1

Table of Contents Abstract ...................................................................................................................................... 3

Chapter 1 : Introduction ........................................................................................................ 4

1.1 Background of the Study ............................................................................................. 4

1.2 Problem Statement ...................................................................................................... 6

1.3 Research Questions (RQs) and Research Objectives (ROs) ....................................... 8

1.4 Scope of the Study....................................................................................................... 8

1.5 Relevance of the Study ................................................................................................ 9

Chapter 2 : Literature Review ............................................................................................ 11

2.1 Definition of Investigated Variables ......................................................................... 11

2.1.1 User satisfaction ...................................................................................................... 11

2.1.2 Attention ................................................................................................................. 12

2.1.3 Preparation .............................................................................................................. 13

2.1.4 Attitude ................................................................................................................... 13

2.2 Theoretical Background ............................................................................................ 14

2.3 Theoretical Framework ............................................................................................. 16

.............................................................................................................................................. 16

2.4 Research Hypothesis ................................................................................................. 16

2.5 Operationalization of Variables ................................................................................ 17

Chapter 3 : Methodology .................................................................................................... 18

3.1 Research Design ........................................................................................................ 18

2

3.2 Population, Sample and Unit of Analysis ................................................................. 18

3.4 Sampling Design ....................................................................................................... 19

3.5 Data Sources .............................................................................................................. 20

3.6 Data Collection Methods ........................................................................................... 20

3.7 Data Analysis ............................................................................................................ 21

Chapter 4 : Data Analysis and Findings ............................................................................. 23

4.1 Demographic background ......................................................................................... 23

4.2 Reliability analysis .................................................................................................... 24

4.3 Hypothesis testing ..................................................................................................... 25

4.3.1 The difference of student satisfaction level on UUM Online Learning between

gender ............................................................................................................................ 25

4.3.2 The difference of student satisfaction level on UUM Online Learning between

age ............................................................................................................................ 26

4.3.3 The influence of attention, preparation and attitude on user satisfaction ......... 26

Chapter 5 : Conclusions and Recommendations ................................................................ 28

5.1 Conclusions ............................................................................................................... 28

5.2 Contribution and Implication .................................................................................... 29

5.3 Recommendations ..................................................................................................... 30

References ................................................................................................................................ 31

Appendices ............................................................................................................................... 33

3

Abstract

Changes in technologies have changed our lives. Education field was not exempted from the

current technological changes. Technology now plays an important role to improve

accessibility in seeking knowledge and wisdom much faster and easier. The changes of

Malaysia's education system and worldwide generally have taken steps to lead the field in

using trusted online access to benefit the education sector. Public and private institutions in

Malaysia have been taking advantage from ease of internet access to provide its students with

more secure and reliable information more efficiency. Therefore, this study is to examine the

level of acceptance using online learning as a portal that helps learning process. In this study,

four basic instruments of attention (AN), preparation (PN), attitude (AE) and user satisfaction

(US) that use as to explain online learning. Furthermore, this study examined whether there is

a mean difference of student satisfaction level on UUM Online Learning between gender and

age. Students of Northern University of Malaysia (UUM) which have access of UUM Online

Learning have been selected to participate in the study. The research has been conducted

through a survey with a 100 set of questionnaire. A total of 100 usable data provide by the

respondents is being used to achieve the objectives of the study. Based on the Regression

Analysis, the result showed significant relationship between attention and preparation and

student satisfaction on UUM Online Learning. It means that, these two elements are

important in order to ensure the students will be satisfied with the UUM Online Learning.

The research conducted can improve in learning process of the students, specifically UUM

students. So, the government should provide a better service for online learning to increase

the satisfaction level among students. UUM Information Technology (IT) also should provide

a better system of UUM Online Learning. Other researcher should engage the same study or

study that relates in Online Learning for example the external factors that influence the

satisfaction on Online Learning.

4

Chapter 1 : Introduction

1.1 Background of the Study

The internet world is now very widespread and has many uses, every year more and more

internet users has increased rapidly (Thornburg, 1998). Radio took 38 years to reach 50

million users and television takes 13 years to reach 50 million users and the Internet took

only 4 years to reach 50 million users. This shows that Internet user is increasing every year.

With the internet, all amenities and innovations are easy to reach. Such as education, that

many receive as a result of internet innovation has led to online learning. The landscape of

distance education is changing. This change is being driven by the growing acceptance and

popularity of online course offerings and complete online degree program at colleges and

universities worldwide (Eom, Wen & Ashill 2006). E-learning in our country is more focused

on long-distance learning and on-line are mostly only offered university level as well as

private colleges which hade joint overseas universities. Among the local institutions that offer

virtual learning is University Putra Malaysia through IDEAL (Institute for Distance

Education and Learning). Through joint ventures with local companies Mahirnet Sdn. Bhd.,

UPM inaugural offering a virtual Bachelor of Communications.

