This document discusses various concepts related to research methodology including: 1. Research problems can involve areas that need improvement or difficulties that need to be eliminated. Sources of research topics include personal experiences, literature, theories, previous research, and more. 2. Factors determining the research problem include ethical issues, significance, feasibility, and availability of subjects. Criteria for selecting topics include novelty, interest, practical/theoretical value, and more. 3. The statement of the problem should include a clear problem statement, evidence it exists, probable causes, and a specific research question.

1. ADVANCED EDUCATIONAL
RESEARCH METHODOLOGY
UNIT-II
Dr.N.Sasikumar
Assistant Professor
Department of Education
Alagappa University
Karaikudi-630003

2. RESEARCH PROBLEM
 This can be anything that anybody finds
unsatisfactory or unsettling
 Research problems involve areas of concern or
conditions that might need improvement and
difficulties that need to be eliminated

3. SOURCES OF RESEARCH TOPICS
 Personal experiences
 Literature sources
 Existing theories
 Previous research
 Academic experiences
 Brain storming
 Intuition
 Consultations
 Social issues
 Professional experience

4. FACTORS DETERMINING THE RESEARCH PROBLEM
 Ethical issues
 Significance for nursing
 Personal motivation
 Qualifications of the researcher
 Feasibility of the study
 Support from administration
 Availability of subjects.

5. CRITERIA FOR SELECTION OF A RESEARCHABLE TOPIC
 Novelty
 Researcher’s Interest in the Problem
 Practical Value of the Problem
 Theoretical Value of the Problem
 Availability of Data
 Capability of the Researcher
 Special Equipment
 Sponsorship
 Administrative Support
 Cost of Research
 Time Frame
 Hazards

6. STATEMENT OF THE PROBLEM
This should include
 A clear statement that the problem exists,
 Evidence that supports the existence of the problem,
 Evidence of an existing trend that has led to the
problem,
 Definitions of major concepts and terms (this can be
provided below in a subsection),
 A clear description of the setting,
 Probable causes related to the problem, and
 A specific and feasible statement.

7.  The Topic
This is a brief description of the proposed area of study. Include at
least two sentences.
 The Research Problem
This is an area of conflict, concern, or controversy (a gap between
what is wanted and what is observed). Include the most relevant reference
that supports the claim.
 Background and Justification
The evidence and relevance from the literature and published or
archival data showing the problem exists. Include at least two references.
You should also have a theoretical basis for the study.

8.  Deficiencies in the Evidence
Include a brief discussion that details the area of need (in relation to
the problem) and the deficiency or lack of evidence in the literature.
 Audience
Discuss who is affected and who benefits.
 Definition of Terms
Provide complete scientific definitions and appropriate references
if necessary. Include as many terms or variables as needed.
 Purpose of the Study
Create a sentence that begins with “The purpose of this study is . .
.” Clearly identify and define the central concepts or ideas of the study.

9. EXAMPLE OF THE FLOW OF IDEAS IN THE PROBLEM STATEMENT
T
opic Research
Problem
Justification
for Research
Problem
Deficiencies in
the Evidence
Relating the
Discussion
to Audiences
Subject
area
•Concern or issue
•A problem
•Something that
needs a solution
•Evidence from the
literature
•Evidence from
•In this body of
evidence what is
missing or what
practical experience do we need to
•How will addressing
what we need to know
help researchers,
educators, policy
know more about? makers, and other
individuals?
An Example
Ethical
issues
in
colleges
Flow of Ideas
Ethical
violations
among football
recruiters
•Gap in the literature
•Reports of violations
Description
identifying and
characterizing
violations
•Assessing violations
•Helps recruiters develop
better ethical standards
•Understand ethical
issues

10. WHAT IS LITERATURE REVIEW?
 It is a survey of existing theories, empirical
research studies and reports. This is done to
understand the critical points of current
knowledge, findings and theoretical and
methodological contributions to a particular area
of research.
 It provides an understanding about what has been
done in the past in a particular area of research.
 It gives strong theoretical foundation about the
selected research area.

