may be useful to help students and educators understand how to improve the way they learn and teach, respectively.

Determining students’ learning styles provides information about their specific preferences. Understanding learning styles can make it easier to create, modify, and develop more efficient curriculum and educational programs. It can also encourage students’ participation in these programs and motivate them to gain professional knowledge [ 9 ]. Therefore, determining learning style is quite valuable in order to achieve more effective learning. Researching learning styles provides data on how students learn and find answers to questions [ 5 ].

Considering the potential problems encountered in the undergraduate education of physiotherapists, determining the learning style of physiotherapy students may enable the development of strategies to improve the learning process [ 12 ]. Studies on learning styles in the field of physiotherapy have mostly been conducted in developed countries such as Canada and Australia [ 13 , 14 ]. A study conducted in Australia examined the learning styles of physiotherapy, occupational therapy, and speech pathology students. The results of this study suggest that optimal learning environment should also be taken into consideration while researching how students learn. The authors also stated that future research was needed to investigate correlations between learning styles, instructional methods, and the academic performance of students in the health professions [ 14 ].

To the best of our knowledge, there are no prior publications in the literature that report Turkish physiotherapy students’ learning styles. Furthermore, previous studies mostly used Kolb’s Learning Style Inventory (LSI), Marshall & Merritts’ LSI, or Honey & Mumford’s Learning Style Questionnaire (LSQ) to assess learning styles [ 5 , 13 , 15 , 16 , 17 , 18 ]. Some of these studies also suggested that learning behavior and styles should be investigated using different inventories [ 5 ]. Moreover, a scale that was indicated as valid and reliable for Turkish population was needed to accurately determine the learning styles of Turkish physiotherapy students. Therefore, we opted to use the Grascha-Riechmann Learning Style Scales (GRLSS) to assess the learning styles of physiotherapy students, which will be a first in the literature.

Learning style preferences are influential in learning and academic achievement, and may explain how students learn [ 19 ]. Previous studies have demonstrated a close association between learning style and academic performance [ 20 , 21 ]. Learning styles have been identified as predictors of academic performance and guides for curriculum design. The aim of this study was to determine whether learning style preferences of physiotherapy students could affect academic performance by identifying the learning styles of Turkish physiotherapy students and assessing the relationship between these learning styles and the students’ academic performance. Since physiotherapy education mainly consists of practice lessons and clinical practice and mostly requires active student participation, we hypothesized that physiotherapy students with a Collaborative learning style according to the GRLSS would have higher academic performance.

A cross-sectional survey design using a convenience sample was used. The study population consisted of 488 physiotherapy students who were officially registered for the 2013–2014 academic year in Dokuz Eylul University (DEU) School of Physical Therapy and Rehabilitation. A minimum sample size of 68 participants was calculated with 95% confidence interval and 80% power by using “Epi Info Statcalc Version 6”. Inclusion criteria were (i) age ≥ 17 years, (ii) official registration in DEU School of Physical Therapy and Rehabilitation for the 2013–2014 academic year, (iii) being a first-, second-, third-, or fourth-year undergraduate student of physiotherapy, (iv) ability to read, write, and understand Turkish, and (v) being willing and able to participate in the study. Exclusion criteria were (i) unwilling to participate in the study, (ii) inability to read, write, and understand Turkish. The questionnaire was distributed to the physiotherapy students in a classroom setting during the final exam week of the academic year. Due to the absence of participants who did not attend final exams and were not actively attending classes (non-attendance students), questionnaires were distributed to 217 students in total.

184 physiotherapy students with a mean ± SD age of 21.52 ± 1.75 years participated in the study. Participants were informed verbally and in writing about the purpose of the study and the survey that would be implemented. A research assistant was available in the classroom to provide assistance if required. Demographic characteristics (age, gender, undergraduate year) comprised the first section of the questionnaire, followed by the GRLSS to assess learning style.