In the United States, there are thousands of educational websites which claim that

they offer e-learning program. But according to Linda C. Joseph, a researcher from Columbus

(Ohio) Public Schools, the e-learning concept is not just the delivery of lecture notes to

students or submitting assignments to the lecturer by e-mail alone, but the actual charge must

be fulfilled a forum/discussion, two parties in two-way communication, organizing

information more orderly in terms of lecture notes, schedules, fees, tutorials and

examinations. To meet the criteria stated above, learning is more effective and can be

performed interactively.

5

Looking back at the changes that occurred in the country's education system

especially teaching methods, it changed along with the changes in the education system of the

world. Starting with traditional teaching methods that use the black board, followed by the

use of the white board (white board), and further involvement Teaching Aids in the session,

currently integrating information technology and application of the Internet in the learning

session: e-learning (e-learning) has widespread (Juhazren Junaidi & Madihah Jailani, 2010).

Now, computer technology will not only help in applying theory learning, but also contribute

to new learning methods in the world education. Jamalludin and Zaidatun (2003) argue, is

focused on the use of computers and how to perform the migration strategy information used

to meaningful and useful knowledge. For body text lesson, it is presented through a variety of

media use, attractive and more dynamic. With this, he was able to attract students and

stimulate their minds.

The e-learning at Northern University of Malaysia (UUM) started in year 2000

developed jointly by local IT Company and UUM, it comprises of twelve modules that

provides UUM’s academic community with arrays of innovative strategies and activities to

enhance the conventional face-to-face instruction. Currently, the system runs on the campus

integrated LAN with 5920 data points and a database of 150 megabyte size. The network

capacity which supports the system is 2 megabyte per second (Mbps) via internet network, 10

(Mbps) via satellite and 1 gigabyte via intranet. The total storage for each user is 30

megabytes (Ahmad et al, 2009).

In the study, we have two variables where the independent variables (IV) include

attention, preparation and attitude and dependent variable (DV) is satisfaction on UUM

Online Learning. In this study we will see how attention, preparation and attitude will affect

satisfaction on UUM Online Learning. For IV like attention, taking into several factors such

as whether the learning will be more fun, and see an increase in student achievement. For

6

preparation, we will see whether the UUM Online Learning can help students in the learning

process and preparation before the exam. For attitudes, we will see factor such as the

willingness to use UUM Online Learning. For DV we will see consumer satisfaction in using

the UUM Online Learning, whether the user is satisfied with the service provided by UUM

IT.

1.2 Problem Statement

The issue that the student of UUM encountered is about the satisfaction on online learning.

Based on the observation that has been done towards several students complaints regarding

UUM Online Learning, a lot of the students are not satisfied with the UUM Online Learning

due to its uneasy to access, uneasy to upload files and many more other issues. The e-

Learning market has a growth rate of 35.6%, but failures exist.

Little is known about why some users stop their online learning after their initial

experience. Information system research clearly shows that user satisfaction is one of the

most important factors in assessing the success of system implementation. So we investigate

three factors that influence satisfaction on online learning that is attention, preparation and

attitude. These factors have strong relation to influence satisfaction online learning.

Many researchers from psychology and information system fields have identified

important variables dealing with Online Learning. Among them, the technology acceptance

model and the expectation and confirmation model have partially contributed to

understanding e-Learning success. A summary of the literature relevant to all the factors vital

to the activities of satisfaction online learning, is presented below in Table 1.

7

Author(s) Factors Arbaugh (2000) Perceived usefulness and perceived ease of use, flexibility of e-Learning,

interaction with class participants, student usage, and gender

Piccoli et al. (2001) Maturity, motivation, technology comfort, technology attitudes, computer

anxiety, and epistemic beliefs, technology control, technology attitudes,

teaching styles, self-efficacy, availability, objectivist and constructivist,

quality, reliability, and availability, pace, sequence, control, factual

knowledge, procedural knowledge, conceptual knowledge, timing,

frequency, and quality

Stokes (2001) Students’ temperaments (guardian, idealist, artisan, and rational)

Arbaugh (2002) Perceived flexibility of the medium, perceived usefulness and perceived

ease of use, media variety, prior instructor experience, virtual immediacy

behaviors, and interaction

Arbaugh and Duray (2002) Perceived usefulness and perceived ease of use, perceived flexibility

