Learning Styles Module as a Part of a Virtual Campus Ismo Hakala, Tuomo Härmänmaa, Sanna Laine Kokkola University Consortium Chydenius University of Jyväskylä Kokkola, Finland

Abstract— For several years now, learning style mapping has been carried out for our students of the master's degree education in information technology. To better utilize learning styles in practice, a learning style module was integrated into the multimedia platform used in the education. The learning style module serves both the student and the educator. The goal was to create an application which, in the long run, would diversify the learning environment and make learning more efficient. This study describes the functioning and integration of the learning style application. The deployment of the application is monitored by collecting statistics of its use and feedback of its usability and usefulness from students and lecturers. In addition, the study presents the distribution of our students' learning styles. Keywords—Learning styles; blended learning; virtual campus; video lectures; educational tools

I.

INTRODUCTION

Studies of learning styles arose at least five decades ago from interest in individual differences. Nowadays, there are number of learning styles theories, and the research is being conducted increasingly also in domains outside psychology. Although the popularity of learning styles in several disciplines bears testimony to the importance of the research area, this diversity may be one of the reasons that have caused the study field to become somewhat fragmented. Also, the commercialization of some successful learning styles instruments may impede independent research [1]. The term learning style is often used sloppily, and competing theories have produced an enormous number of ambiguous terms to describe the concept. Alongside the term ”learning style”, ”cognitive style” and ”learning strategy” are also often mentioned in the literature. Sometimes the terms are used interchangeably. Also the term “preferences” is strongly related to learning styles. Favoring one teaching method over another is often referred to as learning preference. Learning styles and other terms related to it are clarified e.g. in [2]. Hartley [3] defined learning styles as the “ways in which individuals characteristically approach different learning tasks”. In [4], learning styles are defined as a “biologically and developmentally imposed set of personal characteristics that make the same teaching method effective for some and ineffective for others”. Grasha [5] defines learning styles as “personal dispositions that influence a student’s ability to acquire information, to interact with peers and the teacher, and to otherwise participate in learning experiences”. He defines such qualities to be e.g. student’s motives, perceptual skills,

modes of processing information, and a variety of preferences for sensory stimulation, gathering information, social relationships, and the qualities of the physical environment. In [6] learning style models are divided into “processbased”, “preference-based” and “cognitive skills-based” models. Process-based models, like that of Kolb [7] and the Honey and Mumford’s model [8], include some kind of information processing approach. Preference-based models focus upon an individual's learning preference. The Dunn and Dunn’s model [9] as well as the Grasha-Riechmann model [10] are chosen as examples of that group. Cognitive skills-based models emphasize learning styles’ relationship with cognitive skills. For example, the Keefe and Monk’s model [11] assumes that cognitive skills development is a prerequisite for effective learning. Similarly, according to the Letteri’s model [12], the process of learning can be categorized into six stages and failure to process information in any one of these stages represents a deficit in acquisition of cognitive skills. Also Curry [13] made efforts to organize the learning styles field and created her “onion model”. In the onion model, existing style theories are integrated into a single model that distinguishes three levels. The Instructional Preference layer refers to the individuals' choice of environment in which to learn. This layer interacts most with the external features like learning environment, learner expectations, and teacher expectations and is thus considered the least stable layer in the model. The second layer is called the Information Processing Style layer and refers to the individual’s approach to process and assimilate information. Curry [13] defines this to be more stable than the Instructional Preferences layer but still modifiable by learning strategies. The innermost layer is the Cognitive Personality Style layer. It is defined as the individual’s approach to adapting and assimilating information but, unlike in the Information Processing Style, it does not interact directly with the environment. This makes the layer the most permanent level in the model. Coffield et al. [1] found 71 different learning style instruments, and theories. They considered 13 of them as major models. To order the models, they grouped 50 models into five “families”. The grouping was based on the extent to which the developers of learning style models and instruments appear to believe that learning styles are fixed. At the left-hand end of the continuum, Coffield et al. placed models that emphasize the influence of genetics on fixed, inherited traits and on the interaction of personality and cognition. Moving along the

