project sta (group)

FACULTY OF COMPUTER & MATHEMATICAL SCIENCES
STA416: APPLIED PROBABILITY AND STATISTICS
GROUP: NCTN3B
FINAL PROJECT

PREFERABLE STUDY PLATFORM AMONG ONLINE DISTANCE
LEARNING (e-PJJ) UiTM BACHELOR DEGREE STUDENTS IN
FACULTY OF COMPUTER & MATHEMATICAL SCIENCES

PREPARED BY STUDENT ID
NAME 2020154679
AMAN AKHBAR BIN ABD RAZAK 2020121491
MUHAMAD NORFARIS BIN FAISAL 2020791869
NUR SARAH BINTI JAMALUDIN 2020794499
SAIDATUL AKMAR BINTI MOHD AZLIMI

PREPARED FOR
MADAM NUR HUDA NABIHAN BINTI MD SHAHRI

DATE OF SUBMISSION
27th JANUARY 2021

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TABLE OF CONTENTS

ACKNOWLEDGMENT .................................................................................................. 1
1.0 INTRODUCTION ......................................................................................................2

1.1 BACKGROUND OF STUDY ..................................................................... 3
1.2 PROBLEM STATEMENT........................................................................... 4
1.3 OBJECTIVES............................................................................................... 4
2.0 METHODOLGY ........................................................................................................5
2.1 DEFINE POPULATION.............................................................................. 5
2.2 DEFINE VARIABLES ................................................................................ 5
2.3 DATA COLLECTION ................................................................................. 6
3.0 STUDY DESIGN ........................................................................................................7
4.1 DESCRIPTIVE STATISTICS ................................................................... 17
4.2 STATISTICAL ANALYSIS ...................................................................... 30
5.0 FINDINGS ................................................................................................................36
6.0 DISCUSSION............................................................................................................39
APPENDIX .....................................................................................................................40

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ACKNOWLEDGMENT

All praises to Allah and His blessing for the completion of this assignment. We are thankful
to Allah for all the opportunities, trials and strength that have been showered our team members
to complete this project. The success and final outcome of this assignment required a lot of
guidance and assistance from many people and we extremely fortunate to have got this all
along. First and foremost, we would like to sincerely thank our statistics lecturer, Madam Nur
Huda Nabihan Binti Md Shahri for her guidance, understanding, patience and most
importantly, she has provided positive encouragement and a warm spirit to finish this
assignment. We are really grateful because we managed to complete the assignment within the
time given. It has been a great pleasure and honour to have her as our lecturer.

Our deepest gratitude goes to all our family members who have been supporting us since our
first day entering the university. Their support helped us to move forward and keep us pushing
ourselves beyond the limit during the hard time. We also appreciate the support that we
received from our family such as financial support to help us purchase the material needed for
this course. It would not be possible to finish this assignment without the support from them.
We offer our special thanks to all colleagues for their motivation, prayers and their sincere help
during our studies. We would sincerely like to thank all our group members (Aman, Faris,
Sarah and Akmar) who were together through thick and thin. This assignment cannot be
completed without the effort and co-operation from our group members.

Last but not least, we would like to express our gratitude to our friends and respondents
for support and willingness to lend their time answering our questionaire. Their guidance,
encouragement, suggestion and very constructive critism have contributed immensely to the
evolution of our group ideas on this assignement. May Allah shower the above cited
personalities with success and honour in their life.

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1.0 INTRODUCTION

The standard of education in Malaysia is currently improving over the years.
Developments in science and technology are main factors that have a beneficial effect on
students' academic achievements. Students have maximized this ability to use online learning
in recent years. At the time of learning content delivery, students who have used online learning
will communicate with each other and with the educators. This curriculum offers students a lot
of advantages and helps the learning process go smoothly, and they can do better at work at the
same time. If learners can grasp the information using the most common learning style, the
learning process would be more interesting and precise. Distance learning in higher education
is not a recent concept, and information must certainly be gained to boost the quality of
education. This research aims to evaluate the preferable study platform among online distance
learning (e-PJJ) bachelor degree students in the Faculty of Computer and Mathematical
Sciences UiTM Shah Alam and it’s relationship with students characteristic likes gender, age,
course, semester, credit hours and various other factors affecting their learning style.

