[Latest] Free UGC NET Physical Education Unit 8 Notes 2024

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UGC NET Physical Education Unit 8 Note

Research Methodology Part I

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Research Methodology

Part-I

Meaning

Research is an endeavor to discover answers to intellectual and practical problems through the application of scientific methods.

“Research is a systematized effort to gain new knowledge”-Redman and Mory.
Research is the systematic process of collecting and analyzing information (data) in order to increase our understanding of the phenomenon about which we are concerned or interested.

Objectives of Research

The purpose of research is to discover answers through the application of scientific procedures.

The objectives are:

To gain familiarity with a phenomenon or to achieve new insights into it.
To portray accurately the characteristics of a particular individual, situation or a group.
To determine the frequency with which something occurs or with which it is associated with something else.
To test a hypothesis of a causal relationship between variables.

Characteristics of Research

Research is directed towards the solution of a problem.
Research is based upon observable experience or empirical evidence.
Research demands accurate observation and description.
Research involves gathering new data from primary sources or using existing data for a new purpose.
Research activities are characterized by carefully designed procedures.
Research requires expertise i.e., skill necessary to carryout investigation, search the related literature and to understand and analyze the data gathered.
Research is objective and logical – applying every possible test to validate the data collected and conclusions reached.
Research involves the quest for answers to unsolved problems.
Research requires courage.
Research is characterized by patient and unhurried activity.
Research is carefully recorded and reported.

Scientific Method

‘Science’ refers to the body of systematic and organized knowledge which makes use of scientific methods to acquire knowledge in a particular field of inquiry.
Scientific method is the systematic collection of data (facts) and their theoretical treatment through proper observation, experimentation and interpretation.
Scientific method attempts to achieve a systematic interrelation of facts by experimentation, observation, and logical arguments from accepted postulates and a combination of these three in varying proportions.

Basic Postulates In Scientific Method

It relies on empirical evidence.
It utilizes relevant concepts.
It is committed to only objective considerations.
It presupposes (seek) ethical neutrality.
It results into probabilistic predictions.
The methodology is made known.
Aims at formulating scientific theories.

Criteria of Good Research

Purpose clearly defined.
Research process detailed.
Research design thoroughly planned.
High ethical standards applied.
Limitations frankly revealed.
Adequate analysis for decision maker’s needs.
Findings presented unambiguously.
Conclusions justified.
Researcher’s experience was reflected.

Quality of Good Research

• Systematic
• Logical
• Empirical
• Replicable
• Creative
• Use of multiple methods

NEED FOR RESEARCH

Exploration
Describe
Diagnostic
Hypotheses
Induction And Deduction

Inductive and deductive

Deduction (general to specific)
“top-down“ approach – thinking up a theory about our topic of interest – then narrow that down

Induction (specific to general)
Bottom up approach – moving from specific observations to broader generalizations and

Scope of Research

Research for decision making
Throws light on risks and uncertainty
Identify alternative courses of action
Helps in economic use of resources
Helps in project identification
Solves investment problem
Solves pricing problems
Solves allocation problems
Solves decision making issues in HR
Solves various operational and planning problems of business and industry
Provides the basis for all government policies in our economic system.
Helps social scientists in studying social relationships and in seeking answers to various social problems.
For students, research means a careerism or a way to attain a high position in the social structure.
For professionals in research, it may mean a source of livelihood.

Problems in Research

Not similar to science
Uncontrollable variables
Human tendencies
Time and money
Lack of computerization
Lack of scientific training in the methodology of research
Insufficient interaction between university research departments and business establishments
Lack of confidence on the part of business units to give information
Lack of code of conduct
Difficulty of adequate and timely secretarial assistance
Poor library management and functioning
Difficulty of timely availability of published data.
Ignorance
Research for the sake of research-limited practical utility though they may use high sounding business jargon (shabd jaal).

Role of Research In Decision Making

Decision-making is the process of selecting the best alternative from the available set of alternatives.
Management is chiefly concerned with decision- making and its implementation.
These decisions should be based on appropriate studies, evaluations and observations.
Research provides us with knowledge and skills needed to solve the problems and to meet the challenges of a fast paced decision-making environment.

According to Herbert A Simon, decision- making involves three activities:

Intelligence Activity – scanning the environment for identifying conditions necessary for the decision.

Designing Activity – identifying, developing and analyzing the alternative courses of action.

Choice Activity – choosing the best course of action from among the alternatives.

FACTORS THAT AFFECT MANAGERIAL
DECISIONS

INTERNAL FACTORS – factors present inside an organization such as resources, technology, trade unions, cash flow, manpower etc.

EXTERNAL FACTORS – factors present outside the organisation such as government policies, political factors, socio-economic factors, legal framework, geographic and cultural factors etc.

QUANTITATIVE FACTORS – factors that can be measured in quantities such as time, resources, cost factors etc.

QUALITATIVE FACTORS – factors that cannot be measured in quantities such as organizational cohesiveness, sense of belonging of employees, risk of technological change etc.

UNCERTAINTY FACTORS – factors which cannot

Research Methodology

(Part – II)

Types of Research Methods

1) On the basis of objectives
Fundamental research
Applied research
Action research

2) On the basis of nature of data
Qualitative Research
Quantitative Research

3) On the basis of the nature of findings.
Explanatory
Exploratory
Descriptive

4) On the basis of approach involved
Longitudinal Research
Cross-sectional Research
Mixed Research

5) On the basis of Experimental manipulations.
Experimental research
True- experimental Research
Quasi-experimental Research
Non – Experimental Research
Historical
Philosophical
Ex-post facto Research
Correlational Studies

TYPES OF RESEARCH METHODS

1). Descriptive Research

It is a fact finding investigation which is aimed at describing the characteristics of an individual, situation or a group (or) describing the state of affairs as it exists at present.
It includes surveys and fact findings enquiries of different kinds.
It answers the question , what is?
It works as both qualitative and quantitative but mostly serve as qualitative.

Points to be noted –
It gathers data on the basis of opinions, views, observations at present.
No manipulation.
No cause and effect.
Sample size should be large (N >30).

(Example– Effectiveness of Physical Education teacher towards development of physical education profession).

2) Analytical Research

It is also called in-depth study and is primarily concerned with testing hypothesis and attempts to explain complex phenomena. Different types of analytical research are – Historical, Philosophical , research synthesis etc.-
It is concerned with the question, “WHY”.

3) Exploratory Research (Formulate Research) –

It is conducted for a problem that has not been clearly defined and to explore group or questions.
The answer and analysis may not may not offer a final conclusions but can provide significant insight into a given situation.
It is having qualitative approaches.
It seeks the question, how long?

Example – How to improve the mental abilities of physical education students?

4) Fundamental Research

It is also known as basic or pure research undertaken for the sake of knowledge, without any intention to apply it in immediate practice.
It is mainly concerned with generalizations and with the formulation of theory.
It is undertaken out of intellectual curiosity and is not necessarily problem-oriented.
It aimed to improve scientific theories for improving predictions or natural phenomena.

Examples – i) How this universe begins?
ii) Why are people involve in physical activity?

5). Applied Research or Action Research

It is carried out to find a solution to a real life problem requiring an action or policy decision. It is a solution specific. It aims at findings a solution for an immediate problem facing a society or an organization.

Focused on an immediate problems.
Focused on general immediate problems

it can be exploratory, but usually descriptive. It is very specific.

Action Research

Focused on educational problems

Focused on an immediate problems.

Have more control over settings.

Example – 1) How to improve the strength in the class?
2) How to improve the economical condition?
3) How to improve teaching efficiency?

6). Experimental Research –

It is designed to assess the effect of one particular variable on a phenomenon by keeping the other variables constant or controlled.
It is a cause and effect research.
It seeks the question, what will be?

Important points –
Manipulations
Cause and effect
Quantitative approach
Unbiased
Control
Example – Effect of four weeks Diet and exercise plan on obese females.

7) Historical Research –

It is the study of past records and other information sources, with a view to find the origin and development of a phenomenon and to discover the trends in the past, in order to understand the present and to anticipate the future.
It is also called Retrospective Cohort Research.

Example-
Study about Indus valley civilization.
Study about the role of Baron Pierre D. Coubertin for the promotion of Modern Olympics.

7) Conceptual Research (Philosophical)

It is generally used by philosophers and thinkers to develop new concepts or to reinterpret existing ones. It is related to some abstract ideas or theory.

(Example– Socialization is more important than humanization or individualization. )

8) Empirical Research

It is a data based research which depends on experience or observation alone.
It solely depends on available data, evidence and performance.
It is aimed at coming up with conclusions without due regard for system and theory.

(Example – Whenever there is a stimulus there will be a response by changing human behavior – OPERANT THEORY.)

9) Explanatory Research –

It is the research conducted for a problem which was not well research before.
It is actually a type of research design which focuses on explaining the aspects of your study.

Some other types of research

One-time Research – Research confined to a single time period.
(Example – Population researches are called as one time research. )

Longitudinal Research – Research carried on over several time periods.
( Example – Discoveries, inventions .)

Cross-sectional Research –
Research carried out for a short period of time.