Hong (2002) Gender, age, scholastic aptitude, learning style, and initial computer skills,

interaction with instructor ,interaction with fellow students, course

activities, discussion sessions, and time spent on the course

Thurmond et al. (2002) Computer skills, courses taken, initial knowledge about e-Learning

technology, live from the main campus of the institution, age, receive

comments in a timely manner, offer various assessment methods, time to

spend, scheduled discussions, team work, acquaintance with the instructors

Kanuka and Nocente Motivating aims, cognitive modes, and interpersonal behaviors

(2003)

Table 1: Related references about the critical factors that influence satisfaction online

learning

8

1.3 Research Questions (RQs) and Research Objectives (ROs)

The general objective of the study is to examine the relationship between UUM students

behaviour and satisfaction on UUM Online Learning. The specific objectives of the study are:

1. To examine the relationship between attention and student satisfaction on UUM

Online Learning.

2. To examine the relationship between preparation and student satisfaction on UUM

Online Learning.

3. To examine the relationship between attitude and student satisfaction on UUM Online

Learning.

4. To investigate the mean difference of student satisfaction level on UUM Online

Learning in gender.

5. To investigate the mean difference of satisfaction level on UUM Online Learning

among age.

Therefore, the study focuses on answering the following issues:

1. Does attention relates to student satisfaction on UUM Online Learning?

2. Does preparation relates to student satisfaction on UUM Online Learning?

3. Does attitude relates to student satisfaction on UUM Online Learning?

4. Does student satisfaction level on UUM Online Learning different in gender?

5. Does student satisfaction level on UUM Online Learning different among age?

1.4 Scope of the Study

This scope of the study is to examine the relationship between attention, preparation and

attitude to User satisfaction on UUM Online learning among students University Utara

Malaysia. Thus, the scope of respondents will be among students in campus Sintok. We

9

found some factor will be given the impact to the satisfaction on UUM Online Learning. In

this case, have three aspects which are attention, perception and attitude. The attention,

perception and attitude are independent variable (IV) which will be impact to the satisfaction

on UUM Online Learning which dependent variable. So, in this research, we focus on

examine the student satisfaction on UUM Online Learning (DV).

In this study, the population only focus on the student from UUM which is for the

respondent. We use 100 respondents which from different sex, age, level of education, and

the frequency of use UUM Online Learning. So, The researcher distributed 100 pieces of

questionnaires to the student in University Utara Malaysia. The questionnaires were

distributed to all the schools in this university, there are COB, CAS and COLGIS. Also,

questionnaires were given to the students from all residential hall which includes Dpp Mas,

Dpp Tnb, Dpp Proton, Dpp Tradewinds, Dpp Pertronas, Dpp Eon, Dpp Sime Darby, Dpp

Tm, Dpp Misc, Dpp Bsn, Dpp Yab, Dpp Mualamat, Dpp Sme and Dpp Bank Rakyat. The

sample is selected among UUM students and the results will be generated among UUM

students only.

1.5 Relevance of the Study

The study will benefit to the following group:

1. Practitioner

It is hope that the study findings will contribute in providing the suggestions towards

improving the current UUM Online Learning. By understanding, the satisfaction level

of UUM Online Learning among students, UUM IT may use it as a guidance to

develop and further improve their current services in achieving the expected quality

services from its clients. Moreover, UUM IT also can gain then information regarding

10

the relationship between attention, preparation and attitude among students and their

satisfaction on UUM Online Learning.

2. Academician

The study also may become a reference to others that doing the same study or engage

with Online Learning, especially among the Malaysia Public Universities (IPTA). In

addition, the academician can gain the information how benefits Online Learning to

the students and the factors affecting the satisfaction level among students.

11

Chapter 2 : Literature Review

2.1 Definition of Investigated Variables

2.1.1 User satisfaction

User satisfaction is a dependent variable for this study. According Bolliger & Oksana Wasilik

(2009) student satisfaction is defined as the student’s perceived value of his or her

educational experiences at an educational institution. The user satisfaction dimension gauges

opinions of the students about online learning based on their experience with the course. This

is rated on perceptions of satisfaction, enjoyment, success and recommend ability. The net

benefits dimension captures positive aspects of online learning in terms of learning

enhancement, empowerment, time savings, and academic achievement, as well as negative

aspects of online learning in terms of lack of face-to-face contact, social isolation, quality

concerns, and dependence on technology.