The analytical student tends to use descriptive method to obtain accurate details and
favoured taking notes in a learning situation. Throughout the learning process, they are always
positive and interested, other times they will use their creativity to generate a mental image.
By watching and listening, they can create a mental image of what they experience. This
approach will help them appreciate their lessons better. By competing with other students and
whether they feel pressured, competitive students learn more efficiently. Competitive learners
influenced by external influences, such as peers, educators, and parents. Therefore, if students
aware of their choice for learning styles, they can gain more knowledge in a shorter period.
This research provides descriptions of the importance of the learning styles of students to assist
them in being able to achieve in their studies. If preferred learning styles are known for various
minority groups, then specialized teaching techniques can be applied to these students for
further improvement.

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1.1 BACKGROUND OF STUDY

It is possible to describe learning as lasting changes in life-induced behaviour. The style
of learning refers to the preferred way for a person to process new knowledge for successful
learning. For an individual, the learning process is different; learning does not occur in all
students at the same level and standard, even in the same educational setting. This may be
linked to the diverse backgrounds, abilities, limitations, interests, goals, motivation levels, and
research approaches of students. As for part-time students are much more likely to have careers
and families in general, and may thus face challenges balancing several distinct goals. Although
some individuals who embark on a university course immediately after school can do so
because it is a good way to delay big decisions about what to do with one's life, there may be
a strong reason for others who study part-time to do so. They may want to advance their career
or they may have a specific topic that they are very interested in.

There are bigger challenges such as balancing of conflicting interests, finance, and
studying itself. The work itself can not be avoided, and even for those who are highly educated,
but who have not studied for a while, the need for essay writing, critical thinking, and absorbing
a lot of information can prove overwhelming. Therefore it is necessary to give part-time
students assistance with study skills. Educators should become more conscious of these varied
approaches to enhance undergraduate education. Learning styles can help students and teachers
understand how to strengthen the way they learn and teach. Determining the learning patterns
of students offers details regarding their particular interests. Understanding learning styles will
make it easier for more successful curriculum and educational programs to be produced,
updated, and developed. It can also facilitate the participation of students in these programs
and encourage them to develop professional knowledge. Therefore, to achieve more productive
learning, defining the learning style is very valuable.

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1.2 PROBLEM STATEMENT
The biggest challenge for faculty teaching in college multicultural classrooms is to build
teaching methodologies that help all students learn and understand the topics. It is important to
investigate the learning styles of students to have the best learning environment for students
and to use learning methods that are appropriate for their learning. Students have different
background, strengths and weaknesses, desires, goals, senses of duty, motivation levels, and
research approaches. The knowledge of how students learn affects both students and their
progress. There is a gap in the literature concerning this specific category of adult learners,
particularly when it comes to minority groups. Education aims not only to teach subject areas
to students but also to develop skills in all their preferred methods of learning. Practically, we
hope that the findings will be significant to education stakeholders, including understanding
the cultures represented by students on how to determine on which methods of
teaching/learning may be used to enhance learning in various subject areas.

1.3 OBJECTIVES
The objectives of this study is to identify the preferable study platform and their relation
between the characteristics of students among online distance learning (e-PJJ) bachelor's
degree students at the UiTM Shah Alam Faculty of Computer and Mathematical Sciences.

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2.0 METHODOLGY

This is a descriptive statistics (DS) survey where quantitative data and qualitative data obtained
from survey form to identify the preferable study platform and their relation between the
characteristics of students among online distance learning (e-PJJ) bachelor's degree students at
the UiTM Shah Alam Faculty of Computer and Mathematical Sciences. A survey questionnaire
was administered among 30 e-PJJ students that involved in three programs of Computer
Science which is CS230 - Bachelor of Computer Science (Hons), CS240 - Bachelor of
Information Technology (Hons), CS255 - Bachelor of Computer Science (Hons) Data
Communication & Networking.

2.1 DEFINE POPULATION

In this research, the target population consisted of 30 e-PJJ UiTM bachelor degree students in
Faculty of Computer & Mathematical Sciences. This comprised 60% boys and 40% girls as
this students were considered appropriate for the study because e-PJJ is a type of e-learning
system which enables working adults to participate in the distance learning program of UiTM.
The system provides students with access to course materials and lecture notes, as well as
interactions between students and lecturers.

2.2 DEFINE VARIABLES

The method of sampling used to conduct this project is a stratified sampling technique.
Stratified sampling technique is a sample obtained by dividing the population into subgroups
or strata according to some characteristic relevant to the study. The main principle of the
stratified sampling is that each member of the population has an equal chance of being selected
to be in sample and that the sample replicates the population. The selection of the sample was
done at four levels. First, the target population was categorized into three courses (CS230 -
Bachelor of Computer Science (Hons), CS240 - Bachelor of Information Technology (Hons)
and CS255 - Bachelor of Computer Science (Hons) Data Communication & Networking) and
the percentage of each course to the population was computed. For instance, course CS230 had
12 students representing about 40% of the population, CS240 had 13 students representing
about 43.3% and CS255 had 5 students representing 16.7 % of the population.

