Vol. 8, Núm. 2 / octubre 2016 – marzo 2017 / ISSN 2007-1094

 

Learning styles of postgraduate distance learning students of the Universidad Autónoma de Tamaulipas

 

Arturo Amaya Amaya[1]

Universidad Autónoma de Tamaulipas

Alfredo Cuellar Cuellar[2]

State University of California in Fresno

 

Abstract

This paper presents the results of a research project related to the learning styles of postgraduate distance learning students from the University of Tamaulipas, Mexico. These postgraduate studies were created in 1996: nowadays, 14 generations have graduated from the Master of Human Resources Development; 13 generations, from the Master of Quality Management; and 8 from the Master in Educational Technology. The instrument used in this research was created by Whiteley and is based on the model of multiple intelligences developed by Gardner and the neuro-linguistic programming model by Bandler and Grinder. The research was conducted with a sample of 72 participants, who represent one hundred percent of the students enrolled. The results showed that the most prevalent learning styles are logical and social, and the auditory and physical learning styles were the less predominant. Consequently, it was able to recommend content, resources and learning activities for each learning style.

 

Keywords: Distance education; adaptive learning; learning styles; ICT.

 

 

INTRODUCTION

 

The Higher Education Institutions (HEIs) consider the current scenarios increasingly relevant, permeated by the signs of globalization, information, technologies, virtualization, strategic value of knowledge and innovation, which have influenced the educational processes and the access to knowledge (Amaya, 2014). Based on the foregoing, the HEIs need to work and orient their efforts and resources towards educational innovation, the improvement of teaching materials for distance learning, the incorporation of information and communication technologies (ICTs) in the educational processes, as well as in teacher training. In this manner, the new proposals or solutions of the HEIs will be more effective to face the current education scenarios.

 

In the face of this critical reality, it is important to identify in which manner these new scenarios affect the quality of the education programs, and even more so, what is it that the HEIs need to do in order to make most of them, and at the same time, resolve the social problems assigned to them, such as, the expansion of quality higher education, equity and inclusion.

 

Scope of distance learning

 

Distance Learning (DL) is emerging as a pertinent solution to the problems of higher education, due to the fact that it overcomes geographic barriers, as it is not necessary to move to any other place; it also solved the problems of time by making it possible for the student to balance their study with work and family obligations, and for them to choose their own schedule; the student is able to follow the same formative program with people that share the same interests, but that are in different locations. These sui generis characteristics of DL represent a wider range of information offers and learning opportunities for the new generations of students (Gallego & Martínez, 2002).

 

The vertiginous advances of information technologies have influenced the education processes and the access to knowledge. In the face of this premise, the current DL programs should not only be more or less critical to the social formation demands, but also need to be supported by investigations that present empirical evidence that justifies and favors the evolution and the acknowledgement of DL as a new quality education system.

 

On the other hand, the evaluation and accreditation processes to which the HEIs are currently subject to force them to use investigations oriented towards the improvement of the quality of education. Speaking of the quality of education gives rise to different study topics, among which is the quality of the teaching materials, in which knowledge is stored, in addition to bearing the contents and a good part of the teaching methods that, when perfectly articulated and set up, are able to turn into the pillar of any DL systems (García, 2002).

 

In DL, the teaching materials have a relevant role in the construction of new knowledge, but given that it is not an easy task to guarantee their effectiveness, the HEIs are responsible for the formation of the professors in the management of the theory on learning styles and their implementation, and the best way to do that is by generating experience in these same practices in their own contexts (Madrigal and Trujillo, 2014). For this, it is fundamental that the professors know information related to their students, how to identify their predominant learning styles and, then, work on the redesign or development of ad hoc teaching materials, as well as on the implementation of adaptive learning mechanisms with the support of ICTs.

 

The importance of learning styles in distance learning

           

Learning styles possess more influence than could be imagined; for example, they lead the way for the learning process; they may also internally alter the direction, representing the experiences and recovering information. People perceive and acquire knowledge differently; they develop ideas, think and act in different ways. Furthermore, they have preferences towards one or several cognitive procedures that help them give meaning to new information. The term “learning styles” entails, specifically, the ways to collect, interpret, organize and think about the new information (Gentry & Helgesen, 1999).

 

When a new concept is learned, some students focus on the details, while others focus on the logical elements; some are more independent and want to learn alone, and others prefer to study with other classmates or close to their professors; some prefer reading or going to conferences, while others prefer to carry out practical activities (Davis, 1993).

 

The learning styles in DL must have a serious impact on the teaching styles, particularly because the distance students interact in an asynchronous and intensive manner with the teaching materials available in the learning management systems (LMS). It is worth mentioning that the information provided by the diagnoses of learning styles allow to diversify the teaching activities and procedures that facilitate for the students to learn more about themselves; this aspect is considered a fundamental indicator of vocational conduct (Alonso and Gallego, 1995).