Diagnostic Research –
It is also called clinical research which aims at identifying the causes of a problem, frequency with which it occurs and the possible solutions for it.
( Example – What is the cause of obesity in the whole world.)

Normative Research –
Also called normative survey research in which only data are collected from the surveys and analysis of them from the norms and results are declared, no need of variable manipulation.
Examples – Modification of different physical ability tests or making a new motor abilities testing test for different games).

Quantitative Research

It is employed for measuring the quantity or amount of a particular phenomena.
When you want to confirm or test something.
Deals with numbers and statistics.
Its studies include surveys, experimental, content analysis, etc.
( Examples – What is the average population of India?
What should be the average weight of elite athletes?

Qualitative Research

It is a non-quantitative type (nominal or categorical) of analysis which is aimed at finding out the quality of a particular phenomenon.
When you want to understand something.
It deals with words and meaning.
Its studies include interviews, focus groups, literature review, etc.

(Example – Comparative study of attitude towards sports between male and female).

Mixed method
It is also called pragmatic approach to science involves using the method which appears best suited to the research problem and not getting caught in philosophical debates.

This may also use different techniques at the same time or one after another.

Ex-Post Facto Research –
It is also called Quasi Experimental Design in which you study what you can’t control so you just examine how an already existing independent variable affects a dependent variable.
It comes under descriptive as well as experimental research studies.
It is “after the fact” research. It is not randomly selected.
There are no variable manipulations.
(Example – How weight influences self –esteem level in adults).

Methods of Research

Difference between Type, Method, Methodology and technique in Research

Methods of Research – It is defined as a tool or instruments used to accomplish the goals and attributes of a study.

Type of Research – These are the types of research methods which can be classified into several categories according to the nature and purpose of study.

Methodology – Methodology is the systematic, theoretical analysis of the methods applied to the field of study.

Techniques – It is the particular step took to collect the data for further analysis and interpretation process. Used mainly for Data collection and Selection of statistical analysis Procedure

STEPS OF RESEARCH PROCESS

Defining a research problem.
Formulating a research problem.
Extensive literature survey.
Developing or formulating hypothesis.
Preparing Research design.
Sampling design.
Collecting data.
Execution of project.
Analysis of data.
Testing hypothesis.
Generalization and Interpretation
Preparation of the report.

RESEARCH PROBLEM

The term ‘problem’ means a question or issue to be examined.

Research Problem refers to some difficulty /need which a researcher experiences in the context of either theoretical or practical situation and wants to obtain a solution for the same.

HOW DO WE KNOW WE HAVE A RESEARCH PROBLEM?

Players requirements
Conversation with sports persons, coaches, sports lovers
Observation of inappropriate behavior or conditions in the team, club, association.
Deviation from the performance
Success of the competitor
Relevant reading of published material (trends, regulations)
Records and reports.

The first step (definition of the problem) in the research process involves three activities:

Identification of a problem
Selection of the Problem
Formulation of the Problem
Stating the Problem

1) IDENTIFICATION OF THE RESEARCH PROBLEM

This step involves identification of a few problems and selection of one out of them, after evaluating the alternatives against certain selection criteria.

2) CRITERIA OF SELECTION
The selection of one appropriate researchable problem out of the identified problems requires evaluation of those alternatives against certain criteria.
They are:
Internal / Personal criteria – Researcher’s Interest, Researcher’s Competence, Researcher’s own Resource: finance and time.

External Criteria or Factors –
Researchability of the problem, Importance and Urgency, Novelty of the Problem, Feasibility, Facilities, Usefulness and Social Relevance, Research Personnel.

Four Yardstick to select a research Problem
Administrative Feasibility
Reasonability
Novelty
Significance

3) FORMULATION OF THE RESEARCH PROBLEM

Formulation is the process of refining the research ideas into research questions and objectives.

Formulation means translating and transforming the selected research problem/topic/idea into a scientifically researchable question. It is concerned with specifying exactly what the research problem is.

4) STATEMENT OF THE PROBLEM

Problem definition or Problem statement is a clear, precise and succinct statement of the question or issue that is to be investigated with the goal of finding an answer or solution.

There are two ways of stating a problem:

Posting question / question
Ex. – Will keto diet plan benefit endurance elite athlete or not?

Making declarative statement / statements
Ex. – Effect of keto diet plan on endurance athletes.

REVIEW OF LITERATURE

Literature Review is the documentation of a comprehensive review of the published and unpublished work from primary or secondary sources of data in the areas of specific interest to the researcher.

It is an extensive survey of all available past studies relevant to the field of investigation.

To find out problems that are already investigated and those that need further.

It gives us knowledge about what others have found out in the related field of study and how they have done so.

PURPOSE OF REVIEW

To gain a background knowledge of the research topic.
To identify the concepts relating to it, potential relationships between them and to formulate researchable hypothesis.
To identify appropriate methodology, research design, methods of measuring concepts and techniques of analysis.
To identify data sources used by other researchers.
Point a way for further research.
See what has and has not been investigated.

Two types of literature

1) Critical literature – Certain published studies that relate directly to the topic under investigation and so are critical to the subject. These studies must be cited for the review of literature to be complete.

2) Allied literature – Allied literature involves those studies that are related to the investigation but are more peripheral than central in nature.

SOURCES OF LITERATURE

Primary Source –

Literature review most relies on Primary sources.

It is written by a person who developed the theory or conducted the research (original author).

Most primary sources found in published literature.

Secondary Source –

These are the studies prepared by someone other than original researcher.
It is used when primary source is unavailable.

Types of literature sources

Reports, Theses, Newspapers, Books, Indexes, Abstracts, Emails, Journals Catalogues, Conference, Internet Encyclopedias, proceedings, Some government, Dictionaries, Company repons publications, Bibliographies, Government Surveys, publications, Unpublished, manuscript sources, Interviews

RECORDING THE LITERATURE

The most suitable method of recording notes in an organized manner is the card system.
The recording system involves use of two sets of cards:

Source cards (3″x 5″) – used for noting bibliographic information such as author, title, publisher, copyright data, web address, etc.

Note cards (5″x 8″) – used for actual note taking. Contains information about the topic, facts about the topic.

SOURCE CARDS

The recording of bibliographic information should be made in proper bibliographic format.

The format for citing a book is:
Author’s name, (year), Title of the book, Place of publication, Publisher’s name.
For Example; Koontz Harold (1980), Management, New Delhi, McGraw-Hill International.

The format for citing a journal article is:
Author’s name, (year), Title of the article, Journal name, Volume (number), pages.
For Example; Sheth J.N (1973), A Model of Industrial Buying Behaviour, Journal of Marketing, 37(4), 50-56.

NOTE CARDS

Detailed Information extracted from a printed source is recorded on the note cards.

It is desirable to note a single fact or idea on each card, on one side only.

Steps of review of Literature –

Structure of Literature review –

1) INTRODUCTION – Give a quick idea of the topic of literature review, such as the central theme or organizational pattern.

2) BODY – Contains your discussions of sources and is organized either chronologically, trend, thematically, or methodologically.

3) CONCLUSIONS AND RECOMMENDATIONS – Discuss what you have drawn from reviewing literature so far. Where might discussion proceed?

FORMULATION OF HYPOTHESIS

Hypotheses

Hypotheses are tentative, intelligent guesses as to the solution of the problem.
It describes in concrete terms what you expect to happen in the study.
A hypothesis is an assumption about relations between variables.
Research Hypothesis is a predictive statement that relates an independent variable to a dependent variable.
Hypothesis can be defined as a logically conjectured relationship between two or more variables expressed in the form of a testable statement.

TYPES OF HYPOTHESIS
Mainly there are two types of hypothesis –

1) Null Hypothesis
When a hypothesis is stated negatively, it is called null hypothesis. It is a ‘no difference’, ‘no relationship’ hypothesis. i.e., It states that, no difference exists between the parameter and statistic being compared to or no relationship exists between the variables being compared.
It is usually represented as HO .

Example:
H0: There is no relationship between a family’s income and expenditure on recreation.

2) Alternate or Research Hypothesis
It is the hypothesis that describes the researcher’s prediction that there exists a relationship between two variables or it is the opposite of the null hypothesis. It is represented as HA or H1.

Example:
HA: There is a definite relationship between family’s income and expenditure on recreation.

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Some other types of hypothesis…..

1) Descriptive Hypothesis
These are assumptions that describe the characteristics (such as size, form or distribution) of a variable. The variable may be an object, person, organization, situation or event.

Examples:
“Public enterprises are more amenable (responsible) for centralized planning”.

Group study helps to achieve the good results in exams.

2) Relational Hypothesis [Explanatory Hypothesis]
These are assumptions that describe the relationship between two variables. The relationship suggested may be positive, negative or causal.

Example:
“Families with higher incomes spend more for recreation”.

3) Causal Hypothesis states that the existence of or change in one variable causes or leads to an effect on another variable. The first variable is called the independent variable and the latter is the dependent variable.

Example –
Effect of Autogenic training on mental stress.

4) Simple Hypothesis – It shows a relationship between one dependent variable and a single independent variable.

Example – Effect of aerobic exercises on Age.

