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CHAPTER III

METHODOLOGY

OVERVIEW

This chapter deals with the methodology of the present study. Here

the investigator has presented the method used for the study, population

and area, sample, description of tools, scoring procedure for data

collection and statistical techniques employed.

METHOD USED FOR THE STUDY

According to Best and Khan (1995), “Research is a systematic

activity that is directed towards discovery and the development of

organized body of knowledge”. In any given investigation it may not be

only desirable but also necessary to use one or more general types of

research methods in combination. The decision about the method or

methods to be employed however always depends upon the nature of the

problem and the kind of data necessary for its solution.

Since the problem selected for the present study is concerned with

“survey type” the researcher has adopted the “survey method” which

suggests the gathering of evidence relating to current conditions.

Survey Research is a method for collecting and analyzing data,

obtained from a large number of respondents representing a specific

population, collected through highly structured questionnaire or interview.

The survey is often the only means through which opinions, attitudes,

suggestions and other such data can be obtained. The survey method

gathers information and facts from a large number of cases. It is

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concerned with conditions or relationships that exist, practices that

prevails beliefs, points of view or attitudes that are held, processes that are

going on, effects that are being felt or trends that are developing.

Survey methods provide three types of information:

(i) of what exists by studying and analyzing the important aspects

of the present situation.

(ii) Of what we want by clarifying goals and objectives possibly

through a study of the conditions existing elsewhere or what

experts otherwise consider to be desirable and undesirable.

(iii) Of how to get these through discovering the possible means of

achieving the goals on the basis of the experiences of others or

opinion of the experts (Sidhu, 2002).

On the whole, survey method involves a clearly defined problem

and definite objectives; it requires imaginative planning, careful analysis

and interpretation of the data gathered and logical and skillful reporting of

the findings (John W. Best, 1992). Using this method, the investigator has

gathered information to measure the parental influence, emotional

intelligence and academic achievement of the higher secondary students.

AREA OF THE STUDY

The area of the study consists of two southern revenue districts of Tamil Nadu

namely, Tirunelveli and Thoothukudi. The map is attached herewith Map 3.1.

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POPULATION FOR THE STUDY

The population for the study includes all the higher secondary

students in government, aided and matriculation higher secondary schools

of the above mentioned southern districts. According to the government

norms, there are three educational districts centered at Tirunelveli,

Cheranmahadevi and Tenkasi in Tirunelveli revenue district and two

educational districts centered at Thoothukudi and Kovilpatti educational

districts in Thoothukudi revenue district. They are shown in the Map 3.2.

192

193

194

SAMPLE FOR THE STUDY

A sample is the representative part of the population. The

investigator had used stratified random sampling for selecting the sample.

The sample consists of 1080 students of higher secondary level. The

students are selected from 27 higher secondary schools, who have been

randomly selected from Tirunelveli, Cheranmahadevi, Tenkasi,

Thoothukudi and Kovilpatti educational districts. The stratification has

been done on the basis of sex, group of study, nature of schools, location

of schools, type of schools and community. The details regarding schools

covered and the number of students from each school is given in the

appendix F.

Table 3.1 Educational District wise distribution of the sample

S.No

.

Name of the educational

districts

School

s

Sample Percenta

ge

1 Tirunelveli 6 240 22.22

2 Cheranmahadevi 6 240 22.22

3 Tenkasi 6 240 22.22

4 Thoothukudi 6 240 22.22

5 Kovilpatti 3 120 11.11

Total 27 1080

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The following is the break up of the sample on the basis of sex, group of study,

medium of studey nature of schools, location of schools, type of schools and

community.

Table 3.2 Variable wise distribution of the sample

Variable Category N %

Sex Male 586 54.26

Female 494 45.74

Locality Rural 521 48.24

Urban 559 51.76

Medium of instruction Tamil 719 66.57

English 361 33.43

Group of study Science 411 38.6

Arts 368 34.07

Vocational 301 27.87

Type of school

Govt. 340 31.48

Aided 400 37.04

Matriculatio

n

340 31.48

Nature of school

Boys 127 11.76

Girls 231 21.39

Co-

Education

722 66.85

Community

SC/ST 218 20.19

MBC 201 18.61

BC 605 56.02

OC 56 5.19

It is inferred from the above table that the sample consists of

54.26% of boys and 45.74 % of girls, 66.57 % of the students are studying

in Tamil medium and 33.43% are studying in English medium, 48.24

percent of the students are residing at rural area and 51.76 percent of the

students are residing at city, 38.6 percent of the students are from science

group, 34.07 percent of them are arts group and 27.87 percent are

vocational group, 31.48 percent of the students are from government

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schools, 37.04 percent are from are aided and 31.48 percent are

matriculation schools, 11.76 percent of the students are from boys 21.39

percent are from girls and 66.85 percent are from co-education schools,

and 20.19 percent of the students are SC/ST, 18.61 percent are MBC,

56.02 percent are BC and 5.19 percent are OC.

