Compiled Shoe

8/10/2019 Compiled Shoe

1/26

Abstract: Main objective, statistical method, summary of most important results,major conclusion,

maximum 2 pages.Minimum 1 page.

One page e raikho.


2/26

Introduction:

Club activities (extracurricular activities) have long been recognized for influencing social skills

of students. Besides creating a culture and promoting the spirit of students, extracurricularactivities have been thought to have a relationship with students academic performance

development of responsibility, discovering their abilities and interest, self discipline and

leadership skills.

BRAC University has a total of more than five thousand (5000) students in its undergraduate and

post-graduate programs. Enlistment in at least one club is mandatory for the students of BRAC

University. There are about 40 clubs and forums in this university. Active members in the club

have to do different activities according to their responsibilities and characteristics of the club.

The general idea of this research is to find out whether there is a relationship between club

activities and students academic performanceor not. The research is on the students of BRAC

Business School of BRAC University. As a complete list of the population is unavailable, this

research is based on a sample drawn from the population. We want a broader concept about the

controversial relationship between club activities and students CGPA (Cumula tive Grade Point

Average). This research has been conducted using SPSS (Statistical Package for the Social

Sciences), version 11.5 and Microsoft Word 2007. SPSS has been used to record and analyze the

data collected. Microsoft Word, on the other hand has been used to prepare the questionnaire.

A number of different statistical techniques have been used in this study. Frequency tables and

cross tabulations are used to show the structure of the distribution. On the one hand, chi square is

used to measure the association between qualitative variables, and on the other, correlation is

used to calculate the strength of the relationship between different quantitative variables.

Regression has been used to analyze the influence of different variables on others. Finally, the

research uses hypothesis testing to examine the significance of the sample findings in the

population.

The research is significant .There can be two reasons behind its significance. If there is no

relationship found, universities may reduce their expenditure and save their time due to club


3/26

activities. If there is a positive relationship between Club activities and academic performance,

universities may encourage their students more about being engaged in club activities. If there is

a negative relationship, club activities will not be an effective program.

Statement of the problem:

Over the years the costs and effect of club activities (extracurricular activities) have

generated many studies and numerous debates in their relation to academic performance.

Many Authorities have had controversies on whether a great deal of time and money should be

devoted to these activities especially in this time of tight budget. They believed that

students should focus solely on a narrowly defined traditional in class instruction that

impact academic achievement. Whether or not there is a relationship between students

participation in University based club activities and students performance is yet to be

undertaken.

Research Questions:

Our research question is relational. The research questions are-

1. Is there any association between club activities and academic performance?

2. Is there any relationship between club activities and academic performance?

3. What is the pattern of the relationship if there is any relationship?

Research hypothesis:

The following hypotheses were postulated to guide the investigation:

Null hypothesis 1-Club activities have no Influence on the students academic performance

(CGPA)

Alternative hypothesis 1-Club activities have some influence on the students academic

performance (CGPA)


4/26


5/26

Sampling:

This research is based on sampling model. We followed probability sampling method in this

research.

Population:

Theoretical population: All the students of BRAC Business School of BRAC University.

Accessible population: All the students of BRAC Business School are not accessible. For

example, some of them graduated and left the university, some of the students might not be

available in the university during the survey etc. So, we will be excluding such part of the

population.

Sampling frame:

The sampling frame is available here. The sampling frame is the list of existing BRAC Business

School Student ID Numbers.

Sampling method:

We will be using two stage simple random cluster sampling in this research. Firstly, we divided

our population into different clusters according to different sections of the core major courses

offered by BRAC Business School. We are choosing the sections of the major courses because

our study is only on the students of the BBA program. After that, we selected 5 sample sections.

Then, we selected 10 students from every section (a total of 50) randomly by simple random

sampling without replacement.

Variables:

The Variables used are-

Gender, Club Membership status, Weekly Club Activity Hour, Status of Helpfulness and

Harmfulness of Club activities, Weekly study hour, Class Skipping Status, CGPA Before Joining

Club, CGPA After Joining Club and Preference Status, Change in CGPA Before and After

joining the club (Current CGPA).