5) Complex Hypothesis – It shows the relationship between two or more dependent variables and two or more independent variables.

Example –
Effect of aerobic, anaerobic, Plyometric exercises on Age and health.

6) Directional hypothesis–
Directional hypothesis are those where one can predict the direction (effect of one variable on the other as ‘Positive’ or ‘Negative’).

Example –
There will be a positive relationship of moral values and social recognition.

7) Non-directional hypothesis–
Non Directional hypotheses are those where one does not predict the kind of effect but can state a relationship between variable 1 and variable 2. It is more hypothetical.

Example –
There will be a positive relationship of moral values and social recognition.

FORMS OF RELATIONSHIPS

X = Independent variable Y = Dependent variable

NON-DIRECTIONAL
There is a relationship between X & Y
Relationships could be Negative or positive.
As X changes, Y does NOT changeNo Change = NO RELATIONSHIP

DIRECTIONAL

If X goes up, Y up…. (Positive relationship)
or
As X increases, y decreases (Negative relationship)

Research Designs
A research design is the arrangement of conditions for collection and analysis of Measures of variables specified in the problem research.

It constitutes the blueprint for the collection, measurement and analysis of data.

It includes an outline of what the researcher will do from writing the hypothesis and its operational implications to the final analysis of the data.

Research design is all about –

What is the study about ?
Why is the study being made?
Where will the study be carried out?
What type of data is required?
What will be the sample design?
What techniques of data collection will be used?
How will the data be analyzed?
In what style will the report be prepared?

Need of research design

For smooth sailing of the various research operations.
Maximal information with minimal expenditure, effort, and money.
For advance planning of the methods to be adopted for collecting the relevant data and techniques.

Writing styles

APA style ( American Psychological Association) -1929. Eg.- Dwivedi, M. (year).Title.journal,vol(issue),pages.

Dwivedi, M. (2019). Determining teaching effectiveness. International Journal of Physiology, 4(2), 31-34.

MLA style (Modern Language Association)- 1985.
Eg. – Dwivedi, Meenakshi. “Title.”JournalVolume.issue no.(year):pages.

Dwivedi, Meenakshi. “Determining teaching effectiveness.” International Journal of Physiology 4.2 (2019): 31-34.

Chicago – (also known as turbarian) Eg. – Dwivedi, Meenakshi.
“Title”.Journalvolume,no.issue(year):pages.

Dwivedi, Meenakshi. “Determining teaching effectiveness“.
International Journal of Physiology 4, no. 2 (2019): 31-34.

Harvard style –
Author Name, year, Title Journal volume(issue), page no.

RESEARCH PAPER

Title, 2. Abstract, 3. Introduction, 4. Review of literature, 5. Purpose, 6. Research objectives, 7. Methods and materials,
Results, 9. Conclusions, 10. Recommendations, 11. References

THESIS/DISSERTATION

Preliminary pages
Main Body –
• Chapter I
• Chapter II
• Chapter III (Methodology)
• Chapter IV
• Chapter V
• Bibliography
• Appendix
• Introduction
• Purpose

Chapter –III (Methodology)

Selection of subjects
Selection of Variables
Sources of data
Sample size
Sampling design
Collection of data/Experimental Design
Classification of data
Statistical tool or Design

One may split the whole research design into the following parts –

The sampling design
The observation design
The experimental design
Data Collection Design
The statistical design

Types of Research Designs –

On the basis of –

1) Descriptive research design – Case study, Natural Observation, Survey

2) Experimental research design- Pre – Experimental, True – Experimental Quasi-Experimental

3) Exploratory Research Design

Variables

A variable is a measurable characteristic of the individual, group and situation that varies.
E.g. – Age, Gender, Climate, Attitude
A variable is taken in research to get measurement.
It provides a matter to study further in research.
Variability depends upon the hypothesis.

Variable or Attribute

A variable is a characteristic of any value, person, whereas an attribute is a specific value on a variable (qualitative).

For example;
The variable SEX/GENDER has 2 attributes – Male and Female.
The variable AGREEMENT has 5 attributes – Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree.

Seven Types of variables

Independent variable (Exogenous) –
A variable which is being manipulated. An independent variable is the one that influences the dependent variable in either a positive or negative way.
Dependent variable (endogenous) –
A variable which is observed as the effect on the variable.
The variable that changes in relationship to changes in another variable(s) is called a dependent variable.
E.g. – Effect of altitude training on endurance athletes.
Intervening variable –
An intervening variable is a hypothetical variable that is not likely to be directly observable but that links the independent and dependent Variable. They can’t be measurable.

E.g. – Effect of altitude training on endurance athletes.
Intervening variable – Adaptation capacity

4) Moderator variable –
Affect the relationship between independent and dependent variables by modifying the effect of intervening variables. Unlike extraneous, they are measured and taken into consideration.
In correlation studies, the moderating variable is defined as a third variable — z — that affects the correlation between two variables x and
E.g. – Effect of altitude training on endurance athletes.
Moderator variable – Age , gender, language.

Control variable-

• It is not possible to consider every variable in a single study. Therefore, the variable that are not used in a particular study must be held constant so that they will not have a biasing effect on other variables.

• It is also used to minimize the effect of extraneous variables.
[ E.g. – Effect of altitude training on endurance athletes. Moderator variable – Age , gender, language. ]
Moderate variable — Control Variable
Age – 25-35 years
Gender – Male
(We can control variables by delimiting and limiting it).

6) Extraneous variable or Nuisance variable –
• Any variable that you are not intentionally studying in your research is an extraneous variable that could threaten the internal validity of your results.
• It is the one that may affect the dependent variable and is not related to the major purpose to the experiment.
• It disturbs the effect of independent variable on dependent variable.
• It is very dangerous.

E.g. – Effect of altitude training on endurance athletes.
Extraneous variable – Pre-altitude training, pre- knowledge
• If not controlled –
Extraneous Variable — Confounding Variable

7) Confounding variable –

• More dangerous form of Extraneous variable.
• Extra variable that have a hidden effect on your experimental results.
• A variable is considered to be confounding because it provides an alternative explanation for your results.
• It has mainly two major problem, increase variance and introduce bias.

Various other categories of VARIABLES

Continuous variable – that have infinite number of values.
E.g. – time , weight, height.
Discrete variable – whole numbers without having point in between.
E.g. – scores of basketball,
Quantitative variable – numerical value variable.
E.g. – discrete or ratio variable.
Qualitative variable – no numeric value. E.g.- nominal and ordinal.
Ordinal variable – similar to categorical variable but in order.
E.g. – Increment or decrement.
Categorical variable (Nominal variable) – variable that can be put into categories.
E.g. – male and female

Explanatory vs Extraneous Variable
The variables selected for analysis are called explanatory variables and all other variables that are not related to the purpose of the
study but may affect the dependent variable are extraneous.

Types of scores (data)

1) Nominal – data which can’t be given a numerical value. It is a least powerful level of measurement. It is categorical data. Eg- male and female.
2) Ordinal – same as nominal data but in order. It could be categorical and numerical data.
3) Interval- interval data is a numerical data (whole number) could be negative as well as positive.
4) Ratio – is defined as a variable measurement scale that not only produces the order of variables but also makes the difference between variables known along with information on the value of true zero. It is calculated by assuming that the variables have an option for zero, the difference between the two variables is the same and there is a specific order between the options.

ETHICAL ISSUES

What is Ethics?

It is the branch of philosophy that deals with morality.
The application of moral rules and professional codes of conduct to the collection, analysis, reporting, and publication of information about research subjects.Specifically –

1) Right to privacy
2) Confidentially
3) Informed consent

BY HIPPOCRATES – A set of principles that determine the right and acceptance conduct.

Research ethics are the set of ethics that govern how scientific and other research is performed at research institutions such as universities.
Meaning – It is a Greek word, ethos = custom or spirit of community.

Difference between Ethical and Unethical

Ethical- Participants care, Research methods are used properly, true result are presented, published properly no copyright violation

Unethical- Causing harm to individual, breaching confidentiality, biasness

DIFFERENCE BETWEEN MORAL VALUES AND ETHICS

Moral Values –
These are the actual system of beliefs emerged out of person’ core value.
It is individually tailored to a person’s life experience.
It’s subject to opinion.

Ethics –
They are our morals in action. Ethics refers to the rule by external sources, e.g., code of conduct of a workplace, university, and organization etc.

Why it is important…….
Protects vulnerable group and other illegal participants.
Ensure fullest respect, dignity, Privacy, fair treatment for subjects.
It gives the right to confidentiality and informed consent.
Provide a clear view of the research and its results.

AREAS OF SCIENTIFIC DISHONESTY

Confidentiality
Sharing information that can be used to identify a research participant is a violation of the Code.
Even disclosing minimal information (e.g., initials of participant’s name, disorder, address of participant, aspects of treatment) through any form of communication, including social media, should not be done.
Compliance (confirming to rule)
Each project involving human or animal participants must undergo an initial review to ensure compliance with applicable local, institutional, state, and federal regulations.
Calibration (To check by comparison with a standard)-
In order to ensure that research results are accurate, safe, and reliable, research must be conducted using commonly accepted principles regarding equipment maintenance and calibration.
Fabrication (To construct)
Fabrication as “making up data or results and recording or reporting them.” Example – recording or reporting data results for research participants, who do not exist.
Falsification –
Falsification as “manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record”.
Plagiarism
As “the appropriation of another person’s ideas, processes, results, or words without giving appropriate credit.”
Objectivity
You should aim to avoid bias in any aspect of your research.
Faulty data-Gathering procedures –
Machines should be calibrating correctly, data collection procedures should be done properly.
Poor data storage and retention – should be available for verification of others.
Misleading authorship.
Unacceptable publication practice.