continuum, learning style models are based more on the idea of dynamic interplay between self and experience. At the righthand end of the continuum, theories pay greater attention to personal factors such as motivation, and environmental factors. From numerous learning style models, we chose to use the Felder-Silverman learning style model [14]. The model was initially developed to be applied for students in engineering and the sciences in particular. Thus we considered our master's students in information technology to have educational background which is quite similar to that of the majority of populations on which the model is applied. The FelderSilverman model was developed by combining components from other popular theories. The authors utilized for example Jung’s theory of psychological types [15] and the Kolb’s learning style model [7]. Only the learning dimensions considered particularly relevant to science education were included in the Felder-Silverman model. Being a condensed combination of much researched theories and developed for students like ours, the Felder-Silverman model is the most natural choice for us. In the Curry’s onion model, the Felder-Silverman model overlaps the middle layer (information processing layer) and the inner layer (cognitive personality style layer). In the Coffield’s categorization, it belongs to the second family from right. In this family, models favor the principle that “learning styles are flexibly stable learning preferences” [1]. For example, the model of Kolb and that of Honey-Mumford are also placed in the same family. Originally, our motivation for learning style mapping was to enhance students’ learning process by providing them with information about learning and study techniques. A personal learning style result provides the student with information about one's own strengths and weaknesses as a learner. Another aim is to encourage students to use and improve their less dominant learning styles. Moreover, the awareness about different learning styles alone can activate the student to ponder over and develop one's own study techniques. To better utilize learning styles in practice, (i)

a learning style application was integrated into the multimedia platform used in the education, and

(ii)

the application was meant to be used also by lecturers.

A lecturer can observe students’ learning style distributions and even compare his/her own learning style result between the course participants’ average results. The paper is organized as follows: The next chapter presents the Felder-Silverman learning style model. Chapter III discusses how the learning style models are utilized in related work. In Chapter IV, the virtual campus, CiNetCampus Studies environment, is introduced. Chapter V describes the Learning Style Module integrated to the virtual campus. In Chapter VI, the learning style results of our master's students in information technology are briefly presented and preliminary evaluation of the Learning Style Module is made. Before the conclusion, the role of the learning style application is assessed in Discussion, in Chapter VII.

II.

FELDER-SILVERMAN LEARNING STYLE MODEL

According to the Felder-Silverman model, learning styles are “characteristic ways of taking in and processing information” [16]. These characteristic ways are defined through four (in theory orthogonal) dimensions. Originally, the model had five dimensions, but the inductive-deductive was later removed. The reason was that Felder considered the deductive way of teaching more inefficient and thought that most of the students prefer deductive presentation only because it is more concise than inductive presentation. A. Sensitive – Intuitive Dimension This dimension depicts what type of information the student preferentially perceives. Sensing learners prefer sights, sounds and physical sensations and tend to be concrete, practical, methodical, and oriented toward facts and hands-on procedures. Intuitive learners prefer memories, ideas and insights. Intuitive learners are more comfortable with abstractions (theories, mathematical models) and more likely to be rapid and innovative problem solvers. The scale is identical to the sensingintuitive scale of the Myers-Briggs Type Indicator based on the Jung’s Theory of Psychological Types [16]. B. Visual – Verbal Dimension Visual-verbal dimension tells what type of sensory information is perceived most effectively. Visual learners are better in remembering sights, pictures, diagrams, and symbols. Verbal learners remember written and spoken explanations. Visual-verbal distinction has origins e.g. in cognitive studies of information processing [17], C. Active – Reflective Dimension This dimension depicts how students process information. Active learners like trying things out. Reflective learners prefer thinking things through. This dimension (like visual-verbal) has parallels in visual-auditory-kinesthetic (VAK) formulation of modality theory. It is also related to the extravert – introvert dimension in the Jung-Myers-Briggs model [14]. D. Sequential – Global Dimension Sequential-global dimension describes how the student characteristically progresses toward understanding. Sequential learners progress in small, logical and incremental steps in a steady pace. Global learners progress in large leaps, in an uneven pace. This axis also has numerous parallels. Sequential learners might be considered left-brain dominant, analytic and auditorysequential [17]. Global learners are biased towards right-brain dominance and visual-spatial learning style [17]. E. The Index of Learning Styles (ILS) An important reason for choosing a learning style model is that it is easy to asses and results are easy to interpret with the Index of Learning Styles (ILS) questionnaire developed for the Felder-Silverman model [18]. The questionnaire includes 44 questions with two alternatives (11 questions for each axis). As a result, the ILS gives the strength of learning style preferences on each four dimensions. Learning style preferences can be mild, moderate or strong. If the preference is mild, the person is more likely to change his/her learning style in different situations, and it can be said that the learning style is well balanced on the axis concerned. A person with a moderate

An example of an ILS result.

preference learns best in an environment which provides support for his/her preference. A strong preference can make learning more difficult in an environment which favors a contrary learning style. In Fig. 1 there is an example of an ILS result. The result shows a learning style preference which is moderately active, mildly intuitive, strongly verbal, and mildly sequential. III.

