· perception towards engineering education and analyze it in the light of their demographic...

ELK ASIA PACIFIC JOURNAL OF SOCIAL SCIENCES

ISSN 2394-9392 (Online); DOI: 10.16962/EAPJSS/issn.2394-9392/2014; Volume 1 Issue 4 (2015)

www.elkjournals.com ………………………………………………………………………………………………………………

PERCEPTION OF INDIAN STUDENTS TOWARDS ENGINEERING EDUCATION: A STUDY AND

ANALYSIS IN DEMOGRAPHICAL SETUP IN BUNDELKHAND REGION

Pankaj Mishra

Assistant Professor

Amity Business School

Amity University Madhya Pradesh

Maharajpura, Gwalior

Madhya Pradesh, India

ABSTRACT

Keywords: Engineering education, Students perception, Technical education

Introduction

In India, the delivery system of engineering

education has undergone drastic changes in

the past decade. Earlier, the engineering

education was made available only at few

renowned educational institutions and taking

admission therein used to be prerogative of

few sections of society. However with

changing socio-political circumstances this

scenario underwent a massive change and

the government allowed various private

universities and colleges to come up in

technical and professional education sector.

Also, in order to ensure that every citizen

Over the decades Engineering has been one of the sought after careers in our country. However with flooding of

dozens of technical institutions in the recent times, the quality of education as well as of passed out graduates

have been eroding substantially. Frustrated engineers are taking jobs for which they are overqualified and,

therefore, underpaid. Further, a global economic slowdown has only worsened the employment situation. Under

these circumstances the interest of a common student has recently been shifting away from engineering

education. And this phenomenon has created a troubled situation for various engineering colleges, as well as for

the prospects of engineering education in the region.This research paper attempts to study the students’

perception towards engineering education and analyze it in the light of their demographic background, with the

purpose of exploring ways to re-strengthen the prospects of engineering as a career among the students. The

study population is drawn from the candidates who sought admission to Uttar Pradesh Technical University run

courses for the session 2014-15, in Bundelkhand region. Our sample consisted of 75 students taking part in

UPTU admission counseling process at counseling centers in Bundelkhand region. The responses were obtained

using Non Probability Judgment sampling method. The subsequent data analysis was done using standard

statistical tools. The findings of this study may prove to be helpful in redefining our approach towards delivering

the technical education to the students, who have been losing interest in the recent years rendering thousands of

seats vacant across various engineering colleges.

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has equal access to technical education, the

government also provided the scholarship

schemes for financially poor and backward

sections.

All these initiatives further witnessed the

growth in no. of educational institutions as

well as in the no. of students taking

admission into these courses. However this

growth inherently came up with a downside.

These institutions started producing

engineers, with most of them being

unemployable. As per the NASSCOM

(National Association of Software and

Services Companies) skills survey, at

present only 27% of engineering graduates

are employable.

This devaluation in quality of engineering

education sent signals of despair across all

the student community, who further wanted

to pursue Engineering as a career. Then

there was impending fallout. In subsequent

years the no. of admissions into Engineering

colleges dipped to lowest levels and in the

state of Uttar Pradesh many technical

institutions were forced to shut down.

This situation called upon a need to inquire

the students’ mind and evaluate their

perception towards engineering education.

Undergraduate technical education in

India

According to multiple estimates, India trains

around 1.5 million engineers, which is more

than the US (0.1Mn) and China (1.1Mn)

combined. According to data from AICTE,

the regulator for technical education in

India, there were 1,511 engineering colleges

across India, graduating over 550,000

students back in 2006-07. Fuelled by fast

growth since then, the numbers of colleges

and graduates have more than doubled, as

shown in the table below:

Table I: Institutions and students over past years

Year No. of Engg.

institutions

Students

intake

% Growth in

institutions

% Growth in students

intake

2006 1511 550986 ------- ---------

2007 1668 653290 10 18

2008 2388 841018 43 29




………………………………………………………………………………………………………………

2009 2972 1071896 24 27

2010 3222 1314594 8 23

2011 3393 1485894 5 13

2012 3495 1761976 3 19

Source: AICTE

As shown, over the years the no. of

Engineering institutions and students’

intake have been rising, which is depicted

in the graph below:

Figure I: No. of Engg. Institutions over

past years

Figure II: Students’ intake over years

However if we glance at the % growth, the

data shows a perturbing pattern as depicted

further:

Figure III: Institutions growth over years

Figure IV: Percentage growth of

Students’ intake over years




………………………………………………………………………………………………………………

The percentage growth in number of

engineering institutions in India have came

down from peak of 43% in 2008-09 to 3% in

2012-13.During the same time the growth in

students ‘intake which was 29% initially,

plummeted to 13% in 2011 and reached at

19% in 2012.This downward trend in the

growth trajectory of engineering education

has triggered the debate over its declining

demand among students. In the state of Uttar

Pradesh the situation is no different from

that of the rest of India. According to a

senior official of Uttar Pradesh Technical

University (UPTU), which governs the

engineering, management and architecture

courses in 837 institutions across the state,

during 2008 to 2012 the state has seen the

opening of over 150 colleges per year.

However, there has been a corresponding

decrease in the number of students

appearing in the entrance examinations for

these courses with the year 2010 seeing

almost 60% seats going empty.

With such grim looking prospects of

undergraduate engineering education in

current times, especially in the state of UP,

the researcher found it worthwhile to look at

and study the perception of students towards

engineering education, with specific

reference to the Bundelkhand region of Uttar

Pradesh. Also the influence of various

demographic factors on their perceptions

needed to be analyzed in order to

recommend the focus of efforts on those

demographic factors which have significant

influence over the perceptions of students

towards engineering education. These

efforts are essentially needed to improve the

prospects of engineering education in the

region.

Objectives

1. To study the demographic

background of students seeking

admission into Engineering courses

of Uttar Pradesh Technical

University.

2. To study the Perception of students

towards engineering education.

3. To examine the difference in

perception among the students on

basis of different demographic

variables.

Research Methodology

The research study adopted was Descriptive

in nature. The Non Probability Judgment

sampling method was used for collecting the

data. A self administered questionnaire was

used to elicit responses from the students




………………………………………………………………………………………………………………

who came to participate in the counseling

process for admission to B.Tech courses at

the UPTU counseling centre. Out of 75

questionnaires distributed among the

students, 50 were received with complete

and proper information. Our further analysis

is based on these completely filled

questionnaires obtained.

Hypotheses

Ho1: There is no significant difference in

perception among Male and Female

students.


perception among students of different age

groups.


perception among students from different

Parent Income groups


perception among students from different

native backgrounds.

Data analysis and discussion

The responses of students in the sample were

viewed in the light of their demographic

background,

The scale items used to measure students’

responses were checked for Reliability using

Cronbach’s Alpha, with following scores

obtained:

Table II: Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of

Items

.720 .718 10

The value obtained of Cronbach’s Alpha is 0.720, which is more than 0.70, hence the scale is

reliable

Table III: Tests of Normality

gende Kolmogorov-Smirnova Shapiro-Wilk




………………………………………………………………………………………………………………

On the basis of Perception scores obtained, we now attempt to examine our Hypotheses

regarding influence of various demographic factors on the perception of students:

Ho1: There is no significant difference in perception among male and female students.

The Null hypothesis assumes that there is no influence of gender variable over perception of

students. We will use T-test to verify the hypothesis.

Further, as shown in the table above the data distribution is assumed to be normal, clearing the

Kolmogorov-Smirnov test of Normality.

Table IV: Group Statistics

gender N Mean Std.

Deviation

Std. Error

Mean

Total

perception

1 male 32 38.88 4.696 .830

2 female 18 38.06 4.007 .944

In the table below, the Levene’s test confirms the equal variance in the data, prior to conducting

the t-test.

T- Test

r Statist

ic

df Sig. Statist

ic

df Sig.

Total

perception

1 male .176 32 .013 .816 32 .000

2

female

.140 18 .200* .945 18 .348

*. This is a lower bound of the true significance.

a. Lilliefors Significance Correction




………………………………………………………………………………………………………………

Table V: Independent Samples Test

Levene's

Test for

Equality of

Variances

t-test for Equality of Means

F Sig. t df Sig.

(2-

tailed

)

Mea

n

Diff

eren

ce

Std.