Cumulative grade point average (CGPA) shown on the students’ transcripts was used as the measure of academic performance. The students’ CGPAs at the end of the 2013–2014 academic year were obtained from the records held in the student affairs unit of the DEU School of Physical Therapy and Rehabilitation. CGPA was derived by multiplying the grade point (out of 100) with the credit units for each module or course and then dividing the total sum by the total credit units taken in the program.

The local university ethics committee provided ethical approval and informed consent was obtained from the participants before inclusion. Ethical protocol number was 1432-GOA.

Data collection

Grasha-riechmann student learning style scales.

The GRLSS is a five-point Likert-type scale ( response format: strongly disagree, moderately disagree, undecided, moderately agree, strongly agree ) consisting of 60 items which was designed based on student interviews and survey data [ 22 , 23 ]. In accordance with the response to student attitudes toward learning, classroom activities, teachers and peers, six learning styles were defined [ 24 ]. Learning styles that form subscales are the Independent, Avoidant, Collaborative, Dependent, Competitive, and Participant learning styles [ 24 , 25 ]. The six main styles in the GRLSS are described in Table  1 and the scoring of the GRLSS is shown in Table  2 [ 23 , 24 ]. The GRLSS was adapted to Turkish in 2003 and found to have good reliability [ 25 ] (Table  3 ).

The learning styles of the physiotherapy students in the current study were identified according to GRLSS and the students were grouped based on their predominant (highest scoring) style. The mean and median academic performance values of each group were calculated and the significance of the differences between groups was statistically analyzed.

Statistical analysis

Statistical analyses were performed to compare academic performances among the learning style groups and test the significance of pairwise differences. All data were analyzed using Statistical Package for Social Science software (IBM Corporation, version 20.0 for Windows). Descriptive statistics were summarized as frequencies and percentages for categorical variables. Continuous variables were presented as mean and standard deviation when normally distributed and as median and interquartile range when not normally distributed. Mann-Whitney U test was used for between-group analyses of abnormally distributed variables. The variables were investigated using visual (histograms, probability plots) and analytical methods (Kolmogorov-Smirnov/Shapiro-Wilk test) to determine whether they showed normal distribution. As parameters were not normally distributed, the correlation coefficients and their significance were calculated using Spearman test. Strength of correlation was defined as very weak for r values between 0.00–0.19, weak for r values between 0.20–0.39, moderate for r values between 0.40–0.69, strong for r values between 0.70–0.89, and very strong for r values over 0.90 [ 26 ]. As the academic performance was not normally distributed, the Kruskal-Wallis test was conducted to compare this parameter among the six learning style groups. The Mann-Whitney U Test was performed to test the significance of pairwise differences using Bonferroni correction to adjust for multiple comparisons. An overall 5% type-I error level was used to infer statistical significance ( p  < 0.05).

A total of 217 physiotherapy students were invited to participate in the study. Eighteen students refused to participate. Fifteen surveys were discarded due to missing item responses. As a result, data obtained from 184 students were used for the analyses. Overall response rate was 84.8%.

Demographic characteristics (gender, year) and learning style preferences are presented in Table  4 . The most common learning styles among the physiotherapy students according to the GRLSS were Collaborative (34.8%) and Independent (22.3%). The results of GRLSS subscale scores were given in Table  5 . The highest subscale score was Collaborative (Mean ± SD = 3.57 ± 0.62), while Competitive score was the lowest (Mean ± SD = 2.81 ± 0.69).

A moderate positive correlation between academic performance and Participant score was found (p < 0.001, r = 0.400) . A weak negative correlation was also found between academic performance and Avoidant score (p < 0.001, r = − 0.317) . No other significant correlation between academic performance and subscale scores was found (Table  6 ) .

When students were grouped according to learning styles, between-group (Kruskal-Wallis) analysis showed a significant difference in the academic performance of the groups (p < 0.001). Post-hoc (Mann-Whitney U) analysis revealed significantly higher academic performance in the Participant learning style group compared to all of the other learning style groups (Independent, Avoidant, Collaborative, Dependent, and Competitive) (Table  7 ).

