omer rm final

7/31/2019 Omer RM Final

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Letter of Transmittal


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Table of Contents


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Abstract

The research is aimed at determining whether Learning (CGPA) is influenced by

factors such as background, gender, field of interest, music, attachment to the

university, age, fluency of language, previous performance, martial status, intentions

for studying, perception of a good teacher, hobbies and subject of majoring. Data

used was primary which was collected through questionnaires. The sampling

technique applied was quota sampling by administering 80 questionnaires each to

Greenwich University, IQRA University and SZABIST. The model applied was GLM.

The result showed that the above factors contributed to learning (CGPA) by up to

76%. Other variables had no direct effect on learning.


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1. Introduction

1.1 Learning

Learning is acquiring new knowledge, behaviors, skills,values, preferences or

understanding, and may involve synthesizing different types of information.

The ability to learn is possessed by humans, animals and some machines.

Progress over time tends to follow learning curves.

Human learning may occur as part of education or personal development. It

may be goal-oriented and may be aided by motivation. The study of how

learning occurs is part of neuropsychology, educational psychology, learning

theory, and pedagogy

Learning may occur as a result ofhabituation or classical conditioning, seen in

many animal species, or as a result of more complex activities such as play,

seen only in relatively intelligent animals and humans. Learning may occur

consciously or without conscious awareness. There is evidence for human

behavioral learning prenatally, in which habituation has been observed as early

as 32 weeks into gestation, indicating that the central nervous system is

sufficiently developed and primed for learning and memory to occur very early

on in development.

Play has been approached by several theorists as the first form of learning.

Children play, experiment with the world, learn the rules, and learn to interact.

Vygotsky agrees that play is pivotal for children's development, since they

make meaning of their environment through play.

.
http://en.wikipedia.org/wiki/Knowledgehttp://en.wikipedia.org/wiki/Behaviorhttp://en.wikipedia.org/wiki/Skillhttp://en.wikipedia.org/wiki/Value_(personal_and_cultural)http://en.wikipedia.org/wiki/Preferencehttp://en.wikipedia.org/wiki/Understandinghttp://en.wikipedia.org/wiki/Informationhttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Learning_curvehttp://en.wikipedia.org/wiki/Educationhttp://en.wikipedia.org/wiki/Personal_developmenthttp://en.wikipedia.org/wiki/Goal-orientedhttp://en.wikipedia.org/wiki/Motivationhttp://en.wikipedia.org/wiki/Neuropsychologyhttp://en.wikipedia.org/wiki/Educational_psychologyhttp://en.wikipedia.org/wiki/Learning_theory_(education)http://en.wikipedia.org/wiki/Learning_theory_(education)http://en.wikipedia.org/wiki/Pedagogyhttp://en.wikipedia.org/wiki/Habituationhttp://en.wikipedia.org/wiki/Classical_conditioninghttp://en.wikipedia.org/wiki/Play_(activity)http://en.wikipedia.org/wiki/Conscioushttp://en.wikipedia.org/wiki/Prenatalhttp://en.wikipedia.org/wiki/Habituationhttp://en.wikipedia.org/wiki/Gestationhttp://en.wikipedia.org/wiki/Central_nervous_systemhttp://en.wikipedia.org/wiki/Developmental_Psychologyhttp://en.wikipedia.org/wiki/Vygotskyhttp://en.wikipedia.org/wiki/Vygotskyhttp://en.wikipedia.org/wiki/Developmental_Psychologyhttp://en.wikipedia.org/wiki/Central_nervous_systemhttp://en.wikipedia.org/wiki/Gestationhttp://en.wikipedia.org/wiki/Habituationhttp://en.wikipedia.org/wiki/Prenatalhttp://en.wikipedia.org/wiki/Conscioushttp://en.wikipedia.org/wiki/Play_(activity)http://en.wikipedia.org/wiki/Classical_conditioninghttp://en.wikipedia.org/wiki/Habituationhttp://en.wikipedia.org/wiki/Pedagogyhttp://en.wikipedia.org/wiki/Learning_theory_(education)http://en.wikipedia.org/wiki/Learning_theory_(education)http://en.wikipedia.org/wiki/Educational_psychologyhttp://en.wikipedia.org/wiki/Neuropsychologyhttp://en.wikipedia.org/wiki/Motivationhttp://en.wikipedia.org/wiki/Goal-orientedhttp://en.wikipedia.org/wiki/Personal_developmenthttp://en.wikipedia.org/wiki/Educationhttp://en.wikipedia.org/wiki/Learning_curvehttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Informationhttp://en.wikipedia.org/wiki/Understandinghttp://en.wikipedia.org/wiki/Preferencehttp://en.wikipedia.org/wiki/Value_(personal_and_cultural)http://en.wikipedia.org/wiki/Skillhttp://en.wikipedia.org/wiki/Behaviorhttp://en.wikipedia.org/wiki/Knowledge


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Problem Statement:

Influence of Learning (CGPA) by factors such as gender, field of interest, Job Nature,

fluency of language, previous performance, marital status and majoring field.