ETHICAL ISSUES REGARDING COPYRIGHT

Various points are –

You need permission to use figures and tables from other published sources.

Quotes are ok if properly referenced.

E.g. – “A set of principles that determine the right and acceptance conduct” by HIPPOCRATES.

If you are intentionally violating the ethics regarding educational purposes, you are in trouble.

STAKEHOLDERS IN RESEARCH –

1) The research participants- those who directly and indirectly involved in the research.

2) The researcher – Anyone who collect information for specific purpose of research.

3) The funding body – Responsible for financing a research activity.

Principles of Ethics –

🞭 Honesty
🞭 Objectivity
🞭 Integrity
🞭 Carefulness
🞭 Openness
🞭 Respect for Intellectual property
🞭 Confidentiality
🞭 Responsible publication
🞭 Competence
🞭 Legality
🞭 Animal care
🞭 Human protection

Validity

The word “valid” is derived from the Latin validus, meaning strong.

The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure.Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.)

Degree to which a test or instrument measures what it is supposed to measure.

The validity tests are categorized into two broad components namely, Internal and external validity are concepts that reflect whether or not the results of a study are trustworthy and meaningful.

Two types of Validity –

1) Internal validity – Internal validity refers to the validity of the findings within the research study. It is primarily concerned with controlling the extraneous variables and outside influences that may impact the outcome.

This is especially important in experimental studies to ensure that the experimental treatment (X) is, in fact, responsible for a change in the dependent variable (Y).

2) External validity – External validity refers to the extent to which the results of study can be generalized or applied to other members of the larger population being studied.

Factors That Improve Internal Validity

Randomization

Blinding

Double blind set-up

Experimetal manipulation

Factors that Improve External Validity

Inclusion and exclusion criteria
Replication- refers to conducting the study again with different samples or in different settings to see if you get the same results.
Field experiments.
Reprocessing or calibration- using statistical methods to adjust for problems related to external validity.

Difference between internal and external validity

Internal Validity

Focus on accuracy and strong research methods

Controls extraneous variables

Conclusions are warranted

Eliminates alternative explanations

External Validity

Results translate to world at large
Findings are generalizable
Outcomes apply to practical situations
Results can be translated into another context

Threats to internal validity

History–the specific events which occur between the first and second measurement.
Maturation–the processes within subjects which act as a function of the passage of time. i.e. if the project lasts a few years, most participants may improve their performance regardless of treatment.
Testing–the effects of taking a test on the outcomes of taking a second test.
Instrumentation–the changes in the instrument, observers, or scorers which may produce changes in outcomes.
Statistical regression–It is also known as regression to the mean. This threat is caused by the selection of subjects on the basis of extreme scores or characteristics. Give me forty worst students and I guarantee that they will show immediate improvement right after my treatment.
Selection of subjects–the biases which may result in selection of comparison groups. Randomization (Random assignment) of group membership is a counter-attack against this threat. However, when the sample size is small, randomization may lead to Simpson Paradox, which has been discussed in an earlier lesson.
Experimental mortality–the loss of subjects. For example, in a Web-based instruction project entitled Eruditio, it started with 161 subjects and only 95 of them completed the entire module. Those who stayed in the project all the way to end may be more motivated to learn and thus achieved higher performance.
Selection-maturation interaction–the selection of comparison groups and maturation interacting which may lead to confounding outcomes, and erroneous interpretation that the treatment caused the effect.
John Henry effect–John Henry was a worker who outperformed a machine under an experimental setting because he was aware that his performance was compared with that of a machine.

How is this different from external validity?

External validity asks whether the findings of a study can be generalized to patients with characteristics that are different from those in the study, or patients who are treated in a different way, or patients who are followed up for longer durations.

In contrast, ecological validity specifically examines whether the findings of a study can be generalized to naturalistic situations,

Types of validity

1) Face validity – Also called logical validity. This validity testing procedure is very simple but casual. The scores are personally observed by face to face conversation with respondents by the researcher or observer.A direct measurement of face validity is obtained by asking people to rate the validity of a test as it appears to them. This rater could use a likert scale to assess face validity. For example:

the test is extremely suitable for a given purpose
the test is very suitable for that purpose;
the test is adequate
the test is inadequate
the test is irrelevant and therefore unsuitable

2) Content validity – In this an expert opinion is taken to rate each item’s relevance. For more accuracy two experts should be asked to rate the test separately. It is also subjective validity like face validity. It is usually done for educational settings.

3) Criterion validity – It is assessed when one is interested in determining the relationship of scores on a test to a specific criterion. It is a degree to which scores on a test are related to some recognized standards or criterions.
It is of two types –

Concurrent validity – It is a type of criterion validity that involves correlating an instrument with some criterion that is administered at about the same time (concurrently).
Predictive validity – When the criterion is with some later behavior, for example – entrance examination is used to predict later success. Predictive validity is a major concern.

4) Construct validity – If the test shows the association between the test scores and predictions of the theoretical trait. It doesn’t have a criterion for comparison rather it utilizes a hypothetical construct for comparison.

It is the most valuable and most difficult way to measure validity. A construct is something that happens in the brain, like a skill, level of emotion, ability or proficiency. For example, proficiency in any language is a construct.
It demonstrates that the test is actually measuring the construct it claims it’s measuring.

For example, you might try to find out if an educational program increases emotional maturity in elementary school age children. Construct validity would measure if your research is actually measuring emotional maturity.

Difference between Reliability and Validity

Reliability (Consistency)

It refers to the degree to which the results obtained by measurements and procedures can be replicated. It is an integral part of validity.
In reliability, the group should be heterogeneous, not homogeneous.
Reliability expressed by correlation coefficient (ranges from 0-1).

There are three aspects of reliability –

i) Equivalence
ii) Stability
iii) Internal consistency (homogeneity)

Ways to find out the reliability –

1) Inter-rater or inter-observer reliability – If two observers observe the same thing.

2) Test retest method – To measure test-retest reliability, you conduct the same test on the same group of people at two different points in time. Then you calculate the correlation between the two sets of results.

3) Parallel forms reliability – Using two different tests to measure the same thing.Parallel forms reliability is also called equivalent forms reliability uses one set of questions divided into two equivalent sets (“forms”), where both sets contain questions that measure the same construct, knowledge or skill.

The two sets of questions are given to the same sample of people within a short period of time and an estimate of reliability is calculated from the two sets.

4) Split half method – In split-half reliability, a test for a single knowledge area is split into two parts and then both parts given to one group of students at the same time. The scores from both parts of the test are correlated.

A reliable test will have high correlation, indicating that a student would perform equally well (or as poorly) on both halves of the test. It’s Steps are-

Administer the test to a large group

students (ideally, over about 30).

Randomly divide the test questions into two parts. For example, separate even questions from odd questions.

Score each half of the test for each student.

Find the correlation coefficient for the two halves. See: Find Pearson’s Correlation Coefficient for steps.

5) Spearman brown prophecy formula – The Spearman-Brown Formula (also called the Spearman- Brown Prophecy Formula) is a measure of test reliability. It’s usually used when the length of a test is changed and you want to see if reliability has increased.
The formula is:
rkk = k(r11) / [1 + (k – 1)* r11]

Where:
• rkk = reliability of a test “k” times as long as the original test,
• r11 = reliability of the original test(e.g. Cronbach’s Alpha),
• k = factor by which the length of the test is changed. To find k, divide the number of items on the original test by the number of items on the new test. If you had 10 items on the original and 20 on the new, k would be 20/10 = 2.

Example question: a test made up of 12 items has a reliability (R11) of .68. If the number of items is doubled to 24, will the reliability of the test improve?

Solution: Insert the given numbers into the formula and solve. We are given:
• r11 = .68.
• k = 24/12 = 2.
So:
rkk = 2(.68) / [1 + (2 – 1)* .68] = .81.
Doubling the test increases the reliability from .68 to .81.

6) Internal consistency reliability (cronbach’s alpha)- Using a multi-item test where all the items are intended to measure the same variable. With more than two variables.

Cronbach’s alpha is the most common measure of internal consistency (“reliability”). It is most commonly used when you have (not dichotomous) multiple Likert questions in a survey/questionnaire that form a scale and you wish to determine if the scale is reliable.

Formula – Alpha = [n/(n – 1)] x [(Vart – ΣVari)/Vart]
Alpha = estimated reliability of the full-length test n = number of items
Vart = variance of the whole test (standard deviation squared) ΣVari = sum the variance for all n items

7) Kuder – Richard Formula – Kudar-Richardson is a measure reliability for a test with binary variables. It is used when you have two options for the questions.