The current study assessed the learning styles of Turkish physiotherapy students, and investigated the relationship between their learning styles and academic performance. The results revealed that the Collaborative learning style was most common among the Turkish physiotherapy students. However, students with Participant learning style had statistically higher academic performance when compared to the others. In addition, we found a positive correlation between Participant score and academic performance of the students, which supports the previous finding, while a negative correlation was found between Avoidant score and academic performance. In the case of physiotherapy students in this study, the emphasis should be on developing Participant and Collaborative learning skills. This might involve providing more class activities, discussions, and group projects.

The physiotherapy program at DEU has a combined case study-based and traditional style curriculum including lectures, tutorials, seminars, case study presentations, and supervised small group clinical practice in the hospital and at other health centers. Learning tasks and assessment methods include individual written examinations, practical examinations, homework and assignments as well as collaborative oral presentation and research projects. In the physiotherapy discipline, clinical practice improves students’ occupational skills and is seen as a crucial part of the teaching process [ 12 , 27 ]. Similarly, the teaching and learning approach at DEU is heavily based on practical training and requires active participation and group work. This could be a reason for the greater preference for Collaborative learning style.

Previous studies have indicated that physiotherapy students prefer abstract learning styles [ 28 ] and have desirable approaches to studying [ 29 ]. Canadian and American physiotherapy students preferred Converger (40 and 37% respectively) or Assimilator (35 and 28% respectively) learning styles [ 13 ]. According to descriptions of the learning style categories in the Kolb LSI, Convergers enjoy learning through activities like homework problems, computer simulations, field trips, and reports and demonstrations presented by others. On the other hand, Assimilators prefer attending lectures, reading textbooks, doing independent research and watching demonstrations by instructors when learning. In our study, Turkish physiotherapy students preferred Collaborative (34.8%) or Independent (22.3%) learning styles. According to GRLSS, Collaboratives prefer lectures with small group discussions and group projects (similar to Assimilators), while Independents prefer self-pace instruction and studying alone (similar to Convergers). Therefore, it can be concluded that learning styles of Canadian, American, and Turkish physiotherapy students are similar to each other.

Katz and Heimann used the Kolb LSI in their study and reported average learning style scores instead of the number of students in each of the four learning styles. They reported Converger as the “average” learning style for physiotherapy students [ 30 ]. In our study, the largest proportion of the physiotherapy students had a Collaborative learning style. Moreover, the average learning style was also Collaborative, with the highest average score.

Competitive learning style was the least frequently preferred (5.4%) by Turkish physiotherapy students in our study. The low preference for Competitive learning style indicates that students were less likely to compete with other students in the class to get a grade. Mountford et al. assessed learning styles of Australian physiotherapy students using Honey & Mumford’s LSQ and found that the Pragmatic learning style was the least preferred. According to LSQ, Pragmatists tend to see problem solving as a chance to rise to a challenge [ 31 ]. Considering that both Competitives and Pragmatists like challenges, the least frequently preferred styles of Australian and Turkish physiotherapy students seem to be similar to each other.

Alsop and Ryan pointed out that “personal awareness of learning styles and confidence in communicating this are first steps to achieve an optimal learning environment” [ 32 ]. According to Kolb’s theory, a preferred learning style affects a person’s problem solving ability [ 13 ]. Wessel et al. also stated that in order to provide students the best learning opportunity, educators must be aware of the learning styles and students’ ability to solve problems [ 13 ]. Indeed, evidence supporting these views can be found in the literature. Previous studies showed that students who were aware of their learning style had improved academic performance [ 33 , 34 ]. Nelson et al. found that college students who were tested on their learning style and were given appropriate education according to their learning style profile achieved higher academic performance than other students [ 33 ]. Linares also investigated learning styles in different health care professions (physiotherapy, occupational therapy, physician assistants, nursing and medical technology) and found a significant relationship between learning style and students’ readiness to undertake self-directed learning [ 15 ]. However, Hess et al. found no association between learning style and problem-solving ability in their study [ 35 ].