6/26

Measurement Scales:

For qualitative data we use nominal and ordinal scale, and for quantitative data we use interval

and ratio scale. In case of nominal scale we can only do counting and in case of ordinal scale we

can do both counting and ranking. In terms of interval scale, along with counting and ranking,

Addition and subtraction can also be done. Finally for ratio scale counting, ranking, Addition,

subtraction, multiplication and division all is possible. The measurement scales for the chosen

variables are as follows:

Gender : Nominal

Club Membership status : Nominal

Weekly Club Activity Hour : Ratio

Weekly Club Activity Hour range: Ordinal

Helpfulness Status : Ordinal

Harmfulness Status : Ordinal

Weekly study hour : Ratio

Class Skipping Status : Nominal

CGPA Before Joining Club : Ratio

CGPA After Joining Club : Ratio

Change in CGPA Before and after joining the club: Ordinal

Preference Status : Nominal

Research Design:

The research is a relational research. Firstly unit of analysis is identified and then the variables

are defined to collect data and measurement. The sampling method used is the probability

sampling and the technique of sampling is two stage simple random cluster sampling. The

Collection of data is done through setting a questionnaire relevant to the Chosen variables and


7/26

the collected data is sorted to different measurement scales. Finally the data is being analyzed

with the SPSS software to properly define different variables and their relationships to each

other.


8/26

Statistical Analysis

Frequency Distribution

The Fifty respondents of this study can be classified into various categories. The distribution of

the sampling units within these categories can be best explained by frequency tables. A

frequency table is constructed by arranging collected data values in ascending order of

magnitude with their corresponding frequencies. Such a table consists of the frequency,

percentage, valid percentage and cumulative percentage.

Student gender

Frequency Percent Valid Percent

Cumulative

Percent

Valid Male 22 44.0 44.0 44.0

Female 28 56.0 56.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table illustrates the percentage of respondents gender

(e.g. male and female). Where -

Among 50 respondents 44% belong to the male group

56% of the respondents belong to the female group

Active Club Member


Cumulative

Percent

Valid No 12 24.0 24.0 24.0

Yes 38 76.0 76.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table explains the percentage of respondents who are

active club members. Where -

24% of the respondents are not active club member

76% of the respondents are active club member


9/26

The above mentioned frequency table demonstrates the percentage of respondents

agreement that whether club activity is helpful for their study. Where -

28% of the respondents have strongly agreed that club is helpful for their studies

50% of the respondents have agreed that club is helpful for their studies

The rest 22%of the respondents have agreed that club is not helpful for their studies

Club Kills Study Time


Cumulative

Percent

Valid Strongly Agree 5 10.0 10.0 10.0

Agree 20 40.0 40.0 50.0

Do Not Agree 25 50.0 50.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table demonstrates respondents varying agreement on

whether club activity kills their study time. Now, this table consists of a cumulative

frequency of 50% including strongly agree and agree; excluding the option of do not

agree. Where -

10% of the respondents strongly agree that club activity kills their study time.

40% of the respondents agree that club activity kills their study time.

The rest 50% of the respondents agree that club activities does not kill their study time.

Club Helps For Study


Cumulative

Percent

Valid Strongly Agree 14 28.0 28.0 28.0

Agree 25 50.0 50.0 78.0

Do Not Agree 11 22.0 22.0 100.0

Total 50 100.0 100.0


10/26

Bunk Classes for Club


Cumulative

Percent

Valid No 33 66.0 66.0 66.0

Yes 17 34.0 34.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table shows the percentage of respondents that bunk

classes for club activities. Where -

66% of the respondents have not bunked any classes for club

34% of the respondents have bunked their classes due to club

Prefer Class than Club


Cumulative

Percent

Valid No 1 2.0 2.0 2.0

Yes 49 98.0 98.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table shows the percentage of respondents that prefer

attending classes than club activities. Where -

Only 2% of the respondents do not prefer their classes than club

98% of the respondents prefer classes than club


11/26

CGPA range after joining club


Cumulative

Percent

Valid Poor 3 6.0 6.0 6.0

Good 18 36.0 36.0 42.0

Better 18 36.0 36.0 78.0

Excellent 11 22.0 22.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table illustrates how respondents CGPA has been