Most students who reported higher levels of interaction with instructor and peers

reported higher levels of satisfaction and higher levels of online learning. A number of

previous research studies suggested that an interactive teaching style and high levels of

learner-to-instructor interaction are strongly associated with high levels of user satisfaction

and learning outcomes. In this study, to achieving user satisfaction among students is a

primary goal while using UUM Online Learning. UUM Online Learning helps the learning

process of the students itself. User satisfaction can be defined as how efficient and effective

the UUM Online Learning that provided in UUM for student get the information at UUM.

Satisfaction also refers to the extent to which students are happy to used UUM Online

Learning as a portal learning process to access information. Information system research

12

clearly shows that user satisfaction is one of the most important factors in assessing the

success of system implementation.

2.1.2 Attention

The first Independent variable in this study is attention. Attention is main factors that define

the user satisfaction on UUM Online Learning. According to Anderson (2008) attention is

capture the learners’ attention at the start of the lesson and maintain it throughout the lesson.

The online learning materials must include an activity at the start of the learning session to

connect with the learners. Online learning can help student to find information critical for

learning should be highlighted to focus learners’ attention. For example, in an online lesson,

headings should be used to organize the details, and formatted to allow learners to attend to

and process the information they contain. Learners should be told why they should take the

lesson, so that they can attend to the information throughout the lesson.

According Kim and Bonk (2006), the previous study show the data presented here

also indicate that the continued explosion in online learning will bring increased attention to

workshops, courses, and degree programs in how to moderate or mentor with online learning.

Given that many respondents expect to receive some sort of training and support from their

institutions to be ready for online teaching, colleges and universities need to consider how

they will respond to these needs. UUM Online Learning helps student pay more attention to

what is going on in lecture such as when conceptual questions will be presented. Lecturer

also need give attention to online learning for development and expansion of online education

to easy student asses their coursework in online learning. When individual give attention in

class, they will participate in the class because they implement that UUM Online Learning

can help them in the study. Consequently, a higher learning satisfaction should exist.

13

2.1.3 Preparation

In the study, course planning and preparation are important activities within the context of

online learning. We focused on encouraging students’ active learning in lectures, whereas

previous studies have made more use of audience response technology during lectures for

formative or summative assessment. The present study suggests that a number of future

improvements can be made to increase student preparation and engagement with active

lectures. Encouraging more students to undertake pre reading is vital for students like ours,

with diverse cultural, learning approaches, and knowledge backgrounds. The preparation

means how UUM Online Learning can help the students to prepare their works, notes and

material needed. Once the UUM Online Learning can help them much in their study, the

students will be satisfied with the UUM Online Learning.

Preparation of learning material could be very helpful to student get the material

before they start for learning process as well. Before class, students can review learning

objectives, key concepts, and supplemental materials posted on the online learning for

preparation their course and they can give attention in class. It is because, they make

preparation early using online learning and ease they attraction with lecturer. Student using

online learning to assess their preparation for class, students then complete online quizzes,

which provide immediate feedback to students and data for instructors to assess students’

knowledge levels. Instructors are able to reduce class time spent on topics that the students

clearly understand, increase time spent on problem areas, and target individual students for

learning process.

2.1.4 Attitude

According to Paris (2004) proposed that affect, behaviour, and cognition are distinguishable,

yet interrelated components of attitude. Attitude also can be defined as learners impression

14

about performing the target behaviours. Attitude has been described as predispositions to

respond in a particular way towards a particular object or class of objects in a consistently

favourable or unfavourable way. Educators have known that learner attitudes and responses

are interconnected and that a positive correlation exists between the two. Burns’s study

supports this with the statement that “attitudes are evaluated beliefs which predispose the

individual to respond in a preferential way” (Burns, 1997). Attitude toward delivery process

could represented by perceived easiness/difficulties in using various instructional

technology/media in an online class (Nguyen, D., D., & Zhang, Y., J. 2011). For a student

ease of learning may include comprehensive presentation of course content, feedback from

instructor, and communication with classmates. Previous studies indicated that the attitude of

learners will positively influence learners’ satisfaction and acceptance of the Online

Learning.

. Positive attitude toward UUM Online Learning can encourage and motivate students

to participate in online courses as well as online activities. Hence, students should eliminate

attitude such as aversion and anxiety while using the UUM Online Learning. Based on last

review, they found the result of analysis has shown that, attitude have positively influenced

the students’ performances on the implementation of online learning system. In this study,

attitudes give an impression satisfaction students in use of UUM Online Learning to access

information during learning process.

