the perception of youth in higher education institution

THE PERCEPTION OF YOUTH IN HIGHER EDUCATION INSTITUTION TOWARDS THE VOLUNTEERISM PROGRAM IN KUALA TERENGGANU

NAME:

WAN MOHAMAD ASYRAF BIN WAN AFTHANORHAN

SUPERVISOR:

MISS SURIANI AB.RAHMAN

Bachelor of Science (Hons.) (Statistics)

Faculty of Computer and Mathematical Sciences

University of Technology MARA

July 16th, 2012

1

BACKGROUND OF STUDY Volunteerisme was the wide scope and involved many of

participants from a variety of field either in the academic, economic, constitutional, religion, consumerisme, environment, gender sensitivity, and youths.

(Azizan, 2009) The word of “volunteer”, means willingly and no force from

other people to contribute something work The other meaning of volunteerisme was “the behaviour of volunteer”. In addition, the people that do something work without force and able to do work with sincerity is called “volunteerisme” for both gender which is the male and female.

( Kamus Dewan 2005 ).

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PROBLEM STATEMENT

Nowadays, the volunteer activity is still low in Malaysia even the society know the advantage for involving in this program.The involvement of Malaysia society especially to the youth in higher education in an effort to help those who are marginalized who needs the helps which is still at a low level and this lack of enthusiasm of youth was very dissapointed since the groups mostly are not active in this volunteer programme .This statement shows the different cultural values and lifestyle of the people in Malaysia. Basically, Malaysia society have caring, courtesy, respect for elders and each other mutual helps. The study of perception of youth in higher education towards the volunteer programme is very essential or important to all community. This is because the youth will gain the eperience besides helps the goverment to overcome the problem of society.However, the community still does not shows any commitment to helps the people surroundings especially to helps the victims from tsunami,floods,earthquake or any disaster for reduces the burden of goverments.So,it is very important to understanding and know the most factors that contribute the perception of youth towards the volunteer programme and which one is the best factor of volunteerisme. 3

OBJECTIVE OF STUDY

The objective research are : To examine the influences of effects and barrier of

involvement towards the level of involvement in volunteerisme.

To determine the influences of of effect and barrier towards the level of involvement in volunteerisme for male perception.

To determine the influences of of effect and barrier towards the level of involvement in volunteerisme for female perception.

To identify the most contribute factors for the perception of youth in higher education towards the volunteerism programme.

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LITERATURE REVIEW• TYPE OF VOLUNTEERING

There are two main types of volunteering : managed and unmanaged. Managed volunteering takes place through organizations in the Non profit, Public, and Private sectors, and tends to be more organized. An, example of this is home based care programmes. In contrast, unmanaged volunteering is the spontaneous and sporradic helping that takes place between friends and neighbours (Dingle, 2001).

• EFFECT OF VOLUNTEERINGVolunteering can be cost-effectives, it is not entirely cost- free. If managed effectively and efficiently, it is requires an infrastructures at all levels : local,provincial and national levels that will allow for the training and appropriate placement of volunteers. Goverments may contribute by supporting such infrastructures. Further, if goverments is better informed about the people who volunteer, it is likely to become more aware of how policy legislation it introduces can affect, both directly and indirectly, people giving of thier time. There is also a growing awareness of how to create an environment in which more spontaneous forms of unmanaged volunteering can flourish and be promoted ( Dingle, 2001)

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• BARRIER OF VOLUNTEERING1. There are 3 factors that challenge volunteering which is

globalization, relation with states, and the relation with the market (Dingle, 2001)

2. Globalization can be defined as the acceleration and intensification of interaction and integration among people and goverment of different nations ( Rothenberg, 2003).

3. Relation with the states is the theories of goverments suggest that the volunteers step in to fill the gaps left by the withdrawal of the state ( Ogden et all, 2004).

4. Relation with the market has developed in increased interest in volunteering (Dingle, 2001). Business developed programmes to support staffs involvement in voluntary activities in the community.

