Knowledge, Attitude, Barriers, Motivation, and Adaption of Blended Learning · 2020. 9. 17. ·...

SMCC Teacher Education Journal

178

Knowledge, Attitude, Barriers, Motivation, and Adaption of Blended Learning

JASMINE ROSE R. FIELhttps://orcid.org/0000-0003-1456-1741

[email protected] de Cagayan University

School of Graduate Studies, Cagayan de Oro City, Philippines

Gunning Fog Index: 13.86 • Originality 99% • Grammar Check: 99%Flesch Reading Ease: 37.18 • Plagiarism:

ABSTRACT

Educational Institutions worldwide are transitioning to blended learning where technology is used and supplement traditional face-to-face instruction. This study investigated the knowledge, attitude, barrier, motivation, and adaption of blended learning in one of the uprising HEI in Mindanao, Saint Michael College of Caraga. The study was conducted to 150 faculty, both full-time and part-time in basic education and tertiary level. A descriptive correlational and causal design utilized the data in describing the relationship among variables. The research found out that the majority have less experience in blended learning. The results also showed that blended learning helps students conveniently though they lack the availability of computers. Subsequently, making the knowledge, attitude, and motivation the most predicted reason for teachers’ application. In lieu of this, institutional administrator, especially the human resource office, is highly recommended to take appropriate interventions to sustain the engagement of the faculty toward blended learning. Thus, continuous proceedings of how well-blended learning strategies are accepted and adapted in multicultural settings are significant.

SMCC Teacher Education JournalISSN Print: 2008- 0598 • ISSN Online: 2008-0601

Volume 2 • June 2020DOI:

Peer Reviewed Journal

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KEYWORDS

Blended learning, knowledge, attitude, barrier, motivation, adaption, descriptive-correlational, Philippines

INTRODUCTION

Blended learning is a twenty-first-century vocabulary and is overlooked among educators. Albeit its significance, lots of institutions, both private and government sectors, took the emergence of the application of technology with skepticism. Regardless of any hindrance, the advent of more advanced teaching strategies with the aid of computers is on (Barrera, Jaminal, & Arcilla, 2020). Universities worldwide are transitioning to blended learning, where technology enhances and supplements traditional face-to-face instruction. Investigation of how well-blended learning strategies are accepted and adopted in multicultural settings is needed to facilitate this transition (Moukali, 2012). The use of blended learning is expanding globally (Vaughn, 2007).

On the other hand, an overwhelming embrace of technology-savvy teaching is not that easy. Wilson (2001) revealed that faculty members were willing to use the technology but need more institutional support. Instructors need to prepare for both synchronous and asynchronous events. When such a synchronous event yields information about learners, integration means that this information is available to subsequent learning activities, whether performed inside or outside class (Howard, Remenyi, & Pap, 2006).

As a part of revolutionary information occurrences, several educational programs across disciplines in global communities are infusing blended learning as another educational tool into delivering instructional services (Hilliard, 2015; Moukali, 2012). Bonk & Graham (2006); Lim & Morris (2000) concluded in a survey of Higher Education that participants expected a dramatic rise in the use of blended learning approach in the coming years, and affirmed by Arabasz & Baker (2003) revealing that 80 percent of all higher educating institution offer blended learning courses. For the Philippines, the internet opportunities and investing Filipino in using ICT as a way of life are some of the thrusts of 2011 Philippine Digital Strategies of Commission in Information and Communication Technology. Thus, educators should take more steps towards their teaching skills to keep up with the current educational atmosphere (Moukali, 2012).

Albrecht (2006) reports high students’ satisfaction with blended learning, and others have reported faculty satisfaction (Vaughan & Garrison, 2006). This idea is confirmed by Marquis (2004) in a survey that found that 94% of lecturers believed that blended learning “is more effective than classroom-based teaching alone.” The contention is also consistent by Bourne & Seaman (2005); Ayala (2009), who found that the primary interest in blended learning is to benefit the educational process. Graham (2006)


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reported that blended learning is perceived as a means to combine the best of face-to-face and technology-mediated instruction.

Garrison & Vaughan (2008) stated that most administrators, faculty, and students in higher education believe that there has to be a change in how we design educational experiences. We need to preserve the educational values that have been developed over a different period while taking into account the essence of integrating technology into the system. Furthermore, Redoblo (2015) of Negros Occidental saw and experienced the demand through education in the 21st century. Blended learning is considered as the stepping stone for the future that reminds the faculty to look at learning challenges from many directions. Today is the outcome for private institutions to maximize their resources and accommodate the learning needs of the students.

The value of this study fabricated on the idea that the teacher’s adaptability towards this implemmentation influenced their attitude, knowledge, barrier, and motivation (Moukali, 2012). The perceived level of technology utilization in handling classroom discussions in a private school in Agusan del Norte has not been assessed and analyzed in this aspect. With this in mind, the aim of this research to study the level of the knowledge, attitude, barrier, and motivation of Blended learning in a private institution. With many authors offering insights regarding the effect of the technology adaptation in Luzon areas, little was mentioned in Mindanao and what technology might bring to the attitude of our dear teachers, the worth of this study lies on getting first-hand evidence on the level of knowledge, attitude, barriers, and motivation of Blended learning in a private institution teachers. Nonetheless, the worth as teachers lies in finding ways and means to alleviate whatever scenario our classes are in so that, as every time our learners come into class, as meaningful learning can be achieved (Tadlip, 2019).