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2.3 DATA COLLECTION

Data were collected using a self-constructed questionaire that was administered among
UiTM e-PJJ degree students and the link was sent via whatsapp group of intake March 2020.
The participation to answer the survey was voluntarily. Clear instructions were given to the
students on how to fill the survey and their ability to choose one or more option depends on the
questions to reflect their perception. The survey was kept open from 13th November to 14th
November 2020. Stratified sampling technique were implemented in this survey as 30 out of
62 students were selected from the survey. The collected responses were then inserted in an
excel sheet, and sorted according to question, age, course, semester, credit hour, study platform
and etc.

Then participants’ preferences were grouped to explore the collective responses to
identify any possible patterns. The questionnaire is provided in the appendix. The questionaire
was made up of two sections. Section A focused on demographic data such as age, course,
semester, credit hour, study platform, etc and section B measured the variables on an adjective
checklist. Question 1 was measured using paired comparison scale, question 17 & 18 measured
on a 5-point frequency scale (1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often and 5 = Always)
and question 19 were measured on a 5-point semantic distance scale (1 = Very dissatisfied, 2
= Not satisfied, 3 = Neutral, 4 = Satisfied and 5 = Very satisfied).

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3.0 STUDY DESIGN

The statistical procedure and type of variables used in obtaining the data was shown in below
table:

Question Variables Type of variables Scale of
Measurements
1 Gender Qualitative Nominal Data
Qualitative
2 Age Qualitative Interval Data
Qualitative Nominal Data
3 Course Qualitative Interval Data
Qualitative Interval Data
4 Semester
Qualitative Nominal Data
5 How many credit hours do you
take this semester Qualitative Nominal Data

6 Which platforms are you prefer Nominal Data
during online class

7 What times do you prefer to
study

8 Preferable methods use to study

9 What types of students are you Qualitative Nominal Data

10 How good are you with the Qualitative Nominal Data
following skills Qualitative Nominal Data
Qualitative Nominal Data
11 What place or situation you Qualitative Nominal Data
prefer to study Qualitative Nominal Data

12 How is your concentration
during studies

What would you do when you
13 don’t understand what you are

learning in class

14 How do you prepare for your
exam

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15 How much pressure do you feel Qualitative Nominal Data
while studying Ratio Data
Quantitative
16 How many hours you spend per Quantitative Nominal Data
day to study Qualitative Nominal Data
Qualitative Nominal Data
Are you easily distracted from
17

studying

18 Do you feel confident and
relaxed when taking tests

19 Are you satisfied with your
grades

Figure 1: statistical procedure and type of variables used in obtaining the data.

Based on the above data, we have come out with two type of variables:

1. Qualitative Data
2. Quantitative Data

Using this two type variables, we presented the data using pie chart and bar chart. The data as
shown below:

Female
12 (40%)

Male
18 (60%)

Figure 2: Gender of respondent.

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31-35 y/o 36-40 y/o
2 (6.7%) 3 (10%)

26-30 y/o 41-45 y/o
6 (20%) 3 (10%)

46-50y/o
1 (3.3%)

21-25 y/o
15 (50%)

Figure 3: Age of respondent.

CS240 CS255
13 (43.3%) 5 (16.7%)

CS230
12 (40%)

Figure 4: Course taken by respondent.

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Semester 2 Semester 3
21 (70%) 2 (6.7%)

Semester 4
3 (10%)

Semester 1
4 (13.3%)

Figure 5: Semester taken by respondent.

11-14 credit hours 15-18 credit hours
21 (70%) 5 (16.7%)

3-6 credit hours
3 (10%)

7-10 credit hours
9 (30%)

Figure 6:Credit hours taken by respondent.

Figure 7: Preferred platform used by respondent during online class.
Note: This question allow respondent to select more than 1 option (multiple choices), hence it explains the total
of frequency is more than 30.

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Late Night
10 (33.3%)

Evening
5 (16.7%)

Afternoon Morning
6 (20%) 9 (30%)

Figure 8: Preferred study time by respondent.

Figure 9: Preferred study method by respondent.

Note: This question allow respondent to select more than 1 option (multiple choices), hence it explains the total
of frequency is more than 30.

Only study when quizzes, test
and final exams are near.
16 (53.3%)

Always Study
14 (46.7%)

Figure 10: Type of student that represent respondent when studying.

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Figure 11: Studying skill acquired by respondent.