 

There are different models of learning styles, among which the following can be found:

 

·      Kolb’s model (1984), based on learning and whose central axis is the direct experience of the student. It is classified in four dimensions: divergent (concrete and reflective), assimilator (abstract and reflective), convergent (abstract and active) and accommodating (concrete and active).

·      Honey and Mumford’s model (1992), which seeks to improve the effectiveness through the actions of the subjects and is classified in the following dimensions: active, reflective, theoretical and pragmatic.

·      Felder and Silverman’s model (1988), which classifies the students according to the way they receive and process information and is classified in the following dimensions: visual-verbal learning, active-reflective learning, sequential-global learning and sensory-intuitive learning.

 

In this investigation, we resorted to the instrument of learning styles of Sean Whiteley (2006), which has been used in more than three hundred schools, colleges and universities with significant results that have helped the students in their learning. This instrument was designed based on the multiple intelligences model of Howard Gardner (1983) and on the neuro-linguistic programming model of Richard Bandler and John Grinder (1982), also called the Visual-Auditory-Kinesthetic (VAK) model. In this manner, it integrates the potentialities of the seven learning styles of the multiple intelligences model (verbal/linguistic, logical/mathematical, visual/spatial, bodily/kinesthetic, musical/rhythmic, interpersonal and intrapersonal) and the three from the neuro-linguistic programming model (visual, auditory and kinesthetic).

 

The Universidad Autónoma de Tamaulipas (UAT), although it has more than 15 years of experience in the use of DL systems, has not yet carried out research that provides evidence of what are the predominant learning styles of the students that study through their DL system; because of this, the present paper sought to identify them, not only to enhance and improve the methods, techniques and learning and teaching strategies on behalf of the professors, but also to have the very students know how to learn. It is important to make it clear that there is no right mixture of styles, nor can we claim that the styles are fixed or exclusionary; we simply seek to acknowledge that all students learn through different styles. From the foregoing, two research questions arise:

 

·      Which are the learning styles of the students of the masters in Human Resources Development, Quality Management and Educational Technology?

·      What are the differences between the learning styles of the students of the masters in Human Resources Development, Quality Management and Educational Technology?

 

 

METHOD

The educational entity where this investigation was carried out are the excellence centers of the UAT, which offer masters in Human Resources Development and Quality Management since 1996, and the masters in Educational Technology since 2000. It is important to mention that, after more than a decade, these postgraduate studies are still in force.

 

The universe of this research was comprised by 72 students, who represented one hundred percent of the enrollment of these masters; they corresponded to the seventh and eighth generation of Educational Technology; the twelfth and thirteenth generations of Development of Human Resources and Quality Management; and the fourteenth generation of Development of Human Resources.

 

The postgraduates of the excellence centers are offered in a DL model. The students that were surveyed are located in different geographical sites of the country, so that they carry out their studies at a distance, making use at all times of the technological infrastructure available at the UAT.

 

Characteristics of the instrument

 

The instrument used in this investigation was created by Whiteley and is based on the model of multiple intelligences developed by Gardner and the neuro-linguistic programming model of Bandler and Grinder (1982). The latter is also known as the visual-auditory-kinesthetic model (Whiteley, 2006).

This instrument helps not only to identify the learning styles of the students, but also to recognize, through a method of data analysis, the predominant and secondary learning styles of the students. The seventy items that comprise this instrument, even though at the moment of application do not follow a specific order, belong to one of the following seven constructs: visual, verbal, auditory, logical, physical, social and solitary. The answers given by the students must be among the following three options:

 

0 = I can’t relate at all

1 = I can partially relate

2 = I can fully relate

 

Thus, it is possible to determine which are the learning styles that are more and less representative of each student.

 

This instrument was only available in the English language; that is why it was translated to Spanish in order to implement it without complications and with the same interpretation.

 

According to Whiteley (2006), there are around three-hundred schools, colleges and universities where the professors have used this instrument to develop investigations, the results of which could favor the students in their learning. Some institutions are: University of Phoenix, University of Memphis, University of Houston, East Carolina University, Seton Hall University (Virginia), Western State College (Colorado), Florida Community College, St. Petersburg College (Florida), Lake Forest College (Colorado), St John's High School (Ohio), University of Toronto, Oxford Brookes University (Great Britain), University of the West of England (Great Britain), Queensland University of Technology (Australia), Universidade Independente (Portugal), and Accademia Lingua Italiana (Italia).