There are two formulas –

1). The KR20 is used for items that have varying difficulty. It should only be used if there is a correct answer for each question.
KR-20 Scores

The scores for KR-20 range from 0 to 1, where 0 is no reliability and 1 is perfect reliability. In general, a score of above .5 is usually considered reasonable. Dichotomously scored items with a range of difficulty.
Apply the following formula once for each item:
KR-20 is [n/n-1] * [1-(Σp*q)/Var]

where:
• n = sample size for the test,
• Var = variance for the test,
• p = proportion of people passing the item,
• q = proportion of people failing the item.
• Σ = sum up (add up). In other words, multiple Each question’s p by q, and then add them all up.If you have 10 items, you’ll multiply p*q ten times, then you’ll add those ten items up to get a total.

2) KR-21(Second Formula)

The KR-21 is similar, except it’s used for a test where the items are all about the same difficulty.

The formula is [n/(n-1) * [1-(M(n-M)/(nVar))]
where:
• n= sample size,
• Var= variance for the test,
• M = mean score for the test.

EXPERIMENTAL RESEARCH

Experimental researches are the primary approach used to investigate causal (cause/effect) relationships and to study the relationship between one variable and another.

This is a traditional type of research that is quantitative in nature. In short, researchers use experimental research to compare two or more groups on one or more measures. In these researches one variable is manipulated to see if it has an effect on the other variable.

This is a hypothesis testing research or a deductive research method and Experimental designs are used in this way to answer hypotheses. Most importantly, experimental research is completed in a controlled environment.
Answers the question – what if, what will be?

STRUCTURE OF EXPERIMENTAL RESEARCH –

Difference between experimental and non-experimental research

Experimental research is when a researcher is able to manipulate the predictor variable and subjects to identify a cause-and-effect relationship.

This typically requires the research to be conducted in a lab, with one group being placed in an experimental group, or the ones being manipulated, while the other is placed in a placebo group, or inert condition or non-manipulated group.

A laboratory-based experiment gives a high level of control and reliability.
Placebo effect – The placebo effect occurs when a person believes that he or she is receiving real treatment and reports an improvement in his or her condition but in reality no real treatment was given.

Non-experimental research is the label given to a study when a researcher cannot control, manipulate or alter the predictor variable or subjects, but instead, relies on interpretation, observation or interactions to come to a conclusion.

Typically, this means the non-experimental researcher must rely on correlations, surveys or case studies, and cannot demonstrate a true cause-and-effect relationship.

Non-experimental research tends to have a high level of external validity, meaning it can be generalized to a larger population.

Experimental Research types –
These are distinguished on the basis of conditions of Experimental Research –

1) TRUE EXPERIMENTAL RESEARCH – Where all conditions of Experimental research is fulfilled.
2) QUASI-EXPERIMENTAL- Where one condition (Randomization) is not fulfilled.
3) EX-POST FACTO RESEARCH – Where there is neither randomization nor manipulative conditions are fulfilled.

Conditions for experimental research

The research is allowed to manipulate the independent variable in order to see its effect on the dependent variable
Have full control on the experiments by eliminating or controlling the effect of extraneous variables.
Effect is observed in the dependent variable due to the manipulation of the independent variable.

Principles of experiment research

It should be planned
Precision is the hall-mark of experimental research.
Subjects for the study need to be selected keeping in view the objectives of the study.
Random selection should be taken for best results.
Control should be accurate. Not too tight and not too loose.

Three criteria must be present to establish the cause and effect –

The cause must precede the effect in time.
The cause and effect must be correlated with each other.
The correlation between cause and effect cannot be explained by any other variable.

Threats to experimental research

Internal validity – Internal validity refers to the validity of the findings within the research study. It is primarily concerned with controlling the extraneous variables and outside influences that may impact the outcome.

External Validity – External validity refers to the extent to which the results of study can be generalized or applied to other members of the larger population being studied.
What is the Purpose of Experimental Research?

Experimental research seeks to determine a relationship between two (2) variables—the dependent variable and the independent variable.

After completing an experimental
research study, a correlation between a specific aspect of an entity and the variable being studied is either supported or rejected.

Experimental research is based on a methodology that meets three criteria that are important if the results are to be meaningful-

These criteria are as follows:

Random Assignment – Test subjects must be randomly assigned to the treatment groups to control for creation of groups that may systematically differ in another way that impacts the outcome of the treatment.
Experimental Control – All aspects of the treatments are identical except for the independent variable. If all other factors are controlled and kept constant, then if measurable differences are found in the outcomes, the researcher can be assured that the difference is due the independent variable (treatment).
Appropriate Measures – The measures or outcomes must appropriate for testing the hypothesis. The outcome measured must represent the idea being tested in the hypothesis in order for the results to be valid.

STEPS OF EXPERIEMENTAL RESEARCH –

Identify and define the problem.
Formulate hypotheses and deduce their consequences.
Construct an experimental design that represents all the elements, conditions, and relations of the consequences.
Select sample of subjects.
Group or pair subjects.
Identify and control non experimental factors.
Select or construct, and validate instruments to measure outcomes.
Conduct pilot study.
Determine place, time, and duration of the experiment.

Experimental Research

Can demonstrate cause and effect.
Have a sample of participants randomly selected and/or randomly assigned to experimental groups and control groups.
Have an independent treatment variable that can be applied to the experimental group.
Have a dependent variable that can be measured in all groups.

QUASI-EXPERIMENTAL RESEARCH:

Can demonstrate cause and effect.
Have participants that cannot be randomly selected but may sometimes be able to be randomly assigned to experimental groups and control groups.
In every other way quasi-experimental research is very much like experimental research. It has:

An independent treatment variable that can be applied to the experimental group
Dependent variable that can be measured in all groups

CAUSAL-COMPARATIVE or EX POST FACTO DESIGN:

It cannot convincingly demonstrate cause and effect but can strongly suggest it
Has participants that can be randomly selected and assigned to experimental groups and control groups based on preexisting conditions (male vs. female, smoker vs. nonsmoker, one ethnic group vs. another)
An independent treatment variable cannot be manipulated as it is impossible, impractical, or unethical (usually a preexisting condition) focuses first on the cause and searches for the effect.

Ex-post facto means after the fact. It is research that explores a cause for a condition that already exists.

For example, a researcher is interested in how weight influences self-esteem levels in adults. So the participants would be separated into different groups (underweight, normal weight, overweight) and their self-esteem levels measured. This is an ex post facto design because a pre-existing characteristic (weight) was used to form the groups.

Difference between Field research and Laboratory experiment

FIELD RESEARCH

Field research is a research conducted in the real world or a natural setting.
It tends to observe, analyze, and describe what exists in natural settings rather than manipulating a factor under study.
Participants in a field research may or may not know that they are being studied.
Field research studies are more likely to be descriptive, developmental, correlational, and survey in design than they are to be experimental.
Field researches are more likely to be quasi-experimental and ex-post facto research designs.
The principal advantage of field research is its generalizability to real- life contexts .
the results generally are less precise.

LABORATORY EXPERIMENT

Controlled laboratory research is a research conducted in a setting specifically designed for research.
Laboratory research is often described as tightly controlled investigation in which the researcher manipulates the particular factor under study.
The subjects in laboratory research can be selected and placed in conditions more systematically and they usually know that they are participating in a research study.
Field research aims at detection of casual-relationship.
laboratory research studies are more likely to represent a true experimental design.
Lab. Research is not helpful in generalization.
Replicability is the hall-mark of laboratory experimentation and precision in results its basic quality.

Experiment research design

• Experimental Design – A blueprint of the procedure that enables the researcher to test his hypothesis by reaching valid conclusions about relationships between independent and dependent variables. It refers to the conceptual framework within which the experiment is conducted.

• Experimental research design is one of the founding quantitative research methods.

Experimental research design types

The different types of experimental research design are based on how the researcher classifies the subjects according to various conditions and groups.

Types of Experimental Research Design
There are three primary types of experimental research design:

Pre-experimental research design

True experimental research design

Quasi-experimental research design

Essential characteristics

A true experiment research design must essentially consist of the following four characteristics :

manipulation

Control

Randomization

Replication

Manipulation
Control
RANDOMIZATION :
Randomization means that every subject has an equal chance of being assigned to experimental or of study subjects on a random basis.

Through random assignment of subjects under experimental or control groups, chances of systemic bias is eliminated.
Randomization is used in true experimental research design to minimize the thre3a. t of internal validity of the study & to eliminate the e0ect of extraneous variables on dependent variables.

Through randomization, on average the characteristics of the subject in experimentd & control groups are similar, thus influence of extraneous variables on dependant variables is eliminated by dispersing the variability of the subject characteristics equally in both the groups.