UTILIZATION OF LEARNING STYLE MODELS

The implications of learning style instruments can be divided at least in two groups. In the first group, the instruments are used in correlational studies which also explore the similarities and differences between diverse populations. Comparisons are made e.g. between disciplines, language backgrounds, genders and hemisphericity. The correlation of learning styles is studied with e.g. academic performance, level of education and age. Komarraju et al. [19] found that learning styles made a minor contribution to college students’ grade point averages. E.g. Hargrove et al. [20] examined the relationship between students' learning styles, major, gender, and academic performance in engineering with the Kolb’s learning style inventory. In [21], students’ learning styles are compared between disciplines, gender and academic performance as measured by GPA. The second area concerns the use of learning styles information to develop educational innovations and improve educational practices. Learning styles are utilized to make teaching styles more effective. In [22], the learning style model is studied to improve experiential learning in higher education. The concept of learning space in introduced for understanding the interface between student learning styles and the institutional learning environment. The Kolb’s Learning Style Inventory measures an individual's preference of a particular region of the learning space. Each region is associated with a specific process of learning from experience. In [23], six learning style instruments are reviewed in order to suggest classroom activities that work with the different student learning styles and to recommend selection of models under several conditions. A number of learning activities to support each learning mode were collected. Solutions utilizing learning styles in online learning belong also to this group. A typical approach is to modify learning environment to match student’s learning styles. The Felder-Silverman model is used in correlational studies as well as in studies developing educational innovations. College students’ learning style distribution results from various studies are aggregated in [17]. In [24], the Felder-Silverman model was studied as a predictor of academic performance. No significant correlation was found.

In [25], the Felder-Silverman model was used in developing a web-based learning system. The learning system was a complementary tool for the standard lectures. The approach was to modify the learning system to match students’ learning styles. Franzoni et al. [26] developed a method to personalize the learning process according to Felder’s learning styles. The method combines teaching strategies and electronic media. With the help of the method, teachers can calculate the course’s average learning style to choose a suitable media proposed by the adaptive teaching taxonomy. The method also facilitates automatic personalization in hypermedia systems. A reverse approach was used e.g. in [27] and [28], where students’ learning styles were detected by observing how students learn and interact with a web-based education system. The detected learning styles were then compared with the results obtained with the ILS questionnaire. Garcia et al. found that in the sensory/intuitive axis the detected learning style matches ILS results with a high precision. In the active/reflective and sequential/global dimensions, some mismatches were found. The visual/verbal dimension was excluded from the study. Graf et al. developed a standalone tool that can be used for any LMS. The tool extracts relevant data from the LMS database and calculates the learning styles of LMS users. They found a high precision for the proposed approach for all four dimensions. The results of the studies with this reverse approach may be regarded as proofs that students have different ways of using learning environments based on their learning styles. Our approach is not to change the students’ learning environment to match their learning styles but to make it more versatile and to utilize learning styles in teaching in general. No learning environment elements or tools are hidden from any student. To make the students and lectures adapt the recommendations and techniques of the learning style model, we integrated a learning styles module as one of the virtual campus elements. The learning styles module includes a view for both students and instructors. The environment in which the learning styles module is integrated is described in the next chapter. IV.

CINETCAMPUS STUDIES ENVIRONMENT

In all learning situations, the students can make use of the virtual CiNetCampus Studies (CCS) environment, which consists of several different modules integrated to work together. The virtual environment appears as a unitary system to the user. Fig. 2 presents the current modules of CiNetCampus Studies. The most essential applications of the environment are a commercial learning management system (LMS) and a custombuilt multimedia platform integrated to it. The integration permits transmission of teaching materials and all student- and course-specific information between LMS and the multimedia platform. Since most of the environment’s modules are integrated either in the LMS or in the multimedia platform, transmission of all education-related information is also permitted between all other modules integrated in the virtual environment. The most used modules are the LMS, the video sharing module and various communication channels such as coursespecific message lists, chats and video chats. The LMS we use contains all typical learning management system tools.

The current modules of CiNetCampus Studies environment.