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THEREOTICAL FRAMEWORK

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METHODOLOGY• The size of sample is about

171 respondent which is:

• SAMPLING TECHNIQUE USED

1. used is the simple random sampling technique

STATISTICAL TEST

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FACTOR ANALYSIS Factor analysis is

a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved, uncorrelated variables called factors

STRUCTURAL EQUATION MODELLING (SEM)

Structural equation modeling (SEM) is a tool for analyzing multivariate data that has been long known in marketing to be especially appropriate for theory testing (e.g., Bagozzi, 1980).

The Reliability Analysis This step is to determine the

reliability measure for the measuring items under each component

Descriptive Statistics Provide such as frequency and

percentage were used to describe the demographic profile .

Normality test If the measures of skewness for

all items are within the range of -1.0 to 1.0, we can conclude that the distribution of data does not depart from normality.

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NORMALITY TEST

Tests of Normality

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

volunteerisme .098 171 .000 .972 171 .002

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PARAMETRIC TEST

SECTION CRONBACH ALPHA ITEMS

PART B 0.893 26

PART C 0.945 8

PART D 0.864 14

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy.

.892

Bartlett's Test of

Sphericity

Approx. Chi-Square 2330.522

df 325

Sig. .000

FACTOR ANALYSIS FOR SECTION B (OVERALL)

RELIABILITYItems 1 2 3 4B1

B2

.797B3

.641 B4

.721 B5

.699 B6

.802 B7

.820 B8

.775B9

.608 B10

.716 B11

.799 B12

.694 B13

B14

B15

B16

.685 B17

.671 B18

.675 B19

B20

B21

.831 B22

.844 B23

.851 B24

B25

B26

.659

These components were separated by 4 domain (9 factors in the first domain, 3 factors in the second domain, 3 factors in the third domain, and 3 factors in four domain). This is set to the number of factors in the extraction of SPSS (Statistical Packaging for Social Science).Then, naming of each component that are related to the question which is the ( 1 domain = positive perception, 2 domain = interest, 3 domain = information, 4 domain = benefits ).

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FACTOR ANALYSIS FOR SECTION C (OVERALL)



Adequacy.

.900

Bartlett's Test of

Sphericity


df 28

Sig. .000

Rotated Component Matrixa

Component

1 2C1 .861 C2 .867 C3 .760 C4 .773C5 .868C6 .825C7 .648C8 .641

These components were separated by 2 domain (4 factors in the first domain, and 4 factors in the second domain).Then, naming of each component that are related to the question which is the ( 1 domain = positive effect, 2 domain = benefit ).

FACTOR ANALYSIS FOR SECTION D (OVERALL)



Adequacy.

.847

Bartlett's Test of

Sphericity


df 91

Sig. .000


ItemsComponent

1 2 3D1 .775 D2 .779 D3 .748D4 .751D5 .723 D6 .761 D7 .727 D8 .737 D9 .720 D10 .712 D11 .781 D12 .760 D13 .686 D14 .789

These components were separated by 3 domain (10 factors in the first domain, 2 factors in the second domain, and 2 factors in the third domain). Then, naming of each component that are related to the question which is the ( 1 domain = barrier, 2 domain = commitment for self and towards family, 3 domain = commitment towards public relationship ).

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Adequacy.

.626

Bartlett's Test of

Sphericity


df 325

Sig. .000

Factor analysis section B (male)

The number of question is based on the value of the load in excess of 0.60 only. The questions that are less than the value of load will removed. These components were separated by 4 domain (8 factors in the first domain, 4 factors in the second domain, 3 factors in the third domain, and 3 factors in four domain). Then, naming of each component that are related to the question which is the ( 1 domain = positive perception, 2 domain = interest, 3 domain = information, 4 domain = benefits ).

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ItemsComponent

1 2 3 4B1 B2 .778 B3 .722 B4 .605 B5 B6 .839 B7 .670 B8 B9 B10 .662 B11 .797 B12 .794 B13 .771 B14 .611 B15 B16 .673 B17 .761 B18 .747 B19 B20 .644 B21 .779B22 .820B23 .800B24 B25 .735 B26


ItemsComponent

1 2C1 .894 C2 .939 C3 .839 C4 .697C5 .802C6 .929C7 .632C8 .641

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Adequacy.