FRAMEWORK

This study anchored the following theories: Roger’s (1962) Theory of Diffusion of Innovations; Dan’s (1989) Technology Acceptance Model (TAM); Fishbein & Ajzer’s (1975) Theory of Reason Action; Lev Vygotsky’s Cultural Historical Activity Theory (1962); Learning Theories and other related theories relevant to this study. The following is an explanation for all of the theories and models used in this study.

Adaption of innovation is significant in this study because numerous investigations have revealed that this is a sturdy component for blended learning applications. The term blended learning has developed over time through the efforts of several theorists and educational researches. Rogers (2003) stated that many innovations required a lengthy period of many years from the time when they become available to the time when they are widely adopted, which led to the theory for the adaption of innovations and organizations known as the Diffusion of Innovations. Diffusion is the process by which an innovation is communicated through specific channels over time among the


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members of a social system (Rogers, 2003). The four main elements of diffusion theory are innovation, communication channels, time, and the social system.

The Innovation-Decision ProcessThe innovation-decision process is the process through which an individual or other

decision-making unit passes from first knowledge of an innovation to the formation of an attitude toward the innovation, to a decision to adopt or reject, to implementation and use of the new idea, and confirmation of this decision. The innovation-decision process includes five main steps which are: (1) Knowledge, (2) Persuasion, (3) Decision, (4) Implementation, and (5) Confirmation, Rogers (2003).

The knowledge occurs will become an individual or other decisions unit is exposed to an innovation’s existence and gains an understanding of how it functions. However, Persuasion occurs when an individual or other decision making unit forms a favorable or unfavorable attitude toward innovation. Whether the individual gave a specified reinforcement such as exposure to technology materials and devices. Then, the decision takes place when an individual or other decision-making unit engages in activities that lead to a choice to adopt or reject the innovation. Also, the implementation occurs when an individual or other decision-making unit puts on a new idea into use. Finally, the confirmation takes place when an individual seeks reinforcement of an innovation-decision already made, but he or she may reverse this previous decision if exposed to conflicting messages about the innovation (Rogers, 2003)

The series of interactional patterns that occur among teachers, students, and computers present in a blended learning class manifest the relevance of Roger’s Theory of Diffusion of Innovation. Each participant in the blended learning process has a different perception and attitude towards innovation. Thus, this difference will stand as a benchmark on how to magnify the role of innovation to both teachers and students. Understanding the nature of the adaption of innovation will help this investigation identify the target population that may help or hinder the adaption process. Several studies also showed the vital application of innovation theory in applied linguistics and computer-assisted language learning (Grgurovic, 2010).

Technology Acceptance Model (TAM)The technology acceptance model (TAM) was first created by Davis (1989) based on

the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975, cited in Masrom, 2007). The TRA, as Masrom (2007), stated that behavioral intention drives the individual behavior where the behavioral intention is a function of an individual’s attitude toward the behavior and subjective norms surrounding the performance of the behavior. In other words, TRA states that one’s behavior and the intent to behave is a function of one’s attitude toward the behavior and their perceptions about behavior (Masrom, 2007).


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On the other hand, Rao (2002) stated that to understand the user’s behavior towards innovation, one must learn the technology adaption process. The technology acceptance model (TAM) consists of two beliefs, perceived utilities, and perceived ease of application, which determine attitudes to adopt new technology (Rao, 2002). The TAM proposes two specific beliefs, perceived ease of use (PEOU) and perceived usefulness (PU), that determine one’s behavioral intention to use a technology (Wahid, 2007).

.Perceived ease of consideration is to influence perceived usefulness. Perceived usefulness refers to the degree to which the user believes that using the technology will improve user work performance, while perceived ease of use refers to how effortless the user perceives using the technology (Masrom, 2007).

.TAM has been applied in several studies to test the acceptance of new technology presented to users such as email, web browsers, websites, and e-learning. For this study, the researcher will apply TAM to test the acceptance of adopting blended learning at Saint Michael College of Caraga

.Dan’s Technology Acceptance Model and Fishbein Aizer’s Theory of Reasoned Action elaborate the idea that the more knowledge a person has on how to manipulate a particular technology, the more desire kindle in using it. The utilization of these postulates the fact that the individual’s behavior towards technology determines his intention to perform the behavior, and in like manner, his intention adjudicates his attitude toward the behavior and his subjective norm. It concluded some studies that the attitude and subjective norms have a lateral effect on a person’s behavioral intent and adaption of a new system (Siegel et al., 2008).

.TAM and Theory of Reasoned Action have been widely used in many pieces of research from disparate disciplines in order to objectively investigate beliefs and attitudes of different stakeholder groups (Katharaki et al., 2009). These help to understand the role of specific factors and have attracted significant regards in e-learning investigations and studies (Ahuja & Thatcher, 2005). The model, on the other hand, could be extended to enhance its effectiveness better (Venkatesh & Davis 1996).

Cultural-Historical Activity Theory (CHAT).The activity system was designed and developed by several theorists through

different periods. According to Tomberg (2013), Activity theory draws inspiration from the work of the Russian semiotician and psychologists Lev Semenovich Vygotsky (1962), who posted the unity of perception, speech, and action. Kaptelinin & Nardi (2006) stated that activity theory was introduced to an international audience in the late 1970s and 1980s.