While planning this study, we hypothesized that students with a Collaborative learning style would have higher academic performance. Although the Collaborative learning style was the most common, these students did not show significantly higher academic performance. However, students with Participant learning style had statistically higher academic performance when compared to the other learning style groups. Characteristics specific to the Participant learning style are enjoyment from attending and participating in class and interest in class activities and discussions. These students enjoy opportunities to discuss class materials and readings. This may suggest that increasing in-class activities and discussions, which encourage participant-style learning, is needed to increase academic performance. Another approach would be to adapt teaching strategies according to the characteristics of Collaboratives, as they represented the largest body of students. Creating a convenient environment in which students could spend more time sharing and cooperating with their teacher and peers may facilitate collaborative learning, thus enhancing academic performance. Organizing the curriculum to include small group discussions within lectures and incorporate group projects may also be beneficial. As Ford et al. stated, “ Identification teaching profiles could be used to tailor the collaborative structure and content delivery ” [ 36 ].

The most important reason for determining learning style is to create a proper teaching strategy [ 37 , 38 , 39 , 40 ]. However, there seems to be no exact relationship between students’ learning style and the curriculum of a program described in the literature [ 13 ]. Learning style alone is not the only factor that may influence a learning situation. Many factors (educational and cultural context of university, individual awareness, life experience, other learning skills, effect of educator, motivation, etc.) may influence the learning process [ 31 ]. Therefore, expecting a simple relationship between learning style and teaching strategy may not be realistic. Moreover, the review of Pashler et al. showed that there was virtually no evidence that people learn better when teaching style is tailored to match students’ preferred learning style [ 41 ]. Nevertheless, future studies investigating physiotherapy educators’ teaching styles and their association with learning styles and academic performance may elucidate this complex issue.

The major strength of this study is that, to the best of our knowledge, ours is the first study investigating the learning styles of Turkish physiotherapy students with relation to academic performance.

There were some limitations to this study. It should be noted that learning style is a self-reported measure that can change based on experience and the demands of a situation. Therefore, it is subjective and able to provide adaptive behavior [ 42 ]. It should also be kept in mind that the conclusions of this study could be limited due to the cross-sectional design, and respondent bias may be an issue because convenience sampling was used to recruit participants. One possible limitation of the study could be the fact that the three of the scale reliabilities reported for GRLSS was poor.

This study investigated the learning styles of physiotherapy students in only one university (DEU) and this could preclude the generalization of our results. Subsequent studies should include students enrolled in the physiotherapy departments of multiple universities in Turkey to achieve an accurate geographical representation. Moreover, future studies on this topic should be conducted in collaboration with universities in Europe, with which we share a cultural connection.

The results of this study showed that the Collaborative learning style was most common among Turkish physiotherapy students. On the other hand, the physiotherapy students with Participant learning style had significantly higher academic performance than students with other learning styles. Teaching strategies consistent with the unique characteristics of the Participant learning style may be an effective way to increase academic performance of Turkish physiotherapy students. Incorporating more in-class activities and discussions about class material and readings may facilitate Participant learning, thus impacting academic performance positively. Another approach may be to adopt teaching strategies that target the predominant Collaborative learning style. Creating a convenient environment for students to share and cooperate with their teacher and peers and organizing the curriculum to include more small group discussions and group projects may also be supportive. Future studies should investigate physiotherapy educators’ teaching styles and their relations with learning styles and academic performance.

Abbreviations

Cumulative Grade Point Average

Dokuz Eylul University

Grascha-Riechmann Learning Style Scales

Learning Style Inventory

Learning Style Questionnaire

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Acknowledgements

The authors like to thank all physiotherapy students who participated in this study.

No funding was obtained for this study.

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The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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School of Physical Therapy and Rehabilitation, Dokuz Eylul University, 35340, Inciralti, Izmir, Turkey

Nursen İlçin, Murat Tomruk, Sevgi Sevi Yeşilyaprak, Didem Karadibak & Sema Savcı

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Nİ conducted the literature search for the background of the study, analyzed and interpreted statistical data, and wrote the majority of the article. MT conducted the literature search, collected data for the study, analyzed statistical data, and contributed to writing the article. SSY and DK were involved in study planning, data processing, and revising the article. SS contributed to study design and oversaw the study. All authors read and approved the final manuscript.