impacted after joining club. Where -

CGPA of 6% respondents became poor after joining the club

36% respondents CGPA became good after joining club

36% respondents CGPA have become better after joining club

22% respondents CGPA have become excellent after joining club

Change in CGPA


Cumulative

Percent

Valid Low decrease 17 34.0 34.0 34.0

High Decrease 9 18.0 18.0 52.0

Low Increase 17 34.0 34.0 86.0

High Increase 7 14.0 14.0 100.0

Total 50 100.0 100.0

The frequency table on top illustrates the change in CGPA of the 50 respondents. Here -

34% of the respondents experience low decrease in their CGPA after joining the club.

18% of the respondents experience high decrease in their CGPA after joining the club.

34% of the respondents experience low increase in their CGPA after joining the club.

14% of the respondents experience high increase in their CGPA after joining the club.


12/26

Club Activity Hour range (Weekly)


Cumulative

Percent

Valid Inactive 12 24.0 24.0 24.0

Less Active 5 10.0 10.0 34.0

Moderately Active 24 48.0 48.0 82.0

Extremely Active 9 18.0 18.0 100.0

Total 50 100.0 100.0

The above mentioned frequency table exhibits the percentage of respondents weekly hour

range of their club activity. Where -

24% respondents are inactive.

10% respondents spend less active time in club activities.

48% respondents remain moderately active in club activity weekly.

18% respondents remain extremely active with club activities during a week.


13/26

Cross tabulation

A cross tabulation (often abbreviated as cross tab) displays the joint distribution of two or more

variables. They are usually presented as a contingency table in a matrix format. Whereas a

frequency distribution provides the distribution of one variable, a contingency table describes the

distribution of two or more variables simultaneously. Each cell shows the number of respondents

who gave a specific combination of responses, that is, each cell contains a cross tabulation.

In a cross-tab, a cell is a combination of two or more characteristics, one from each variable.

They give a basic picture about the interrelation of two variables and help to find out interactions

between them. They also make it easy to see the most significant relationships between the two

selected variables.

In this research, a cross tab is constructed. The table generated by SPSS is given below.

Interpretations of the contents of the table follow.

Cross Tabulation 1

Bunk Classes for Club * Change in CGPA Cross tabulation

Change in CGPA

Total

Low

decrease High Decrease Low Increase

High

Increase

Bunk Classes

for Club

No Count 6 8 14 5 33

% within Bunk

Classes for Club

18.2% 24.2% 42.4% 15.2% 100.0%

% within Change in

CGPA

35.3% 88.9% 82.4% 71.4% 66.0%

% of Total 12.0% 16.0% 28.0% 10.0% 66.0%

Yes Count 11 1 3 2 17

% within Bunk

Classes for Club

64.7% 5.9% 17.6% 11.8% 100.0%

% within Change in

CGPA

64.7% 11.1% 17.6% 28.6% 34.0%

% of Total 22.0% 2.0% 6.0% 4.0% 34.0%


14/26

Variable disclosure:

Low decrease = {(-0.29)0} = Decrease in CGPA from 0.00 to 0.29

High decrease = {(-1)(-.30)} = Decrease in CGPA from 0.30-1.00

Low increase = (0.010.25) = Increase in CGPA from 0.01 to 0.25

High increase = (0.26 - 1)= Increase of 0.26-1.00

Conclusion and discussion:

Conclusion 1

35.3% students who have low decrease in CGPA after joining club do not bunk classes.

88.9% students who have high decrease in CGPA after joining club do not bunk classes.

82.4% students who have low increase in CGPA after joining club do not bunk classes

71.4% students who have high increase in CGPA after joining club do not bunk classes

Discussion:

Here we can see only 35.3% students who have low decrease in CGPA after joining club do not

bunk classes, which means 64.7% of them bunk classes. This implies that those have low

decrease in CGPA are not concerned about their studies and a majority of them bunk classes for

the club activities.