2.2 Theoretical Background

TAM was introduced by Davis (1986) to explain computer-usage behaviour. Since then,

TAM has been the most frequently cited and influential model for understanding the

acceptance of information technology and has received extensive empirical support. The

theoretical basis of TAM was Theory of Reasoned Action (TRA) (Fishbein and Ajzen’s,

15

1975). TRA is a widely-studied model from social psychology which is concerned with the

determinants of consciously intended behaviours. According to TRA, a person’s performance

of a specified behaviour is determined by his or her behavioural intention (BI) to perform the

behaviour, and BI is jointly determined by the person’s attitude (A) and subjective norm (SN)

concerning the behaviour in question.

Behavioural intention (BI) measures a person's relative strength of intention to

perform behaviour. Attitude consists of beliefs about the consequences of performing the

behaviour multiplied by his or her evaluation of these consequences. Subjective norm (SN) is

seen as a combination of perceived expectations from relevant individuals or groups along

with intentions to comply with these expectations. In other words, the person's perception that

most people who are important to him or her think he should or should not perform the

behaviour in question. To put the definition into simple terms: a person's volitional

(voluntary) behaviour is predicted by his attitude toward that behaviour and how he thinks

other people would view him if he performed the behaviour. A person's attitude, combined

with subjective norms, forms his behavioural intention.

Next, TAM proposes external variables as the basis for tracing the impact of external

factors on two main internal beliefs, perceived usefulness (PU) and perceived ease of use

(PEU). According to Davis (1989), perceived ease of use is the degree to which a person

believes that using a particular system would be free of effort and perceived usefulness is the

degree to which a person believes that using a particular system would enhance his or her job

performance. These two beliefs both influence users’ attitude toward using information

systems (IS).

16

2.3 Theoretical Framework

Figure below shows the theoretical framework with three independent variables which is

attention (AN), preparation (PN) and attitude (AE) and satisfaction on UUM Online Learning

among students (US). Based on this framework, the attention, preparation and attitude will be

examined towards the student satisfaction on UUM Online Learning.

Independent Variables (IV) Dependent Variable (DV)

2.4 Research Hypothesis

H1: There is relationship between attention and satisfaction on UUM Online Learning.

H2: There is relationship between preparation and satisfaction on UUM Online Learning.

H3: There is relationship between attitude and satisfaction on UUM Online Learning.

H4: There is mean difference of student satisfaction level of UUM Online Learning in gender.

H5: There is mean difference of student satisfaction level of UUM Online Learning among

age.

Attention

Attitude

Preparation

User satisfaction on

UUM Online

Learning

17

2.5 Operationalization of Variables

All demographic variables such as genders, age, educational level, the frequency of used

UUM Online Learning before entering the class and the time spending for UUM Online

Learning were tapped by direct single questions. Satisfaction on UUM Online Learning is a

dependent variable that indicates the user satisfaction while using the UUM Online Learning

for study purposes. It has been developed six items to measure this variable, a sample item

being: “My experience at using Online Learning is good.” This variable has been measured

by interval scale which is ranged from strongly disagree until strongly agree. With the

interval scale we come to a form that is "quantitative" in the ordinary sense of the word

(Stevans, 1946).

Attention is the independent variable which has been measured by five items. The

sample of item for attention being: “Pay more attention to what is going on in lecture when

conceptual questions will be presented.” Preparation also is one of the independent variable

in the study which has been measured by five items. The sample of item for preparation

being: “In my opinion, UUM Online Learning helps me in the learning process.” Attitude

also is the independent variable which has been measured by six items. The sample item for

attitude being: “I am willing to use UUM Online Learning.” All the three independent

variables are measured by interval scale which is ranged from strongly disagree until strongly

agree.

18

Chapter 3 : Methodology

3.1 Research Design

The study is done in the form of hypothesis testing that involves the collection of data on

quantitative. The hypothesis testing design permits the researcher to test relationship between

attitudes, perception and attention which is independents variables. Attitudes is individual

behaviour defined as the individual’s general feelings or beliefs of the extent of benefits or

losses resulting from performing that behaviour, and it is a function of the product of one’s

normative belief of expected behaviour and his/her motivation to conform to the expectation

(Foong & Khoo,2013). Satisfaction on UUM Online learning which is dependent variable.

According to Entwistle (1989), the learning environment provides the context which students

are either encouraged to engage a deep approach or pushed toward a surface approach to

learning. In other words, learning environment deters adoption of certain strategy for learning

that determines the “depth” of learning.

Qualitative research design applied in this research whereby the survey will be

conducted through questionnaire. Handling the questionnaire is relatively easy while at the

same time provides the breadth and speed in term of its coverage. The research design with

the principle of cross-sectional field survey where questionnaire was used for data collection.

Therefore, hypothesis testing will facilitate the researcher to identify the relationship between

attitudes, perception and attention to satisfaction on UUM Online Learning among students in

Northern University of Malaysia, Sintok.