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Correspondence to Nursen İlçin .

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Nursen İlçin, PT, PhD.

İlçin graduated from Dokuz Eylul University, School of Physical Therapy and Rehabilitation in 1998. She received her Master’s degree in 2002 and PhD in 2009 from Dokuz Eylül University. She is currently a associate professor in Geriatric Physiotherapy Department.

Murat Tomruk, PT, PhD.

Tomruk graduated from the School of Physical Therapy and Rehabilitation at Dokuz Eylul University in 2009. He received his MSci degree in Musculoskeletal Physiotherapy in 2013 and his PhD degree in 2018. His doctorate thesis was about manual therapy. He works as a research assistant at Dokuz Eylul University since 2011.

Sevgi Sevi Yeşilyaprak, PT, PhD.

Sevgi Sevi Yeşilyaprak’s speciality is shoulder rehabilitation. Her primary research interests are orthopaedic and sports injuries of the shoulder, shoulder biomechanics, proprioception, and exercise. She has one active and two completed grants. Yeşilyaprak teaches courses on musculoskeletal physiotherapy including sports physiotherapy, musculoskeletal disorders, therapeutic exercises, exercise prescription, and manual physiotherapy techniques.

Didem Karadibak, PT, PhD.

Karadibak obtained her BS degree in Physiotherapy from Hacettepe University in 1992 and her MS and PhD degrees from the Physical Therapy Program of the Institute of Health and Sciences, Dokuz Eylul University in 1998 and 2003, respectively. She is currently a professor of Cardiopulmonary Rehabilitation in the Dokuz Eylul University School of Physical Therapy and Rehabilitation.

Sema Savcı, PT, PhD.

Savcı obtained her BS degree in Physiotherapy from Hacettepe University in 1988 and her MS and PhD degrees from the Physical Therapy Program of the Institute of Health and Sciences, Hacettepe University in 1990 and 1995, respectively. She is currently a professor and serving as the Head of Cardiopulmonary Rehabilitation in the Dokuz Eylul University School of Physical Therapy and Rehabilitation.

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Written ethical approval was taken from the Dokuz Eylül University’s local ethics committee (approval number 1432-GOA) and written informed consent obtained from all the participants.

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İlçin, N., Tomruk, M., Yeşilyaprak, S.S. et al. The relationship between learning styles and academic performance in TURKISH physiotherapy students. BMC Med Educ 18 , 291 (2018). https://doi.org/10.1186/s12909-018-1400-2

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This paper examined study habit and mental ability as predictors of students' Mathematics Achievement. The study reviewed related and relevant literatures which gave the study a strong empirical and theoretical footing. Students' Study Habit and Mental Ability Questionnaire (SSHMAQ) was developed as a research instrument together with an Algebra Achievement Test (AAT). The data were analyzed using chisquare and Pearson Product Moment Correlation (PPMC) and all the hypotheses were tested at 0.05 level of significance. The results showed that independent variables (study habit and mental ability) have positive correlation with students' achievement in algebra. However, the findings of the study also revealed that each of the independent factors positively significantly correlated to the achievement of students in Algebra. Based on the Chi-square values, 0.781* showed positive correlation between study habit and student achievement in Algebra likewise 0.823* of chi-square value which showed a positive correlation between mental ability and student's achievement in Algebra. Recommendations and suggestions on effective strategies towards the learning algebra were offered based on the outcome of the survey conducted on the participants.