TOOLS USED IN THE PRESENT STUDY

The investigator has constructed and validated the parental

influence scale with the help of his guide Sadananthan for his

investigation. The second tool was an adopted inventory of Thomas

Alexander. The investigator also prepared self identification proforma.

1. Samy and Satha Parental Influence Scale (SSPIS) (2009)

Parental Influence Scale

2. Adapted the Emotional Intelligence Inventory developed by

Thomas Alexander (2007)

DESCRIPTION OF THE TOOLS

1. PARENTAL INFLUENCE SCALE

The parental influence scale was designed by Lourdusamy and

Sadananthan and it was named as Samy & Satha Parental Influence Scale

(SSPIS). The scale attempts to find out the level of parental influence on

the students in four areas and also the over all parental influence.

Preparation of the draft tool

The investigator prepared the scale based on Likert type. The Likert Scale is a

popular format of questionnaire that is used in educational research. It was invented by

Rensis Likert, an educator and psychologist. The Likert Scale is an ordered, one-

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dimensional scale from which respondents choose one option that best aligns with

their view. There are typically between four and seven options. Five is very common.

All options usually have labels, although sometimes only a few are offered and the

others are implied. A common form is an assertion, with which the person may agree

or disagree to varying degrees. In scoring, numbers are usually assigned to each option

(such as 1 to 5).The format of a typical five-level Likert item is:

1. Strongly disagree, 2. Disagree, 3. Neither agree nor disagree,

4. Agree, 5. Strongly agree

The investigator read standard books and journals on family and

parental influence on academic achievement of children. Also he

consulted parents, experts and decided the different dimensions of

parental influence. The investigator showed it to the experts. On the

opinion of the experts and the order they arranged, the following

dimensions of parental influence scale were identified for the study. They

are namely, parenting, parent and school relationship, parent and academic

involvement and parent and multi skill development. Then for each

dimension twenty five statements were prepared and each statement has to

be answered in a fivepoint rating scale with the options namely highly

agree, agree, undecided, disagree and highly disagree.

Selection of Items

The tool was administered to 50 higher secondary students drawn

from Christhu Raja higher secondary school, St John’s higher secondary

school, Angelo matriculation school, St. Ignatius higher secondary school

and Kallanai - Corporation girls higher secondary school, Tirunelveli. For

refinement of the tool, item validity was calculated. The Parental

influence scale has four dimensions. Each dimension consists of 25 items.

By using product moment correlation, item-total correlation was found.

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The items which were having correlation value above 0.4 were retained

and other items were discarded. The item-total correlation is shown in the

following table 3.3.

Table 3.3

Item-total correlation value of SSPIS

Item No ‘r’ value Item No ‘r’ value Item No ‘r’ value Item No ‘r’ value

1* 0.405 21* 0.592 41* 0.658 61* 0.513

2* 0.425 22 0.393 42 0.291 62 0.312

3* 0.478 23* 0.825 43 0.353 63* 0.769

4* 0.455 24 0.311 44* 0.687 64* 0.658

5* 0.536 25* 0.543 45* 0.586 65 0.291

6 0.298 26* 0.644 46* 0.427 66 0.253

7 0.325 27 0.363 47 0.356 67 0.387

8* 0.489 28* 0.424 48* 0.654 68* 0.586

9* 0.476 29* 0.466 49 0.289 69* 0.527

10* 0.458 30 0.387 50* 0.458 70* 0.456

11* 0.467 31 0.344 51* 0.862 71* 0.654

12* 0.547 32* 0.687 52* 0.534 72* 0.789

13* 0.459 33* 0.518 53* 0.711

14* 0.543 34* 0.579 54* 0.844

15 0.297 35* 0.773 55* 0.464

16* 0.524 36* 0.802 56* 0.518

17 0.298 37* 0.559 57* 0.579

18 0.387 38* 0.513 58* 0.773

19* 0.874 39 0.312 59* 0.802

20* 0.896 40* 0.769 60 0.359

N.B. * marked items are valid items.

The valid items were retained. Finally the tool consisted of only 52

items.

