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Learning styles of millennial students at a pharmacy school in the Philippines

Background: The millennial generation already composes the majority of populations across different pharmacy schools in the Philippines. The need to explore millennial students’ learning styles and its governing factors thereby become more valuable in changing and innovating instructional approaches, designs, and strategies used in their learning environment. Aims: This study aimed to generally describe the learning styles of the millennial pharmacy students from a college institution in the Philippines using the Vermunt’s Inventory of Learning Styles (ILS). Specifically, it aimed to determine the appropriate approaches in response to the students’ learning styles, and the relationship between and among the variables of the study. Method: A quasiexperimental research design was employed in this study using online survey as the method of data collection. Descriptive statistical analysis was employed to analyse the data using Microsoft Office Excel 2013 and IBM Statistical Package for Social Sciences Statistics. Pearson’s correlation coefficient investigated the relationship between and among the independent and dependent variables, while t-test and one-way ANOVA tested for significant difference among groups. Results: There were 124 out of 168 students who participated in the study making the overall response rate at ~74%. The most prevalent learning style among the millennial pharmacy students enrolled in De La Salle Medical and Health Sciences Institute, College of Pharmacy is applicationdirected (3.85±0.46), followed by reproduction-directed (3.81±0.45), undirected (3.73±0.49) and lastly meaning-directed (3.52±0.54). The students’ perceived grades were significantly reflected by their learning styles. Conclusion: Results of this study may be used in increased capitalising and development of the learning style profile of millennial pharmacy students to application-directed approaches. Instructional approaches, designs and strategies must cater to how students learn effectively and strategically, and consider all possible governing factors that affect learning styles of students. RESEARCH ARTICLE


Introduction
'Learning style' refers to the organisation and control of the strategies for learning and knowledge acquisition and is configured by the cognitive, affective and personality particularities of the learner (Magdalena, 2015). Much educational research has focused on the concept of learning styles. Several authors have proposed that the ability to typify student learning styles can augment the educational experience. As such, instructors might tailor their teaching style so that it is more congruent with a given student's or class of students' learning style (Romanelli et al., 2009). The current generation of college learners can be viewed as the group between the years of 1982 to 2002 and are often referred to as the millennials (Kotz, 2016). Social researchers suggest that these learners may be different than older generations as a result of aspects of their upbringing (Sickler, 2009). There are no published studies that have systematically examined the learning styles of millennial pharmacy students (Romanelli et al., 2009).
The millennial generation already composes the majority of populations across different pharmacy schools in the Philippines. Their knowledge of the different learning styles may help improve their academic performance as they learn more about themselves and how to acquire knowledge in the most effective manner, especially in situations where the instructor's teaching style does not match the students' preferred learning style (Choi et al., 2014).
Vermunt's Inventory of Learning Styles (ILS) integrates four components of learning: processing strategies, regulation strategies, mental models of learning, and learning orientations (Vermunt, 1994). He identified four different learning styles: meaning-directed, reproductiondirected, application-directed, and undirected, which displayed characteristic patterns of factor loadings across the four components of learning (Boyle et al., 2003). Students who learn in a meaning-directed way try to understand the meaning of what they learn, discover relations between separate facts or views, structure the learning material into a larger whole, and try to critically engage to what they learn. In reproduction-directed learning, students try to remember the learning content in order to be able to reproduce it in a test. They memorise the learning materials and go through the study materials in a sequential way, step by step, without thinking much about relations between larger units. Students who learn in an application-directed way try to discover relations between what they learn and the world outside. They try to find examples of what they study and think about how they would be able to apply what they learn in practice. Finally, students who learn in an undirected way do not know how to approach their studies. This pattern can often be seen with students who are in transition from one form of schooling to another (Vermunt & Donche, 2017).
This study would be useful to the development of instructional design and teaching methods among faculty members of the College of Pharmacy, De La Salle Medical and Health Sciences Institute (DLSMHSI), especially considering the newly revised and prescribed policies, standards, and guidelines for the Bachelor of Science in Pharmacy programme. Also, by identifying the governing factors associated with the learning styles of the students, it is particularly useful to facilitate the effective learning of the students, create a conducive learning environment and context, and develop the learning outcomes for the pharmacy students. Therefore, this study aims to generally describe the learning styles of the millennial pharmacy students in DLSMHSI College of Pharmacy using the Vermunt's ILS. The survey consisting of a list of statements on study strategies, motives and attitudes, is used to gain clearer insight into how students go about their studies and how they perceive their own learning (Vermunt, 1994). Specifically, it aims to: 1) assess the learning styles of the pharmacy students at DLSMSHI enrolled in the second semester, academic year 2017-2018; 2) describe the demographic characteristics of the pharmacy students enrolled in DLSMHSI; 3) identify the most prevalent learning style of the students using the Vermunt's ILS and determine the relationship of the student characteristics with the learning style.