.775

Bartlett's Test of

Sphericity


df 28

Sig. .000

Factor analysis section C (male)KMO and Bartlett's Test


Adequacy.

.693

Bartlett's Test of

Sphericity


df 91

Sig. .000

The number of question is based on the value of the load in excess of 0.60 only.These components were separated by 3 domain (8 factors in the first domain, 3 factors in the second domain, and 2 factors in the third domain). Then, naming of each component that are related to the question which is the ( 1 domain = barrier, 2 domain = commitment for self and towards family, 3 domain = commitment towards public relationship ).

The number of question is based on the value of the load in excess of 0.60 only. The questions that are less than the value of load will removed. These components were separated by 2 domain (4 factors in the first domain, and 4 factors in the second domain). Then, naming of each component that are related to the question which is the ( 1 domain = positive effect, 2 domain = benefit ).

Factor analysis section D (male)

ItemsComponent

1 2 3D1 .812 D2 D3 .824 D4 .848 D5 .679 D6 .768 D7 .820 D8 .630D9 .815 D10 .816 D11 .881 D12 .746 D13 .774D14 .625



Adequacy.

.844

Bartlett's Test of

Sphericity


df 325

Sig. .000

Factor analysis section B ( female)

The number of question is based on the value of the load in excess of 0.60 only. The questions that are less than the value of load will removed. These components were separated by 3 domain (14 factors in the first domain, 3 factors in the second domain, and 3 factors in the third domain). Then, naming of each component that are related to the question which is the ( 1 domain = positive perception, 2 domain = interest, 3 domain = information ).

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ItemsComponent

1 2 3B1 B2 .704 B3 B4 .669 B5 .659 B6 .649 B7 .691 B8 .705 B9 B10 .676 B11 .746 B12 .663 B13 B14 B15 .700 B16 .720 B17 .684 B18 .612 B19 .641 B20 .617 B21 .832B22 .839B23 .839B24 B25 .620 B26 .609

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Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .917

Bartlett's Test of Sphericity Approx. Chi-Square 941.079

df 28

Sig. .000

Factor analysis section C (female)

The number of question is based on the value of the load in excess of 0.60 only. The questions that are less than the value of load will removed. These components were separated by 2 domain (5 factors in the first domain, and 3 factors in the second domain). Then, naming of each component that are related to the question which is the ( 1 domain =

positive effect, 2 domain = benefit ).



Adequacy.

.843

Bartlett's Test of

Sphericity


df 91

Sig. .000

These components were separated by 3 domain (10 factors in the first domain, 2 factors in the second domain, and 2 factors in the third domain). Then, naming of each component that are related to the question which is the ( 1 domain = barrier, 2 domain = commitment for self and towards family, 3 domain = commitment towards public relationship ).

Factor analysis section D (female)


ItemsComponent

1 2C1 .845

C2 .862

C3 .650

C4 .781

C5 .835

C6 .682

C7 .731

C8 .744

Component

1 2 3D1 .811 D2 .799 D3 .768D4 .750D5 .714 D6 .747 D7 .737 D8 .773 D9 .726 D10 .711 D11 .766 D12 .753 D13 .756 D14 .801

STRUCTURAL EQUATION MODELLING (AMOS)

Variable Estimate C.R. P Result

Y <---

X2 -2.644 -2.035 .042 Significant

Y <---

X1 .121 .775 .438 Not significant

OVERALL

ModelNFI

Delta1RFI

rho1IFI

Delta2TLI

rho2CFI

Default model

.923 .885 .956 .933 .956

Baseline Comparisons

Regression Weights

Model NPAR CMIN DF PCMIN/

DF

Default model

30 53.482 24 .000 2.228

CMIN

Model RMSEA LO 90 HI 90 PCLOSE

Default model

.085 .054 .116 .032

RMSEA

This model are already fit.