Note: This question allow respondent to select more than 1 option (multiple choices), hence it explains the total
of frequency is more than 30.

Coffee School study
Shop lounge Classroom
4 (13.3%) 1 (3.3%) 3 (10%)

Bedroom Gazebo
12 (40%) 1 (3.3%)

Living hall -
silent
1 (3.3%)
Living
room
1 (3.3%)

Library
7 (23.3%)

Figure 12: Preferred study location by respondent.

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Figure 13: Concentration level by respondent when studying.
Note: This question allow respondent to select more than 1 option (multiple choices), hence it explains the total
of frequency is more than 30.

Figure 14: Action taken by respondent if they don’t understand the subject during learning session.
Note: This question allow respondent to select more than 1 option (multiple choices), hence it explains the total
of frequency is more than 30.

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Figure 15:Respondent readiness for examination.

Note: This question allow respondent to select more than 1 option (multiple choices), hence it explains the total
of frequency is more than 30.

Some degree of pressure Not much pressure
18 (60%) 3 (10%)

A lot of pressure
9 (30%)

Figure 16: Pressure level encountered by respondent when studying.

1-2 hours 3-4 hours
11 10
(36.7%) (33.3%)

Less than one hour
9 (30%)

Figure 17: Time taken to study by respondent.

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17. Are you easily distracted from studying?

Figure 18: Distraction level by respondent when studying.

18. Do you feel confident and relaxed when taking tests?

Figure 19: Confident and relax level by respondent when studying.

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19. Are you satisfied with your grades?

Figure 20: Respondent satisfaction with their grades.

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4.0 RESULTS

4.1 DESCRIPTIVE STATISTICS

In order to find the most preferable study platform among online distance learning (e-PJJ)
UiTM bachelor degree students in Faculty of Computer and Mathematical Sciences, we
focused on four (5) variables that consists of age, credit hours, course, study time and study
platform. Below is the calculation for the chosen variables:

1. Quantitative Data

i. Age

3.30%

10%

10% 50% 21 - 25 years old
6.70% 26 - 30 years old
31 - 35 years old
36 - 40 years old
41 - 45 years old
46 - 50 years old

20%

Figure 21: Respondent age range.

Figure 21 shows the survey distribution among Faculty of Computer and Mathematical
Sciences students based on their age range. Majority of the respondents age are between 21 to
25 with percentage of 50% followed by students at age between 26 to 30 with percentage at
20%. While the least respondent is from age 46 to 50 with only 3.3%.

Grouped Data – Respondent Age Range

Sample size = 30 Mean = 29

Minimum value = 1 Median = 25.5

Maximum value = 15 Mode = 23.625

Range = 14 Variance = 61.03

Midrange = 8 Standard Deviation = 7.81

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Measures of Central Tendency (for grouped data)

For mean it is supposed to be done like as shown below,

Mean, ̄ =  fx
n

870
x̄ = 30

̅ = 29 years old

For median it is supposed to be done like as shown below;

 f[n − m−1 • C

Median, ~x = Lm + 2
[f ]
m

Then from the data provided, the median = 15.5th value which is in the class of 26-30 hence
L=25.5, N=30, F=15, f=6 and with W=5.

Hence now the median become,

Median, ~x = 25.5 + [320−15] ⋅ 5

6

~x = 25. 5

For the mode, a modal class will be that 21-25 years old but to get the mode value it is
calculated as shown below,

Mode, xˆ = Lm + [ 1 ] • C
1+ 2

Then now L=20.5, fm-1=0, fm=15, fm+1=6 and class width W= 5.
Now the mode become,

Mode, ̂ = 20.5 + [(15−01)5+−(015−6)] ⋅ 5
̂ = 23.625

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Age Number of Midpoint x² fx fx² Cumulative

Student / (x) frequency

21 – 25 Frequency (f) 23 529 345 7935 15
26 – 30 15 28 784 168 4704 21
31 – 35 6 33 1089 66 2178 23
36 – 40 2 38 1444 114 4332 26
41 – 45 3 43 1849 129 5547 29
46 – 50 3 48 2304 48 2304 30
1

30 7999 870 27000

Table 1: Grouped Data – Respondent Age Range.

For variance of sample grouped data is obtained using the following formula,

∑ ⋅ 2 − ( ⋅ )2

, 2 =
− 1

2 = 27000 − (870)2
30

30 − 1

2 = 1770
29

2 = 61 ⋅ 03

And now to get the standard deviation, we get the square root of variance,

Standard deviation, s = f (x − x)2

n −1

= √61.03
= 7 ⋅ 81

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ii. Credit Hours

10%

16.70%

30% 3 - 6 credit hours
7 - 10 credit hours
11 - 14 credit hours
15 - 18 credit hours

43.30%

Figure 22: Credit hours taken by respondent.