3.2 Population, Sample and Unit of Analysis

According to Fraenkel, Wallen, & Hyun (1993) population means the group to which the

researcher would like the results of a study to be generalizable it includes all individuals with

19

certain specified characteristics. Sample is a source for data study. Sample also as an example

of the general population sample. What is the relationship between population and sample?

Population as described above is a group individual’s or objects to be studied. If the

population size has been identified, is too difficult for researchers to involve all individuals in

the population. Then Researchers can select a representative of that population. Individuals

who represent a population sample study cited. Research carried out on samples and based on

the characteristics of the sample, inference performed on a population. For this research, the

population will only cover the students of Northern University of Malaysia (UUM) that use

UUM Online Learning.

The sampling populations for this study are about 100 as respondents, who are student

that use UUM Online Learning. Samples are to be made of groups of research to investigate

user satisfaction on UUM Online Learning. It is a subset or sub-groups in the population

selected. Sample reflects the population selected. Researcher use convenience sampling as

sampling method. Researcher use this method in order to determine the sample involve in this

research. Through this convenience sampling, each student that used UUM Online Learning

will be selected as respondents to examine the level of satisfaction on UUM Online Learning

as a portal that helps them in learning process. The unit of analysis for the study is an

individual which is students of Northern University of Malaysia (UUM).

3.4 Sampling Design

According to Mugo (2002), a sample is a finite part of statistical population whose properties

are studied to gain information about the whole. When dealing with people, it can be define

as a set of respondent selected from a large population for the purpose of a survey. Besides

that, Mugo said sampling is the act, process, or technique of selecting a suitable or a

20

representative part of population for the purpose of determining parameters or characteristic

of the whole population.

Most research questions in qualitative studies lead to one of two classes of analysis

which is within-case analysis or cross-case analysis (Onweugbuzle & Leech, 2007). Sample

is the selected group among the population of large group. The list selected form the large

group of population in this research are from students of College of Business, College of Art

and Science and College of Law, Government and International Studies.

As the study is interested to generalise the findings to the whole population, the

probability sampling is the most suitable design for this study. The systematic sampling will

be used to collect the survey data. The sampling is consists of 100 students that represent the

whole Northern University of Malaysia, Sintok.

3.5 Data Sources

The study involves the use of primary data. The primary data has been collected through

survey method where the questionnaires has been distributed to the respondents. This method

is considered as the main method in collecting the data and accepted by many researchers.

Questionnaire focus on getting clear information about issue in hand and also will give a

large coverage of respondents in the study.

3.6 Data Collection Methods

The data has been collected through survey which is conducted around UUM. Since the study

is to examine the satisfaction on UUM Online Learning among students, so the questionnaire

has been distributed among 100 students in class, library and DPP. A questionnaire is a pre-

formulated written set of questions to which respondents record their answers, usually within

rather closely defined alternatives (Sekaran and Baugie, 2013). We designed a questionnaire

21

with questions to examine the satisfaction on UUM Online Learning among students. The

answer ranged from “strongly disagree”, “disagree”, “neutral”, “agree” and “strongly agree”.

3.7 Data Analysis

The quantitative statistical software programs will be utilized to address the research

objectives which include the following analysis.

1. Descriptive Analysis

This analysis is used to describe demographic background of respondent profile. This

analysis has been used to find out the mean and standard deviation of each variable

such as gender, age and educational level.

2. Reliability Analysis

Reliability Analysis provides a unique estimate of the internal consistency and

reliability. Reliability analysis is also used to train new observers in coding schemes

and observational data collection (Jansen, Wiertz, Meyer and Noldus, 2003).

Cronbach’s alpha will be used for this test to estimate how highly the items in the

questionnaire which is attention, attitude, preparation and user satisfaction on UUM

Online Learning are related in order to determined reliability or the instrument.

3. Independent Samples T-Test

Independent samples T-Test is used to investigate the mean difference of student

satisfaction level on UUM Online Learning in gender.

4. ANOVA Test

ANOVA test is used to compare the means of the samples which is more than two

groups. In the study, we use ANOVA test to compare between user satisfactions on

UUM Online Learning among age.

22

5. Regression Analysis

Regression analysis is a statistical tool for the investigation of relationships between

variables (Sykes, 1993). Regression analysis used to access the relationship between a

dependent (predicted) variable which is user satisfaction on UUM Online Learning

and several independent (predictor) variables, attention, preparation and attitude.