Methodology
A quasi-experimental research design was employed in this study using online survey as the method of data collection. The study population consisted of all the pharmacy students enrolled at DLSMHSI College of Pharmacy, therefore, a one hundred percent (100%) sampling technique was utilised in the research project. The inclusion criteria included: 1) the participants should be officially enrolled in the second semester of the academic year 2017-2018; and 2) must have an age of 25 years and below. Participation in the study was voluntary and the respondents were not rewarded for their cooperation. Participants were given a brief orientation about the project and the informed consent. They were asked to read, comprehend and agree with the consent prior to self-administration of online survey questionnaire. The entire survey took about ten to fifteen minutes to complete. The researchers waited for respondents to complete the survey, and then gave a letter of gratitude to each student who participated. The researchers started collecting data from third week of April 2018 to first week of May 2018. Furthermore, the time and place to conduct data collection was based on the availability and location of the students.
The learning styles were measured by ILS (Vermunt, 1994). The questionnaire comprised of two parts (A and B) with a total of 120 statements covering four learning components: cognitive processing strategies, metacognitive regulation strategies, conceptions of learning, and learning orientations. For the strategy items, students were requested to indicate on a 5-point scale the degree to which they use the described learning activities in their studies. The scale varies from '1 -I seldom or never do this', to '5 -I (almost) always do this'. For the items on learning conceptions and learning orientations, students were asked to indicate on a 5-point scale the degree to which the described views and motives correspond to their own views and motives. Here the scale varied from '1-completely disagree' to '5 -completely agree'. To identify the learning styles, researchers classified the 120-item questionnaire into four major classifications (meaningdirected, reproduction-directed, application-directed, and undirected).
All research data collected were prepared and encoded in Microsoft Office Excel 2013 for statistical analysis. Each participant who indicated their name was not included for confidentiality purposes. IBM SPSS v.21 was used for correlation and descriptive analysis. Descriptive statistical analysis, measuring the frequency, mean and standard deviation, was employed to describe the different variables in the study. To investigate the relationship between and among independent and dependent variables, Pearson's Correlation Coefficient was used. Independent Samples t-test and one-way ANOVA were used to test for significant difference among groups.

Student Demographic Characteristics
A total of 124 out of 168 students participated in the study having an overall response rate of ~74%. Majority of the respondents were female and at third year level, while their academic status, whether as regular (students with no failed or incomplete subjects) or irregular (students with failed or incomplete subjects), did not significantly differ ( Table I).

Comparison of mean scores of different groups in different learning styles
There were no significant differences found in the comparison of means between gender, year level, and academic status of students in different learning styles (Table II). However, it can be noted that fourth year level students had higher mean scores in all types of learning style as compared with both second and third year level students

Association of the different factors with learning styles
Across the learning styles, application-(p=0.000, r=0.336), meaning-(p=0.002, r=0.275), reproduction-directed (p=0.025, r=0.201), were found to significantly affect the perceived general weighted average (GWA) of students, while other factors such as age, gender, year level, and academic status of students had no relationship with learning styles (Table III).

Learning styles
Comparing all the mean scores of different learning styles, application-directed was the most prevalent learning style among the millennial pharmacy students in the DLSMHSI. This was followed by reproduction-directed and undirected learning styles (Table IV).      Vermunt (1994) distinguishes four different learning styles: application-directed, reproduction-directed, meaning-directed, and undirected learning style. What distinguishes Vermunt's learning styles from other models is that it was developed as a diagnostic tool for use in a higher education context. As the survey participants were already in tertiary education, Vermunt's questionnaire was utilised and applied. Students with an applicationdirected learning style try to employ what they learn to actual, real-world settings (Busato et al., 1998). The high mean score of the respondents in this type of learning style (3.850.46) may be attributed to the pharmacy curriculum of the DLSMHSI College of Pharmacy since their internships in community, hospital, and manufacturing pharmacy are incorporated in the curriculum wherein students are simultaneously taking their experiential education along with their subjects from the school. For instance, third year level students are undergoing internship in the manufacturing setting while fourth years are taking their major internship in hospital pharmacy practice. Their exposure to the real-world setting might have contributed to their scores. The curriculum design, which placed the internship towards the end as a platform for integration, may suggest why students had higher means for application-directed learning style. This may have resulted in lower mean scores for the other learning styles, reproduction-directed (3.81±0.45) that primarily reflects cognitive recall, undirected (3.73±0.49) that follows no pattern, and meaning-directed (3.52±0.54) that engages in higher order of thinking than recall. These were the learning styles that were described for the survey participants, the millennial students.