Replication
The action of copying or reproducing something.
Replication in computing involves sharing information so as to ensure consistency.
Pre-experimental design

Delphi Survay

A Delphi survey method uses questionnaire but in a different manner then the typical survey the Delfi technique uses a series of questionnaires in which a way that the response don’t finally reach a conscious consensus about the topic it basically need experts opinion

A set of statements or questionnaire prepared for considerations each stage in the Delphi technique is called a round

o Static-group design

a) ONE-SHOT CASE DESIGN
In this research design, a single experimental group is exposed to a treatment & observations are made aFer the
implementation of that treatment. *”:
There is no random assignment oT subjects to the experimental group & no control group at ali.

b) ONE-GROUP PRETEST-POST TEST DESIGN

It is the simplest type of pre-experimental design, where only the experimental group is selected as the study subjects.
A pretest observation of the dependant variables is made before implementation of the treatment to the selected group, the treatment is administered, & finally a posttest observation of dependant variables is carried out to assess the efect of treatment on the group.
Some researchers also argue this design as subtype of quasi-experimental research design. However in absence of both randomization & conPol group.
This design ethically can rot be placed under the classification of quasi-experimental research design.

c) Static group design

• This design attempts to make up for the lack of a control group but falls short in relation to showing if a change is occurred. In the static group comparison study, two groups are chosen, one of which receives the treatment and the other does not.

A posttest score is then determined to measure the difference, after treatment, between the two groups. This study doesn’t include any pre-testing and therefore any difference between the two groups prior to the study are unknown.

(Treatment )X —– O1(Experimental group)
O2(Control group)

ADVANTAGES OF PRE-EXPERIMENTAL DESIGN:
Very simple & convenient to conduct these studies in natural settings, especially in nursing.
Most suitable design 1or the beginners in the 1ieId of experimental research.

DISADVANTAGES OF PRE-EXPERIMENTAL DESIGN:

Considered a very weak experimental design to establish causal relationship between independent & dependent variables, because it conVols no threat to internal vd idity.
It has very little control over the research.
It has a higher threat to internal validity of research, & may have a selection bias, which can be very serious threats for in using lhis particular design.

TYPES OF TRUE EXPERIMENTAL DESIGN

Post-tost only
Solomon four group design

C) Solomon four group design
(Proposed by Solomon in 1949)

The solomon four group design is the only true-experimental group design to specially evaluate one of the threats to external validity, reactive or interactive effects of testing.
This combines the randomized-groups and the pretest-posttest randomized-groups designs. This designs allows a replication of the treatment effect.

Drawbacks of solomon four group design

Unfortunately, it is also an inefficient design, as twice as many participants are required.
Very limited in use. Used in college level type of research.
No good way to analyze it statistically.
Best alternative one for this is 2*2 ANOVA set up.

D) FACTORIAL DESIGN

In factorial design, researchers manipulate two or more independent variables simultaneously. To observe their effects on the dependent variables.

This design is used when there are more than two independent vańablas. cóled factors to be tested.

For example, a researcher wants to observe the efect of two different protocols of mouth care on prevention of VAP when performed at different frequencies in a day.

This design also facilitates the tesóng of several hypotheses at a single time.

E) CROSSOVER DESIGN

In this design, subjects are exposed to more than one treatment, where subjects are randomly assigned to diñerent orders of Peatme nt.
It is also known as ‘repeal measures design’.
This design is more efficient in establishing the highest possible similarity among subjects exposed to different conditions, where groups compared obviously haxe equal distribution of characteristics.

Though crossover design is considered as an extremely powerful research design, sometimes it is not effective because when subjects are exposed to two diñerent conditions, their responses of the second condition may be influenced by their experience in the first condition.

ADVANTAGES OF TRUE EXPERIMENTAL DESIGN

Experimental research designs are considered the most powerful designs to establish the causal relationship between independent & dependant variables.
Where the purpose of research is explanation, causal relationships may be established among the variables by experimentation, especially in studies involving physical objects, where the variables are more easily controlled than in human studies.
In this studies, the controlled environment in which the study is conducted can yield a greater degree of purity in observation.
Conditions not 1ound in a natural setting can be created in an experimental setting, where the independent variable is manipulated by the investigator.
In the experimental approach, we can often create conditions in a short period of time that may take years to occur naturally. For example, in genetic studies we can breed strains in very small ti me, which would take a long time in nature to occur.
When the experiment is conducted in a laboratory, experimental unit, or other specialized research setting, it is removed from the pressure & problems of real-life situations & the researcher can pursue his or her studies in a more leisurely, careful, & concentrated way

In experimental studies conducted in natural settings iike hospitals or communities. it is not possible to impose control over extraneous variables.

Another disadvantage of the experimental research design is that it is very di0icuit to get cooperation from the study pañicipants, because it may involve medicai or surgical treatment or intervention, which may make the prospective subjects reluctant to participate in research study.

DIFFERENCE BETWEEN EXPERIMENTAL, DESCRIPTIVE and EXPLORATORY RESEARCH

An Introduction to Exploratory Research
Exploratory research is a study that seeks to answer a question or address a phenomenon. The nature of the entity being studied does not allow a variable to be manipulated by the researcher, it cannot be

completed in a controlled environment, or most likely, the researcher can’t determine all the influences on the entity, therefore a more exploratory look at the topic is more beneficial. It is also known as the inductive method.

Purpose of Exploratory Research
The purpose of exploratory research is to investigate a specific phenomenon. Exploratory research seeks to learn as much as possible between two variables— the dependent variable and the independent variable.

The exact nature of the dependent variable may not be known or understood before the experiment begins, and therefore, is observed and recorded more holistically.

After completely an exploratory research study, a description of the relationship between the two variables is explained. It is likely that from an exploratory study, an experimental study could be done, because the relationship between the variables has been established.

What type of Data are Collected in Exploratory Research?

The types of data collected for exploratory research are likely the same as an experimental study. However, exploratory research is unique because the data are either collected “in the field” or the data already exists, and must be organized in a way that has not been done before.

Large volumes of data are collected for exploratory research, because the data must then be analyzed from many different perspectives, looking for possible relationships between the variables.

DESCRIPTIVE RESEARCH

1) Descriptive Research is a fact finding investigation which is aimed at describing the characteristics of an individual, situation or a group (or) describing the state of affairs as it exists at present.

2) Descriptive research includes surveys and fact findings enquiries of different kinds.

3) Hypothesis is not compulsory.

4) It answers the question, What is?

5) It has both qualitative and quantitative approach but mostly called as qualitative approach.

6) Descriptive research is used to describe characteristics and/or behavior of sample population.

7) Descriptive research can be explained as a statement of affairs as they are at present with the researcher having no control over variables.

Moreover, “descriptive studies may be characterized as simply the attempt to determine, describe or identify what is, while analytical research attempts to establish why it is that way or how it came to be”

Important Points –

1) It gathers data on the basis of opinions, views, and observations at present.

2) Also called observational studies.

3) It has many uncontrolled variables.

4) It includes cross-sectional studies.

5) It creates a base for further research.

6) No manipulation.

7) No cause and effect.

8) Sample size should be large.

There are 3 distinctive methods to conduct descriptive research –

Observation,
Case study and
Surveys.

Difference between exploratory, experimental and descriptive research

SAMPLING DESIGNS

A sample is “a smaller (but hopefully representative) collection of units from a population used to determine truths about that population” and sampling is the statistical procedure that is concerned with the selection of the individual observation and make statistical inferences about the population.
It is finite and exact in number.
It is the key to survey and experimental research.

Why sample?

Resources (time, money) and workload
Gives results with known accuracy that can be calculated mathematically.

What is Population?
Population – The infinite number of individuals or items which serve as source of data in a study technically are called Population.
Population unit – It is whatever you are counting.

What is your population of interest?
To whom do you want to generalize your results?
All doctors
School children
Indians
Women aged 15-45 years
Other

Can you sample the entire population?
Yes but it depends on the nature of and type of research.
Sampling Frame – A sample Frame is a complete list of all the members of the population that a researcher wishes to study.

For example,

In the most straightforward case, such as the sentencing of a batch of material from production (acceptance sampling by lots), it is possible to identify and measure every single item in the population and to include any one of them in our sample.

However, in the more general case this is not possible. For example, There is no way to identify all rats in the set of all rats. Where voting is not compulsory, there is no way to identify which people will actually vote at a forthcoming election (in advance of the election).

As a remedy, we seek a sampling frame which has the property that we can identify every single element and include any in our sample.
The sampling frame must be representative of the population.

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

SAMPLING STEPS

Defining the population of concern.
Specifying sampling frame.
Specifying sampling method.
Determining the sampling size.
Objectives of the study.
Financial implications.
Implementation of sampling plan.
Sampling and data collecting.
Reviewing the sampling process.

IMPORTANCE OF SAMPLING –

Large sample sizes more accurately represent the whole.
It gives balance between obtaining the statistically valid representation.
Larger sample will lead to minimum biasness.
Following the central limit theorem.
Statistical confidence interval with less error rate.
If the population under investigation is homogenous, a small sample will do otherwise for a heterogeneous population a large sample will be required.
In statistics a sample of 30 is considered large.

THE SAMPLE MUST FULFILL FOUR CRITERIA –

Efficiency
Representativeness
Reliability
Flexibility

SIZE OF THE SAMPLE –
In descriptive research there should be 10-20% of the population size.
In normative studies, size of the sample may directly proportional to the size of the population.
In survey studies sample should be kept 20-30% more than original population.