23

Chapter 4 : Data Analysis and Findings

4.1 Demographic background

Based on Table 1, the demographic profiles of the study includes gender, age, educational

level, frequency and time spending (hours/week). The sample profiles showed a higher

number of female (58) respondents than male (42), representing a ratio of 58% and 42%,

respectively. The major respondents were students with age between 21 – 25 years old (88),

second higher 26 – 30 years old (10) and the last is 31 – 35 years old (2). The entire sample

of age representing a percentage of 88%, 10%, 2% respectively.

Besides, the sample profiles also show a higher number of student of Bachelor’s

Degree which is 47, Master’s Degree (7) and the lowest is PhD’s Degree which only 6

students. It represents a percentage of 87%, 7% and 6%. For the frequency of the students

accessing the UUM Online Learning before the class started, it showed that never (3), rarely

(14), sometimes (46), often (34) and very often 3.The entire sample of this variables

represents a percentage 3%, 14%, 46%, 34% and 3% respectively. For the last variable which

is total time spending (hours/week) showed that 43 students spend around 0 – 2 hours per

week, 34 students 2 – 4 hours per week, 12 students 4 – 6 hours per week, 9 students 6 – 8

hours per week and 2 students more than 8 hours per week. This entire sample represent a

percentage 43%, 34%, 12 %, 9% and 2 % respectively.

24

Variable Frequency (N=100) Percentage %

Gender

Male

Female

42

58

42%

58%

Age

21 – 25 years old

26 – 30 years old

31 – 35 years old

88

10

2

88%

10%

2%

Educational Level

Bachelor’s Degree

Master’s Degree

PhD’s Degree

87

7

6

87%

7%

6%

Frequency

Never

Rarely

Sometimes

Often

Very Often

3

14

46

34

3

3%

14%

46%

34%

3%

Hours

0 – 2 hours

2 – 4 hours

4 – 6 hours

6 – 8 hours

More than 8 hours

43

34

12

9

2

43%

34%

12%

9%

2%

Table 1: Descriptive Analysis

4.2 Reliability analysis

Based on Table 2, the result indicates that the alpha value for each variable ranged from

0.846 and 0.884. Based on Nunnaly (1980), the score between 0.60 and 0.70 is acceptable

and more than 0.80 is considered good. Thus, the reliability of each variable of this study is

met.

Variables Number of items Alpha Value

Attention 5 0.884

Preparation 5 0.869

Attitude 6 0.871

User Satisfaction 6 0.846

Table 2: Reliability Analysis

25

4.3 Hypothesis testing

4.3.1 The difference of student satisfaction level on UUM Online Learning between

gender

Independent Sample t-Test was performed to investigate the mean difference of student

satisfaction level on UUM Online Learning in gender. Based on table 3, the result shows the

equal variances assumed (p= 0.461 > 0.05), so that we choose equal variances assumed. The

result shows no significant difference of student satisfaction level on UUM Online Learning

between gender (p=0.687 > α). The result indicates that no significant different of student

satisfaction level on UUM Online Learning between male and female students.

Group Statistics

Gender N Mean Std. Deviation Std. Error Mean

US Male 42 3.5000 .91064 .14052

Female 58 3.5690 .73418 .09640

Independent Samples Test

Levene's Test for

Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence

Interval of the

Difference

Lower Upper

US Equal

variances

assumed

.547 .461 -.419 98 .676 -.06897 .16466 -.39572 .25779

Equal

variances not

assumed

-.405 76.490 .687 -.06897 .17041 -.40832 .27039

Table 3: Independent Sample T-Test

26

4.3.2 The difference of student satisfaction level on UUM Online Learning between

age

A one-way ANOVA between-groups analysis of variance was performed to investigate the

mean difference of user satisfaction on UUM Online Learning among age. Based on table 4

below, the result shows no significant difference of user satisfaction on UUM Online

Learning between age of UUM students (p=0.587).

ANOVA

US

Sum of Squares Df Mean Square F Sig.

Between Groups .709 2 .354 .536 .587

Within Groups 64.131 97 .661

Total 64.840 99

Table 4: One-Way ANOVA

4.3.3 The influence of attention, preparation and attitude on user satisfaction

Multiple Linear Regression has been performed to determine the best set of predictors

variable in predicting DV. The R-Square of 0.485 implies that the three predictor variables

explain about 48.5% of the variance in the US. This is a good and respectable result. The

ANOVA table revealed that the F-statistic (30.171) is large and the corresponding p-value is

highly significant (0.0001) or lower than the alpha value of 0.05. This indicates that the slope

of the estimated linear regression model line is not equal to zero confirming that there is

linear relationship between US and the three predictor variables (attitude, preparation and

attention). This finding is consistent with previous studies (Anisah Abdul Ghani, 2014; Sun et

al., 2008).