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Male before fit Male after fit


DF

Default model

30 33.876 24 .087 1.412

ModelNFI

Delta1RFI

rho1IFI

Delta2TLI

rho2CFI

Default model

.817 .726 .939 .901 .934


DF

Default model

32 22.478 22 .032 1.022

ModelNFI

Delta1RFI

rho1IFI

Delta2TLI

rho2CFI

Default model

.979 .901 .997 .995 .997

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Default model

.108 .000 .187 .149

VariableEstimate S.E. C.R. P

Result

Y <--- X2 -3.206 3.696 -.868 .386Not significant

Y <--- X1 .173 .441 .393 .694Not significant

Male before fit

Regression weight


Default model

.025 .000 .144 .542

Male after fit

Estimate S.E. C.R. PResult

Y <--- X2 -1.490 1.041 -1.431 .152Not significant

Y <--- X1 .454 .155 2.932 .003Significant

Regression weight

When X2 goes up by 1 unit, Y goes down by 1.490 unit since the present of negative sign. The regression weight estimate, 1.490 has a standard error of about 1.041. By dividing the regression weight estimate by the estimate of its standard error gives 1.041. In other words, the regression weight estimate is 1.041 standard error is above zero. The probability of getting the critical ratio as large as -1.431 is absolute value is greater than 0.05. In other words, the regression weight estimate for X2 in the prediction of Y is not significantly different from zero at the 0.05 level.

Take the regression weight which model that are fit

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Female before fit Female after fit


DF

Default model

30 44.729 24 .006 1.864

ModelNFI

Delta1RFI

rho1IFI

Delta2TLI

rho2CFI

Default model

.914 .871 .958 .936 .957


DF

Default model

31 28.192 23 .020 1.226

ModelNFI

Delta1RFI

rho1IFI

Delta2TLI

rho2CFI

Default model

.946 .915 .990 .983 .989

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Default model

.080 .042 .116 .088

Estimate S.E. C.R. PResult


Y <--- X1 .027 .199 .136 .892Not significant

Female before fit

Regression weight


Default model

.041 .000 .086 .580

Female after fit

Estimate S.E. C.R. P Result


Y <--- X1 .106 .147 .720 .471Not sigificant

Regression weight

When X2 goes up by 1 unit, Y goes down by 2.243 unit since the present of negative sign. The regression weight estimate, 2.243 has a standard error of about 1.179. By dividing the regression weight estimate by the estimate of its standard error gives 1.179. In other words, the regression weight estimate is 1.179 standard error is above zero. The probability of getting the critical ratio as large as -1.901 is absolute value is greater than 0.05. In other words, the regression weight estimate for X2 in the prediction of Y is not significantly different from zero at the 0.05 level.

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No Hypothesis statement Result

1 H1 There is significant and direct influences of barrier involvement on level of involvement

Supported

2 H2 There is significant and direct influences of effect involvement on level of involvement

Not supported

3 H3 There is significant and direct influences of barrier involvement on level of involvement for male perception

Not supported

4 H4 There is significant and direct influences of effect involvement on level of involvement for male perception

Supported

5 H5 There is significant and direct influences of barrier involvement on level of involvement for female perception

Not supported

6 H6 There is significant and direct influences of effect involvement on level of involvement for female perception.

Not supported

ConclusionSummary Results for the overall Hypothesis in the Study

For the whole perception, we can conclude that the barrier of invovement is direct influences towards the level of involvement. Otherwise,the effect of involvement is not direct influences towards the level of involvement. Thus, the perception of youth towards the barrier of involvements is the factor to prevent them from involve in this program

For male perception, we can conclude that the barrier of involvement is not directly influences towards the level of involvement. Otherwise, the effect of involvement is directly influences towards the level of involvement. Hence, the most contribute between both factor is the effect of involvement.

For female perception, we can conclude that the barrier and effect of involvement are not direct influences towards the level of involvement.Thus, the perception of female said the volunteerism program is meaningless and nothing since both of factor are not significant.

Redefining the word voluntaryObjective changes in the youth movement Online volunteer registration

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the perception of youth in higher education institution

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