A Study On The Relation Between Learning Styles And Students’ Academic Engagement

Abstract

Educational policies and practices pertaining to initial professional formation focus upon the implementation of the student-centered concept. New tendencies regarding quality assurance of educational programs recommend that curricula should contain the most efficient teaching methods, in order to contribute to the formation of students’ professional competences. Specialty literature studies claim that the efficiency and performance of these competences depend largely not only on the course design but also on the learning style as well as on the student’s level of engagement in his/her own learning activity. Students’ academic engagement represents an umbrella term which implies students’ active engagement in the learning activities offered by the training programs. Academic engagement is often linked with good learning outcomes, such university persistence, high level of test achievement etc. The present study proposes to identify the level of academic engagement, the modality of self-regulated learning, as well as the type of relation established between the two constructs with the students of two specializations (technical and social studies). The measuring of constructs is achieved through applying the Inventory of Learning Styles and Utrecht Work Engagement Scale. We expect significant differences between the two groups of students in the level of academic engagement and in the modality of self-regulated learning. The implications on the practical educational level of the study refer to the fact that the instructional system should be designed to support the academic engagement and to stimulate the identification of other learning modalities.

Keywords: Academic engagementlearning engagementlearning styleself-regulated learningstudents

Introduction

Specialty literature presents numerous proposals of theorists (learning models) which would guide teachers in projecting the instructional design with a view to initiate, activate and support students’ learning in order to facilitate the forming of competences specific to the chosen study domain. One of the directions of high education educational policies refers to student-centered learning, to the development of certain strategies to involve students to play an active role in their own learning, to learn how to learn, to become autonomous and independent as learners. Many universities take clear and systematic measures with a view to allocate resources efficiently and to help students with their own learning, to facilitate success, all these being indicators of university practice quality (Kuh, 2009). Students’ engagement in learning represents an indicator of university retention and of graduation rate (Tinto, 1993).

It has been known that we are different not only in the way we behave, think and feel but also in the modality to learn. Honey and Mumford (1986) considers that not only students learn differently but also, they process information and represent knowledge in different ways that they prefer to use distinct types of educational resources. Interpreting the individual differences in learning (learning ability, learning style and learning goals, background knowledge) in the educational process not only contributes to obtaining learning performances but also to obtaining satisfaction and well-being which represents determinant factors of learning engagement and motivation.

Problem Statement

It has been known that students’ engagement in their own learning activity represents an indicator of academic success (Hu, 2011), of improving academic satisfaction and motivation (Appleton, Christenson, & Furlong, 2008). Students’engagement is a concept studied as early as 1990 and has been associated with students’ learning and personal development (Casuso-Holgado et al., 2013).

Academic engagement represents a multidimensional, complex phenomenon with substantial variations of terms and definitions: school engagement (Fredricks, Blumenfeld, & Paris, 2004), student engagement (Handelsman, Briggs, Sullivan, & Towler, 2005; Kuh, 2003), educational engagement (Wehlage et. al, 1989), study engagement (Schaufeli, Salanova, González-Romá, & Bakker, 2002).

Analyzing the subject student learning engagement, specialty literature studies are mostly centered rather on the learning environment, namely upon those learning opportunities present in the academic environment (Vekkaila, 2014), but also upon the activities offered by universities (McCormick, Kinzie, & Gonyea, 2013), ex. teachers (Anderson, Christenson, Sinclair, & Lehr, 2004) and peers (Buhs & Ladd, 2001), while others are centered on students’ personal characteristics which influence their engagement in learning, for example self-efficacy (Caraway, Tucker, Reinke, & Hall, 2003), family background (Marks, 2000). Two approaches of academic engagement concept can be distinguished: “one emphasizes the degree of willing student compliance with organizational and subject rules, values and processes, and the other focuses on students’ active participation and emotional commitment to their learning” (Casuso-Holgado et al., 2013).