.Vygotsky also emphasized the centrality of mediating devices, such as language and other symbols or tools, in the development of mind and thought. ALexei N. Leont’ev(1981) created a formal structure for operationalizing the activity system as a sophisticated, multilayered unit of analysis. According to Engetrom (1999), LEont’ev’s (1978, 1981) created a great three-level scheme of activity, action, operation and


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correspondingly, motive, goal, and instrumental conditions. As indicated by Engestrom’s (1999) model, an activity system consists of people. Artifacts, an object or motive, socio-cultural rules, and roles (Kaptelinin & Nardi, 2006).

According to Yamagata-Lynch (2010), activity theory is a methodology that spawned from Cultural-Historical Activity (CHAT) that can be valuable for qualitative researchers and practitioners who investigate issues related to real-world complex learning environments. This analysis method is designed to enhance understanding of human activity situated in a collective context and, graphically represented the series of triangle diagrams (Engestrom 1987; Kaptelinin 2005, cited in Yamagata-Lynch, 2010).

Robertson (2007) stated that the activity is seen as dynamic, contextually bound, and the basic unit of analysis. Activities are distinguished from one another by the tangible or intangible objects achieved. If the object changes, then so do the activity. Tools (artifacts) mediate between the subject and the object. These tools (artifacts) such as physical tools, language, and symbols created and transformed in the course of an activity. Furthermore, Yamagata-Lynch (2010) indicated some benefits of using the activity system. This method can guide researchers and practitioners in their design, implementation, analysis, and development of conclusions in a research study or program evaluation. It supports a systematic and systemic approach to understanding human activities and interactions in complex real-world environments..It also can help researchers and practitioners understand individual activities, and the context affects one another. Lastly, it can help document the historical relationships among multiple activities by identifying how the results from a past activity affect activities.

.Yamagata-Lynch (2010) summarized the elements of the activity system, which was developed by Engestrom to the following description:

.In this model, the Subject is the individual or group of individuals involved in the activity. The tool includes social others and artifacts that can act as resources for the subject in the activity. The object is the goal or motive of the activity. The rules are any formal or informal regulations that, in varying degrees, can affect how the activity takes place. The community of labor refers to how the tasks conveyed among the community. The outcome of an activity system is the result of the activity.

Activity theory GenerationsRobertson (2007) described the three activity theory generations in detail. This

explanation indicated to the level that each generation represents the First generation: represents activity at the individual level. The relationship between the subject and object mediated through tools. When the object transformed, the outcome is achieved; Second generation: which shows activity at a collective level. Rules may be explicit and implicit. Division of labor refers to the explicit and implicit organization of the community; The Third generation represents networked activity and incorporates the idea of boundary objects. That is, as Edward (2005 cited in Robertson, 2007) objects that operate at the interface of many contexts. Where two (or more) activity systems come into contact,


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there may be contradictions and tensions through which expansive learning is possible through questioning, analysis, reflection and debate (Russell, 2002)

On the other hand, Lev Vygotsky Cultural Historical Activity Theory acclaimed as the “best-kept secret of academia” (Engestrom, 1993, pp 64, as cited in Roth & Lee, 2007). The classical mediational triangle of the theory is the same as the first-generation Activity Theory. The utilization of the theory opens the realization that the higher mental functioning of humans is interposed by technical and psychological aspects, as determined by the apex of the triangle. Consequently, lower elementary processes are subconsciously acted upon directly on the object as indicated in the figure.

Vygotsky’s Activity Theory represented a shift away from a perception of human intellectual operation as residing in the atomic individual – as had been the widely accepted psychological view at that time – and towards a belief that emphasizes the distributive nature of consciousness.

Learning Theories.Behaviorism, cognitivism, and constructivism are parts of the traditional

learning paradigms as benchmarks that measured learning procedures. The academic environment needs to transform education from a teacher-centered way of teaching to a constructivist model by endowing educators and learners with the integration of ICTs into all areas of the teaching and learning process. The change from behaviorism to the more constructivist approach of learning makes how one understands knowledge creation, where cooperation is magnified rather than acquisition alone (Engestrom & Sannino, 2010). However, the influence of technological innovations on teaching and learning should have careful consideration. Manifestations of behaviorism, cognitivism, and constructivism is at a time when teaching and learning were not entrenched upon by technology. These theories have not lost its significance; they need to be applied uniquely to connect the current teaching and learning environment. The learning environment is composed of factors of behavioral, cognitive, social, and constructivist learning theories. The learning paradigm in the technology age is networked, socialized and technological. The central point of connection is that learning in the learning theory in this digital environment takes place across networked communities and information technologies (Dias et al., 2014).

Learning theories can direct educational structure and facilitation as well as teachers’ preparation in the purpose and function of blended learning facilitation. Furthermore, subsisting learning theories will assist teachers in understanding how learners’ knowledge acquisition and development take place. With this knowledge, facilitators will knowledgeable with ideas on how to design and facilitate blended learning intervention programs (Dias et al., 2014).

The Learning Theory will help unveil the concept that as a person grows and exposes to ample of experiences and knowledge, its behavior and intellectual capacity are also improved. Thus, it will concretize the studies of John B. Watson in the early


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20th century, B.F. Skinner, Ivan Pavlov, and others in Behaviorism, Noam Chomsky in Cognitivism, and John Dewey, Jean Piaget, Jerome Bruner, Lev Vygotsky, others in Constructivism. Scrutinized the demographic profile of the participants as factors in this study have an essential role in the effectiveness of implementing blended learning classes (Tohidi & Jabbari, 2012).