Error

Differ

ence

95% Confidence Interval

of the Difference

Lower Upper

Total

perception

Equal

varia

nces

assu

med

.006 .937 .623 48 .536 .819 1.315 -1.825 3.464

Equal

varia

nces

not

assu

med

.652 40.2

40

.518 .819 1.257 -1.721 3.360

Presenting the results for Independent- samples t-test:

The test shows no significant difference in perception scores for male (M=38.88, SD=4.7) and

female (M=38.06, SD=4.007) students; t(48)=0.623, p=0.53(two tailed).Hence the Null hypothesis

is accepted. It means that there is no significant difference in perception of male and female

students.

Ho2: There is no significant difference in perception among students of different age groups.




………………………………………………………………………………………………………………

The Null hypothesis assumes that there is no influence of age over perception of students. We will

use T-test to verify the hypothesis

Table VI: Tests of Normality

agegroup

(Binned)

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Total

perception

1 <= 18 .181 37 .003 .825 37 .000

2 19+ .175 13 .200* .921 13 .257



A Normal distribution of population for both age groups is assumed as Age group1 has large

enough sample size and Age group2 clears the Kolmogorov-Smirnov test of Normality.

Table VII :Group Statistics

agegroup

(Binned)

N Mean Std.

Deviation

Std. Error

Mean

Total

perception

1 <= 18 37 38.41 4.336 .713

2 19+ 13 39.08 4.856 1.347


the t-test.

T- Test




………………………………………………………………………………………………………………

Table VIII: Independent Samples Test

Levene's Test

for Equality of

Variances


F Sig. t df Sig. (2-

tailed)

Mean

Differe

nce

Std.

Error

Differ

ence

95% Confidence

Interval of the

Difference

Lower Upper

Total

perception

Equal

variance

s

assumed

1.027 .316 -

.466

48 .643 -.672 1.442 -3.570 2.227

Equal

variance

s not

assumed

-

.441

19.

16

6

.664 -.672 1.524 2.516


The test shows no significant difference in perception scores for Group1 (M=38.41,

SD=4.33) and Group2 (M=39.08, SD=4.85) students; t(48)=0.466, p=0.64(two tailed).Hence

the Null hypothesis is accepted. It means that there is no significant difference in

perception among students of different age groups

Ho3: There is no significant difference in perception scores among students from different

income group families.

The Null hypothesis assumes that there is no significant difference in perception of students

from different parents’ income group.

To examine our hypothesis, we will conduct One Way ANOVA test for assessing the difference

in perception scores among various income groups.




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Table IX :Tests of Normality

Income category

collapsed

Kolmogorov-Smirnova Shapiro-Wilk

Statisti

c

df Sig. Statisti

c

df Sig.

Total

perception

1 upto 1 lakh .199 34 .002 .793 34 .000

2 from 1 to 2 lakh .192 7 .200* .867 7 .176

3 Above 2 lakh .268 9 .062 .887 9 .185



With large sample size for 1st income group, the normal distribution may be assumed. For

remaining groups the Kolmogorov-Smirnov test confirms a Normal distribution.

Test of Homogeneity of Variances

Table X: Homogeneity of variances

Levene

Statistic

df1 df2 Sig.

.655 2 47 .524

The Levene’s test confirms (Sig. value=0.524) equal variances among different income groups.

Table XI: ANOVA

Total perception

Sum of

Squares

df Mean

Square

F Sig.




………………………………………………………………………………………………………………

Between

Groups

128.722 2 64.361 3.621 .034

Within Groups 835.458 47 17.776

Total 964.180 49

Since the Sig value is less than 0.05, there is significant difference between groups. Hence we

reject our Null hypothesis. It means that the perceptions of students belonging to different

parents’ income groups are different.

The Mean values in Descriptives table show the difference in perception scores across the three

groups. To know about which group significantly differs from each other, we conduct Post Hoc tests.

Table XII: Descriptives

Total perception

N Mean Std.

Deviation

Std.

Error

95% Confidence

Interval for Mean

Minim

um

Maxim

um

Lower

Bound

Upper

Bound

1 upto 1

lakh

34 38.62 4.652 .798 36.99 40.24 20 44

2 from 1 to

2 lakh

7 41.71 2.498 .944 39.40 44.02 39 45

3 Above 2

lakh

9 36.00 3.240 1.080 33.51 38.49 31 43

Total 50 38.58 4.436 .627 37.32 39.84 20 45

Post Hoc Tests

Table XIII: Multiple Comparisons

Dependent Variable: Total perception

Tukey HSD




………………………………………………………………………………………………………………

(I) Income category

collapsed

(J) Income category

collapsed

Mean

Difference (I-

J)

Std.