Objective:

To study the effect of factors such as gender, field of interest, Job Nature, fluency of

language, previous performance, marital status and majoring field on Students

Learning (CGPA).

Research Hypothesis:

H1: There is significant effect ofgender on Studentss CGPA

H2: There is significant effect of field of interest on Studentss CGPA

H3: There is significant effect of fluency of English on Studentss CGPA

H4: There is significant effect ofprevious performance on Studentss CGPA

H5: There is significant effect ofmarital status on Studentss CGPA

H6: There is significant effect ofmajoring field on Studentss CGPA

H7: There is significant effect ofJob Nature on Studentss CGPA

Operational definition:

Field of interest: Have fun and make friends, Just get a degree to show your

parents, Get a good degree to get a good job, Get into a good university for

higher studies, Get a degree and get married, Other.

Performance: previous acadamic records.

Majoring field: Finance, Marketing, Human Resource, Entrepreneur,

Profession, etc.


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3. Literature Review


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4. Methodology:

This chapter describes the theoretical framework employed in this study and

the qualitative research methods applied. The basic research question and the

specific variables are identified. A description of the data collection

instruments is included, and statistical tests applied are described.

4.1. Data and Data Variables:

The data variables used in this study are as background, gender,Job Nature, field

of interest,attachment to the university, fluency of language, previous performance,

marital status. Primary data was used for the research collected through

questionnaires.

4.2. Sample and sampling technique:

300 questionnaires (100 each University) were floated at Greenwich

University, IQRA University and SZABIST. The Response rate was

approximately 80% which was 240 (80 each University).

4.3 Model:

The model used to analyze the data is as follows:

4.3.1: The Generalized Linear Model (GLM)

In statistics, the generalized linear model (GLM) is a flexible generalization of

ordinary least squares regression. The GLM generalizes linear regression by

allowing the linear model to be related to the response variable via a link

function and by allowing the magnitude of the variance of each measurement

to be a function of its predicted value.
http://en.wikipedia.org/wiki/Statisticshttp://en.wikipedia.org/wiki/Linear_regressionhttp://en.wikipedia.org/wiki/Linear_regressionhttp://en.wikipedia.org/wiki/Statistics


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RESULTS AND DISCUSSIONS:

Tests of Between-Subjects Effects

Dependent Variable:CGPA

Source

Type III Sum

of Squares df Mean Square F Sig.

Corrected

Model

26.194a 36 .728 18.283 .000

Intercept 13.532 1 13.532 340.024 .000

Gender 2.622 1 2.622 65.882 .000

Job Nature 3.061 5 .612 15.382 .000

Majoring 1.390 4 .348 8.732 .000

Eng Fluency .155 1 .155 3.906 .049

performance 1.259 4 .315 7.908 .000

Marital Status 1.696 2 .848 21.309 .000Interests 2.589 5 .518 13.008 .000

. .

Error 7.960 200 .040

Total 2205.121 237

Corrected Total 34.154 236

a. R Squared = .767 (Adjusted R Squared = .725)

Tests of between subjects effect simply shows the significance of factors on

the dependant variable (CGPA). The above mentioned variables which include

background, gender, field of interest,attachment to the university, fluency of

language, previous performance, marital status all have significant effect on the

students learning (CGPA) up to 76% while 24% effect was by other factors.


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Pair wise Comparisons


(I)

Gend

er

(J)

Gend

er

Mean

Difference

(I-J)

Std.

Error Sig.a

95% Confidence Interval

for Differencea

Lower

Bound

Upper

Bound

1.00 2.00 -.404* .050 .000 -.503 -.306

2.00 1.00 .404* .050 .000 .306 .503

(1 being Male and 2 being female)Based on estimated marginal means

* The mean difference is significant at the .05 level thats means

male and female performance are not same in C.G.P.A.

a. Adjustment for multiple comparisons: Least Significant Difference

(equivalent to no adjustments).

Pairwise Comparisons


(I)

Job

Natur

e

(J)

Job

Natur

e

Mean

Difference

(I-J)

Std.