88.9% students who have High decrease in CGPA after joining club do not bunk classes and

only 11.1% of them bunk classes for club. That means as after joining club a major decrease has

occurred in their CGPA, therefore, majority of them try not to bunk classes for club.

Total Count 17 9 17 7 50

% within Bunk

Classes for Club

34.0% 18.0% 34.0% 14.0% 100.0%

% within Change in

CGPA

100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 34.0% 18.0% 34.0% 14.0% 100.0%


15/26

82.4% students who have low increase in CGPA after joining club do not bunk classes and only

17.6% of them are serious about club activities. That means majority students who give more

priority to class rather than club has gained lower increase in their CGPA even after joining the

club.

71.4% students who have high increase in CGPA after joining club do not bunk classes and only

28.6% of them Bunk classes. From here it can be said the students who gained high increase in

their CGPA even after joining the club are more serious about their studies and club holds low

priority to them.

Conclusion 2:

64.7% student who bunk classes has low decrease in their CGPA after joining club.

5.9% student who bunk classes has high decrease in their CGPA after joining club.

17.6% student who bunk classes has low increase in their CGPA after joining club.

11.8% student who bunk classes has high increase in their CGPA after joining club.

Discussion:

Students who have the tendency to bunk classes for club very few of them face high decrease in

CGPA but majority of them face low decrease in their CGPA. As low as 17.6% students who

prioritize club has low increase in their CGPA but very few, 11.8% of bunkers manage to gain a

high increase in their CGPA.

Conclusion 3

66.0% students do not bunk classes for club

34.0% students bunk classes for club

34.0% students face low decrease in CGPA after joining the club

18.0% students face high decrease in CGPA after joining the club

34% students face low increase in CGPA after joining the club

14.0% students face high increase in CGPA after joining the club


16/26

10% of the students who does not bunk classes for club have high increase in their CGPA

and 28% of them have a low increase in CGPA.

Only 6% of the respondents who bunk classes have a low increase in CGPA and 4% of

them have a high increase.

Discussion:

Realizing the importance of classes, 66% students do not bunk classes for club activities and

majority of students face low decrease in their CGPA after joining the club. Only a lowest

amount, 14.0%, students face High increase in their CGPA after joining club.

The students who bunk classes for the sake of club activities, only 4% of them experience high

increase in CGPA. On the other hand, the students who does not bunk classes for club activities,

10% of them experience high increase in CGPA.

Chi-Square

Chi-square is a statistical test commonly used to compare observed data with data we would

expect to obtain according to a specific hypothesis. The chi-square test is always testing what

scientists call the null hypothesis, which states that there is no significant difference between the

expected and observed result.

The SPSS generated measure of the Chi-square between smoking status and smoker(s) in the

family is given below.

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 11.362a 3 .010

Likelihood Ratio 11.530 3 .009

N of Valid Cases 50

a. 3 cells (37.5%) have expected count less than 5. The minimum

expected count is 2.38.


17/26

Conclusion 4

The Chi-Square table show that the value is 11.362 which is greater than 0 and the significant

error is only 1% which is lower than 5%.

Discussion:

As the value of the Chi-Square table is greater than 0 and the significant error is less than 5%, it

can be said there is moderate association between bunking classes for club activities and CGPA

after joining club, which nullifies the null hypothesis that there is no influence of club activities

on students CGPA.

Cross Tabulation 2:

In this research, a cross tab is constructed to see the relationship between Club activity hour

range (Weekly) and Change in CGPA. The table generated by SPSS is given below.

Interpretations of the contents of the table follow.

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Club Activity Hour range

(Weekly) * Change in CGPA

50 100.0% 0 .0% 50 100.0%


18/26

Club Activity Hour range (Weekly) * Change in CGPA Cross tabulation

Change in CGPA

TotalLow decrease High Decrease Low Increase High Increase

Club

Activi

tyHour

rang

e

(Wee

kly)

Inactive Count 2 0 5 5 12

% within Club Activity Hour

range (Weekly)

16.7% .0% 41.7% 41.7% 100.0%

% within Change in CGPA 11.8% .0% 29.4% 71.4% 24.0%

% of Total 4.0% .0% 10.0% 10.0% 24.0%

Less Active Count 0 2 2 1 5


range (Weekly)