The specialty literature lays more and more emphasis on explaining performance and progress in learning from the perspective of academic engagement, presenting different models of academic engagement. Most approaches consider academic engagement as being a multidimensional construct, made up of three interdependent components (behavioural, cognitive and emotional) whose compound effect reflects students ‘positive approach of learning (Li & Lerner, 2011; Appleton et al., 2008; Fredricks et. al., 2004; Schaufeli et al., 2002). Behavioural engagement consists of students’ active engagement in learning and academic tasks, including behaviours such as effort, persistency and focus, asking for questions and contributions to class discussions; affective engagement refers to indicators such as the presence of interest and happiness and the lack of boredom, anxiety, and sadness, and cognitive engagement refers to investment in learning, and involves aspects such as willingness and thoughtfulness to expand the effort required to understand and master difficult tasks, the use of appropriate learning strategies, challenge preference, and self-regulation. Reeve & Tseng, 2011 add to the previously mentioned model a fourth dimension – agentic engagement which implies that students play an active role in student learning based on their motivation and how the environment supports and nourishes that motivation. (Reeve & Tseng, 2011). The learning activity engagement model proposed by Schaufeli and collaborators (2002) consider that learning experience is characterized by absorption (is defined as students ‘sense of being deeply engrossed and fully concentrated in their studies), vigor (refers to students’ sense of high levels of mental resilience and energy while studying, their willingness to exert and invest effort into their academic-related activities, their persistence in the face of obstacles, and their positive approach to learning) and dedication (is characterised by students’ sense of enthusiasm, inspiration, significance, challenge, and pride for engaging in their studies, as well as their perception of school-related activities as meaningful) (Alrashidi, Phan, & Ngu, 2016). The model proposed by Schaufeli et al., (2002) describe students’ psychological engagement rather than their behaviour in the school environment, but at the same time it offers new information about the motivational approach of engagement (Alrashidi, et. al., 2016; Phan & Ngu, 2014).

The research in the field concentrated upon the indicators of academic engagement: a high level of quality in learning is associated with effort mobilization, persistency in task achieving, interest and motivation to comply with academic tasks. It turns out that there is a relation between students’ engagement in the learning activity and the learning strategies. Considering that motivation is the most important condition of learning (Kadivar, 2003) and that it can be explained through some aspects of activity engagement (vigor, dedication and absorption), we have proposed to investigate the efficacy of strategies to increase students’ motivation. One of these strategies can be self-regulation learning (Hedeshi, 2017), this being considered a factor that explains academic engagement (McClelland & Morrison, 2003; Pintrich & Groot, 1990). Self-regulated learning is a multidimensional construct that emphasizes the active role of the learner (Zimmerman, 2008). The general view upon self-regulated learning refers to the fact that through it, learners construct their knowledge actively and use various cognitive and metacognitive strategies to control and to regulate academic learning. A student who has self-regulation capacities in learning is aware of the requirements of the tasks to be achieved and also of his own needs in order to develop the learning activity to a considerable extent. Students control the learning process through planning, organization, monitoring and constant evaluation, settle learning standards and objectives which help them to decide if their learning process has to continue likewise or if he has to change the learning modality. The specialty literature is not very generous in explaining the modality in which students perceive their engagement strategies in the learning activities (Ulmanen, Soini, Pyhältö, & Pietarinen, 2014).

In our study we shall refer to the learning model of Vermunt (1996), which approaches learning style as learning orientation and as a learning model specific for the learner. The style is represented by the result of the interrelations between personal and contextual influences, without being a stable personality trait (Negovan, 2010). Vermunt differentiates four learning styles, each of them having distinct characteristics according to the following criteria: the manner of processing the learning content, learning orientation, affective processes activated during study, mental models and the manner of regulation learning. The four learning styles conceptualized by Vermunt approached only from the perspective of the component related to the learning regulation strategy (the manner of planning and monitoring learning), are: persons with a learning style directed on significance (ask themselves questions, diagnose and correct their understanding problems), persons with a learning style directed on application (they test understanding, especially of abstract concepts), persons directed on reproduction (they check their understanding periodically and they apply self-testing) and undirected persons (presents a low level of self-regulation) (Negovan, 2010).

Research Questions

The following research questions had been formulated:

• Are there any significant differences between the students from the two programs of studies (technical and social studies), respectively the level of study programs (master and bachelor) as regards academic engagement?

• Are there any significant differences between the students from the two study programs (technical and social studies), respectively the level of study programs (master and bachelor) in as regards regulation strategies used in learning?

• Are there significant associations between the components of academic engagement and regulation strategies in learning?