Error Sig.a


for Differencea

Lower

Bound

Upper

Bound

1.00 2.00 .631

*

.100 .000 .434 .828

3.00 -.152 .085 .075 -.319 .015

4.00 .167* .061 .007 .047 .287

5.00 .108 .069 .117 -.027 .243

6.00 .239* .064 .000 .112 .365

2.00 1.00 -.631* .100 .000 -.828 -.434

3.00 -.783*

.108 .000 -.995 -.570


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4.00 -.464* .095 .000 -.651 -.277

5.00 -.523* .086 .000 -.693 -.353

6.00 -.392* .096 .000 -.581 -.204

3.00 1.00 .152 .085 .075 -.015 .319

2.00 .783* .108 .000 .570 .995

4.00 .319* .071 .000 .179 .459

5.00 .259* .080 .001 .101 .418

6.00 .390* .081 .000 .230 .550

4.00 1.00 -.167* .061 .007 -.287 -.047

2.00 .464* .095 .000 .277 .651

3.00 -.319* .071 .000 -.459 -.179

5.00 -.059 .052 .252 -.161 .042

6.00 .071 .053 .182 -.034 .177

5.00 1.00 -.108 .069 .117 -.243 .027

2.00 .523* .086 .000 .353 .693

3.00 -.259* .080 .001 -.418 -.101

4.00 .059 .052 .252 -.042 .161

6.00 .131* .060 .029 .013 .248

6.00 1.00 -.239* .064 .000 -.365 -.112

2.00 .392* .096 .000 .204 .581

3.00 -.390* .081 .000 -.550 -.230

4.00 -.071 .053 .182 -.177 .034

5.00 -.131* .060 .029 -.248 -.013


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1. Finance (Banking\consultancy\Mutual Funds, etc)

2. Marketing (Advertising\ Branding\ PR, etc)

3.

Human Resource4. Entrepreneur (Business man\women)

5. Profession (Pilot\Doctor\engineer)

6. Other: _________________

Based on estimated marginal means

* The mean difference is significant at the .05 level.





(I)

perfor

manc

e

(J)

perfor

manc

e

Mean

Difference

(I-J)

Std.

Error Sig.a


for Differencea

Lower

Bound

Upper

Bound

1.00 2.00 .161* .045 .000 .071 .250

3.00 -.046 .055 .398 -.154 .061

4.00 .218* .058 .000 .103 .332

5.00 .265* .088 .003 .092 .438

2.00 1.00 -.161* .045 .000 -.250 -.071

3.00 -.207* .064 .001 -.334 -.080

4.00 .057 .070 .417 -.081 .195

5.00 .105 .087 .229 -.066 .276

3.00 1.00 .046 .055 .398 -.061 .154

2.00 .207* .064 .001 .080 .334

4.00 .264* .075 .000 .117 .411


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5.00 .311* .096 .001 .122 .501

4.00 1.00 -.218* .058 .000 -.332 -.103

2.00 -.057 .070 .417 -.195 .081

3.00 -.264* .075 .000 -.411 -.117

5.00 .048 .098 .628 -.146 .241

5.00 1.00 -.265* .088 .003 -.438 -.092

2.00 -.105 .087 .229 -.276 .066

3.00 -.311* .096 .001 -.501 -.122

4.00 -.048 .098 .628 -.241 .146

1. Better

2. Good

3. Same

4. Bad

5. Worse



a. Adjustment for multiple comparisons: Least Significant

Difference (equivalent to no adjustments).


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(I)

Intere

sts

(J)

Intere

sts

Mean

Difference

(I-J)

Std.

Error Sig.a


for Differencea

Lower

Bound

Upper

Bound

1.00 2.00 -.221 .116 .060 -.450 .009

3.00 .074 .058 .202 -.040 .187

4.00 -.115 .064 .071 -.241 .010

5.00 .245* .065 .000 .116 .375

6.00 -.251* .076 .001 -.400 -.101

2.00 1.00 .221 .116 .060 -.009 .450

3.00 .294* .105 .005 .088 .501

4.00 .105 .098 .285 -.088 .299

5.00 .466

*

.103 .000 .262 .670



(I)

English

(J)

English

Mean

Difference(I-J)

Std.Error Sig.a


for Differencea

LowerBound

UpperBound

YES NO .131* .066 .049 .000 .262

NO YES -.131* .066 .049 -.262 .000

(1 = English easy, 2 = English difficult)






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6.00 -.030 .123 .806 -.272 .212