.0% 40.0% 40.0% 20.0% 100.0%

% within Change in CGPA .0% 22.2% 11.8% 14.3% 10.0%

% of Total .0% 4.0% 4.0% 2.0% 10.0%

Moderately Active Count 11 3 9 1 24


range (Weekly)

45.8% 12.5% 37.5% 4.2% 100.0%

% within Change in CGPA 64.7% 33.3% 52.9% 14.3% 48.0%

% of Total 22.0% 6.0% 18.0% 2.0% 48.0%

Extremely Active Count 4 4 1 0 9


range (Weekly)

44.4% 44.4% 11.1% .0% 100.0%

% within Change in CGPA 23.5% 44.4% 5.9% .0% 18.0%

% of Total 8.0% 8.0% 2.0% .0% 18.0%

Total Count 17 9 17 7 50


range (Weekly)

34.0% 18.0% 34.0% 14.0% 100.0%

% within Change in CGPA 100.0% 100.0% 100.0% 100.0% 100.0%

% of Total 34.0% 18.0% 34.0% 14.0% 100.0%


19/26

Variable disclosure:

Inactive = 0.00 hour

Less Active = (0.5 - 9) hours

Moderately Active = (10 - 16) hour

Extremely Active = (17 - 23) hour

Conclusion and Discussion:

Conclusion 1

11.8% of students who have low decrease in their CGPA after joining club are inactive

0.0% of students who have high decrease in their CGPA after joining club are inactive

29.4% of students who have low increase in their CGPA after joining club are inactive

71.4% of students who have high increase in their CGPA after joining club are inactive

Discussion:

From above it can be summarized that 100% students who have high decrease in their CGPA

spend some time in club activity and 71.4% students who have a high increase in their CGPA are

inactive. That indicates spending time in club activities have a negative impact on students

CGPA and by spending less time on it CGPA can be improved.

Conclusion 2

44.4% students who are extremely active have low decrease in their CGPA after joining

club.

44.4% students who are extremely active have high decrease in their CGPA after joining

club.

11.1% students who are extremely active have low increase in their CGPA after joining

club.

0.0% students who are extremely active have high increase in their CGPA after joining

club.


20/26

Discussion:

It can be said that extremely active members face low or high decrease in their CGPA and very

few of them gain low increase in their CGPA. The point to be noted here is those who are

extremely active club members, they never gain high increase in their CGPA, which indicates

that there is a negative relationship between being active in club and CGPA after joining club.

Conclusion 3

24.0% of students are Inactive

10.0% of students are Less Active

48.0% of students are Moderately Active

18.0% of students are Extremely Active

34.0% students face low decrease in CGPA after joining the club

18.0% students face high decrease in CGPA after joining the club

34% students face low increase in CGPA after joining the club

14.0% students face high increase in CGPA after joining the club

Discussion:

Is can be seen that majority of students are moderately active and very few of them are inactive

or extremely active. On the other hand it can be seen that majority students face low increase or

low decrease in their CGPA after joining Club. From these, it can be concluded that club

activities have some influence over students CGPA and the more active the students are the less

favorable it is to the CGPA.

Chi-Square Tests

Value df

Asymp. Sig. (2-

sided)

Pearson Chi-Square 22.783a 9 .007

Likelihood Ratio 25.505 9 .002

N of Valid Cases 50

a. 14 cells (87.5%) have expected count less than 5. The minimum

expected count is .70.


21/26

Conclusion 4

The Chi-Square table show that the value is 22.783 which is greater than 0 and the significant

error is only .7% which is lower than 5%.

Discussion:

As the value of the Chi-Square table is greater than 0 and the significant error is less than 5%, it

can be said there is more association between weekly club activity status and CGPA after joining

club, which nullifies the null hypothesis that there is no influence of club activities on students

CGPA.

Correlation

Correlation is a process that is used to describe the strength of a relationship between two

variables. Correlation coefficient measures how strong or weak the relation is between the

variables. This value lies between -1 to +1. If there is no relation between the variables, the

correlation coefficient is 0 or very weak. Similarly, if they have positive strong association, the

correlation coefficient would be near about +1. On the other hand, a negative strong relation

contains a value that leans towards -1.The SPSS generated correlation table is given below.