Implementation of the instrument

 

The instrument was used at two stages: the first stage comprised the school cycle of January-April, 2009; the students of the twelfth, thirteenth and fourteenth generations of the masters in the Development of Human Resources; the twelfth and thirteenth generations of Quality Management; and the seventh generation of Educational Technology. In the second stage took place during the school cycle of January-April, 2010; only the students of the eighth generation of the masters in Educational Technology were surveyed, which initiated their educational activities in this same school cycle.

 

The data collection was carried out in the videoconference session and through e-mail, that is, we explained to the students the characteristics of the instrument, as well as the indications to fill it; after the students had access to the instrument via e-mail, we asked them to return it through the same means for the concentration, analysis and interpretation of the information.

 

Data analysis design or plan

 

For this investigation, we designed 93 variables. The first corresponds to the number of the survey; the following eight, the general information of the student (name, postgraduate program, generation, generation and postgraduate program, beginning of the postgraduate program, academic field of the postgraduate program, gender and profession); the following seventy, with the same number of questions as the investigation instrument; and finally, fourteen variables belong to the learning constructs.

 

This study was based on research questions and on an instrument related to the study area, which was applied to all the students of the defined universe, i.e., it was a census design.

 

We performed two types of analysis: descriptive and differential. In the first descriptive analysis, we used frequencies of students per master’s degree, starting year of the master’s and gender. In the second descriptive analysis, we first identified the ten questions that correspond to each learning construct and, afterward, we averaged the results from each group of questions in order to identify the most and less representative learning style of the postgraduate programs.

 

In the differential analysis or hypothesis test, we handled the averages to recognize the differences between the learning styles of the students of each postgraduate program.

 

 

RESULTS

The results have been organized in two sections. The first comprises the results that arose from the descriptive analysis that have to do with the frequencies of the students per master’s degree, starting year of the master’s and their gender, as well as the averages of the learning styles that are most and less representative of the postgraduate programs of the excellence centers of the UAT.

 

The second section shows the results of the differential analysis or hypothesis test regarding the differences between the learning styles of the masters in Development of Human Resources, Quality Management and Educational Technology, and identifies the learning style more representative of each master’s degree.

 

Results of the descriptive analysis

 

In Table 1, we observe that the highest graphical representation belongs to the master’s in Development of Human Resources, with 41.7%; meaning, 30 of the 72 students that represent the universe study this master’s.

 

Table 1. Frequency of students per master’s degree.

 

In Table 2, the highest graphical representation can be seen in the year 2007, with 37.5%; meaning, 27 of the 72 students that represent the universe started their master’s this year.

 

Table 2. Frequency of students per year of starting year of their master’s.

 

 

In Table 3, the highest statistical representation belongs to women, with 55.6%; meaning, 40 of the 72 students that represent the universe are women.

 

Table 3. Frequency of students by gender.

 

In Table 4, the highest average belongs to the social profile, with an average of 1.4833 on the original scale of 0 to 2. On the other hand, the lowest average lies on the physical profile, with an average of 1.0736. For this reason, the social profile is the most representative, whereas the physical is the less representative of the postgraduate programs of the excellence centers of the UAT.

 

Table 4. Averages by profile.

 

 

Results of the differential analysis or hypothesis test

 

In Table 5 and in the figures corresponding to the master’s in Quality Management, this is the most representative of the visual profile, with an average of 1.2938; of the auditory profile, with 1.1000; and of the logical profile, with 1.4063. The master’s in Development of Human Resources is the most representative of the verbal profile, with an average of 1.2800; of the physical profile, with 1.1667; and of the social profile, with 1.6067. The master’s in Educational Technology is the most representative of the solitary profile, with an average of 1.2346.

 

Table 5. Average of the profiles by master’s degree.

 

 

The following figures graphically represent the differences of each profile per master’s degree.

 

Figure 1. Means of visual profile per master’s degree.

 

Mean of the VISUAL PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

 

Figure 2. Means of the verbal profile per master’s degree.

 

Mean of the VERBAL PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

 

Figure 3. Means of the auditory profile per master’s degree.

 

Mean of the AUDITORY PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

 

Figure 4. Means of the physical profile per master’s degree.

 

Mean of the PHYSICAL PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

 

Figure 5. Means of the logical profile per master’s degree.

 

Mean of the LOGICAL PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

 

Figure 6. Means of the social profile per master’s degree.

 

Mean of the SOCIAL PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

 

Figure 7. Means of the solitary profile per master’s degree.

 

Mean of the SOLITARY PROFILE

Name of the master’s degree

Master’s in Educational Technology

Master’s in Development of Human Resources

Master’s in Quality Management

 

 

CONCLUSIONS

 

Our conclusions seek to give a response to the two research questions of this study as well as to formulate recommendations based on the results that will allow re-designing the teaching materials of the education programs in order to support and improve the learning of the students.

