基本上，这一章将收集数据，并描述在这项研究中，将采用的方法，以实现研究目标。在本章中，将从基本的理论框架和假设。理论框架和发展的假设是检查的依赖变量（绿色计算的做法）和独立变量之间的关系（运动意识，能源效率，材料回收，态度和社会影响）。此外，本研究还将对本文的研究设计、数据采集和后续的数据分析进行了较为详细的研究。这是旨在给读者一个更清晰的框架和图片的整体研究。 Psychology Essay 代写: Green Computing Practices Among Malaysian Youth

** Introduction**

Basically, this chapter is going to collect data and describe the methodology that will be employed in this research in order to achieve the research objectives. In this chapter, it will start with the basic theoretical framework and hypothesis. Theoretical framework and development of hypothesis is to examine the relationship between the dependent variable (green computing practices) and independent variables (campaign awareness, energy efficiency, materials recycling, attitude, and social influence). In addition, this research will also discuss the research design, data collection and follow by the data analysis in more detail. This is aim to give a clearer framework and picture to the reader about the overall study.

## 3.2 Research Framework

The researcher has been discussing about the research framework in chapter 2 (Literature Review). However, this research will be studying on how the independent variables (campaign awareness, energy efficiency, material recycling, attitude and social influence) can relate to the dependent variable (green computing practices). In this research, the dependent variable will be the study of green computing practices among Malaysian youths. Based on figure 3.1, the independent variables are campaign awareness, energy efficiency, material recycling, attitude and social influence while the dependent variable is green computing practices.

In figure 3.1 has illustrates the relationship between independent variables and dependent variable. The dependent variable (green computing practices) is the primary interest that this study wants to investigate, whereas the independent variable (campaign awareness, energy efficiency, materials recycling, attitude, and social influence) is the elements that may influence the dependent variable.

## Figure 3.1 Theoretical frameworks of a study of green computing practices among Malaysian Youth

Campaign Awareness

H1

Energy Efficiency

H2

Green Computing Practices

Materials Recycling H3

H6

Attitude

H4

Social Influence

H5

Independent Variable Dependent Variable

## Source: Developed for this study

## 3.3 Hypotheses Development

The hypothesis development is developed base on the Dependent Variable and Independent Variables, and the objectives of this research. The statements of hypotheses will be described in this part. Hypothesis is a testable statement that logically conjectured relationship between two or more variables. It gives the researcher some clues or ideas on what could be modified in order to solve the research problems. Basically, the hypotheses are derived from the theoretical framework that is discussed in previous section. However, hypothesis can test out the most appropriate factor or impact that lead to learning-life experience.

From this study, the hypotheses for the relationship between independent variables and dependent variable are as follow:

## H1: There is a significant relationship between the campaign awareness and green computing practices.

This research will investigate out the relationship between campaign awareness and green computing practices on how this factor can help the Malaysian youths to practice green computing.

## H2: There is a significant relationship between the energy efficiency and green computing practices.

This study will figure out the relationship between energy efficiency and green computing practices on how energy efficiency can affect the Malaysian youths to practice green computing.

## H3: There is a significant relationship between the materials recycling and green computing practices.

This research will judge on the relationship between materials recycling and green computing practices which the materials recycling factor can help Malaysian youths to practice green computing.

## H4: There is a significant relationship between the attitude and green computing practices.

This study will investigate out on the relationship between attitude and green computing practices on how a person’s attitude can help Malaysian youths to practice green computing.

## H5: There is a significant relationship between the social influence and green computing practices.

This research will figure out the relationship between social influence and green computing that social influence can cause the Malaysian youths to practice green computing.

## H6: Campaign awareness, energy efficiency, materials recycling, attitude and social influence can influence green computing practices.

This study will judge on the relationship between independent variables (campaign awareness, energy efficiency, materials recycling, attitude and social influence) and dependent variable (green computing practices) which can affect Malaysian youths to practice green computing.

