The title of the current research project is "Factors Influencing Higher Education Students' Behavioral Intention Toward Hybrid Learning in Malaysian Private Universities". This study shed new light on the factors influencing higher education students' behavioral intention towards hybrid learning in Malaysian private universities.
INTRODUCTION
- Introduction
- Research Background
- Online Basic Learning Method
- Hybrid Learning System in Malaysian Private Higher
- Problem Statement
- Research Problem
- Research Objectives
- General Objective
- Specific Objectives
- Research Questions …
- General Research Question
- Specific Research Questions
- Hypotheses of Study …
- Significance of Study …
- Chapter Layout
- Conclusion
To examine the factors influencing the behavioral intention of higher education students towards hybrid learning in Malaysian private universities. Which factors influence the behavioral intention of higher education students towards hybrid learning in Malaysian private universities.
LITERATURE REVIEW
Introduction …
Review of Past Hybrid Learning Studies
Underlying Theories
- Technology Acceptance Model (TAM)
- Theory of Planned Behaviour (TPB)
- Social Cognitive Theory (SCT)
- Theory of Connectivity
- Social Support Theory
- Campus Class Technology Theory (CCT)
Review of Variables …
- Behavioural Intention Towards Hybrid Learning
- Perceived Usefulness of Hybrid Learning System …
- Perceived Ease of Use
- Internet Access
- Self-efficacy …
- Teacher Support …
- Campus Support …
Proposed Conceptual Framework …
Hypotheses Development
- Relationship Between Perceived Usefulness of Hybrid
- Relationship Between Internet Access and Higher Education
- Relationship Between Teacher Support and Higher Education
- Relationship Between Campus Support and Higher Education
Conclusion
METHODOLOGY
Introduction
This chapter will identify the research design, data collection methods, sampling design, instrument, construct measurement, data processing and data analysis.
Research Design
It can determine the causes of procedures and evaluate the consequences of changes in current norms ("Causal Research (Explanatory Research)," n.d.). The cause-and-effect relationship between the independent and dependent variables is determined by using the causal research in our study. The causes are the independent variables, while the effect is the dependent variable in this study.
We chose informal research because the aim of this study is to investigate the factors influencing the behavioral intention of higher education students towards hybrid learning in Malaysian private universities. We are able to recognize the cause-and-effect relationship between factors such as perceived usability of a hybrid learning system, perceived ease of use, internet access, self-reliance, teacher support, and campus support, while assessing the effect on student behavioral intent in higher education. education versus hybrid learning in Malaysian private universities.
Data Collection Method
- Primary Data
- Secondary Data
Primary data sources are usually selected and adapted to suit a particular research project (Formplus Blog, 2020). Moreover, the questions in the questionnaire were fixed-alternative questions, which helped us save time compared to open-ended questions. SPSS software was used to review all data from the questionnaire after generation.
Primary data was used in this study because this research attempts to understand the behavioral intentions of higher education students. Primary data became more specific because of the information collected and we were able to find the gaps, gaps or additional information that needed to be collected.
Sampling Design
- Target Population
- Sampling Frame and Sampling Location
- Sampling Elements
- Sampling Technique
- Sampling Size
Although these selected private universities represented only 8 of the total of 51 private universities in Malaysia, the total student population is 116,000 students as shown in Table 3.1, which is 41% of the total number of private university students in Malaysia, which is about 280,000 students . In addition, all selected private universities have the potential to better enable and effectively implement hybrid learning in the future due to increased resources and opportunities, such as easier access to funding. The selected private universities are located in 4 states of Malaysia, namely Perak, Selangor, Negeri Sembilan and Kuala Lumpur.
Therefore, higher education students who have studied in private universities will be included in completing the questionnaire. In our study, the target population was 116,000 higher education students in Malaysian private universities.
Research Instrument
- Questionnaire Survey
- Pre-test
- Pilot Study
- Data Collection
Seow Ai Na, reviewed the questionnaires before they were approved by the UTAR Scientific and Ethical Review Committee (SERC), then we made a minor change based on the feedback. A pilot study is a type of prediction test in which a small number of questionnaires are sent to ensure the accuracy, internal consistency and reliability of the questionnaires (Trakulmaykee et al., 2013). Prior to the actual research, the pilot test offers the opportunity to detect and correct any problems in the questionnaires (Dikkow, 2016).
Questionnaires were distributed to higher education students studying at MMU, UTAR, TARUMT, UCSI, INTI, Taylor's, Sunway and HELP using social media platforms such as Facebook, WhatsApp and Instagram. Some respondents did not complete the questionnaires due to lack of time, impatience and the omission of some questions.
Constructs Measurement
- Origins of Constructs
- Research Questionnaire Sections Management
- Scale of Measurement
- Nominal Scale
- Ordinal Scale
- Interval Scale
According to research by Admin (2020), a nominal scale is the primary level of a measurement scale in which numbers are used as "labels" to classify or name objects. An ordinal scale is a type of variable measurement scale used to show the order of variables rather than the differences between them (QuestionPro, 2021). The implementation of this scale is easy to remember because 'Ordinal' sounds like 'Order', which is exactly the aim of this scale.
The interval scale refers to the level of measurement in which the features that make up the variables are measured with points or numerical values and equal distances between them (Salkind, 2010). The Likert scale is commonly used in questionnaires to understand the extent to which respondents agree with the statement.