Item Validity

For further improvement and refinement of the scale, the scale

consisting of

72 items, (the draft tool II) was administered again to 50 students of

higher secondary students in Christhu Raja higher secondary school, St

John’s higher secondary school, Angelo matriculation school, St. Ignatius

higher secondary school and Kallanai - Corporation girls’ higher

secondary school, Tirunelveli. The responses were scored. The total score

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for each student was calculated. The tool was arranged in decending order

of scores. The first 27% of the cases were considered as upper group and

the lowest 27% of the cases were considered as lower group. That is 14

students were in the upper group and 14 students were in the lower group.

The mean and standard deviation for the upper and the lower groups were

computed. The ‘t’ test (small sample) was used for calculating ‘t’ value

for each item. For 27 df at 5% level of significance the table value of ‘t’ is

2.05. The items which were having less than 2.05 were discorded and the

items which were having greater than 2.05 were retained. Thus the tool

has 52 items. The ‘t’ value of the item was given in the table 3.4.

Table 3.4 ‘t’ value for the items in the tool SSPIS

Item No ‘t’ value Item No ‘t’ value Item No ‘t’ value Item No ‘t’ value

1* 4.465 16* 3.496 31* 2.689 46* 2.772

2* 4.425 17* 3.828 32* 2.583 47* 2.655

3* 3.478 18* 3.545 33* 3.525 48* 3.584

4* 2.455 19* 2.648 34* 2.650 49* 2.525

5* 3.536 20* 3.523 35* 3.456 50* 3.458

6* 3.499 21* 3.469 36* 2.868 51* 2.652

7* 2.476 22* 3.689 37* 3.436 52* 2.787

8* 3.458 23* 3.417 38* 2.713

9* 2.467 24* 2.577 39* 2.846

10* 3.447 25* 2.776 40* 2.536

11* 2.461 26* 2.804 41* 3.520

12* 3.444 27* 3.560 42* 2.576

13* 3.522 28* 3.411 43* 2.771

14* 3.880 29* 2.770 44* 2.806

15* 2.895 30* 2.657 45* 3.514

N.B. * marked items are valid items. The valid items were retained.

Finally the tool consisted of only 52 items.

Establishing Validity

Validity refers to the appropriateness of the interpretation of the

results of a test or evaluation instrument for a given group of individuals

and not to the instrument itself (Norman E Gronlund and Robert L. Linos

1990). It is known that every test is constructed within a purpose, i.e to

200

provide measures of a defined variable. Then it is said that the test is

valid. The investigator established the content validity.

Content Validity

The draft tool I (SSPIS) which consisted of 100 items, was given to

five experts in St. Xavier’s College of Education (Autonomous),

Palayamkottai for their comments and suggestions. Some irrelevant items

were deleted and some items were reformulated and refined on the basis

of the suggestions given by them. The tool was also given to the guide for

his comments. Some modifications were made in the statements on the

basis of his comments. Thus the draft tool II (SSPIS) has 72 statements.

Thus the content validity of the tool was established.

Establishing Reliability

The investigator used test – retest method to establish reliability of

the final tool that consists of 52 items. For establishment of reliability the

investigator collected the required data from a total of 50 students of

higher secondary students of Christhu Raja higher secondary school, St

John’s higher secondary school, Angelo matriculation school, St. Ignatius

higher secondary school and Kallanai - Corporation girls’ higher

secondary school, Tirunelveli. After an interval of 15 days the same tool

was administered to the same set of students. The reliability coefficient

was found as 0.80 which is highly reliable. Thus, the reliability of the tool

was established. It is given in the following table:

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Table 3.5 Dimension – wise reliability coefficient - SSPIS

No Dimension Reliability

coefficient

1 Parenting 0.79

2 Parent and school relationship 0.80

3 Parent and academic involvement 0.81

4 Parent and multi skill development 0.78

5 Parental Influence 0.80

Table 3.6 Description of Final Tool of SSPIS

No Dimensions Item numbers

1 Parenting 1 – 13

2 Parent and school relationship 14 – 26

3 Parent and academic

involvement

27 – 39

4 Parent and multi skill

development

40 – 52

The highest possible score is 260 and lowest score is 52.

Table 3.7 Scoring Key

Responses Scores

Highly Agree 5

Agree 4

Undecided 3

Disagree 2

Highly disagree 1

2. EMOTIONAL INTELLIGENCE INVENTORY

The emotional intelligence inventory was designed by Thomas

Alexander (2007). It was adopted by the investigator. The inventory

consists of 80 items. The inventory attempts to find out the emotional

intelligence of the students in four areas and also the over all emotional

intelligence.