11. SIGNIFICANCE OF LITERATURE SURVEY
 Research begins with literature survey, but there
is no end to it.
 It is like infrastructure for systematic research.
 With strong foot in literature, any researcher can
reply with any kind of criticisms/questions.
 Literature survey itself can be a research output.
 It provides every idea about a new research.
 Without literature survey, invention is difficult.
 It is a road map for research.
 Without studying past, studying future is difficult.

12. WHAT CONSISTS LITERATURE SURVEY?
 Many believe that literature survey means reviewing only the
journal articles, which is not correct. It includes:
 Original theories written by founders
 Journals
 Books
 Committee and Commission reports
 Government reports
 Dissertations and theses
 News papers
 Archives materials
 Website materials
 Personal communications with leading scholars

13. HYPOTHESIS
 Hypothesis is considered as an intelligent guess or prediction, that gives
directional to the researcher to answer the research question.
 Hypothesis or Hypotheses are defined as the formal statement of the tentative
or expected prediction or explanation of the relationship between two or
more variables in a specified population.
 A hypothesis is a formal tentative statement of the expected relationship
between two or more variables under study.
 A hypothesis helps to translate the research problem and objective into a
clear explanation or prediction of the expected results or outcomes of the
study.
 Hypothesis is derived from the research problems, literature review and
conceptual framework.
 Hypothesis in a research project logically follow literature review and
conceptual framework.

14. IMPORTANCE OF HYPOTHESIS
 It provides clarity to the research problem and research
objectives
 It describes, explains or predicts the expected results or
outcome of the research.
 It indicates the type of research design.
 It directs the research study process.
 It identifies the population of the research study that is to be
investigated or examined.
 It facilitates data collection, data analysis and data
interpretation
 It stimulates the thinking process of researcher as the
researcher forms the hypothesis by anticipating the outcome.

15. TYPES OF HYPOTHESIS
HYPOTHESIS
Directional Hypothesis
Non Directional Hypothesis
Null Hypothesis
Attributive Hypothesis
(Descriptive)
Associative Hypothesis
Casual Hypothesis
(Explanatory)
Question Form
Hypothesis
Correlational Hypothesis
Difference Hypothesis

16. DIRECTIONAL HYPOTHESIS
 Directional Hypothesis predicts the direction of the
relationship between the independent and dependent
variable.
 If, however, the hypothesis uses so-called comparison
terms, such as “greater”, “less”, “ better”, or “worse”,
then it is a directional hypothesis. It is directional
because it predicts that there will be a difference between
the two groups and it specifies how the two groups will
differ
 Example- “High quality of Teacher education will lead
to high quality of teaching skills.”

17. NON DIRECTIONAL HYPOTHESIS
 Non -directional Hypothesis predicts the relationship
between the independent variable and the dependent
variable but does not specific the directional of the
relationship.
 If the hypothesis simply predicts that there will be a
difference between the two groups, then it is a
nondirectional hypothesis. It is non-directional because it
predicts that there will be a difference but does not
specify how the groups will differ.
 Example- teacher student relationship influence student’s
learning.

18. ATTRIBUTIVE HYPOTHESIS (DESCRIPTIVE)
 The attributive hypothesis explains the
propositions that typically state the existence size,
form or distribution of some variables
Example
 There is a drop out students in high schools
 Attendance in schools has not increased after the
introduction of special class
 There is no water source in the planet “Jupiter”

19. ASSOCIATIVE HYPOTHESIS
 The associative hypothesis considered the
relationship between variables expressed in the
forms such as association and difference form
Example
 Families with higher income ladies spend more
money on cosmetics usage.(Association Form)
 The drop out rate in rural school is higher than
those in urban schools (Difference form)

20. CASUAL HYPOTHESIS (EXPLANATORY)
 Causal Hypothesis predicts a cause and effects
relationship or interaction between the
independent variable and dependent variable.
This hypothesis predicts the effect of the
independent variable on the dependent variable.
 The relational propositions which strongly imply
or state the existence of change in one variable
causes or leads to an effect on another variable.
The first variable typically the independent
variable and the later the dependent variable.