Given the conceptions of different scholars, experts, and practitioners in the field of education regarding the dynamics of what makes students perform academically and what makes them stay and finish, Figure 1, summarily explains the intent of this proposed study.

.Figure 1 shows the schematic presentation showing the interplay of variables in the study. The faculty’s level of knowledge, attitude, barrier, and motivation towards the adaption of Blended Learning by their age, gender, and teaching experience is influential. Thus, this study captures the necessity to account for the levels K, A, B, M of the faculty of Saint Michael College of Caraga in the adaption of the blended learning approach.

OBJECTIVE OF THE STUDY

This study determined the Knowledge, Attitude, Barriers, Motivation, and Adaption of Blended Learning of Saint Michael College of Caraga Faculty.

METHODOLOGY

Research Design A descriptive-correlational design was utilized in this study. Inclusion with

this method is a study in which the researcher is primarily interested in describing relationships among variables and seeking to establish a causal connection.

Research Setting Saint Michael College of Caraga was selected as the location for conducting this

study. The school is situated in the heart of the town of Nasipit, Agusan del Norte along the Atupan St. and is beside the town parish, Saint Michael Parish Church. Missionarii Sacratissimi Cordis (MSC) fathers founded the school in 1948. It offers complete education from elementary up to college. There are a variety of educational programs offered in Saint Michael College of Caraga for both male and female students.

The researcher purposefully chose this institution to help to the researcher’s Alma Mater, and the population of the prospected participants is good enough to acquire quality information for the benefit of the study.

Participants and Sampling Procedure The participants of this study were the 150 faculty both part-time and fulltime

basic education teachers and college instructors from Saint Michael College of Caraga,


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Nasipit, Agusan del Norte. The research used the purposive sampling method in selecting its participants.

Table 1. Distribution of Participants of the Study

Participants Full-time Part-time Total

Basic Education 51 13 64

College 50 36 86

Total 101 49 150

Research Instruments The survey structure employed was designed after a few existing investigations have

been utilized in some related studies. In this study, the researcher used 1 set questionnaire to gather data.Survey Questionnaire. One source of items was a study conducted in 2008 by

Brooks, and titled “An Analysis of Factors that Affect Faculty Attitudes toward a Blended Learning Environment.” For the researcher to use some items from the Brooks questionnaire, a permission request was sent to the original researcher and creator of the instrument, Lori Brooks, who provided the researcher with permission to use items from the questionnaire survey.

Brooks’ questionnaire was a modified version of a research instrument developed by Wilson in 2002 for his Ph.D. dissertation. Brooks (2009) emphasized, “Wilson’s survey instrument was validated his dissertation by a review of the literature as well as an expert panel “who were familiar with distance education policies and procedures.” The name of Wilson’s survey instrument was Faculty Attitudes towards Technology-Based Distance Education.

There were two types of questions on the survey of this study. Likert-type scale responses were used in most items to rate the extent to which participants agree or disagree with each item statement. The questionnaire packet took approximately 20 minutes to complete. The survey consisted of 64 questions split into six separate sections, which was done because DeYellis (2003) stated that shorter scales are useful because they place less of a burden on participants.

Data Gathering Procedure.The researcher sent a permission letter to conduct the study to the Dean of the

School of Graduate Studies and Vice President for Research, Publication, and Extension of Liceo de Cagayan University. Another letter was addressed to the Vice-President for Academic Affairs of Saint Michael College of Caraga for approval to conduct the study. Then, the researcher conducted pre-orientation relating to the purpose, process, and benefits of the study. Subsequently, consent on questionnaires were given to the full-time and part-time faculty of Saint Michael College of Caraga. After a week,


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the questionnaires were retrieved, data were sent to the statistician for analysis and interpretation of the data.

To ensure quality work, the manuscript had undergone content validity from experts in the field. It followed the analytical procedure of the research ethics and received its approval from the Research Ethics Review Committee; thus, the manner of gathering the data was done in a proper course of action. All necessary procedures and requirements were done to finally present the data to the adviser and research panel for approval for binding.

Statistical Techniques Frequency, Percentage was utilized to determine the impact of the demographic

profiles of the participants. Weighted Mean was also used in gathering the level of the participants’ knowledge, attitude, barriers, motivation, and adaption of Blended Learning. Pearson Product Correlation was used to analyze the significant relationship between the adaption of blended learning and knowledge, attitude, barriers, and motivation. Lastly, the multiple regression analysis was used to determine the significant variable that best predicts the adaption of blended learning of the faculty members from Saint Michael College of Caraga.