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Table 3.8 Item distribution – emotional intelligence

Dimensions Item numbers

Self-awareness 1 – 17

Self-management 18 – 40

Social awareness 41 – 52

Relationship management 53 – 80

The above table shows that 80 items are equally distributed on the

four areas namely self-awareness, self-management, social awareness, and

relationship management. The author has already established the

reliability and validity of the tool. The author established the concurrent

validity of the tool. The concurrent validity is 0.81.

Table 3.9 Scoring key for emotional intelligence

Responses Scores

Highly Agree 5

Agree 4

Undecided 3

Disagree 2

Highly disagree 1

DATA COLLECTION

Data were collected with the help of the research tools outlined in

this chapter. The investigator has met the heads of the schools, got

permission and administered the tools to 1080 higher secondary students

belonging to these schools, forming the sample. The tools were

administered to the students with the help of the respective class teachers.

These tools were administered to the higher secondary students by the

investigator in one sitting. The investigator administered the tools only in

Tirunelveli Thoothukudi revenue districts. He administered the tools all

over these districts from August 2009 to July 2010. The students have

been given the duration of the time limits for answering the items of the

tools as given in table 3.10.

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Table 3.10 Duration of the administration of the tools

Tools Duration

Parental influence 20 mins

Emotional intelligence 35 mins

Total duration of the tools 55 mins

The total time taken for all the tools is fifty five minutes.

SCORING OF THE RESPONSES

The responses of the students on all the tools were scored according

to the weightage assigned by the tool constructors. The incomplete or

partially answered items were left out. The scores obtained were kept as a

raw score. Academic achievement score was the marks obtained by XI

standard students in the Govt. public examination 2009–2010 for various

subjects. The marks were collected from the school records. The

percentage of the total marks was taken as the score for the academic

achievement.

TABULATION OF THE RESPONSES ON THE DATA SHEETS

The scores obtained on each of the tool and academic achievement

of every respondent were entered in printed data sheet. The data were fed

into the computer and stored in the compact disk. The collected data were

analysed with the help of the SPSS statistical package.

STATISTICAL TECHNIQUES USED

The major statistical techniques used were

1. Mean and Standard Deviation

204

2. Fixing levels and scoring out the cases with the help of T-scores

3. Critical ratio test (t-test)

4. Analysis of variance (ANOVA)

5. Chi-square test

6. Pearson’s product moment correlation

7. Regression and

8. Factor Analysis

The above techniques have been elaborated in the following pages.

PERCENTAGE ANALYSIS

It is used for computing the level of parental influence and

emotional intelligence of the respondents.

After calculating Mean and Standard Deviation, the raw scores

were converted in to T- scores with the help of the formula.

Where T = T- score

X= Raw score

M= Mean

S= Standard Deviation

S

M][X1050T

−+=

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Table 3.11 The levels are fixed as follows

Fixation Below 40 40 to 60 Above 60

Scores Mean-1SD< Mean Mean+1SD>

Levels Low Moderate High

THE ‘t’ TEST

The ‘t’- test is used to find out the significant difference between

the means of different variables for different subgroups.

Where M1= the mean for the first group

M2= the mean of the second group

S1= the standard deviation for the first group

S2= the standard deviation for the second group

N1= the size of the first group

N2= the size of the second group

Here the investigator has fixed 5% level of significance to test the

hypothesis.

ANOVA

Analysis of variance has been used to find out the significant

difference among SC/ST, MBC, BC and OC higher secondary students,

the difference among boys, girls and co-education school higher

secondary students and the difference among aided, government and

matriculation school higher secondary students, in their parental influence

and emotional intelligence.

)/NS/N(S

MMt

22

212

1

21

+

−=

206

SCHEFFE INTERVAL

Scheffe is the most conservative of all post hoc tests. It has more

power when making complex comparisions. It is appropriate to use

Scheffe test only when making post hoc complex comparisons. (eg more

than K-1). If the F ratio is significant then Scheffe test is used to find

which group is more significant. It is calculated by

I Scheffe = [(K-1)*(Fα)*(MSE)*(1/n1+1/n2)]

1/2

Where K - No of groups

Fα – Critical value of F at 5% level (table value)

MSE = MSW - Mean scores within groups

n1,n2 – No of samples within / between groups

CHI-SQUARE ANALYSIS

The Chi-square analysis is employed to test the association between

the variables father’s education, mother’s education, father’s occupation,

mother’s occupation and rank in the family of the higher secondary

students and their parental influence and emotional intelligence.