However, fluent YouTube-like management of lecture videos doesn’t usually include commercial learning platforms. Originally, our custom-built multimedia platform, based on open source application, was developed for that purpose [29]. All the degree program's lectures are given in face-to-face sessions, which are recorded and distributed, both live and ondemand, through the CCS environment’s video sharing module. The video sharing module provides a flexible way to share both live and on-demand lecture videos and built functionalities for the activation and utilization of students in the CCS environment. Thus, the environment provides the student with an opportunity to choose whether to participate in the study faceto-face, with live video or with on-demand video. The student can watch lecture videos while simultaneously communicating with other students and the lecturer with the help of both text chat and video chat. For communicating with the lecturer, the text chat and the video chat are integrated in the Lecturer's View module. The Lecturer’s View module shows distance students’ pictures and the chats on the wall of the classroom, enabling the lecturer and the face-to-face participants to see the distance participants. Thus the CiNetCampus Studies environment functions as a platform for several different applications benefiting education and students, something that commercial learning management systems normally cannot do. In addition to the video distribution system, a commercial video chat, an online survey design system and, most recently, an application mapping students' learning styles have been integrated into the CiNetCampus Studies environment.

V.

LEARNING STYLES MODULE

Learning styles (LS) module of the CiNetCampus Studies environment is a custom based web-application, which has been linked to a separate web-based survey tool, LimeSurvey (see Fig.3). The tool is a well-known open source application which supports 28 different question types, and the user interface is translated to over 80 languages. Web-based questionnaires are easy to design by using its design tools, and the questionnaires are saved to its MySQL database. The ILS questionnaire’s user interface was designed by LimeSurvey, and the questionnaire has been linked to the LS module integrated to the CCS environment. A student/lecturer logs in to the CCS environment and responds to the questionnaire. Responses with a respondent’s ID are saved in LimeSurvey’s MySQL database. The LS module gets the responses from the database and presents the analyzed results in its own user interfaces in the CCS environment. From the user’s viewpoint, the LS module appears as a unitary solution integrated to the CCS environment. Users open the questionnaire by clicking the ”Start questionnaire” button in the CCS environment, and the summary of the questionnaire is shown in the users’ personal page in the same environment. Individual summaries of the questionnaire have also been designed for the lecturers and the education provider. These summaries are also shown in the environment. A. Student’s LS Module View In the student’s LS Module view, the student is provided with the ILS questionnaire. When the user logs in into the CiNetCampus system, the system checks whether the user has already filled in the learning style questionnaire. If not, he/she

Learning Style Module architecture in CinNetCampus Studies environment.

will be asked to fill it in. The ILS results are recorded in a database which enables the presenting of summaries to the students and lecturers. After completing the survey, the user will be guided to his/her personal CiNetCampus page, where the survey result is shown in a graphical form. The result diagram consists of four learning style axes and the student’s score on them. By moving the mouse cursor on top of the elements of the diagram, the user will receive additional information about the learning style axis. It is the student’s choice whether to read only the short introduction of each dimension or examine the theory of the Felder-Silverman model more deeply via links that are included in the LS Module. The links contain more precise instructions for interpreting the results as well as practical study advice. Fig. 4 shows a student’s learning styles result on the LS Module view. Among the additional information, there is also a link enabling the user to compare his/her own ILS result with the results of other users. The learning style survey result will remain as a permanent part, in a form of a compacted graphic element, of the student's personal CiNetCampus page. Through it, the student can at any time return to examine the learning style result and get to know, more deeply, the learning style theory or perhaps retake the test. In the case of retaking the test, the newest score will replace the previous in the summaries presented to students and lecturers. All results will, however, remain in the database.

A student’s view in the LS Module on her personal CiNetCampus page.

B. Lecturer’s LS Module View The lecturer will be able to examine the results of the students in his/her own ongoing courses through the lecturer's LS Module view. When the course begins, the lecturer will automatically get a summary of the distribution of the learning style results for the students enrolled in the course. Individual test results cannot be seen by the lecturer. Only diagrams of the ILS scores are shown. If the instructor has also responded to the

Fig. 6 shows the overall distribution of 110 results. The previous results are combined with 15 new results, and 10 old results are replaced with new ones. Of the students, 39 were women and 71 men. Sensing-intuitive and visual-verbal are the most skewed dimensions. Divided in categories, there is a clear majority of sensors and visuals: 83% are sensors and 73% visuals. For the active-reflective and sequential-global dimensions, the results were distributed more evenly and the distributions are more symmetric. There were 41% of active and 59% reflective learners as well as 53% sequential and 47% global learners. The results are in line with many studies exploring engineering students’ learning styles, gathered into

A lecturer’s view in the LS Module showing students’ learning style profiles in his/her course.