21. CASUAL HYPOTHESIS
 In this the independent variable is the
experimental or treatment variable. The
dependent variable is the outcome variable
Example
 Effective communication in English teaching will
increase the speaking ability of students
 Problem solving methods in mathematics
teaching increase the general problem solving
ability of the pupil.

22. NULL HYPOTHESIS
 Null hypothesis is a non-directional hypothesis, it
states that no significant difference or no
relationship exists.
 Null Hypothesis is also called statistical
hypothesis because this type of hypothesis is used
for statistical testing and statically interpretation.
 The null hypothesis predicts that, there is no
relationship between the independent variable
and dependent variable.

23. NULL HYPOTHESIS
It is denoted by Ho
Example:
 There is no significant relationship between
academic achievement and study habit.
 There is no difference in emotional maturity
between boys and girls.

24. QUESTION FORM HYPOTHESIS
 it Is the simplest form of empirical hypothesis. In simple case of
investigation and research are adequately implemented by
resuming a question.
 Whenever we are not sure of the relationship existing between the
variables, we usually think to frame our hypothesis in the null
form (or) Question form.
Example:
 Does the poor economic status affect the academic performance?
 Is there a significant difference in achievement between male and
female in mathematics?
 How is the ability of 9th class students in learning moral values?

25. SAMPLE
 A sample can be defined as a group of relatively
smaller number of people selected from a
population for investigation purpose.
 The members of the sample are called as
participants
 Sampling: The process of selecting a number of
individuals for a study in such a way that the
individuals represent the larger group from which
they were selected.

26. SAMPLING
Target Population or Universe
The population to which the investigator wants to generalize his
results
Sampling Unit:
smallest unit from which sample can be selected
Sampling frame
The sampling frame is the list from which the potential
respondents are drawn
Telephone directory
List of school
List of student
Sampling scheme
Method of selecting sampling units from sampling frame Sample:
all selected respondent are sample

27. SAMPLE
•A population can be defined as including all people or items with the characteristic one
wishes to understand.
•Because there is very rarely enough time or money to gather information from everyone or
everything in a population, the goal becomes finding a representative sample (or subset) of
that population
SAMPLE UNIT
SAMPLE
.
TARGET POPULATION

28. Three university in TN
SAMPLING BREAKDOWN
All university in India
All university TN
List of TN university

29. WHY SAMPLE?
Get information about large populations
 Lower cost
 More accuracy of results
 High speed of data collection
 Availability of Population elements.
 Less field time
 When it‟s impossible to study the whole population

30. SAMPLING……
 To whom do you want to generalize your
results?
 All Schools
 All Travel Agency
 All Hotel Customer
 Women aged 15-45 years
 Other
 Sample size : Minimum size is 30 no.

31. SAMPLING…….
 3 factors that influence sample representative-ness
Sampling procedure
Sample size
Participation (response)
 When might you sample the entire population?
When your population is very small
When you have extensive resources
When you don‟t expect a very high response

32. The sample must be:
1. representative of the population;
2. appropriately sized (the larger the better);
3. unbiased;
4. random (selections occur by chance);
Merits of Sampling
 Size of population
 Fund required for the study
 Facilities
 Time
WHAT IS GOOD SAMPLE?