Where O= the observed frequency

E = the expected frequency

E

E)Σ[(O 22 −

=χ

Variance between the groups F

Variance within the groups=

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For testing the hypothesis, the investigator has the 5% level of

significance. For finding the degrees of freedom the investigator has used

the following formula.

df= (r-1) (c-1)

Where r= number of rows, c= number of columns

CORRELATION ANALYSIS

Pearson’s product moment correlation is used for determining the

reliability, validity, coefficients and also for ascertaining the relationship

among the dependent variables. This is employed to find out the

relationship between parental influence and emotional intelligence.

Where

r = Product moment correlation coefficient

x,y = Variables studied

N = Number of paired observations.

The investigator has fixed 5% level of significance to test the

hypothesis.

Pearson r is used for estimating the extent of relation exiting among

the different variables taken in pairs for all the different groups. Garrett

(1969) presents the following classification for interpreting the various

values of r, which is adopted for the study.

( )))(/())((

))((r

2222yyNxxN

yxxyN

Σ−ΣΣ−Σ

ΣΣ−Σ=

208

r from 0.00 to + 0.20denotes indifferent or negligible correlation.

r from + 0.20 to + 0.40denotes low correlation.

r from + 0.20 to + 0.70denotes substantial correlation.

r from + 0.70 to + 1 denotes high to very high correlation.

The correlation is interpreted only after the statistical significance

of coefficient of correlation is considered from the tables. In the present

study it is seen the if “r” exceeds 0.161 it is significant at 5%level, if “r”

below 0.161 the correlation is not statistically significant (Garrett 1969)

MULTIPLE CORRELATIONS

Multiple correlations are used for estimating the inter-correlations

among independent variables as well as to the correlations with the

dependent variable. The co-efficient of multiple correlation indicates the

strength of relationship between one variable (independent variable) and

two or more others (dependent variables) taken together. This is employed

to find out the influence of parental influence and emotional intelligence

on academic achievement.

FACTOR ANALYSIS

Harman (1960) defines the procedure of factor analysis as follows:

The principal concern of factor analysis is the resolution of a set of

variables linear by in terms of a smaller number of categories or “factors”.

This resolution can be accomplished by the analysis of the correlation

among the variables. A satisfactory solution will yield factors, which

convey all the essential information of the original set of variables. Thus,

the chief aim is to attain scientific parsimony or economy of description”.

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Guilford (1956) outlines the different steps in factor analytic study in the

following term:

a. Select an appropriate domain for investigation.

b. Develop a hypothesis concerning the factor.

c. Select or construct suitable tests.

d. Select a suitable population.

e. Obtain a sample of adequate axes.

f. Extract factors with commonalities in the diagonal cells or the

correlation matrix.

g. Rotate the reference axes.

h. Interpret the rotated factors.

The present investigation made use of principal-axes method, as it

is one of the satisfactory procedures of factor analysis. Fruchter (1954)

explains the superiority of this method in the following terms.

The principal-axes method of factoring the correlation matrix is of

interest of several reasons. Each factor extracts the maximum amount of

variance, (i.e., the sum of squares of factor loadings is maximized on each

factor) and gives the smallest possible residuals. The correlation matrix is

condensed into the smallest number of orthogonal factors by this method.

The method also has an advantage of giving mathematically unique (least

square) solution for a given table of correlations. Harman (1960) points

out that this method needs larger number of computations. But this

difficulty is overcome with the help of high-speed computers.

210

TEST OF SIGNICICANCE OF EXTRTACTED FACTORS

The test of significance is applied to the obtained factors and only

those, which are significant, are retained for final interpretation.

INTERPRETATION OF FACTORS: PRINCIPLES AND

CRITERIA

a. Locate the group of variables on which the factor has the highest

loadings.

b. Locate the group of variables on which the factor has the lowest

loadings.

c. Examine the possibility of different factors becoming independent.

d. Treat factor loading whose absolute values are greater than 0.30as

significant and neglect others as not significant

The degree of presence of each variable is a factor determined as follows:

a. Factor loading above 0.900 - extremely high presence of the

variable.

b. Factor loading above 0.700 to 0.900 - very high presence of the

variable.

c. Factor loading above 0.550 to 0.700 - considerable presence of the

variable.

d. Factor loading above 0.450 to 0.550 - variable somewhat present.

e. Factor loading above 0.300 to 0.450 - variable present but low.

f. Factor loading below 0.300 - variable not present.

Analysis and discussion of the results follow in the next chapter.

211

FIXING THE LEVEL FOR TESTING HYPOTHESIS

The investigator fixed 5% level of significance for testing the

hypothesis. If the calculated value is greater than the table value, the null

hypothesis is rejected. If the calculated value is less than the table value,

the null hypothesis is accepted.