ILS survey, her/his result is shown in the same diagram with students’ ILS averages, enabling a comparison. The lecturer will also be shown information about the learning style model in general, suggestions for paying attention to different learning styles in teaching and links to additional information. In Fig. 5, a lecturer’s view shows diagrams of students’ learning style result in a specific course. C. Education Provider’s LS Module View The education provider can access a more diverse Education Provider’s LS Module view. The education provider can for example examine the survey results by student or by course or by all students. If more specific statistical information is needed, the database (or a part of it) can be downloaded and processed with statistical analysis software. D. Evaluation The true usability of the LS Module is achieved after it is used by both students and lecturers. The goal is to utilize the learning styles at lectures and in students' study practices. For the moment, we evaluated the module by how readily students answered it after the tool was released and how the students assessed the application through the system usability scale (SUS) survey. E. The Learning Styles Results In a few days, 25 students used the LS Module. The number is acceptable taking into account how many students we have. Only about 20 new students are accepted each year in our study program. Of the respondents, 15 answered the ILS questionnaire for the first time. The survey had been answered previously by 10 students. Before the LS Module, the ILS scores were collected during the application process or along with other student questionnaires. As the current blended learning practices are deployed in the program (about ten years now), 95 students have filled out the questionnaire.

Fig. 6. The distributions and averages of learning style results of the master's degree students in information technology (N=110).

[17]. Only on the active-reflective axis, our students differed most of them being reflective, while usually in engineering student populations, most students tend to be active. The differences between genders are minor. The biggest difference is on the visual-verbal axis. Both genders are visual, men just a bit more on average. F. System Usability Scale (SUS) Results The learning styles survey had been piloted three times during the last ten years before being integrated as a part of our virtual campus environment CiNetCampus Studies. The current version of the survey was introduced in the end of October 2015, and for it the interface was changed and more information about learning styles was added. We wanted to examine the satisfaction of students with the new version and their subjective assessment about the application’s general usability. For the assessment of usability and satisfaction, we wanted a tool that, from the respondents’ viewpoint, would be quick and easy to use but regardless would give a reliable and comparable result. The System Usability Scale (SUS) was developed in the middle of the eighties by Brooke, and in 1996 it was published in a book on usability engineering in industry [30]. Since then it has been widely applied for the assessment of both products and services. The survey is quick and simple to carry out, and it has proven to be a tool that gives a reliable idea about the usability of the product or service examined [31], [32]. Usability and user satisfaction of the new modules developed for CiNetCampus Studies, like the LS Module, have been assessed with the SUS survey. The SUS survey tool itself has also been integrated in CiNetCampus Studies. The survey consists of ten slightly modified claims due to [31]: 1.

I think that I would like to use this product frequently.

2.

I found the product unnecessarily complex.

3.

I thought the product was easy to use.

4.

I think that I would need the support of a technical person to be able to use this product.

5.

I found the various functions in the product were well integrated.

6.

I thought there was too much inconsistency in this product.

7.

I imagine that most people would learn to use this product very quickly.

8.

I found the product very awkward to use.

9.

I felt very confident using the product.

10. I needed to learn a lot of things before I could get going with this product. In the SUS survey tool the, claims are presented both in English and, translated, in Finnish. The claims are evaluated with a 5-point Likert scale (Strongly disagree … Strongly agree). The SUS survey is not supposed to be diagnostic, but it produces a single score on a scale of 0 to 100 that represents a