Figure 22 shows the survey distribution among Faculty of Computer and Mathematical
Sciences students based on credit hours taken by them. Majority of respondent register for 11
to 14 credit hours with percentage at 43.3% followed by 7 to 10 credit hours with percentage
at 30%, and there is also respondent who took 15 to 18 credit hours with percentage at 16.7%.

Grouped Data – Credit Hours Taken by Respondent

Sample size = 30 Mean = 11.17

Minimum value = 3 Median = 25.5

Maximum value = 13 Mode = 11.83

Range = 10 Variance = 12.51

Midrange = 8 Standard Deviation = 3.54

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Measures of Central Tendency (for grouped data)

For mean it is supposed to be done like as shown below,

Mean, x =  fx
n

335
̅ = 30
̅ = 11.17

For median it is supposed to be done like as shown below,

 f[n − m−1 • C

Median, ~x = Lm + 2
[f ]
m

Then from the data provided, the median = 15.5th value which is in the class of 11-14 hence
L=10.5, N=30, F=12, f=13 and with W=4.

Hence now the median become,

Median, ~x = 10.5 + [320−12] ⋅ 4

13

~x = 25. 5

For the mode, a modal class will be that 11-14 credit hours but to get the mode value it is
calculated as shown below,

Mode, xˆ = Lm + [ 1 ] • C
1+ 2

Then now L=10.5, fm-1=9, fm=13, fm+1=5 and class width W= 4.
Now the mode become,

13 − 9
Mode, ̂ = 10.5 + [(13 − 9) + (13 − 5)] ⋅ 4

̂ = 11.83

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Credit Number of Midpoint x² fx fx² Cumulative
Hours Student / (x) frequency
Frequency 13.5 60.75
3–6 4.5 20.25 76.5 650.25 3
7 – 10 (f) 8.5 72.25 162.5 2031.25 12
11 – 14 3 12.5 156.25 82.5 1361.25 25
15 – 18 9 16.5 272.25 335 4103.5 30
13
5
30

Table 2: Grouped Data – Credit hours taken by respondent.

For variance of sample grouped data is obtained using the following formula,

∑ ⋅ 2 − ( ⋅ )2

, 2 =
− 1

2 = 4103 ⋅5 − (335)2
30 − 30

1

2 = 362.667
29

2 = 12 ⋅ 51

And now to get the standard deviation, we get the square root of variance,

Standard deviation, s = f (x − x)2

n −1

= √12 ⋅ 51

= 3 ⋅ 54

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2. Qualitative Data

i. Course

16.70%

40% CS230 - Bachelor of Computer
Science (Hons)

CS240 - Bachelor of Information
Technology (Hons)

CS255 - Bachelor of Computer
Science (Hons) Data
Communication & Networking

43.30%

Figure 23: Course taken by respondent.

Figure 23 shows the survey distribution among Faculty of Computer and Mathematical
Sciences students based on course taken by them. Majority of respondent sign up for CS240 –
Bachelor of Information Technology (Hons) with percentage at 43.30% followed by CS230 –
Bachelor of Computer Science (Hons) with percentage at 40% and lastly, CS255 – Bachelor
of Computer Science (Hons) Data Communication & Networking with percentage at 16.70%.

Ungrouped Data – Course Taken by Respondent

Sample size = 3 Mean = 10

Minimum value = 5 Median = 12

Maximum value = 13 Mode = None

Range = 8 Variance = 19

Midrange = 9 Standard Deviation = 4.36

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Measures of Central Tendency (for ungrouped data)

For mean it is supposed to be done like as shown below,
∑

, x̅ =
12 + 13 + 5

x̅ = 10
x̅ = 10

For median it is supposed to be done like as shown below,
Sort in ascending order = 5, 12, 13
Select the middle value.

Median, ̃ = 12

For mode it is supposed to be done like as shown below,
Value that occurs most often.

Mode, ̂ = None

Course Number of Percentage ̅ − ̅ ( − ̅)²
Student / 40% 10 2 4
CS230 - Bachelor of 43% 10 3 9
Computer Science (Hons) 12
CS240 - Bachelor of 16.70% 10 -5 25
Information Technology 13
(Hons)
CS255 - Bachelor of 5
Computer Science (Hons)
Data Communication &
Networking

Table 3: Ungrouped Data – Course Taken by Respondent

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Total ∑( − ̅)² = 38

For variance of sample grouped data is obtained using the following formula,

Variance, 2 = ∑(x − x̅)2
n−1

38
=3−1

= 19

And now to get the standard deviation, we get the square root of variance,

Standard deviation, s = √19
= 4.36

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ii. Study Time

30%

33.30%

Morning
Afternoon
Evening
Late night

16.70% 20%

Figure 24: Study Time by Respondent.