TYPES OF SAMPLING –

I. PROBABILITY SAMPLING

A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined.
When every element in the population does have the same probability of selection, this is known as an ‘equal probability of selection’ (EPS) design. Such designs are also referred to as ‘self-weighting’ because all sampled units are given the same weight.

Probability (Random) Samples – the biggest advantages are –

Accuracy of statistical methods.
Can be generalized.
No bias.

Probability sampling includes:

Simple Random Sampling,
Systematic Sampling,
Stratified Random Sampling,
Cluster Sampling
Multistage Sampling.
Multiphase sampling

II. NON PROBABILITY SAMPLING

Any sampling method where some elements of population have no equal chance of selection (these are sometimes referred to as ‘out of coverage’/’undercovered’), or where the probability of selection can’t be accurately determined.

It involves the selection of elements based on assumptions regarding the population of interest, which forms the criteria for selection. Hence, because the selection of elements is nonrandom, nonprobability sampling not allow the estimation of sampling errors.

FEW POINTS –
It affords bias.
Impossible to repose confidence in the data obtained from non-probability samples.
Variance is difficult to control.
Margin of sampling errors can’t be determined.
They are useful only for pilot studies, case studies, qualitative researches and hypothesis development.

1.SIMPLE RANDOM SAMPLING
(Francis Galton , first person to talk about randomness)

Applicable when population is small, homogeneous & readily available.

In this process of sample selection which is “free and uncontrolled”, systematic, not haphazard.
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 systems is used to determine which units are to be selected.
Advantages of Simple Random Sampling…
Estimates are easy to calculate.
Simple random sampling is always an EPS design.
True representatives and applicable to a large group.
Population should be finite in number.

Disadvantages
If the sampling frame large, this method impracticable.
Minority subgroups of interest in the population may not be present in sample in sufficient numbers for study.

REPLACEMENT OF SELECTED UNITS

Sampling schemes may be without replacement (‘WOR’ – no element can be selected more than once in the same sample) or with replacement (‘WR’ – an element may appear multiple times in the one sample).

For example, if we catch fish, measure them, and immediately return them to the water before continuing with the sample, this is a WR 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 WOR design.

SYSTEMATIC (Random) SAMPLING

Systematic sampling relies on arranging the target population according to some ordering scheme and then selecting elements at regular intervals through that ordered list.
Systematic sampling involves a random start and then proceeds with the selection of every kth element from then onwards. In this case, k=(population size/sample size).
It is important that the starting point is not automatically the first in the list, but is instead randomly chosen from within the first to the kth element in the list.
A simple example would be to select every 10th name from the telephone directory (an ‘every 10th’ sample, also referred to as ‘sampling with a skip of 10’).

As described above, systematic sampling is an EPS method, because all elements have the same probability of selection (in the example given, one in ten).

It is not ‘simple random sampling’ because different subsets of the same size have different selection probabilities – e.g. the set {4,14,24,…,994} has a one-in-ten probability of selection, but the set {4,13,24,34,…} has zero probability of selection.

Advantages Systematic Sampling –
Sample easy to select
It is more straight forward.
Suitable sampling frame can be identified easily
Sample evenly spread over entire reference population

Disadvantages-
Sample may be biased if hidden periodicity in population coincides with that of selection.
Difficult to assess precision of estimate from one survey.

STRATIFIED SAMPLING
Where population embraces a number of distinct categories, the frame can be organized into separate “strata.” Each stratum is then sampled as an independent sub-population, out of which individual elements can be randomly selected.
Every unit in a stratum has same chance of being selected.
Using the same sampling fraction for all strata ensures proportionate representation in the sample.
Adequate representation of minority subgroups of interest can be ensured by stratification & varying sampling fraction between strata as required.

Two types of stratified sampling –
Disproportional vs. Proportional Sampling

The main difference between the two sampling techniques is the proportion given to each stratum with respect to other strata.

In proportional sampling, each stratum has the same sampling fraction while in disproportional sampling technique; the sampling fraction of each stratum varies.

For example, 500 males and 500 females can be selected to represent the population. This cannot be considered random since the males had better chances of being selected as part of the sample.
Disproportional applies to populations with a very high strata population ratio.

Generally, disproportional sample tend to be less accurate and reliable compared to a stratified sample since mathematical adjustments are done during the analysis of the data. This process increases the chance of encountering errors in data analysis.

Advantages –

It gives better results than random sampling when the data are more heterogeneous among them and more homogeneous internally.

We can have more precise information in subgroups.

Finally, since each stratum is treated as an independent population, different sampling approaches can be applied to different strata.

Drawbacks to using stratified sampling.

First, sampling frame of entire population has to be prepared separately for each stratum

Second, when examining multiple criteria, stratifying variables may be related to some, but not to others, further complicating the design, and potentially reducing the utility of the strata.

Finally, in some cases (such as designs with a large number of strata, or those with a specified minimum sample size per group), stratified sampling can potentially require a larger sample than would other methods

POSTSTRATIFICATION

Stratification is sometimes introduced after the sampling phase in a process called “poststratification”.
This approach is typically implemented due to a lack of prior knowledge of an appropriate stratifying variable or when the experimenter lacks the necessary information.
Poststratification can be used to implement weighting, which can improve the precision of a sample’s estimates.

CLUSTER SAMPLING

It is also called Block sampling when simple random sampling is impossible due to the geographical area complexity.
Precisely, when a population is too large for a simple random sampling and it has no sampling frame, cluster sampling is a better option.
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 heterogeneous 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.

Advantages –

Cuts down on the cost of preparing a sampling frame.
It is cost effective. One can get the bigger sample at a limited cost.
It is useful when the complete list of the population is not available or constructing the complete list of the population is difficult.
Disadvantages:
Clusters are required to be of same level but may not be of same characteristics.
It gives less precision than other sampling methods.

Two types of cluster sampling methods.

One-stage sampling. All of the elements within selected clusters are included in the sample.

Two-stage sampling.A subset of elements within selected clusters are randomly selected for inclusion in the sample.

Difference Between Strata and Clusters

Although strata and clusters are both non-overlapping subsets of the population, they differ in several ways.
With stratified sampling, the best survey results occur when elements within strata are internally homogeneous. However, with cluster sampling, the best results occur when elements within clusters are internally heterogeneous.

MULTISTAGE SAMPLING
In multistage sampling, we select a sample by using combinations of different sampling methods. Samples are drawn in different stages.
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) selected at last step are surveyed.
This technique is essentially the process of taking random samples of preceding random samples decreasing the biasness.
Not as effective as true random sampling, but probably solves more of the problems inherent to random sampling.
An effective strategy because it banks on multiple randomizations. As such, extremely useful.
Multistage sampling is used frequently when a complete list of all members of the population does not exists and is inappropriate.

Disadvantages
The technique is complex and combines limitations of clusters and stratified random sampling.
It is less efficient but more accurate.

NON PROBABILITY SAMPLING

Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.
Most researchers are bounded by time, money and workforce and because of these limitations, it is almost impossible to randomly sample the entire population and it is often necessary to employ another sampling technique, the non-probability sampling technique.

Types of Non-Probability Samples

Convenience sample
Purposive sample
Quota sampling
Consecutive sampling
Snowball sampling

1) Quota Sampling –

The population is first segmented into mutually exclusive sub-groups, just as in stratified sampling.
In quota sampling the selection of the sample is non-random.
In quota sampling, the basic segmentation of the population depends on different traits.
The researcher sets a quota, independent of population characteristics.
Usually the basis of quota is age, gender, education, race, religion, divisions, socio- economic status.
Are of two types – proportional and non-proportional.

Drawback

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.

2) Convenience Sampling

Sometimes known as grab or opportunity sampling or accidental or haphazard sampling.
It is the most common in all the sampling procedures.
A type of nonprobability sampling which involves the sample being drawn from that part of the population which is close to hand. That is, readily available and convenient.
The researcher using such a sample cannot scientifically make generalizations about the total population from this sample because it would not be representative enough.
This type of sampling is most useful for pilot testing.
This technique is considered to be the easiest, economical and least time consuming.

Judgmental 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.
A sample is drawn for some specific purpose.

Drawback –

A purposive sampling is not a representative of a large number of the population.
No doubt, judgment sampling is quicker and easier than probability sampling, it is prone to systematic errors.
Purposive sampling
It is also called deliberate sampling.
It is drawn with some specific purpose in mind.
It is easy, useful when there is a specific purpose to be fulfilled.
It cant be generalized.

Consecutive sampling

In this sampling, all the subjects available are included in the sample.
In the design of experiments, consecutive sampling, also known as total enumerative sampling, is a sampling technique in which every subject meeting the criteria of inclusion is selected until the required sample size is achieved.

Along with convenience sampling and snowball sampling, consecutive sampling is one of the most commonly used kinds of nonprobability sampling. Consecutive sampling is typically better than convenience sampling in controlling sampling bias.

Snowball sampling

Snowball sampling is where research participants recruit other participants for a test or study. It is used where potential participants are hard to find. It’s called snowball sampling because (in theory) once you have the ball rolling, it picks up more “snow” along the way and becomes larger and larger.
Snowball sampling consists of two steps:

Identify potential subjects in the population. Often, only one or two subjects can be found initially.
Ask those subjects to recruit other people (and then ask those people to recruit. Participants should be made aware that they do not have to provide any other names.