Purpose of the Study

The present study proposes to identify the level of academic engagement, the modality of self-regulated learning, as well as the type of relation established between the two constructs with the students of two specializations (technical and social studies) and at the level of study programs (bachelor and master).

Research Methods

Findings

The data registered for the two groups of students (technical specialization and respectively social sciences specialization) point out the following (Figure 01 ):

There are no significant differences between the two group of students as regards specializations at the level of academic engagement: general academic engagement t(126)= 10.086, p≤0.000 (m₁= 49.03, SD=22.11; m₂=59.11, SD=8.87), and for the dimensions dedication t(126)= 1.571, p≤0,000 (m₁= 17.46, SD=8.38; m₂=19.03, SD=3.27) and absorption t(126)= 1.714, p≤0,000 (m₁= 13.97, SD=9.07; m₂=15.69, SD=3.74). As concerns the dimension vigor significant differences have been registered between the two groups grupuri vigor t (126) = 6.057, p≤0,000 (m₁= 18.34, SD=7.30; m₂=24.40, SD=3.99); also, significant differences have been registered between the two groups of students as regards the level of studies both at the level of general academic engagement t(126) = 11.500, p≤0,000 (m₁= 47.50, SD=22.09; m₂=59.00, SD=13.51), and also at the level of all the dimensions of academic engagement: dedication t(126) = 4.100, p≤0,000 (m₁= 15.90, SD=7.03; m₂=20.00, SD=5.25) și absorption t(126) = 3.375, p≤0,000 (m₁= 12.90, SD=6.80; m₂=16.28, SD=6.77) and vigor (126)= 4.850, p≤0,000 (m₁=18.60, SD=7.69; m₂=23.45, SD=4.74). The covariance analysis ANCOVA allows us to calculate the combined effect of the level of studies (master or bachelor) and of the specialization type (technical or social) upon students’ academic engagement, thus F₁,₂=7,899, p=0,007, R square=0.300 (F1=13.149, p=0.001, partial eta square= .166; F₂=12.873, p=0.001, partial eta square= .163).

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In point of self-regulation strategies, we have determined the following (Figure 02 ):

There are significant differences as regards the level of studies (bachelor and master) between the two groups of students t (126) = 4.672, p≤0.000 (m₁= 64.27, SD=18.31; m₂=83.95, SD=16.76); equally, significant differences have been registered betweeen the two groups of students as regards the type of specialization (technical or social)t(126) = 2.861, p≤0.000 (m₁=47.50, SD=20.09; m₂=59.00, SD=13.51). The covariance analysis ANCOVA allows us to affirm that the differences related to regulation strategies in learning are explained by the combined effect of the specialization (technical and social studies) and of the level of studies (bachelor, respectively master), as it follows: F₁,₂=8.731, p=0,004, R square=0.365 (F1=23.619, p=0.000, partial eta square= .117; F₂=2.335, p=0.131, partial eta square= .034).]

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In order to identify the modality in which regulation strategies of learning explain students’ academic engagement, we have determined the following (Table 01 ):

The variable academic engagement, as well as its dimensions (vigor, absorption and dedication) correlates strongly with general strategies of learning, which allows us to verify if general strategies of learning can explain academic engagement (Tabel 02.). The linear regression analysis offers us the model through which we can explain that 48% from the variant of general regulation strategies of learning can explain academic engagement of students from technical and social sciences specializations.

Conclusion

The present study proposes to identify the level of academic engagement, the modality of self-regulated learning, as well as the type of relation established between the two constructs with the students of two specializations (technical and social studies) and at the level of the study programs (bachelor and master). Significant differences have been registered in point of regulation strategies of learning both at the level of study programs (bachelor and master), but also at the level of the type of specialization (technical sciences and social sciences). We have not registered significant differences between the groups of students as regards academic engagement towards the analysed criteria. Academic engagement is explained through the variation of the learning regulation strategies. New direction of research can be followed by identifying the weight of the learning regulation strategies types in explaining students’ academic engagement. Information would be valuable not only through the validation of some explanatory models but mainly through developing didactic strategies teachers can use in the educational act. These should involve the mechanisms which can mobilize student’s resources in order to approach academic tasks with implication and engagement, in order to create a prolific learning environment, interactive and exploring which would contribute not only to obtaining academic success but also to reaching well-being through the learning activity.

Acknowledgments

The authors would like to thank all the students who have participated in this research.

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