Figure 24 shows the survey distribution among Faculty of Computer and Mathematical
Sciences students based on their preferred study time. Majority of respondent to study at late
night with percentage at 33.3% and followed by studying in the morning with percentage at
30% least preferred study time is in evening with percentage at 16.7% only.

Ungrouped Data – Study Time by Respondent

Sample size = 4 Mean = 7.5

Minimum value = 5 Median = 7.5

Maximum value = 10 Mode = None

Range = 5 Variance = 5.6667

Midrange = 7.5 Standard Deviation = 2.38

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Measures of Central Tendency (for ungrouped data)

For mean it is supposed to be done like as shown below,
∑

, x̅ =
9 + 6 + 5 + 10

x̅ = 4
x̅ = 7.5

For median it is supposed to be done like as shown below,

Sort in ascending order = 5, 6, 9, 10.

Select the middle value.

Median, ̃ = 6+9
2

= 7.5

For mode it is supposed to be done like as shown below,
Value that occurs most often

Mode, ̂ = None

Study Time Number of Percentage ̅ − ̅ ( − ̅)²
Student /
Morning 30% 7.5 1.5 2.25
Afternoon 9 20% 7.5 -1.5 2.25
Evening 6 16.70% 7.5 -2.5 6.25
Late night 5 33.30% 7.5 2.5 6.25

10

Table 4: Ungrouped Data – Study Time by Respondent.

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Total ∑( − ̅)² = 17

For variance of sample grouped data is obtained using the following formula,

Variance, 2 = ∑(x − x̅)2
n−1

17
=4−1

= 5.6667

And now to get the standard deviation, we get the square root of variance,

Standard deviation, s = √5.6667
= 2.38

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iii. Study Platforms

Webex 6.06%

Microsoft Team 24.24%

Google Meets 33.33%

Telegram 24.24%

Whatsapp 10.12%

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00%

Figure 25: Study platform used by respondent.

Figure 25 shows the survey distribution among Faculty of Computer and Mathematical
Sciences students based on study platform used by them. Majority of respondent using
Telegram and Microsoft Team with percentage at 24.24% respectively and least used platform
is Webex with percentage at 6.06% only.

Ungrouped Data – Platform Used by Respondent

Sample size = 5 Mean = 13.2

Minimum value = 4 Median = 16

Maximum value = 22 Mode = 16

Range = 18 Variance = 51.2

Midrange = 13 Standard Deviation = 7.16

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Measures of Central Tendency (for ungrouped data)

For mean it is supposed to be done like as shown below,
∑

, ̅ =
8 + 16 + 22 + 16 + 4
̅ = 5

̅ = 13.2

For median it is supposed to be done like as shown below,
Sort in ascending order = 4, 8, 16, 16, 22.
Select the middle value.

Median, ̃ = 16

For mode it is supposed to be done like as shown below,
Value that occurs most often

Mode, ̂ = 16

Platform Number of Percentage ̅ − ̅ ( − ̅)²
Student /
Whatsapp 10.12% 13.2 -5.2 27.04
Telegram 8 24.24% 13.2 2.8 7.84
Google Meets 16 33.33% 13.2 8.8 77.44
Microsoft Team 22 24.24% 13.2 2.8 7.84
Webex 6.06% 13.2 -9.2 84.64
16

4

Table 5: Ungrouped Data – Platform Used by Respondent

//This question allow respondent to select more than 1 option (multiple choices), hence it
explains the total of frequency is more than 30.

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Total ∑( − ̅)² = 204.8

For variance of sample grouped data is obtained using the following formula,

Variance, 2 = ∑(x − x̅)2
n−1

204.8
= 5−1

= 51.2

And now to get the standard deviation, we get the square root of variance,

Standard deviation, s = √51.2
= 7.16

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4.2 STATISTICAL ANALYSIS

1. Histogram for the data of the age and number of students.

The histogram depicts that majority of the students were in the age group of between 21-25
years with least of students being in the age group of 46-50.
Measures of Variation (Dispersion)
For Coefficient of Variance, it is supposed to be done like as shown below,

Coefficient of Variance, CV = s x100%
x

7.81
= 29 × 100%

= 26.93%

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For Pearson’s Coefficient of Skewness it is supposed to be done like as shown below,