general measure of perceived usability. Instructions for the scoring of SUS can be found, for example in [30]. Bangor et al. [31], [33] have investigated what a single SUS score for usability means. A SUS score below 50 indicates that the application may have severe problems with usability. A score of over 70 indicates the usability of the application to be at least passable; when the score is high 70s to upper 80s, the usability is at least good; and a score of over 90 indicates a very good usability. The survey was conducted between the end of October and the beginning of November of 2015 as a web-survey through the virtual learning environment CiNetCampus Studies. All the students who answered the learning style survey had the opportunity to participate in the SUS survey also. Altogether 18 students responded to the SUS survey before 20th November. Of these, one student's responses were rejected. The students obtained the SUS score of 78.5, strongly suggesting that the students were satisfied with the usability of the Learning Style module. We wanted to clarify the results of the SUS survey by adding to it three yes/no questions and one open question, which allowed the respondent to make comments about the application and bring up some development issues. In these questions, all 18 respondents were included in the analysis. Only few students commented the application through the open question, saying that it would be nice to have opportunity to do the LS survey from time to time and compare one's own results. In this respect, the application will be improved in the future. Table 1 shows three yes/no questions presented to the students. The distribution of their responses is also shown. Our students typically are adult students, and they have studied at least one degree before our master program. The influence of their studies shows in the results. The students had the opinion that the result of the learning style survey coincides very well with the student’s own opinion of his/her learning style. They also had a very positive attitude to the learning style survey. Most of the students saw the knowledge of their own learning style benefit their studies. Moreover, most students regarded it as a good idea to integrate the Learning style module in CiNetCampus Studies. The first claim in the SUS survey proved slightly problematic. This had also a decreased impact on the SUS score. Even though the learning styles were considered useful for the study, the LS Module was mostly perceived as a single-use tool. For a lecturer, the module provides something new for every course. This should also be the case with students. Easy realizable solutions might include showing the course TABLE I.

ADDITIONAL QUESTIONS IN SUS SURVEY Question

Yes

No

Did the result of the learning style test correspond to your own view?

17

1

Do you think that knowledge of your own learning style is useful for you in your study?

16

2

In your opinion, is the integration of the learning styles application to CiNetCampus useful?

16

2

instructor’s learning style result, a possibility to rate how far each learning style is taken into account or a possibility to indicate which tools or methods are desired for the course. VI.

DISCUSSION

Earlier, the learning style survey data from students were collected in connection with the student selection process. Even though the students willingly responded to the survey, it seems likely that the information about the learning styles was not utilized in any way at the beginning of the study. To make the student adapt the recommendations and techniques of the learning style model, we set out to integrate the learning style survey as one of the CiNetCampus elements. In the best of cases, the student begins deliberately improving his/her learning techniques and trying new methods. He/she may also challenge the lecturer to pay more attention to the learning styles. At its simplest, the student may for example ask the lecturer to provide practical examples of the topic in question. When providing a student with his/her learning style result, it is also emphasized that no learning style instrument is infallible when applied to individuals.

VII. CONCLUSION This study describes the deployment of the Learning Styles Module built for the CiNetCampus Studies environment that is used in connection with the master's studies in mathematical information technology. The paper presents the motivation for learning style evaluation and collection of results and tells about the added value that the integration of the module to the learning environment brings with it. In addition, the usability and need for the module are preliminarily assessed on the basis of the SUS Survey. ACKNOWLEDGMENT The research for this paper was financially supported by European Social Fund, grant no. S20073, without which the present study could not have been completed. The authors wish to thank the Central Finland Centre for Economic Development, Transport and the Environment for their help.

REFERENCES

Integrating the LS Module also into the lecturer’s CiNetCampus Tool makes also lecturers aware of the FelderSilverman learning style model and facilitates the utilization of the model in their everyday work. Before, distribution of learning styles to lecturers wasn't a permanent practice, and the results were not filtered course-specifically. The aim is to encourage them to use methods preferred in different learning styles in their teaching. A course-specific summary about the students' learning style results demonstrates to the lecturer that there are different learners in the course. This is so especially if the lecturer can compare her/his own ILS scores with students’ scores. Felder [14] pointed out, for example, that while a majority of engineering students are sensors (that is also the case with our students) most professors are intuitors.

[1]

It is not the aim of the summary, shown to the lecturer that the lecturer would change the material to correspond to the learning style of the course participants. Learning style models have been criticized particularly for their lack of proving the "meshing" hypothesis [34]. According to the meshing hypothesis, the student learns best with teaching that corresponds to his/her own learning style. However, we believe that paying reasonable attention to each learning style can only positively affect the learning results. For example, traditional lecture study favors verbal students. Most of the students, however, are visual. This also applies to our students. If the distribution of the students participating in a course is seen to be skewed by the lecturer, this may encourage the lecturer to add diversity to the teaching by providing more pictures and diagrams. By beginning the course with a summary about the entire lecture topic or by linking a new topic to other courses or modules, the lecturer can help global learners, and so on. According to the theory, also learning styles less prominently represented by the student should be practiced. Always changing the teaching to correspond to the learning style of the student would thus do a disservice to her/him.

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