Discussion
Although literature suggests that academic performance has little influence on the learning styles of students (Vermunt, 2005;Wilkinson et al., 2013;Choi & Yu, 2014), this study found that perceived grades of students had positive correlation with all types of learning styles, except undirected with negative correlation. Students characterised by an undirected learning style had, for example, problems with processing material for study, experience difficulties with the amount of study material,  Busato et al. (1998), which revealed that positive correlations were found for achievement motivation with the meaning-, reproduction-and the application-directed learning style, and a negative one with the undirected learning style. It may be presumed that millennial students motivated to study effectively using these learning styles have better academic performance.
Being part of the millennial generation, age had no relationship with the learning styles of the students. This is consistent with the study conducted by Vermunt (2005) where age showed little associations with the learning patterns of the student participants, specifically the reproduction-directed, application-directed, and undirected learning. They more often consult other sources than the prescribed syllabus, think that learning is equivalent to constructing their own knowledge and insights, use both deep processing strategies, study out of personal interest, and use a self-regulation strategy directed at their learning process and results, than younger students. However, Vermunt (2005) stated that age is an important predictor of meaning-directed learning. Learning is affected by factors such as the learning environment, interest in the material under study, and learning style preferences (Choi et al., 2014). The ideal learning environment is one that promotes students' motivation to master and acquire a deep understanding of the course material, and that develops self-directed and independent study skills. This mastery approach in learning is essential for the acquisition of critical-thinking and problem-solving skills and for fostering a desire for the lifelong learning attributes that are preferred in students of the healthcare profession. These approaches to learning are also believed to lead to enhanced academic performance (Choi et al., 2014). Moreover, according to these authors, there was no significant relationship found between learning style and academic performance. Each learning style favours a certain teaching method, but there was no relationship found between learning style and academic performance. The learning style profile of the students may be built upon, to develop meaning-directed approaches by focusing on interventions that will promote deep, critical processing and self-regulation.
Other authors have proposed correlations between culture and learning styles (Romanelli et al., 2009). This is based on the concept that culture influences environmental perceptions which may determine the way in which information is processed and organised. Technology may 271 also be influencing the learning styles of younger students and emerging generations of learners. The millennials have been described as more technologically-advanced with higher expectations for the use of computer-aided media in the classroom (Romanelli et al., 2009). In pharmacy education, electronic learning or e-learning effectively increases knowledge and is a highly acceptable instructional format for pharmacists and pharmacy students. However, there is limited evidence that e-learning effectively improves skills or professional practice. There is also no evidence that e-learning is effective at increasing knowledge long term; thus, longterm follow-up studies are required (Salter et al., 2014).
The study reported by Djiwandono (2017), on the other hand, revealed that there was no significant correlation between the learning styles of students and their achievements in language and content course, but found that there was a modest correlation between the amount of verbal report and their ultimate mastery of the course content. He attributed this result to the instructional context and cultural aspects that shaped the respondents' learning styles (Djiwandono, 2017). However, this study has included 22 learners in their twenties. Certainly, a larger sample could be used to yield more information and better assessment of learning. Magdalena (2015), found significant differences with regards to the learning style and learning behaviour, according to the age, experience, and academic performance type. Their study reported that there were significant associations between learning style and learning strategies and suggested that future studies be developed to determine the predictive relationship between learning style and learning strategy. Moreover, in terms of the relationship between learning style and academic performance, metacognitive performance was associated with the theoretical and practical engagement of students with work experience, and deep learning strategy was found to be associated with high performance in the theoretical activities in students who did not have professional experience. Prediction and improvement of academic success represent a current issue in the field of academic learning. Finding the factors which influence academic success has strong implications on research in the learning field, on educational policies, and implicitly on students' learning strategies (Magdalena, 2015).
Similar to the study conducted by Novak et al. (2006), a major limitation also considered was that the teaching styles of the students' instructors were not directly measured. This is because Vermunt's ILS was designed to be answered by students only. Therefore, further research was planned by the researchers to also examine

Carrido & Ramirez
Learning styles of millennial students at pharmacy school in the Philippines Pharmacy Education 20(1) 265 -272 the effect of the instructor's teaching style, and how it affects students' learning style. In addition to examining the instructor's teaching style, the students' personality types may also be explored and related to their learning style. While it is beyond the scope of Vermunt's ILS questionnaire, Myers-Briggs Type Indicator (MBTI) personality types were found to be relevant in describing the students' learning styles (Shuck & Phillips, 1999). Williams et al. (2013) also incorporated the relevance of MBTI personality types on students' learning styles in their study, supporting the need to determine the learning styles of students to facilitate the instructional design of instructors, who are in this case, facilitating the learning of millennial students.

Conclusion
The most prevalent learning style among the millennial pharmacy students enrolled in DLSMHSI College of Pharmacy is application-directed, followed by reproductiondirected and undirected, and lastly meaning-directed. No significant relationship was found between learning style and age, gender, year level, or academic status, but a significant relationship was found with the GWA or academic performance of the students. Results of this study may be used in capitalising and further developing the learning style profile of the millennial pharmacy students to application-directed approaches. Instructional approaches, designs and strategies must cater to how students learn effectively and strategically, and consider all possible governing factors that affect the learning styles of students.