## 3.4 Sampling Procedure

First of all, the sampling procedure will be firstly developed before distributing the questionnaires. After forming the questionnaire, it will be tested and the expert will investigate the relationship between variables. After the expert has approved the questionnaires, it can now then be distributed when conducting the real survey.

## 3.4.1 Sampling Method

Basically, convenience sampling will be applied when distributing questionnaire to the target sample. As its name suggests, convenience sampling, a non-probability sampling method, means that collection of data or information from its respondents who are conveniently available to do so. Additionally, this sampling method is also suitable since the study is still in its exploratory stage, so it is perhaps the best way to get some basic information from the respondent quickly and efficiently. Thus, convenience sampling is the best method to be used to complete this study.

## 3.4.2 Sample Size and Target Respondent

In this research, the researcher will use a total number of 250 questionnaires as the sample size and the target respondent will be the Malaysian youths in a private university in Melaka. The reason why researcher chooses this university is because most of the youths owned either a computer or a laptop. So the researcher would like to know how the response from the Malaysian youths towards green computing practices is. The questionnaires will be collected back and they are required to give the feedback accordingly to their responses to the questionnaire given to them. Hopefully the questionnaires collected back will be zero missing data from all the questionnaires distributed. Since there were no missing data, the percentage of the data will be 100% valid.

## 3.4.3 Research Instruments

Questionnaire will be used as our research instrument. The questionnaires will be designed to understand the factors or perception of Malaysian youths against green computing practices towards the independent variables.

In addition, in order to specifically identify the respondents’ level of agreement and disagreement towards the research topic, the Likert 5 scaling is selected for this research will be one-dimensional scaling method. The Likert 5 scaling is widely used by other researchers, and it is often used on hypothesis testing. So, this Likert 5 scaling will be used for the hypothesis testing in this research. The higher scores in this scaling represent the higher levels of negative effect. The scale will be applied as follow:

1 Strongly Disagree

2 Disagree

3 Moderate

4 Agree

5 Strongly agree

## 3.5 Data Source

In data source, there are two types of data collection methods which are primary data and secondary data. However, only primary data will be employed in this study as this research is done by collecting data and information through questionnaire survey. Questionnaires will be distributed to the Malaysian youths in one of the private university in Malacca during a specific span of time. This survey method allows the researcher to interact closer with the respondents in answering the questionnaire. The researcher may also help the respondents when they face any doubts

## 3.5.1 Primary Data

Primary data is referring to the data that will be written by the researcher base on his opinions right directly from the observations and experiences. The first time collected sample data that representing a population are known as primary data. In this research, the researchers will distribute a total of 250 questionnaires to the Malaysian youths in a private university in Melaka. As the questionnaire surveys are designed to determine the relationship between the dependent variable and independent variable. All the questionnaires will be collected back and that will be the primary data.

## 3.5.2 Secondary Data

Secondary data are those data that had already published which are past researched journals, reference texts, handbooks, encyclopedias, articles from the Internet, any electronic information. However, the secondary data is easier and inexpensively to obtain compare to primary data. In this research, the researcher will be using the collection of data method from the questionnaire which will be distributed, so there will be no secondary data contain in this research.

## 3.6 Data Collection Method

In order to get the reliable result, different approaches can be used such as questionnaire, interview and many more. However, it is important to ensure that the raw data collected from the sample is reliable and relevant to conduct the study. For this research, the questionnaire approach will be used which it will be tested to identify the relationship between the dependent variable and independent variable. The questionnaire for this research topic will be divided into 2 parts, which are demographic and general information and the perception of respondent toward the relationship between variables for this research topic. Overall, this study will describe the green computing practices (campaign awareness, energy efficiency, materials recycling, attitude, and social influence) among Malaysian youths.