RESULTS AND DISCUSSION

Table 2. Knowledge with Blended Learning

Item Mean VerbalDescription

Microsoft Office Word 4.50 Very High

Microsoft Office PowerPoint 4.39 High

Web search engines (e.g., Google, Yahoo, etc.) 4.35 High

Learning Management System (e.g., Blackboard, Moodle, Jusur, etc.) 4.22 High

E-mail programs (e.g., Microsoft Office Outlook, Gmail, Hotmail, Yahoo, etc.) 4.19 High

Digital Video Camera 3.93 High

Scanner device 3.88 High

Web page editors (e.g. HTML editor, Dreamweaver, etc.) 3.09 Average

Electronic bulletin boards 3.04 Average

SmartBoard 2.83 Average

OVERALL MEAN 3.84 High.Table 2 shows the knowledge of the participants with blended learning. The statistics

reveal that most faculty are into Microsoft Office Word with 4.50 mean percentage


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with very high verbal description, Microsoft Office PowerPoint with 4.39, Web search engines having 4.35, Learning Management System with 4.22, Email programs at 4.19 mean percentage, digital video camera at 3.93, and scanner device with 3.88, all of which have a verbal description of high. These followed by web page editors, electronic bulletin boards, and smart boards with a mean percentage of 3.09, 3.04, and 2.83, respectively.

.With the increase in online instruction and blended learning came the need for quality professional development programs that foster learning and encourage real change in the classroom, including the focus on developing best practices. Mastering the Blend is designed as a professional development opportunity to enhance teachers’ face-to-face classroom instruction. (Rice, 2009).

Table 3. Attitudes toward Blended Learning


Blended learning helps students to learn in a convenient way. 4.29 High

Blended learning approach supports collaborative learning. 4.28 High

Blended learning considers the differences in learning styles of students. 4.27 High

Blended learning increases student achievement. 4.26 High

I am interested in implementing blended learning for my course. 4.25 High

Administration believe that blended learning is Important 4.21 High

I prefer teaching a class through blended learning. 4.17 High

Our campus should significantly increase the number of blended offerings. 4.17 High

Blended learning enables administrators to manage the education on my campus. 4.15 High

Technological Infrastructure on my campus is ready to implement blended learning. 4.00 High

OVERALL MEAN 4.21 High

Table 3 shows the attitude of the participants towards blended learning. Blended learning helps students learn at a convenient way rate of 4.29 and received the highest mean percentage. While the rationales that stipulate the blended learning approach supports collaborative learning got 4.28, and 4.27 for blended learning considers the differences in learning styles of students. There is a 4.26 mean percentage who confirms that blended learning increases student achievement. A 4. 25 mean percentage of the faculty claims that they are interested in implementing blended learning for their course and agrees that blended learning is significant in the administration with a 4.21 score.


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The result showed that the faculty who suggested that offering and teaching blended learning in the campus rate the same mean percentage of 4.17. 4.15 and 4.00 rates for faculty who believed that it could help administrators manage education on the campus, and the technological infrastructure of the institution is ready to implement blended learning. This result shows that most of the faculty percieved that blended learning makes instruction conducive to learning since it caters convenience in learning to the students. It provides ways where students can learn enjoyably.

..School administrators and faculty’s attitude toward blended learning has an enormous impact on each other, whether positively or in another way. Brooks (2003) explains that the course administrator’s attitude towards course designers can either support or hinder implementation’s success. On the other hand, the attitude of the course designer for an online learning environment can be parallel to the attitude of the administrators. Thus, if both do not believe in the value of blended learning, the mission to successfully implement the course will not be realized.

Table 4. Barriers that Affect the Adaption of Blended Learning


My students don’t have the internet at home. 3.13 Average

My students don’t have computers at home. 3.12 Average

Blended learning increases my workload. 2.75 Average

My colleagues don’t like blended learning. 2.75 Average

My students don’t have enough technology experience. 2.74 Average

I don’t have enough technical support. 2.73 Average

Blended learning reduces my contact with students. 2.73 Average

I don’t have enough technology experience. 2.50 Average

The Internet is not available on my campus. 2.38 Low

The computer is not available on my campus. 2.19 Low

OVERALL MEAN 2.70 Average

.Table 4 discusses the barriers that affect the adoption of blended learning. The rationale that predicts the highest reason for the rejection of blended learning is that many students do not have internet access at home. It scores 3.13 with an average verbal description. A mean percentage of 3.12 from the faculty express that most of their students do not have computers at home. Blended learning increases workload and is disliked by their colleagues to have the same level of percentage of 2.75. A 2.74 score shows that students do not have enough technology experience. The faculty’s inadequate technical support and belief that blended learning reduces teacher’s contact with its students both received a 2.73 mean rate. Internet and computers are not available on the campus got 2.38 and 2.19 mean percentage, which both have a low verbal description.


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Therefore, through this table, the researcher concludes that the most common barrier that affects blended learning is the unavailability of computers and the internet in their students’ homes.

.Many schools today, although, are trying to cope up with technological changes, are still suffering from a lack of advanced technologies, which could be helpful in the implementation of instruction. What adds to the dilemma is the lack of opportunities for the students to use those technologies at home. Thus, despite its desire to adopt this kind of learning, the adaption is hindered and limited. It is then the prerogative of the school to cater to this end to better support this evolution of learning where technology plays a significant role in the implementation (Rose & Ray, 2011).

Table 5. Motivation of Blended Learning


Blended learning utilizes modern technology for instructors’ educational tools.

4.21 High

Blended learning improves students’ and instructors’ technological skills.

4.19 High

Blended learning helps instructors engage students in active learning.

4.16 High

Blended learning gives students more media resources (e.g., audios, videos, etc.).

4.12 High

Blended learning accommodates different types of students. 4.11 High

Blended learning provides better communication for students and instructors.

4.06 High

Blended learning gives students access to class materials at any time.