Error

Sig. 95% Confidence

Interval

Lower

Bound

Upper

Boun

d

1 upto 1 lakh 2 from 1 to 2 lakh -3.097 1.750 .191 -7.33 1.14

3 Above 2 lakh 2.618 1.580 .233 -1.21 6.44

2 from 1 to 2 lakh 1 upto 1 lakh 3.097 1.750 .191 -1.14 7.33

3 Above 2 lakh 5.714* 2.125 .026 .57 10.86

3 Above 2 lakh 1 upto 1 lakh -2.618 1.580 .233 -6.44 1.21

2 from 1 to 2 lakh -5.714* 2.125 .026 -10.86 -.57

The outcome of these test show that Group2 (1-2 Lakh) and Group3 (Above 2 Lakh)

significantly differ from each other.

Presenting the results from one-way between groups ANOVA with post-hoc tests

A one-way between-groups analysis of variance was conducted to explore the impact of

Family Income on levels of Perception. Subjects were divided into 3 groups according to

their Parents’ income (Group1: upto 1 Lakh; Group 2: from 1 to 2 Lakh; Group 3: Above

2 Lakh). There was a statistically significant difference at the p<0.05 level in perception

scores for the three groups: F (2, 47) =3.6, P=0.03. Post hoc comparisons using Tukey

HSD test indicated that the mean score for Group2 (M=41.71, SD=2.5) was significantly

different fromGroup3 (M=36, SD=3.2). Group1 (M=38.62, SD=4.6) did not differ

significantly from either Group 2 or 3.

Ho4: There is no significant difference in perception scores among students from different

native background

The Null hypothesis assumes that there is no influence of native background (Urban or Rural)

over perception of students. We will use T-test to verify the hypothesis.




………………………………………………………………………………………………………………

Table XIV: Tests of Normality

native

background

Kolmogorov-Smirnova

Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Total

Perception

Urban .249 35 .000 .778 35 .000

Rural

.144

15

.200

.953

15 .579

A normal distribution of population for both groups is assumed as the urban group has large enough

sample size and the rural group clears the Kolmogorov-Smirnov test of Normality

Table XV: Group Statistics

native

background

N Mean Std.

Deviation

Std. Error

Mean

Total

perception

1 urban 35 36.83 4.119 .696

2 rural 15 42.67 1.447 .374


the t-test.

Table XVI:Independent Samples Test

Levene's Test

for Equality of

Variances


F Sig. t df Sig.

(2-

taile

Mean

Differ

ence

Std.

Error

Differ

95% Confidence

Interval of the

Difference




………………………………………………………………………………………………………………

d) ence Lower Upper

Total

perception

Equal

variance

s

assumed

3.768 .058 -

5.323

48 .000 -.5.838 1.097 -8.043 -3.633

Equal

variance

s not

assumed

-

7.387

46.9

49

.000 -5.838 .790 -7.428 -4.248


The test shows that there is significant difference in perception scores for Urban Group

(M=36.83, SD=4.119) and Rural Group (M=42.67, SD=1.447) students; t(48)=-5.323,

p=0.000(two tailed).Hence the Null hypothesis is rejected. It means that there is significant

difference in perception among students of different native backgrounds.

Findings and Conclusions

1. The study showed no significant

difference in perception among students

of different age groups. The students,

irrespective of age group have similar

perception towards engineering

education. Thus age is not a

differentiating factor while looking at

perceptions of students towards

engineering education in Bundelkhand.

2. There is no significant difference in

perception of male and female students

towards engineering education. Thus the

gender difference has no influence over

perception of students.

3. The study found a significant difference

in perception of students belonging to

different parents’ income group. Hence

the parents’ income variable has a

significant influence over perception of

students towards engineering education.

4. The outcome of this study also showed a

significant difference in perception of

students from different native

backgrounds. The students from rural

background found to have more bright




………………………………………………………………………………………………………………

perception about engineering education

than their urban counterparts.

5. The study observed that 60% of male

students decided to pursue engineering

even before they had finished their 10th

standard, whereas this figure was 35% in

case of female students. Thus this study

found a higher proportion of male

students choosing their career objectives

at early stages, as compared to the

female students.