3.00 1.00 -.074 .058 .202 -.187 .040

2.00 -.294* .105 .005 -.501 -.088

4.00 -.189* .044 .000 -.275 -.103

5.00 .172* .066 .010 .042 .301

6.00 -.324* .072 .000 -.466 -.183

4.00 1.00 .115 .064 .071 -.010 .241

2.00 -.105 .098 .285 -.299 .088

3.00 .189* .044 .000 .103 .275

5.00 .361* .067 .000 .228 .493

6.00 -.135 .074 .071 -.282 .011

5.00 1.00 -.245* .065 .000 -.375 -.116

2.00 -.466* .103 .000 -.670 -.262

3.00 -.172* .066 .010 -.301 -.042

4.00 -.361* .067 .000 -.493 -.228

6.00 -.496* .084 .000 -.663 -.330

6.00 1.00 .251* .076 .001 .101 .400

2.00 .030 .123 .806 -.212 .272

3.00 .324* .072 .000 .183 .466

4.00 .135 .074 .071 -.011 .282

5.00 .496* .084 .000 .330 .663

1. Have fun and make friends

2. Just get a degree to show your parents

3. Get a good degree to get a good job

4. Get into a good university for higher studies

5. Get a degree and get married

6. Other



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Dependent Variable: CGPA

(I)

Marital

status

(J)

Marital

status

Mean

Difference

(I-J)

Std.

Error Sig.a


for Difference a

Lower

Bound

Upper

Bound

2.00 3.00 -.225* .056 .000 -.334 -.115

4.00 .175* .048 .000 .081 .269

3.00 2.00 .225* .056 .000 .115 .334

4.00 .400* .061 .000 .279 .521

4.00 2.00 -.175* .048 .000 -.269 -.081

3.00 -.400* .061 .000 -.521 -.279

1. Married

2. Single

3. Committed (gf\bf)

4. Single but looking


*. The mean difference is significant at the .05 level.



The Pairwise Comparison shows the similar or different effect a factor has on

the CGPA. This comparison is with multiple factors within a single category,

eg: Gender, the comparison of the similar or different effects of male or


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females on learning which on the basis of this research have different effects

on learning.



(I)

Major

ing

(J)

Major

ing

Mean

Difference

(I-J)

Std.

Error Sig.a


for Differencea

Lower

Bound

Upper

Bound

1.00 2.00 -.095* .039 .014 -.172 -.019

3.00 -.048 .073 .515 -.191 .096

4.00 .361* .076 .000 .211 .511

5.00 .265* .102 .010 .064 .466

2.00 1.00 .095* .039 .014 .019 .172

3.00 .048 .072 .509 -.095 .191

4.00 .456* .081 .000 .296 .616

5.00 .360* .108 .001 .147 .574

3.00 1.00 .048 .073 .515 -.096 .191

2.00 -.048 .072 .509 -.191 .095

4.00 .408* .105 .000 .202 .615

5.00 .313* .129 .016 .059 .566

4.00 1.00 -.361* .076 .000 -.511 -.211

2.00 -.456* .081 .000 -.616 -.296

3.00 -.408* .105 .000 -.615 -.202

5.00 -.096 .115 .406 -.323 .131

5.00 1.00 -.265* .102 .010 -.466 -.064

2.00 -.360* .108 .001 -.574 -.147


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3.00 -.313* .129 .016 -.566 -.059

4.00 .096 .115 .406 -.131 .323

1. Finance (Banking\consultancy\Mutual Funds, etc)

2. Marketing (Advertising\ Branding\ PR, etc)

3. Human Resource

4. Entrepreneur (Business man\women)

5. Profession (Pilot\Doctor\engineer)

6. Other: _________________





5.2 Frequency of responses

189

48

Gender

Male

Female


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3016

20

90

40

41

Job Nature

Finance

(Banking\consultancy\Mut

ual Funds, etc)

Marketing (Advertising\

Branding\ PR, etc)

Human Resource

Entrepreneur (Business

man\women)

Profession

(Pilot\Doctor\engineer)

Other

108

90

15

168

Majors

Finance

(Banking\consultancy\Mutu

al Funds, etc)

Marketing (Advertising\

Branding\ PR, etc)

Human Resource

Entrepreneur (Business

man\women)

Other


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216

21

English Fluency

Yes

No

101

65

35

25 11

Previous Performance

Better

Good

Same

Bad

Worse


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160

41

36

Marital Status

Married

Single

Committed (gf\bf)


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5.3 ASSUMPTIONS of GLM

A. Test of Normality

Tests of Normality

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Standardized

Residual for CGPA

.062 237 .026 .989 237 .062

We take into accountShapiro-Wilk as it is more Robust.

B. Assumption that error is independent

The Graph shows that the errors are independent, not in a single place or

bunched together.


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8. FUTURE RECOMMENDATIONS:

I would like to recommend the following few things to the people who carry out

similar researches in order to acquire more accurate results: Incorporate some other significant variables

A large sample size to be used

Gather data from large number universities so that generalization could

be made.

we found the effects of factors on learning, you should f ind the degree of

effect of each factor on learning

Use models to determine which factors have favorable effect and whichhave inverse effects on learning.


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9. References:

omer rm final

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