School Science and Mathematics

Robert Reys

Zenodo (CERN European Organization for Nuclear Research)

Francis Jose Bearneza

Psychology and Education: A Multidisciplinary Journal

Psychology and Education , Joan Alendajao

During the twentieth century, the meaning of successful Mathematics learning underwent several shifts in response to changes in both society and schooling. For roughly the first half of the century, success in learning the mathematics of pre-kindergarten to eighth grade usually meant facility in using the computational procedures of arithmetic, with many educators emphasizing the need for skilled performance and others emphasizing the need for students to learn procedures with understanding. To this end, the researchers is conducting a study to identify academic predictors of learning proficiency across strands of mathematics of grade 8 students of a public secondary school in Marikina City, the Marikina High School. The study is descriptive in nature and makes use of 6 groups of subjects: they were composed of 42 Grade 8 of Marikina High School, a secondary public school in the Schools Division of Marikina City, Metro Manila. From the research findings, it can be concluded that the majority of the respondents got a high rating in Algebra and Geometry, most of the student respondents fell above the passing rate of the subject Mathematics, and most of the student respondents accumulated a high score rating in Statistics and Probability. The null hypothesis is rejected; therefore, there is a significant difference between students' proficiency levels in Mathematics along with Algebra and Geometry. In academic characteristics related to the proficiency level of the students along study strategy in terms of Rehearsal, analyzing its contents again and again in studying math materials is strongly agreed by the student-respondents; Organization, reading through the class notes textbook and finding out the most important parts is strongly agreed; Self-regulation, listing down related formula first is strongly agreed; Study Environment, making it a hobby to study Math at a fixed time is agreed; Attitude towards Mathematics, student-respondents treat Mathematics difficult but an interesting subject. There is no significant difference in the Academic Characteristics of the respondents except in terms of Attitude towards Mathematics and Time and Study Environment, which have a strong positive/negative difference in the academic characteristics of the respondents. Moreover, a significant relationship exists between academic characteristics and students' proficiency levels.

Abdul Taram

This study is based on students&#39; low learning outcomes, low learning preparation, and lack of optimization of learning style math learning causes less effective mathematics study. This research aims to determine whether there is influence toward math learning outcomes among students who have a high or low learning preparation and learning style visual, auditorial, or kinesthetic in the students Class VII of State Junior High School (SMP Negeri) 1 Banjarmangu Banjarnegara Regency in Even Semester Academic Year 2017/2018. This research population was the students of class VII SMP Negeri 1 Banjarmangu Banjarnegara Regency in even semester academic year 2017/2018, which consists of 7 classes. With Random Sampling Technique to the class and obtained class VII G as a class of research sample and class VII F as a class of research trial. Data collection techniques used a questionnaire form and test. A multiple-choice test is a matter of learning mathematics outcomes in the form of a qu...

Jurnal Magister Pendidikan Matematika (JUMADIKA)

Louise M Saija

This descriptive and comparative study aims to see the students learning styles and mathematics achievements. The respondent are fifty junior high school students in Lembang, West Bandung, Indonesia. The research instruments are Perceptual Learning Style Preference Questionnaire (PLSPQ) and mathematics problem solving test. The result of this study are: (1) Only twenty percent of the students have exactly one learning style and most of the students has kinesthetic learning style; (2) Students who have three or less major learning styles perform good mathematics achievement, and students who have minor learning styles only, perform better mathematics achievements averagely, comparing with students who have major learning styles; (3) Students perform better mathematics achievement when they have more than one learning style, (4) There is no significant difference in the students’ mathematics achievement, between students who have three or less major learning styles and students ...

Macrothink Institute

Nathaniel Q Autida

Learning styles are different approaches individuals prefer for acquiring knowledge and information. This study examines the influence and relationship between learning styles and mathematical performance among junior high school students at Tolotolo National High School. By identifying and recognizing students' preferred learning styles, educators can better understand and meet students' learning needs. The research aims to identify the dominant learning style among students and its correlation with mathematical performance. Results show that students at Tolotolo National High School predominantly prefer auditory learning. However, the study found no significant correlation between auditory learning and mathematical performance. Interestingly, a significant relationship was found between kinesthetic learning styles and higher academic achievement in Mathematics with a significance score of 0.001. These findings suggest that while auditory learning is prevalent, kinesthetic learning plays a role in academic success. These insights contribute to developing effective teaching strategies and styles that encourage students to become more successful academically.