4.05 High

Blended learning facilities the tracking of student performance. 4.04 High

Blended learning makes better use of class time. 4.03 High

Blended learning helps in evaluating student achievement. 4.03 High


Table 5 shows the motivation for blended learning. The blended learning utilizes modern technology for instructors’ educational tool, improves students and instructors’ technological skills, helps instructors engage students in active learning, gives students more media resources (e.g., audios and videos), and accommodates different types of students have a mean percentage of 4.21, 4.19, 4.16, 4.12, and 4.11 respectively. Blended learning provides better communication for students and instructors has 4.06, and a score of 4.05 for blended learning gives students access to class materials at any time. Then the blended learning facilities the tracking of student performance with


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4.04, and the same score of 4.03 goes to blended learning makes better use of class time, and blended learning helps in evaluating student achievement.

Table 6. Adaption of Blended Learning

Item Mean Verbal Description

1. I feel confident that, as time goes by, my ability to address my students’ technology needs will continue to improve. 4.17 High

2. I feel confident about using technology resources (such as spreadsheets, electronic portfolios, etc.) to collect and analyze data from student tests and products to improve instructional practices

4.15 High

3. I feel confident that I will be comfortable using blended learning in my teaching 4.10 High

4. I feel confident I can regularly incorporate technology into instruction based on curriculum standards 4.09 High

5. I feel confident that I have the skills necessary to use the computer for instruction. 4.08 High

6. I feel confident that I can successfully teach relevant subject content with appropriate use of technology. 4.07 High

7. I feel confident I can be responsive to students’ needs during computer use. 4.07 High

8. I feel confident that I understand computer capabilities well enough to maximize them in my classroom. 4.05 High

9. I feel confident that I can effectively monitor students‘ computer use for project development in my classroom 4.03 High

10. I feel confident that I can use correct computer terminology when directing student 3.99 High

11. I feel confident in computer use. 3.99 High

12. I feel confident that I can help students when they have difficulty with the computer 3.99 High

13. I feel confident that I can mentor students with inappropriate uses of technology in blended learning. 3.98 High

14. I feel confident in my ability to evaluate the software for teaching and learning 3.92 High

15. I feel confident in my ability to evaluate the software for teaching and learning. 3.91 High

16. In Blended learning, It is easy to stick to my aims and accomplish my goals. 3.90 High

17. I find it easy to convert the computer-based tests into my class discussion. 3.79 High

18. I have enough equipment and support to do online assessments of my students as a normal practice in teaching and learning 3.66 High

19. I receive technical support for online testing is available for the schools. 3.62 High

20. I engage with outside organizations to get computers, tablets, or other mobile computing equipment. 3.58 High



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Table 6 reveals that there is a 4.17 mean percentage which expressed that the participants are beginning to be confident in addressing the technological needs of the students. This rationale receives the highest score among the other variables in the table. While, teachers’ engagement with outside organizations to get computers, tablets or other mobile computing equipment gets the lowest with 3.58 mean percentage. Although, each of them has a verbal description of high.

The evolution of technology brought new kinds of learners. Changes in behaviors and attitudes towards learning are dramatically affected by this change. Teachers of different fields realized that to be able to cope up with this gigantic shift in education, the adaption of new kinds of teaching should be adopted. The introduction of blended learning gives way to unlock the difficulty experienced by many classroom teachers. More and more teachers adopt this technological innovation to enhance learning among students (Weaver & Qi, 2005).

Table 7. Testing the Significant Relationship

Variable 1 Variable 2 Correlation Coefficienta P-valueb Remarksc

Adaption of Blended Learning

Knowledge 0.438 0.000 Significant; Moderate

Attitude 0.344 0.000 Significant; Moderate

Barriers -0.055 0.504 Not Significant

Motivation 0.540 0.000 Significant; Moderate

A Pearson Correlation was performed to calculate the relationship of the teachers’ level of knowledge, attitude, barrier, and motivation towards the adaption of blended learning. There was a positive correlation between the variables knowledge (r= 0.438, p= 0.000), attitude (r= 0.344, p= 0.000), motivation (r= 0.540, p= 0.000), and negative correlation on barriers that affect the adaption of blended learning (r= -0.055, p= 0.504).

Furthermore, Table 7 shows the relationship between the adaption of blended learning and motivation is highly significant (r=0.540). Moreover, the relationship is direct and moderate. That is, as the level of motivation increases, the level of teacher’s adaption of blended learning also increases. These results are also evident to knowledge with blended learning, attitude toward blended learning, and motivation of blended learning.

Therefore, the level of knowledge, attitude, and motivation are statistically significant to the teachers’ adaption of blended learning. The relationship of these variables (knowledge, attitude, and motivation) towards the adaption of blended learning is direct, moderate, and highly significant at α=0.01 level.


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CONCLUSIONS

Teacher’s motivation manifests a significant impact on the application of blended learning. It claims the most predicted reason for teachers’ adaption of blended learning. The more motivated the teacher is, the more he is apt to using the said medium. Motivation is the result and manner of an organization where people are forced to do a specific action or behavior. Motivation is then followed by the instructor’s knowledge about the tool. People tend to push things away that are not familiar or not well introduced to them. Knowledge of technology and how to use this makes a person confident in utilizing it as part of instruction. On the verge of this study, it reveals that most faculty are not well familiar with frontier technologies, thus, limiting their knowledge in employing those in their instruction. Due to the innovation of technologies, the demand for introduction to the teachers is dramatically challenged. Without the introduction of these materials may lead numbers of teachers to lag. Many institutions are not making full use of technology as part of their comprehensive school reform. Some reasons for this limitation are the competing priorities, lack of reliable information, resources, and expertise on those mediums.