33. TYPES OF SAMPLE BASED ON TWO FACTORS:
THE RESPRESENATION BASIS
 PROBABILITY SAMPLING
 NON PROBABILITY SAMPLING

34. •Probability sample – a method of sampling that uses
of random selection so that all units/ cases in the
population have an equal probability of being chosen.
•Non-probability sample – does not involve random
selection and methods are not based on the rationale of
probability theory.
Sampling
T
echniques
Probability
Non-
Probability

35.  Probability (Random) Samples
 Simple random sample
 Systematic random sample
 Stratified random sample
 Cluster sample
Probability
Sampling
Simple
Random
Sampling
Systematic
Sampling
Stratified
Random
Sampling
Proportionate
Dis Proportionate
Cluster
Sampling
One-
Stage
Two
Stage
Multi-
Stage

36. Non-Probability Samples
Convenience samples (ease of access)
sample is selected from elements of a population that are
easily accessible
Purposive sample (Judgmental Sampling)
You chose who you think should be in the study
Quota Sampling
Snowball Sampling (friend of friend….etc.)

37. SIMPLE RANDOM SAMPLING
• Applicable when population is small, homogeneous & readily
available
• All subsets of the frame are given an equal probability. Each
element of the frame thus has an equal probability of selection. A
table of random number or lottery system is used to determine
which units are to be selected.
• Every item has on equal chance to be selected
Advantage
 Easy method to use
 No need of prior information of population
 Equal and independent chance of selection to every element

38. Simple random sampling
Every subset of a specified size n from the population
has an equal chance of being selected

39. SUITABILITY
• This method is suitable for small homogeneous
• Randomly selecting units from a sampling frame.
„Random‟ means mathematically each unit from the
sampling frame has an equal probability of being
included in the sample.
• Stages in random sampling:
Define
population
Develop
sampling
frame
Assign each
unit a
number
Randomly
select the
required
amount of
random
Systematically
select random
numbers until it
meets the
sample size
numbers requirements
Kumar

40.  Sampling schemes may be without replacement or with
replacement
 For example, if we catch fish, measure them, and
immediately return them to the water before continuing
with the sample, this is a with replacement design,
because we might end up catching and measuring the
same fish more than once. However, if we do not return
the fish to the water (e.g. if we eat the fish), this becomes
a without replacement design.
REPLACEMENT OF SAMPLE UNITS

41. •Similar to simple random sample. No table of random
numbers – select directly from sampling frame. Ratio
between sample size and population size
Define
population
Develop
sampling
frame
Decide the
sample size
Work out
what fraction
of the frame
the sample
size represents
Select
according to
fraction (100
sample from
1,000 frame then
10% so every
First unit
select by
random
numbers
then every
10th unit
selected
10th unit) (e.g. every
10th)
Sunil Kumar

42. ADVANTAGES:
Sample easy to select
Suitable sampling frame can be identified easily
Sample evenly spread over entire reference population
Cost effective
DISADVANTAGES:
Sample may be biased if hidden periodicity in population
coincides with that of selection.
Each element does not get equal chance
Ignorance of all element between two n element
SYSTEMATIC SAMPLING

43. Systematic sampling
Every member ( for example: every 20th person) is
selected from a list of all population members.

44.  The population is divided into two or more groups
called strata, according to some criterion, such as
geographic location, grade level, age, or income, and
subsamples are randomly selected from each strata.

45. Stratified random sampling can be classified in to
a. Proportionate stratified sampling
It involves drawing a sample from each stratum in
proportion to the letter‟s share in total population
b. Disproportionate stratified sampling
proportionate representation is not given to strata it
necessery involves giving over representation to
some strata and under representation to other.