Pearson’s Coefficient of skewness, x − xˆ
s

29 − 23.625
= 7.81

= 0.69
Measures of Skewness,

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2. The frequency polygon based on table two credit hours and number of students as

shown below:

Measures of Variation (Dispersion)
For Coefficient of Variance, it is supposed to be done like as shown below,

Coefficient of Variance, CV = s x100%
x

3.54
= 29 × 100%

= 12.21%

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For Pearson’s Coefficient of Skewness, it is supposed to be done like as shown below,

Pearson’s Coefficient of skewness, x − xˆ
s

29 − 11.83
= 3.54

= 4.85

Measures of Skewness,

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5.0 FINDINGS

Course:

A survey has been conducted to examine if courses differ in their preferable study
platform. Three dependent variables were used: (CS230 - Bachelor of Computer Science
(Hons), CS240 - Bachelor of Information Technology (Hons) and CS255 - Bachelor of
Computer Science (Hons) Data Communication & Networking). The independent variable was
courses in Faculty of Computer and Mathematical Sciences for e-PJJ students. The results
showed that there was a statistically significant differences between the students in three
courses on the combined dependent variables where the sample size (3), mean (10), variance
(19) and the standard deviation (4.36).

The results showed that CS240 students prefer Google Meet (9 counts), followed by
Telegram and Microsoft Team (8 counts), then Whatsapp (3 counts) and Webex (2 counts).
CS230 students put similar emphasis on Google Meet (10 counts), followed by Telegram and
Microsoft Team (6 counts), then Whatsapp (5) and Webex (2 counts). Students of CS255 prefer
Google Meet (3 counts) followed by Telegram and Microsoft Team (2 counts). In this three
courses, Webex and Whatsapp were least preferred study platform, Telegram were slightly
more preferred yet with close total frequencies of Microsoft Team study platform. Google
Meet study platform was more preferred among the three courses.

Study Time:

Based on studies of preferred study time by students, there are four dependent variables
were used: Morning, afternoon, evening and late night. The independent variable was courses
in Faculty of Computer and Mathematical Sciences for e-PJJ students. The results showed that
there was a statistically significant differences between the students in three courses on the
combined dependent variables where the sample size (4), mean (7.5), variance (5.6667) and
the standard deviation (2.38).

The results showed that CS240 students prefer studying in the morning (9), afternoon
(6), evening (5) and late night (10). In this four preferred study time, evening and afternoon
were the least preferred study time. While late night was the most preferred study time and
followed by studying in the morning by students.

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Study Platform:

According to the findings of the study, five dependent variables were used: Google
Meet, Microsoft Team, Telegram, Whatsapp and Webex. The independent variable was study
platform. The results showed that there was a statistically significant differences on the
combined dependent variables where the sample size (5), mean (13.2), variance (51.2) and the
standard deviation (7.16).

The result revealed that the most preferred study platform among online distance
learning (e-PJJ) UiTM bachelors degree students in Faculty of Computer & Mathematical
Sciences was Google Meet (22 counts). Followed closely by Telegram (16 counts) and
Microsoft Team (16 counts), then Whatsapp (8 counts) and Webex (4 counts) comes at last.
Since this option allow respondent to select more than 1 option (multiple choices), hence it
explains the total of frequency is more than 30.

Age:
A research has been conducted to examine if among online distance learning students

differ in their preferable study platform according to their age. Five dependent variables were
used: Google Meet, Microsoft Team, Telegram, Whatsapp and Webex. The independent
variable was age. Students were categorized into four age groups, Group 1: 21-25, Group 2:
26-30, Group 3: 36-40 and Group 4: 41-45. The results showed that there was a statistically
significant differences between four age group on the combined dependent variables where the
sample size (30), mean (29), variance (61.03) and the standard deviation (7.81).

In general, they all preferred Google Meet with trivial difference between the four
preference in each age group. To be more specific, first age group mostly preferred Google
Meet and second age group almost preferred Telegram and Google Meet equally. To the third
group, they tend to Google Meet, Telegram and Microsoft Team equally, while for the fourth
and fifth group, Google Meet was best preferred.

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Credit Hours:

Data were analyzed using frequency polygon. The data were reported as the percentage
of respondents among online distance learning (e-PJJ) UiTM bachelors degree students in
Faculty of Computer & Mathematical Sciences. Credit hours was classified into four groups:
Group 1 (3-6 credit hours), Group 2 (7-10 credit hours), Group 3 (11-14 credit hours) and
Group 4 (15-18 credit hours). The results showed that there was a statistically significant
differences between four credit hours group where the sample size (30), mean (11.17), variance
(12.51) and the standard deviation (3.54).