One more variable that has a significant relationship to the adaption of blended learning is the faculty’s attitude toward blended learning. Many teachers understand the role of this new type of learning as an essential tool in this modern era. The application of this kind of learning provides a new dimension to the teaching and learning process. The reult opens the door to a vast pool of knowledge, endowed to the learners, and lead them to innumerable opportunities to embrace learning.

RECOMMENDATIONS

From the drawn conclusions, the following measures are recommended:1. To the School Heads or Top Administrators. Recommending that the top

administrators via the Human Resource Office should take appropriate interventions to sustain the needs of the faculty regarding the adaption of blended learning in their instructions. Since the faculty’s knowledge is limited to basic computer skills, it is, therefore, necessary to supply extensive education and technology training in the utilization of the new technologies. Continuous proceeding training should magnify to support arising issues and inquiries. Moreover, it is essential to encourage engagement by actively informing all the faculties on any discussions, topics, questions, and comments about new technologies available (Sayed & Baker, 2014). Without proper information and implementation, engagement to these materials will fall short and will lead to disentanglement.

2. To Parents/Guardian. Since the foremost barrier is the student’s lack of computer at home, it is impeccable to provide and prioritize the maximal usage of technology in an educational term. Thus, making our Gen X learners adept into learning.


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3. To Future Researchers. It is recommended for future researchers to go in-depth learning about this study to be able to compare the present findings from their collected results. More methodological work should consider to robustly identify the impact and outcomes of blended learning in education. It would also be beneficial to capture qualitative experiences and perspectives of other researchers who met both negative and positive experiences (Evans et al., 2014).

LITERATURE CITED

Ahuja, M. K., & Thatcher, J. B. (2005). Moving beyond intentions and toward the theory of trying: effects of work environment and gender on post-adoption information technology use. MIS quarterly, 29(3), 427-459. Retrieved on April 15, 2020 from https://bit.ly/2EuxuVb

Albrecht, K. (2006). Social intelligence: The new science of success. John Wiley & Sons. Retrieved on April 10, 2020 from https://bit.ly/2YyS0uO

Allen, I. E., & Seaman, J. (2004). Entering the Mainstream: The Quality and Extent of Online Education in the United States, 2003 and 2004. Sloan Consortium. PO Box 1238, Newburyport, MA 01950. Retrieved on April 15, 2020 from https://bit.ly/32EZpub

Arabasz, P., & Baker, M. B. (2003). Evolving campus support models for e-learning courses. Educause Center for Applied Research Bulletin, 1(9), 9. Retrieved on April 10, 2020 from https://bit.ly/3gxYqka

Ayala, J. S. (2009). Blended learning as a new approach to social work education. Journal of Social Work Education, 45(2), 277-288. Retrieved on April 10, 2020 from https://bit.ly/3jeeSYx

Barrera, K., Jaminal B., & Arcilla, F. (2020). Readiness for Flexible Learning amidst COVID 19 Pandemic of Saint Michael College of Caraga, Philippines.

Bonk, C. J., & Graham, C. R. (2012). The handbook of blended learning: Global perspectives, local designs. John Wiley & Sons. Retrieved on April 10, 2020 from https://bit.ly/3aTTJQD

Brooks, L. (2003). How the attitudes of instructors, students, course administrators, and course designers affects the quality of an online learning environment. Online Journal of Distance Learning Administration, 6(4). Retrieved on April 15, 2020 from https://bit.ly/34BkRma


195

Brooks, L. (2009). An analysis of factors that affect faculty attitudes toward a blended learning environment (Doctoral dissertation, TUI University). Retrieved on April 15, 2020 from https://bit.ly/2YBhIyX

Dias, S. B., Diniz, J. A., & Hadjileontiadis, L. J. (2013). Towards an intelligent learning management system under blended learning: Trends, profiles and modeling perspectives (Vol. 59). Springer Science & Business Media. Retrieved on April 15, 2020 from https://bit.ly/3aV54ja

Edward, K. (2005). Resilience: When coping Emotionally Intelliegent. Sage journals: American Psychiatric Nurses Association. Retrieved from https://doi.org/10.1177/1078.390305277526.

Engeström, Y. (1999). Activity theory and individual and social transformation. Perspectives on activity theory, 19(38), 19-30. Rerieved on April 15, 2020 from https://bit.ly/3jcJREq

Engeström, Y., & Sannino, A. (2010). Studies of expansive learning: Foundations, findings and future challenges. Educational research review, 5(1), 1-24. Retrieevd on April 10, 2020 from https://bit.ly/34z7BhO

Fishbein, M. leek Ajzen (1975). Belief, attitude, intention and behavior: An introduction to theory and research, 181-202. Retrieved on April 15, 2020 from https://bit.ly/3jfShLf

Garrison, D. R., & Vaughan, N. D. (2008). Blended learning in higher education: Framework, principles, and guidelines. John Wiley & Sons. Retrieved on April 15, 2020 from https://bit.ly/3gupjp5

Graham, C. R. (2006). Blended learning systems. The handbook of blended learning: Global perspectives, local designs, 3-21. Retrieved on April 16, 2020 from https://bit.ly/34Fdx90