 

What are the learning styles of the students of the master’s in Development of Human Resources, Quality Management and Educational Technology? In the descriptive analysis of this study, after averaging the ten responses that corresponded to each of the seven constructs of learning, it was evidenced that the predominant profiles of the students of the three postgraduate programs of the centers of excellence of the UAT were the social, with an average of 1.4833, and the logical, with 1.3083. On the other hand, the less predominant were the auditory, with 1.0944, and the physical, with 1.0736.

 

What are the differences between the learning styles of the students of the masters in Development of Human Resources, Quality Management and Educational Technology? The students of Quality Management have a more developed visual, auditory and logical profile in comparison to the students of the other two postgraduate programs. Finally, the students of Educational Technology show a greater development in the solitary profile in relation to the students of the other two postgraduate programs.

 

Table 6 more clearly represents the difference between the learning styles (more representative, representative, and less representative) of the students of the three postgraduate programs.

 

Table 6. Summary of the differences between the learning styles of the students of the three postgraduate programs.

 

 

 

 

From a social perspective, the results of this research did not only demonstrate how the students learn using, with more or less intensity, the different learning styles, but they also helped us identify the similarities and differences between the styles of the groups of students of the three postgraduate programs. These same results give us the elements needed to recommend which would be the characteristics of the teaching materials that could be used to improve the academic performance of the students in the three postgraduate programs.

 

For the students of the master’s in Quality Management, we recommend the elaboration of teaching materials that comprise multimedia resources, presentations and videos. It is also possible to include learning activities that use mental or conceptual flow charts, information flow diagrams, as well as graphical representations with a diversity of colors, figures and tables instead of text; this would favor the learning of visual students.

 

For the auditory students, we recommend the recording of small presentations on the more important topics and make them available in the LMS or in electronic sites so that they can be downloaded as podcasts through computers or mobile devices that are connected to the internet, as many times as necessary.

 

For the logical students, the teaching materials must first of all be dully articulated with the objectives and the learning activities; even though this characteristic is fundamental for any distance learning program, the development of skills and behaviors of this type of students depends on the well-made design and development of the learning activities, which shall have an educational sense in order to get their interest. We recommend association activities, mainly when these are illogical and irrational; there are also the activities that demand the development of procedures, for example, those that are based on project or problem methods, in order for the students to test their logical abilities to discern whether to continue with the same procedure or if they prefer to change it or adjust it.

 

For the students of the master’s in Development of Human Resources, we suggest the use of learning techniques and strategies that promote verbal and written communication, for example, learning activities such as the elaboration of reading reports or essays related to a topic, in addition to presentations, out loud readings or simply asking them to record their comments or notes on theories or concepts as digital audio can be of great use to verbal students.

 

For the physical students who like to use the sense of touch, actions and work that require the use of the hands are convenient activities for them, supported with the technology of augmented reality, parting from the fact that they are individuals that take part in distance learning. This type of technology allows them to sense and experiment sensations when performing learning tasks. They also like to learn through writing and drawing, meaning it is possible to design activities such as elaboration of reading reports or essays, as well as the modeling of diagrams, and mental or conceptual maps.

 

For social students, we recommend learning activities such as study cases in which brainstorming is used, in order to present collective solutions, team presentations for which the students must organize themselves, as well as the development of projects or products, due to the fact that the procedures and the behavior of the rest of their classmates helps them formulate their own conclusions. This type of students likes to learn through discussion forums, wikis, blogs and social networks, because this way they test their skills and abilities to socialize and work collectively; information technologies emerge as an educational element that is very important for learning. It is worth noting that the theory of learning styles contributes to the construction of the teaching-learning process from the perspective of the use of technologies, as it is based on individual differences and it is flexible (Melaré, 2011).

 

For the students of the master’s in Educational Technology, we recommend carrying out learning activities that derive in individual or autonomous work. It is typical for the solitary students to invest more time than normal to their studies; therefore, we propose learning activities that promote research through web technologies to complement or strengthen the knowledge acquired in the class sessions. This type of students is very specific in their work, due to this, learning activities related to the elaboration of projects or products are interesting to them, even more so if it is individual work.

 

It is important to clarify that the students do not only learn with one learning style, but that all styles are complementary; meaning that identifying the most representative, representative and less representative learning styles of each group facilitates the improvement of their learning with teaching materials ad hoc to their more representative learning styles. However, this does not mean that the students are not able to learn with the less representative styles, so that the activities have to be designed from a social perspective that favors the majority of students.

 

 

BIBLIOGRAPHIC REFERENCES

 

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Received: 31/10/2015

Published: 17/12/2015