Nelviyanti Podilito

wigati indah sari

The purpose of the research was to determine how far the influence of the ability of students’ mathematical understanding learning style. The subjects in this study were 140 11th grade students of SMK Bina Am-Mak&#39;mur Tangerang Regency Year 2019/2020 which was classified into three learning style groups, which was visual learning style consisting of 32 students, auditorial consisting of 23 students, and kinesthetic consisting of 85 students. The method in this study was ex post facto to know clearly the data on students’ ability of mathematical understanding learning style. The data were taken and processed using the normality test and homogeneity test with Anava One Way, to determine the influence of students &#39; learning style more clearly. After the test, it can be concluded that the average value of the results of the mathematical understanding of students with visual learning style was better than the average value of the results of the mathematical understanding of studen...

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The influence of SDL on learning satisfaction in online learning and group differences between undergraduates and graduates

• Published: 28 August 2024

Cite this article

• Meina Zhu   ORCID: orcid.org/0000-0002-5901-9924 1 ,
• Min Young Doo   ORCID: orcid.org/0000-0003-3565-2159 2 ,
• Sara Masoud 3 &
• Yaoxian Huang 4  

This study examines the influences of learners’ motivation, self-monitoring, and self-management on learning satisfaction in online learning environments. The participants were 185 undergraduates and 99 graduate students majoring in computer science and engineering. The participants’ motivation, self-monitoring, self-management, and learning satisfaction were measured using a questionnaire. Results indicated that motivation, self-monitoring, and self-management significantly influenced learning satisfaction and the three factors together accounted for approximately 60% of the variance in learning satisfaction. Motivation was the most influential factor on learning engagement. Group differences emerged between undergraduates and graduate students in the influences of motivation, self-monitoring, and self-management on learning satisfaction. Compared to undergraduate students, graduate students had statistically higher scores in motivation, self-monitoring, and self-management, but not in learning satisfaction. The three factors also influenced undergraduate and graduate students differently in the regression analysis results. Motivation and self-monitoring, but not self-management influenced undergraduates’ learning satisfaction, whereas motivation and self-management, but not self-monitoring influenced graduates’ learning satisfaction. Further studies are needed to investigate the reasons for the group differences. The implications are that instructors need to utilize SDL strategies extensively to enhance learning satisfaction in online learning. In addition, designers, instructors, and institutions should tailor the learning strategies more effectively for their target audience given the differences in the influence of SDL on learning satisfaction between undergraduates and graduates.

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Exploring students’ self-directed learning strategies and satisfaction in online learning

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Meina Zhu: Conceptualization, investigation (instrument development and data collection), data curation, project administration, initial data analysis, writing-review and editing. Min Young Doo: Conceptualization (supporting); formal analysis; visualization; writing – original draft preparation; writing – review and editing. Sara Masoud: Investigation (instrument development and data collection). Yaoxian Huang: Investigation (instrument development and data collection).

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Appendix: Measurement

Self-directed Learning (27 items)

• Self-management

I prefer to schedule my own learning plan while taking online courses.

I am self-disciplined about completing the required work while taking online courses.

I have good management skills (e.g., time, learning resources, etc.) while taking online courses.

I set specific times to study while taking online courses (e.g., 9:00 am or 10:00 am in the morning).

I set strict time frames for learning while taking online courses (e.g., 1 h, 2 h, etc.).

I am able to keep my learning routine in online courses separate from my other commitments.

I can apply a variety of learning strategies while taking online courses.

I am disorganized while taking online courses. ®

I am confident in my ability to search for information related to learning content in online courses.

I want to learn new information through online courses pertaining to my major.

I enjoy learning new information while taking online courses.

I enjoy the challenges that may occur while taking online courses (e.g., analysis/application of concepts).

I do not enjoy studying for online courses ® .

I critically evaluate information that I received while taking online courses.

I would like to know the deep reasons behind the facts while taking online courses.

I learn from the feedback provided by my peers while taking online courses.

I learn from the feedback provided by my instructor while taking online courses.