Correlations

Club Activity

Hour (Weekly)

Study Hour

(Weekly)

Difference ofBeginning CGPA

and Current

CGPA

Club Activity Hour (Weekly) Pearson Correlation 1 -.839** -.417

**

Sig. (2-tailed) .000 .003

N 50 50 50

Study Hour (Weekly) Pearson Correlation -.839** 1 .439

**

Sig. (2-tailed) .000 .001

N 50 50 50

Difference of Beginning

CGPA and Current CGPA

Pearson Correlation -.417** .439

** 1

Sig. (2-tailed) .003 .001

N 50 50 50

**. Correlation is significant at the 0.01 level (2-tailed).


22/26

The table above describes about the correlation between the quantitative variables- Club activity

hour, study hour, Change in CGPA before and after joining the club.


The correlation between Club activity hour (weekly) and Study hour (weekly) is strongly

negative (-0.839) and significant error is 0.00%. So, there is a significant negative

relationship between these two variables. This significant correlation nullifies the null

hypothesis 2 . So, there is negative relationship between club activities and study hour.

When the club activity hour increases in a week, the study time is highly reduced.

The correlation between Club activity hour and difference in beginning and current

CGPA is moderately negative and significant error is 0.03%.

The correlation between study hour and difference in beginning CGPA and current

CGPA is moderately positive.


23/26


Extra-curricular activities are thought to have a huge impact towards improving individuals

knowledge, skill as well as attributes. Thus, BRAC University encourages its students to be a

part of at least one club. However, it is seen that being an active member of a club, students have

to confront issues that may have an impact towards their CGPA growth. Hence, to find out therelativity between students performance (in terms of CGPA) in their studies with their

participation in club activities, we have tried to conduct a research amongst 50 students of BRAC

Business School. Amongst the participants of the research, 44% were male and the rest 56%

were female.

Throughout the research work on those respondents, it has been made sure that they properly

attempt all the question and answer appropriately. From our finding from the research, we have

found out that 76% of the respondents were active club members while the rest 24% were non-

active members. This percentage shows respondents enthusiasm towards participating in club

activities, and also, that students yet lag behind to actively participate in the club works.

We also wanted to know students belief towards the issue that whether their time and efforts

spent for club activities were affecting their usual study schedules. Thus, according to the

respondents as well as SPSS result we have found out that 50% of the respondents think that

participating in the club activities reduces their time. Contrarily, 78% of the respondents belief

that joining in club activities does not hamper their studies rather it helps their study. According

to them, this happens due to their increased determination to reach certain goal and to become an

achiever for study.

While scrutinizing respondents agreement or disagreement towards the issue that whether theyhave to bunk classes for the sake of club activities or whether it is their preference which

compels them to choose club over class lectures, we came up with very interesting information.

According to the data, 66% of the respondents said that they have not bunked classes due to club

activities. And, 98% of the respondents prefer classes over club activities. These results show

that students actually prefer their classes over club activities.

A chi square of 11.362 shows moderate association between bunking classes for club activities

and CGPA after joining club. It is also significant for the population. The association between

club activity hour ranges (weekly) and change in CGPA is more (22.783) and is also significant

for the population.

Correlation analysis establishes that club activity hour (weekly) and CGPA have a relationship

which is strongly negative (-0.839). This relationship is significant for the population.


24/26

The above mentioned information include the vital issue that only 24% of these respondents

represent as non-active members of the club and the rest of the respondents are active members

(in terms of Less Active, Moderately Active and Extremely Active ). Therefore, we can say that

club activities and students CGPA do have a relationship between them. And according to the

above mentioned information, we can say that club activity has a negative impact over CGPA.

However, to be sure of the true fact about the relationship between these two, we will also

consider the other analyses that are mentioned in this research paper.


25/26

References:

Citation


26/26

Appendix : questionnaire

Compiled Shoe

Documents

Transcript of Compiled Shoe