46. Advantage :
 Enhancement of representativeness to each sample
 Higher statistical efficiency
 Easy to carry out
Disadvantage:
 Classification error
 Time consuming and expensive
 Prior knowledge of composition and of
distribution of population

47.  Cluster sampling is an example of 'two-stage sampling' .
 First stage a sample of areas is chosen;
 Second stage a sample of respondents within those areas is
selected.
 Population divided into clusters of homogeneous units,
usually based on geographical contiguity.
 Sampling units are groups rather than individuals.
 A sample of such clusters is then selected.
 All units from the selected clusters are studied.
 The population is divided into subgroups (clusters) like
families. A simple random sample is taken of the
subgroups and then all members of the cluster selected are
surveyed

48. Cluster sampling
Section 4
Section 5
Section 3
Section 2
Section 1

49. CLUSTER SAMPLING…….
Advantages :
Cuts down on the cost of preparing a sampling
frame. This can reduce travel and other
administrative costs.
Disadvantages: sampling error is higher for a simple
random sample of same size. Often used to
evaluate vaccination coverage in EPI

50. •Cluster sampling: selecting a sample based on specific, naturally occurring
groups (clusters) within a population.
- Example: randomly selecting 20 hospitals from a list of all hospitals in
England.
Multi-stage sampling: cluster sampling repeated at a number of levels.-
Example: randomly selecting hospitals by county and then a sample of
patients from each selected hospital.
Complex form of cluster sampling in which two or more levels of units are
embedded one in the other.
First stage, random number of districts chosen in all states.
Followed by random number of talukas, villages. Then third stage units will
be houses.
All ultimate units (houses, for instance) selecSteundil aKtulmaasrt step are
surveyed.

51. Advantage: A sample selected for ease of access,
immediately known population group and good response
rate.
Disadvantage: cannot generalise findings (do not know
what population group the sample is representative of) so
cannot move beyond describing the sample.
•Problems of reliability
•Do respondents represent the target population
•Results are not generalizable
unil Kumar
S
Use results that are easy to get

52. JUDGMENTAL SAMPLING OR PURPOSIVE SAMPLING
 - The researcher chooses the sample based on who they
think would be appropriate for the study. This is used
primarily when there is a limited number of people that
have expertise in the area being researched
 Selected based on an experienced individual‟s belief
 Advantages
Based on the experienced person‟s judgment
 Disadvantages
Cannot measure the respresentativeness of the sample

53. QUOTA SAMPLING
 The population is first segmented into mutually exclusive sub-
groups, just as in stratified sampling.
 Then judgment used to select subjects or units from each
segment
based on a specified proportion.
 For example, an interviewer may be told to sample 200 females
and 300 males between the age of 45 and 60.
 It is this second step which makes the technique one of non-
probability sampling.
 In quota sampling the selection of the sample is non-random.
 For example interviewers might be tempted to interview those who
look most helpful. The problem is that these samples may be
biased because not everyone gets a chance of selection. This
random element is its greatest weakness and quota versus
probability has been a matter of controversy for many years

54.  Quota sampling
Based on prespecified quotas regarding demographics,
attitudes, behaviors, etc
 Advantages
Contains specific subgroups in the proportions desired
May reduce bias
easy to manage, quick
 Disadvantages
Dependent on subjective decisions
Not possible to generalize
only reflects population in terms of the quota, possibility of
bias in selection, no standard error
Types of Non probability Sampling Designs

55.  Snowball Sampling
 Useful when a population is hidden or difficult to gain access to. The
contact with an initial group is used to make contact with others.
Respondents identify additional people to included in the study
 The defined target market is small and unique
 Compiling a list of sampling units is very difficult
 Advantages
Identifying small, hard-to reach uniquely defined target population
Useful in qualitative research
access to difficult to reach populations (other methods may not
yield any results).
 Disadvantages
Bias can be present
Limited generalizability
not representative of the population and will result in a biased
sample as it is self-selecting.

56. DELIMITATION/LIMITATION
 Limitations Potential weaknesses of the study ,
things researchers could not control
 Delimitations Bounds you set for the study,
things researchers could control Define scope
of the study

57. LIMITATIONS
 Research approach,
 design and methods
 Sample Problem
 Uncontrolled variables Generalizability of the
data
 Reliability and validity of research
instruments

58. DELIMITATIONS
 Number & kinds of subjects
 Treatment conditions
 Tests
 Measures
 Instruments used
 Type of training (time and duration)