Based on Coefficient table, all three predictor variables which are attitude (p=0.298 >

alpha) is not significance in explaining dependent variable. Preparation (p=0.002 < alpha)

and attention (p=0.001 < alpha) were found to be of significance in explaining dependent

variable which is US. The largest beta coefficient is 0.365 which is for attention. This means

27

that this variable makes the strongest unique contributions to explaining the dependent

variable (US), when the variance explained by all other predictor variables in the model is

controlled for. It suggests that one standard deviation increase in attention is followed by

0.365 standard deviation increase in US. The Beta value for preparation is the second highest

(0.329), indicating that it made the lesser contribution than attention.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .697a .485 .469 .58961

a. Predictors: (Constant), Attitude, Preparation, Attention

ANOVAa

Model Sum of Squares Df Mean Square F Sig.

1 Regression 31.466 3 10.489 30.171 .000b

Residual 33.374 96 .348

Total 64.840 99

a. Dependent Variable: US

b. Predictors: (Constant), Attitude, Preparation, Attention

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) .525 .327 1.606 .112

Attention .371 .106 .365 3.501 .001

Preparation .339 .105 .329 3.220 .002

Attitude .094 .089 .097 1.047 .298

a. Dependent Variable: US

Table 5: Regression Analysis

28

Chapter 5 : Conclusions and Recommendations

5.1 Conclusions

The objective of this research is to examine the relationship between attention, preparation

and attitude and user satisfaction on UUM Online Learning. Based on the findings, the

previous chapter (refer table 5) which is Multiple Linear Regression showed significant

relationship between attention and preparation and user satisfaction on UUM Online

Learning. Based on table 5, the p values of two predictor variables which are attention

(p=0.001) and preparation (p=0.002). That means both of two predictor variables influence

the user satisfaction on UUM Online Learning. However, the rational of the relationship need

to be explained further so that it gives a strong proof and reliability for the study. Moreover,

the results of present study will be compared with the pervious study to order to examine the

similarity between them.

H1: The relationship between attention and user satisfaction on UUM Online Learning

Result of regression analysis showed the relationship between attitude and user satisfaction

on UUM Online Learning. The analysis also show attention present the highest value of beta

(b = 0.365 >p). The study was consistent with previous research by Liaw (2008) entitled

Investigating students’ perceived satisfaction, behavioural intention, and effectiveness of e-

learning: A case study of the Blackboard system. The research explains that e-learning

effectiveness can be influenced by multimedia instruction, interactive learning activities, and

e-learning system quality.

29

H2: The relationship between preparation and user satisfaction on UUM Online

Learning

Result of regression analysis showed the relationship between preparation and user

satisfaction on UUM Online Learning. The regression analysis of ease of use present highest

value (b = 0.329, p > 0.05). This means that this variable makes the strongest unique

contributions to explaining the dependent variable (US). This finding is aligned with previous

studies by Al-Doub, Goodwin & Al-Hunaiyyan (2008), where they found the relationship

between preparation and user satisfaction on UUM Online Learning.

5.2 Contribution and Implication

Online learning is important for student to access information about their course, assessment

and exam. The research can provide an useful information to the UUM Information

Technology (IT) and the students itself about the internal factors that affect the user

satisfaction on UUM Online Learning. As the research conducted can improve in learning

process of the students, specifically UUM students, so, the government should provide a

better service for online learning to increase the satisfaction level among students. UUM IT

also should provide a better system of UUM Online Learning. They can improve the quality

of online learning to ease the UUM students access the UUM Online Learning everywhere. It

is because, online learning main references or main portal for students access information

about activities in UUM.

Besides that, UUM IT also can improve the cost-effectiveness of education for UUM

lecturer and students. Means that, student more experience to uses online learning and they

can make preparation early before they do their course. Lecturer also can develop those

teaching strategies which have been demonstrated to result in improved learning outcomes.

IT management support from the faculty or school was also shown to be critical, thus

30

highlighting the importance of an online learning plan for the institution and for the

communication of that plan to all levels of the university.

5.3 Recommendations

1. Practitioner

The IT management in University Utara Malaysia has to make sure that all the independent

variables are well taken care off in order to make sure that the student of UUM has good

experience using UUM Online Learning and are willing as well as wanting to maximize their

usage of the UUM Online Learning.

2. Academicians

Other group of researcher should analyze the external factor that may hinder or enhance the

performance of UUM Online Learning. For example the TNC of the university should held

good relationship with the internet provider in our case the CISCO company. Good

relationship with the vendor may help in increasing the internet connection thus, UUM

Online Learning may perform at its best.

31

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Appendices