Data Processing
- Data Checking
- Data Editing
- Data Coding
- Data Transcribing
Data editing was reviewing and correcting errors to ensure that there were no errors in the data collected and that all data was consistent and complete. Data coding was the assignment of numbers to each option answered by the respondents in the questionnaire. Responses to each demographic question asked in Section A of the questionnaire were coded in Table 3.10.
While the answers to each question in section B and section C of the questionnaire asked were coded as shown in table 3.11. Finally, we checked whether the data entered into the computer were consistent with the data collected in the questionnaire to avoid missing items.
Data Analysis
- Descriptive Analysis
- Inferential Analysis
- Reliability Test
- Normality Test
- Multiple Linear Regression Analysis
The data in section A of the questionnaire can be represented using a pie chart, bar chart or histogram. The order of the data can be easily distinguished using a bar chart, while the nominal scale can be represented using a pie chart. The findings will reveal the strength or weakness of the relationship between the independent and dependent variables.
The reliability test measures the accuracy and degree of consistency of the result for the constructs (Malhotra & Peterson, 2006). The linear relationship between the explanatory (independent) and the response (dependent) variables is attempted to be represented using multiple linear regression.
Conclusion
DATA ANALYSIS AND FINDINGS
Introduction
Descriptive Analysis
- Respondent Demographic Profile
- Gender
- Age
- Ethnicity
- Religion
- University
- Level of Education
- Central Tendencies Measurement of Constructs
- Perceived Usefulness of Hybrid Learning System
- Perceived Ease of Use
- Internet Access
- Self-efficacy
- Teacher Support
- Campus Support
- Higher Education Students’ Behavioural Intention . 76
- Reliability Analysis
- Normality Test
- Multiple Linear Regression Analysis
- Level of Contribution
- The Highest Ranking of Contribution
- The Second Highest Ranking of Contribution
- The Lowest Ranking of Contribution
As shown in Table 4.7, the statement “Hybrid learning system will help me complete study tasks faster” contributes the highest mean value 4.3260 with the standard deviation of 0.74082. Meanwhile, the statement “Hybrid learning will help me increase my productivity” contributes a mean of 4.1640 with a standard deviation of 0.81390. The statement "I have easy access to the Internet" contributes the highest mean value 4.2620 with the standard deviation of 0.66199.
The statement "The teachers or lecturers on campus are competent IT users" contributes the lowest mean value (3.9560) with the standard deviation of 0.83153 as shown in Table 4.11. The statement "The campus has IT technical support that can provide me with data management advice and consulting" contributes the lowest mean value (3.8860) with the standard deviation of 0.76037.
Conclusion
DISCUSSION AND CONCLUSION
Introduction
Summary of Statistical Analyses
- Descriptive Analysis
- Central Tendency
- Reliability Test
- Normality Test
- Inferential Analysis
- Multiple Linear Regression Analysis
In the reliability test, the dependent variable, higher education students' behavioral intention to hybrid learning, showing a Cronbach's Alpha value of 0.743. This means that the six independent variables account for 44.1 percent of the variation in the dependent variable of higher education students' behavioral intention to hybrid learning. According to Table 5.5, other potential variables explained 55.9 percent (100 percent – 44.1 percent) of the dependent variable of higher education students' behavioral intention regarding hybrid learning.
0.435, with the significant contribution of six independent variables to the dependent variable accounting for 43.5 percent. Compared with other independent variables, it has a more significant impact on higher education students' behavioral intention toward hybrid learning.
Discussion on Major Findings
- Influence of Perceived Usefulness of Hybrid Learning
- Influence of Internet Access on Higher Education Students’
- Influence of Self-efficacy on Higher Education Students’
- Influence of Teacher Support on Higher Education Students’
- Influence of Campus Support on Higher Education Students’
This supported the positive influence of the perceived usefulness of the hybrid learning system and the perceived ease of use on higher education students' behavioral intention towards hybrid learning in Malaysian private universities. This proved that Internet access is predominant in higher education students' behavioral intention towards hybrid learning. This supported the negative influence of self-efficacy on higher education students' behavioral intention towards hybrid learning in Malaysian private universities.
This showed that teachers' support is dominant in the intention of higher education students' behavior towards hybrid learning. Therefore, it can be concluded that campus support is not important for the purpose of bringing higher education students towards hybrid learning in Malaysian private universities.
Implications of the Study
- Theoretical Implication
- Practical Implication
In addition, perceived ease of use is the second most important factor influencing the behavioral intention of the higher education students of this study regarding hybrid learning. In addition, access to the Internet is another important factor influencing the behavioral intention of higher education students towards hybrid learning. Finally, in this study, campus support was shown to have a non-significant effect on higher education students' behavioral intentions toward hybrid learning.
Although campus support has an insignificant result, it plays an important role in influencing higher education students' behavioral intention toward hybrid learning. Once these online applications can meet the needs and desires of higher education students, their behavioral intention towards hybrid learning will increase.
Limitations and Recommendations of the Study
In addition, this research included perceived usefulness of hybrid learning system, perceived ease of use, Internet access, self-efficacy, teacher support, and campus support as the independent variables. Therefore, future research could be explored to determine other factors, for example, the course content, in-class activities, perceived satisfaction, and performance expectancy that could be used to justify behavioral intention to hybrid learning. Therefore, future researchers may use quota sampling when distributing questionnaires to respondents to ensure that there is an equal number of respondents from each age group when conducting the research.
This can improve research accuracy by reducing sampling bias, which results in errors during data analysis.
Conclusion
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Uniform Theory of Acceptance and Use of Websites Used by Higher Education Students. Journal of Educational Computing Research.