When presented with a problem I cannot resolve, I ask for assistance through different means while taking online courses.

• Self-monitoring

I am responsible for my own learning while taking online courses.

I am in control of my learning while taking online courses.

I have high learning standards while taking online courses.

I prefer to set my own learning goals while taking online courses.

I evaluate my own performance while taking online courses.

I have high beliefs in my learning abilities while taking online courses.

I can find information related to learning content for myself while taking online courses.

I am able to focus on answering or solving a problem while taking online courses.

I am aware of my own limitations while taking online courses.

Learning satisfaction (6 items)

Overall, I am satisfied with online courses.

The online courses contributed to my educational development.

The online courses contributed to my professional development.

I am satisfied with the level of interaction among students in online courses.

I am satisfied with the level of interaction between my instructor and students in online courses.

In the future, I would be willing to take an online course again.

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Zhu, M., Doo, M.Y., Masoud, S. et al. The influence of SDL on learning satisfaction in online learning and group differences between undergraduates and graduates. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12995-3

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Received : 19 May 2024

Accepted : 12 August 2024

Published : 28 August 2024

DOI : https://doi.org/10.1007/s10639-024-12995-3

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2024 Theses Doctoral

Detecting and Explaining Emotional Reactions in Personal Narrative

Turcan, Elsbeth

It is no longer any secret that people worldwide are struggling with their mental health, in terms of diagnostic disorders as well as non-diagnostic measures like perceived stress. Barriers to receiving professional mental healthcare are significant, and even in locations where the availability of such care is increasing, our infrastructures are not equipped to find people the support they need. Meanwhile, in a highly-connected digital world, many people turn to outlets like social media to express themselves and their struggles and interact with like-minded others. This setting---where human experts are overwhelmed and human patients are acutely in need---is one in which we believe artificial intelligence (AI) and natural language processing (NLP) systems have great potential to do good. At the same time, we must acknowledge the limitations of our models and strive to deploy them responsibly alongside human experts, such that their logic and mistakes are transparent. We argue that models that make and explain their predictions in ways guided by domain-specific research will be more understandable to humans, who can benefit from the models' statistical knowledge but use their own judgment to mitigate the models' mistakes. In this thesis, we leverage domain expertise in the form of psychology research to develop models for two categories of emotional tasks: identifying emotional reactions in text and explaining the causes of emotional reactions. The first half of the thesis covers our work on detecting emotional reactions, where we focus on a particular, understudied type of emotional reaction: psychological distress. We present our original dataset, Dreaddit, gathered for this problem from the social media website Reddit, as well as some baseline analysis and benchmarking that shows psychological distress detection is a challenging problem. Drawing on literature that connects particular emotions to the experience of distress, we then develop several multitask models that incorporate basic emotion detection, and quantitatively change the way our distress models make their predictions to make them more readily understandable. Then, the second half of the thesis expands our scope to consider not only the emotional reaction being experienced, but also its cause. We treat this cause identification problem first as a span extraction problem in news headlines, where we employ multitask learning (jointly with basic emotion classification) and commonsense reasoning; and then as a free-form generation task in response to a long-form Reddit post, where we leverage the capabilities of large language models (LLMs) and their distilled student models. Here, as well, multitask learning with basic emotion detection is beneficial to cause identification in both settings. Our contributions in this thesis are fourfold. First, we produce a dataset for psychological distress detection, as well as emotion-infused models that incorporate emotion detection for this task. Second, we present multitask and commonsense-infused models for joint emotion detection and emotion cause extraction, showing increased performance on both tasks. Third, we produce a dataset for the new problem of emotion-focused explanation, as well as characterization of the abilities of distilled generation models for this problem. Finally, we take an overarching approach to these problems inspired by psychology theory that incorporates expert knowledge into our models where possible, enhancing explainability and performance.

• Computer science
• Mental health services
• Artificial intelligence
• Natural language processing (Computer science)
• Emotions--Psychological aspects
• Emotion recognition
• Computer multitasking
• Distress, (Psychology)

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