Grgurovic, M. (2010). Technology-enhanced blended language learning in an ESL class: A description of a model and an application of the Diffusion of Innovations theory. Retrieved on April 16, 2020 from https://bit.ly/2QrTnHv

Howard, L., Remenyi, Z., & Pap, G. (2006, July). Adaptive blended learning environments. In International Conference on Engineering Education (pp. 23-28). Retrieved on April 16, 2020 from https://bit.ly/3gvqVii


196

Kaptelinin, V., & Nardi, B. A. (2006). Acting with technology: Activity theory and interaction design. MIT press. Retrieved on April 16, 2020 from https://bit.ly/3jfvak1

Katharaki, M., Daskalakis, S., & Mantas, J. (2009). Towards the implementation of Web based courses in postgraduate healthcare curricula: An empirical assessment. In Proceedings of the 7th International Conference in Information & Communication Technologies in Healthcare (pp. 16-18). Retrieved on April 16, 2020 from https://bit.ly/2EC42wo

Kim, D. H., & Morris, M. L. (2009). Learner and instructional factors influencing learning outcomes within a blended learning environment. Educational Technology & Society, 12(4), 282-293. Retrieved from: http://www.ifets.info/journals/12_ 4/24.pdf.

Lim, D. H., & Morris, M. L. (2009). Learner and instructional factors influencing learning outcomes within a blended learning environment. Journal of Educational Technology & Society, 12(4), 282-293. Retrieved on April 16, 2020 from https://bit.ly/2Qt1HXe

Masrom, M. (2007). Technology acceptance model and e-learning. Technology, 21(24), 81. Retrieved on April 16, 2020 from https://bit.ly/3aVbvTs

Moukali, K. H. (2012). Factors that affect faculty attitudes toward adoption of technology-rich blended learning (Doctoral dissertation, University of Kansas). Retrieved on April 16, 2020 from https://bit.ly/2FYPibN

Rao, A. S. (2007). Technology acceptance model for complex technologies in a period of rapid catching-up. Available at SSRN 1016012. Retrieved on April 16, 2020 from https://bit.ly/2Eu1zo5

Robertson, I. (2007). E-learning practices: exploring the potential of pedagogic space, activity theory and the pedagogic device. In Learning and Socio-cultural Theory: Exploring Modern Vygotskian Perspectives International Workshop 2007 (Vol. 1, No. 1, p. 5). Retrieved on April 16, 2020 from https://bit.ly/2YACVZV

Redoblo, C. V. (2015). Blended Learning Approach: A Case Study. JPAIR Multidisciplinary Research, 22(1). Retrieved on April 16, 2020 from https://bit.ly/2Yz26fc

Rogers, E. M. (2003). Diffusion of lnnovations. In D. W. Stacks & M. B. Salwen (Eds.), An Integrated Approach to Communication Theory and Research (Vol. 65, p. 551).


197

Rose, R., & Ray, J. (2011, July). Encapsulated presentation: A new paradigm of blended learning. In The Educational Forum (Vol. 75, No. 3, pp. 228-243). Taylor & Francis Group. Retrieved on April 16, 2020 from https://bit.ly/3htmaY9

Russell, D. (2002). Looking beyond the interface: activity theory and distributed learning: Activity theory and distributed learning David R. Russell. In The RoutledgeFalmer Reader in Psychology of Education (pp. 318-335). Routledge. Retrieved on April 16, 2020 from https://bit.ly/2EDewvr

Tohidi, H., & Jabbari, M. M. (2012). The effects of motivation in education. Procedia-Social and Behavioral Sciences, 31, 820-824. Retrieved on April 16, 2020 from https://bit.ly/31stUno

Tomberg, V. L. A. D. I. M. I. R. (2013). Learning flow management and teacher control in online personal learning environments. Institute of Educational Sciences, Tallinn University. Tallinn. Retrieved on April 16, 2020 from https://bit.ly/34A57Qy

Vaughan, N. D., Cleveland-Innes, M., & Garrison, D. R. (2013). Teaching in blended learning environments: Creating and sustaining communities of inquiry. Athabasca University Press. Retrieved on April 16, 2020 from https://bit.ly/32lyyTA

Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision sciences, 27(3), 451-481. Retrieved on April 16, 2020 from https://bit.ly/3lkCFYQ

Wahid, F. (2007). Using the technology adoption model to analyze internet adoption and use among men and women in Indonesia. The Electronic Journal of Information Systems in Developing Countries, 32(1), 1-8. Retrieved on April 16, 2020 from https://bit.ly/34zfKTq

Weaver, R. R., & Qi, J. (2005). Classroom organization and participation: College students’ perceptions. The Journal of Higher Education, 76(5), 570-601. Retrieevd on April 16, 2020 from https://bit.ly/34xLM29

Wilson, C. (2001). Faculty attitudes about distance learning. Educause Quarterly, 24(2), 70-71. Retrieved on April 16, 2020 from https://bit.ly/3hwMIaN

Yamagata-Lynch, L. C. (2010). Activity systems analysis methods: Understanding complex learning environments. Springer Science & Business Media. Retrieved on April 16, 2020 from https://bit.ly/3jdBPel

Knowledge, Attitude, Barriers, Motivation, and Adaption of Blended Learning · 2020. 9. 17. ·...

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