6. When it came to the priority factors for

selecting a particular institution for

pursuing engineering degree education,

60% students chose the quality

education as their selection parameter

for the institution. Also, an interesting

fact was observed in case of female

students, 30% of which have chosen the

institution because of their parents’

decision to admit their child in a nearest

possible located institute. The same

reason worked for 20% of male students.

Thus the quality education was preferred

by most of the students for choosing an

institution for their admission. However

there were 10% students who were

eyeing at the highest discount in fee

while selecting the institution.

Recommendations

The purpose of the study undertaken was to

understand the influence of demographic

factors on perception of students for

engineering education, in the backdrop of

gradually reducing students’ interest for

engineering courses with particular

reference to Bundelkhand region. Any

demographic factor which tends to

significantly influence the students’

perception for engineering education is

ought to be delved into more deeply by the

educators. They should undertake more

specific studies into concerned demographic

areas in order to bring about those set of

activities which may further enthuse and

motivate more number of students to pursue

engineering education. It will also help in

reinventing our education system in line

with the expectations of prospective

engineering students. Some specific

recommendations suggested by the

researcher in this regard are:

1. The children of parents from middle

Income group should be made aware and

acknowledged about better prospects of

engineering education by educating them

about current advancements taking place

in various fields of engineering and

establishing link between it and the

available branches of engineering




………………………………………………………………………………………………………………

courses. It will strongly help in

emphasizing the bright prospects of

engineering as a career in the mind of

those students, who already carry a

favorable perception for engineering

education.

2. The study showed that students belonging

to rural background have more favourable

perception towards engineering education

in comparison with the urban students.

We need to work upon their perceptions

by creating more avenues for them for

taking admissions into engineering

institutions. Also at the beginning levels

of education the proclivity to study

science and mathematics should be

strengthened among students from rural

areas.

3. This study found that now day, mostly,

the parents of girl students do not want

their children to be away from them for

pursuing their education. In the backdrop

of this fact, further studies need to be

undertaken to find out those locations

from where large number of girl students

come to pursue graduation in

engineering. Such locations need to have

an engineering institution established in

its vicinity.

4. Lastly, there is a strong need to

rejuvenate the foundation of science and

mathematical subjects among the students

at early stages of education, like

secondary school level, which forms the

basis of graduate engineering studies.

And we have to also ensure that students

from rural background should essentially

become part of such an effort.

References

[1] Baillie, C., Lamb, F. & Bramhall, M.,

(2001). A new network of

development in engineering education

in the UK. International Journal of

Engineering Education, 15.

[2] Bevins S, Brodie M, Brodie E. A

study of UK secondary school

students' perceptions of science and

engineering. European Educational

Research Association Annual

Conference 2005. Available from

Sheffield Hallam University Research

Archive (SHURA) from: http://

shura.shu.ac.uk/956/

[3] Haselgrove, S. (1994). The Student

Experience. Buckingham: Society for

Research into Higher Education &

Open University Press.




………………………………………………………………………………………………………………

[4] Norbahiah M, Sarifah N S S. (2013)

Undergraduate Student’s Perception

towards Engineering Program at

UKM. 6th International Forum on

Engineering Education (IFEE 2012).

Procedia - Social and Behavioral

Sciences. 102; 110 – 115.

[5] Times News Network (2014). Only

18% engineering grads are

employable, says survey. Retrieved

from http://

timesofindia.indiatimes.com/city/mu

mbai/Only-18-engineering-grads-are-

employable-says-

survey/articleshow/38438996.cms

[6] PTI (2015). Increasing

engineering institutes affecting

quality. Retrieved from http://

articles.economictimes.indiatimes.co

m/2015-03-15/news




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LIST OF TABLES

Table No. Table Page No.

I Institutions and students over

past years

3

II Reliability Statistics 6

III Tests of Normality For Ho1 6

IV Group Statistics 7

V Independent Samples Test 7

VI Tests of Normality For Ho2 8

VII Group Statistics 8

VIII Independent Samples Test 8

IX Tests of Normality For Ho3 9

X Homogeneity of variances 9

XI ANOVA table 10

XII Descriptives table 10

XIII Multiple Comparisons 10

XIV Test of Normality for Ho4 11

XV Group Statistics 12

XVI Independent Samples Test 12

LIST OF FIGURES

Figure No Figure Page No

I No. of Engg. Institutions over

past years

3

II Students’ intake over years 4

III Institutions growth over years 4

IV Percentage growth of Students’

intake over years

4


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