As a result, it showed that majority (e-PJJ) students took about 11-14 credit hours per
semester. Followed by 7-10 credit hour, then 15-18 credit hours and 3-6 credit hours comes at
last. This factor might depends on students availability and accessibility as majority of the
population are adult learners.

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6.0 DISCUSSION

This study attempted to determine the association between the preferable study platform and
characteristics of students among online distance learning (e-PJJ) UiTM bachelor’s degree
students in Faculty of Computer & Mathematical Sciences. The preferable study platform
among e-PJJ students was identified through this study, and the relationship between the
preferable study platform and the characteristics of students was also clearly sorted out. In
general, learning style preferences were influenced by students’ characteristics. Therefore, it
can be suggested that further comprehensive research is needed to understand the significant
factors that have influenced the preferred online distance learning (e-PJJ) student study
platform.

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APPENDIX

Studying Habits among UiTM PJJ Degree Students

Dear respondents,

We are students from STA416 - Applied Probability and Statistics. The data obtained is for our
subject and this survey is carried out for the research titled 'Studying Habits among UiTM PJJ
Degree Students’. Any information obtained in connection with this study that can be identified
with you will remain confidential. If you are unsure about how to answer the questions, please
give the best answer as you can. We rely on your sincere response as it is the main contribution
for our research. Thank you for your time and cooperation.

* Required

SECTION A: DEMOGRAPHIC INFORMATION
Instruction: Please tick (/) for an appropriate answer.

1. Gender *
Mark only one oval.
Male
Female

2. Age *
Mark only one oval.
21 – 25 years old
26 – 30 years old
31 – 35 years old
36 – 40 years old
41 – 45 years old
46 – 50 years old
Other: __________

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3. Course *
Mark only one oval.

CS230 - Bachelor of Computer Science (Hons)
CS240 - Bachelor of Information Technology (Hons)
CS255 - Bachelor of Computer Science (Hons) Data Communication & Networking

4. Semester *
Mark only one oval.

1
2
3
4
5
Other: __________
SECTION B:
Instruction: Please tick (/) for an appropriate answer.

5. How many credit hours do you take this semester? *
Mark only one oval.

3 – 6 credit hours
7 – 10 credit hours
11 – 14 credit hours
15 – 18 credit hours

6. Which platforms are you prefer during online class? *
Check all that apply.

Whatsapp
Telegram
Google Meets
Microsoft Teams
Webex

7. What times do you prefer to study? *
Mark only one oval.

Morning
Afternoon
Evening
Late Night

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8. Preferable methods use to study? *
Check all that apply.

Study group
Mind maps
Listening to music
Alone
Other: __________

9. What types of students are you? *
Mark only one oval.

Always study
Only study when quizzes, test and final exams are near
Never study

10. How good are you with the following skills? *
Check all that apply.

Memorizing
Writing
Solving math problem
Understanding what graphs and tables indicate
Other: ________________________________

11. What place or situation you prefer to study? *

Mark only one oval.
Library
Bedroom
Coffee Shop
School's study lounge
Classroom
Other: ___________________

12. How is your concentration during studies? *
Check all that apply.

I concentrate well when studying.
I listen attentively in class.
I can focus my attention without too much effort
I work 50 minutes and then take a 10-minute break.

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13. What would you do when you don’t understand what you are learning in class? *
Check all that apply.

Ask my lecturers.
Ask my friends.
Research from reference books on my own.
Research online.

14. How do you prepare for your exam? *
Check all that apply.

I study in a group, or with a friend.
I adjust my study methods for different courses.
I answer past year final questions to study.

15. How much pressure do you feel while studying? *
Mark only one oval.

A lot of pressure.
Some degree of pressure
Not much pressure
I don’t feel pressure at all.

16. How many hours you spend per day to study? *
Mark only one oval.

Less than one hour
1 - 2 hours
3 - 4 hours
More than 4 hours

Please rank between 1 to 5 (Never to Always) for question 17 and 18.

1=Never 2=Rarely 3=Sometimes 4=Often 5=Always

Never Rarely Sometimes Often Always

17. Are you easily distracted from
studying? *
18. Do you feel confident and
relaxed when taking tests? *

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Please rank between 1 to 5 (Very dissatisfied to Very satisfied) for question 19.

1=Very dissatisfied 2=Not satisfied 3=Neutral 4=Satisfied 5=Very satisfied

Very Not Neutral Satisfied Very
dissatisfied satisfied satisfied

19. Are you satisfied with your
grades? *

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