## 3.7 Data Analysis

“Data analysis is a practice in which raw data is ordered and organized so that useful information can be extracted from it and the process of organizing and thinking about data is the key to understand what the data does and does not contain (Wise Geek, 2011)”. After collecting the questionnaires from respondents, the data will be arranged systematically and prepared for statistical computation process at the next stage. However, the questionnaires that will be collected from the respondents will be checked for its validity before keyed-in into Statistical Package for the Social Sciences (SPSS) 17.0 for Windows for further analysis. The data analysis will be done in two stages; the earlier section will be the descriptive analysis while the later stage will be the reliability analysis, hypothesis testing and Multiple Linear Regression Analysis.

In data analysis, the types of analysis the researcher will utilize in this research include descriptive statistics, reliability analysis, Pearson’s Correlation and multiple linear regressions.

## 3.7.1 Descriptive Analysis

Descriptive statistics analysis is based on the three ideas which are the central tendency, variability, and relative standing. “Measurement of central tendency is the summary number that represents a single value in a distribution of scores. While measurement for variability indicates the spread of the scores in a distribution, measurement for relative standing describes one score relative to a group of scores (Vogt, 1999)”.

It is required for the researcher to describe the trends in the data to a single variable in the instrument in order to answer each of the hypotheses in this quantitative research. The descriptive statistics can help in describing these trends since it can be used to indicate the general tendencies in the data that include mean, mode, and median (central tendency). Besides, descriptive statistics can also used to describe the spread of scores which include variance, standard deviation and rank (measurement of variability). A comparison of how one score relates to the other score is then determined to obtain the z scores and percentile rank (relative standing). Therefore, it is able to describe different type of variables by summarize the overall trends or tendencies in the data, provide an understanding of how the scores varied, and show the insight into where one score stands in comparison with others.

## 3.7.2 Reliability Analysis

In this section, Cronbach Alpha, a reliability coefficient that shows how well the items in a sample set are positively correlated to each other, will be used to check the reliability and strength of the data collected from questionnaire survey. The consistency of the results will bring an impact to the research findings in the later part.

## 3.7.3 Hypotheses Testing

Hypothesis testing is the use of statistics to show the probability that a hypothesis is true. This will be running by using the correlation test. As the data collected are normal, the Bivariate Correlations procedure will be employed to compute the Pearson’s correlation coefficient, which is accompanied by significance levels and directions associate proposed.

The strength of association between the variables is interpreted by using the Guilford’s Rule of Thumb in Table 3.1 below:

## Table 3.1: Interpretation of Pearson’s Correlation

## Suggested Interpretation for Correlation Coefficient

Less than 0.20

Slight correlation; almost negligible relationship

0.20 – 0.40

Low correlation; definite but small relationship

0.40 – 0.70

Moderate correlation; substantial relationship

0.70 – 0.90

High correlation; marked relationship

0.90 – 1.00

Very high correlation; very dependable relationship

Source: Guilford, J.P. (1956)

## 3.7.4 Multiple Regression Analysis

As for multiple regressions analysis, it is used to check the impact of multiple variables have on the outcome. However, the researcher will be using multiple linear regression analysis to check the significant difference among the independent variables the green computing practices among Malaysian youths at a private local. A Multiple Linear Regression formula will then be developed to illustrate the degree of contribution of the independent variables towards the level of satisfaction.

## 3.8 Chapter Summary

Basically, in this chapter is about developing the theoretical framework, hypotheses, research design, data collection and data analysis to determine the relationship between the independent variables and dependent variable. However, by using the variable, the researcher will make a hypothesis on the relationship between the independent variable and the dependent variable. Questionnaire will be distributed to Malaysian youths which are still studying in one of the private university in Melaka and the data that had been collected back will be used in data analysis. In the questionnaire, researcher will use the Likert scale as the form of measurement and distribute the questionnaire to 200 different people in the private university in Melaka. Lastly, the researcher will use descriptive analysis, reliability analysis, multiple regression analysis, and Pearson’s correlation analysis to analyze all the primary data.