These steps are repeated until the needed sample size is found.

Data Collection Tool

The various methods of data gathering involves the use of appropriate recording forms. These are called tools or instruments of data collection, they consists of observation,schedule or interview guide, interview schedule, questionnaire, rating scale, check list etc.,

Data Collection Strategies

No one best way: decision depends on:
What you need to know: numbers or stories
Where the data reside: environment, files, people
Resources and time available
Complexity of the data to be collected
Frequency of data collection
Intended forms of data analysis

Selection of appropriate technique for Collecting Data –

You can select a particular technique by considering points given below- Nature, scope and object of enquiry.
Availability of funds. Time factor.
Precision required

Characteristics of Good Measures
There are some points which are considered very important for good measures of data collection- Is the measure relevant?

Is the measure credible? Is the measure valid?
Is the measure reliable?

Relevance

It asks, does the measure capture what matters?

Relevance means related with the research. Choosing the best data collection tool which is relevant with the study.

Credibility

Is the measure believable? Will it be viewed as a reasonable and appropriate way to capture the information sought?

Valid –

Is it what it is supposed to measure?

How well does the measure capture what it is supposed to? Are waiting lists a valid measure of demand?

Reliable –
Is it measuring the same result again and again?

A measure’s precision and stability- extent to which the same result would be obtained with repeated trials.
How reliable are:

Birth weights of newborn infants?

Speeds measured by a stopwatch?

Obtrusive vs. Unobtrusive Methods

Obtrusive
Data collection methods that directly obtain information from those being evaluated
e.g. interviews, surveys, focus groups

Unobtrusive
Data collection methods that do not collect information directly from evaluates
e.g., document analysis, Google Earth, observation at a distance, trash of the stars

Data Collection Tools

Participatory Methods
Records and Secondary Data
Observation
Surveys
a. Interviews
b. Questionnaire
c. Focus Groups
Diaries, Journals, Self-reported Checklists
Expert Judgment
Case studies
Delphi Technique

1) Surveys
Survey means “look carefully and thoroughly at” a phenomenon.

Descriptive research is a study of status and is widely used in education and the behavioral sciences.
The most common descriptive research method is SURVEY. The survey is generally broad in scope.
The researcher usually seeks to determine present practices or opinions of a specified population.
The questionnaire, personal interview, normative survey, Delphi method are the common methods of survey.
The results of the survey could be generalized to a large group.

Types –

Descriptive survey, Opinion poll, Longitudinal survey, Cross-Sectional survey, Correlational Studies, Retrospective survey, Evaluative Survey Comparative Survey

Steps of Surveys-

Statement of the problem. Objectives of the study, Defining the population
Deciding the sampling procedures, Research question (Procedure design), Data collection,
Pilot run, Compilation of data, Statistical analysis, Interpretation of findings and conclusions, Follow Up

Interview

It may be defined as a two way systematic and purposeful conversation between an investigator and an informant, initiated for obtaining information relevant to a specific study.
It gathers first-hand information.

Characteristics of Interview

The participants – the interviewer and the respondent – are strangers. Hence, the investigator has to get himself introduced to the respondent in an appropriate manner
The relationship between the participants and the interviewer is a transitory one. It has fixed beginning and termination points.
Interview is not a mere casual conversational exchange, but a conversation with a specific purpose, viz., obtaining information relevant to a study.
Interview is a mode of obtaining verbal answers to questions put verbally.
The interaction between the interviewer and the respondent need not necessarily be on a face- to-face basis, because interview can be conducted over the telephone also.
Although an interview is usually a conversation between two persons, it need not be limited to a single respondent. It can also be conducted with a group of persons.

Advantages of Interview

In this data tool the depth and detail of information can be secured.
The interviewer can do more to improve the percentage of responses and the quality of information received than other method
The interviewer can gather other supplemental information like economic level, living conditions etc.
The accuracy and dependability of the answers given by the respondent can be checked by observation and probing.
Interviews are flexible and adaptable to individual situations. Even more control can be exercised over the interview situation.

Disadvantage of Interview

The interview results are often adversely affected by interviewer’s mode of asking questions and interactions
Certain types of personal and financial information may be refused in face-to-face interview
Interview poses the problem of recording information obtained from the respondents
Lack of training for the person who conducts the interview.
Interviews are costly both in terms of money and time.

Requirement for Successful Interview

Data availability: The needed- information should be available with the respondent.
Role perception: The respondent should understand his role and know what is required of him.
Role of Interviewer: The interviewer should also know his role. He should establish a permissive atmosphere and encourage frank and free conversation.
Respondent’s motivation: The respondent should be willing to respond and give accurate answers. This depends partly on the interviewer’s approach and skill

Types of Interview

Structured or directive interview

Unstructured or non-directive interview

Focused interview

Clinical interview

Depth interview

Standardized open ended

Closed, fixed, ended.

Structured or Directive Interview

This is an interview made with a detailed standardized schedule. The same questions are put to all the respondents and in the same order. Each question is asked in the same way in each interview. This type of interview is used for large-scale formalized surveys.

Unstructured or Non-directive Interview

The interviewer encourages the respondent to talk freely about a given topic with a minimum of prompting or guidance. In this type of interview, a detailed pre-planned schedule is not used. Only a broad interview guide is used. The interviewer avoids channeling the interview directions. This interviewing is more useful in case studies rather than in surveys.

Focused interview

This is a semi-structured interview where the investigator attempts to focus the discussion on the actual effects of a given experience to which the respondents have been exposed. The interview is focused on the subjective experiences of the respondent, i.e., his attitudes, and emotional responses regarding the situation under study.
Clinical interview

This is similar to the focused interview but with a subtle difference. While the focused interview is concerned with the effects of a specific experience, clinical interview is concerned with broad underlying feelings or motivations or with the course of the individual’s life experiences.

Depth interview

This is an intensive and searching interview aiming at studying the respondent’s opinion, emotions or convictions on the basis of an interview guide. This is generally a lengthy procedure designed to encourage free expression of his/her feeling, emotion, his knowledge about a particular area of study.
Interview Process

Preparation – The first step in the interviewing process is preparation and preplanning. The interviewer should keep the copies of the interview schedule/guide (as the case may be) ready for use. He should also have the list of names and addresses of respondents
Introduction – The investigator is a stranger to the respondents. Therefore he should be properly introduced to each of the respondents.
Developing rapport – Before starting the research interview, the interviewer should establish a friendly relationship with the respondent. This is described as “rapport“. It means establishing a relationship of confidence and understanding between the interviewer and the respondent
Carrying the interview forward: After establishing rapport, the technical task of asking questions from the interview schedule starts.
Recording the interview: It is essential to record responses as they take place in the interview.
Closing the interview: After the interview is over, take leave off the respondent, thanking him with a friendly smile.

Interview Problems

Inadequate response – in the interview the respondent gives a relevant but incomplete answer. When the respondent remains silent or refuses to answer the question, irrelevant response, in which the respondent’s answer is not relevant to the question asked etc.,
Interviewer’s bias: The interviewer is an important cause of response bias. He may resort to cheating by ‘cooking up’ data without actually interviewing. The interviewers can influence the responses by inappropriate suggestions, word emphasis, tone of voice and question rephrasing.
Non-response Non-response refers to failure to obtain responses from some sample respondents. There are many sources of non-response; non-availability, refusal, incapacity, inaccessibility.

Non-availability: Some respondents may not be available at home at the time of call. This depends upon the nature of the respondent and the time of calls. For example, employed persons may be available during working hours. Farmers may not be available at home during the cultivation season.

Refusal: Some persons may refuse to furnish information because they are approached at the wrong hour and so on.

Incapacity or inability may refer to illness which prevents a response during the entire survey period. This may also arise on account of language barrier.

Questionnaire

Quite often a questionnaire is considered as the heart of a survey operation. Hence it should be carefully constructed.
List of research or survey questions asked to respondents, and designed to extract specific information from the respondents is called a Questionnaire.

It serves four basic purposes:

Collect the appropriate data

Make data comparable and amenable to analysis

Minimize bias in formulating and asking questions.

To make questions engaging and varied.

Steps in Questionnaire Construction

Preparation

Constructing the first draft

Self-evaluation

External evaluation

Revision

Pre-test or Pilot study

Revision

Second Pre-test if necessary

Preparing final Copy

Advantages of Questionnaire

Allows a wider range and distribution of the sample than the interview method
Provides greater access to more educated respondents and to persons in higher income brackets
Provides an opportunity for respondents to give frank. Anonymous answers
Allows greater economy of effort (i.e.. a single instrument. duplicated and distributed to numerous respondents. can produce a large amount of data)
Can be constructed so that quantitative data are relatively easy to collect and analyze
Can be designed to gather background information about respondents as well as original hard-to- obtain data
Facilitates the collection of large amount of data in a short period of time.
Allows the corrections in exploratory studies, of insightful information about a relatively unexplored problem area or subject.
Can be completed at the leisure of respondents-within time limits set by the surveyor-without imposing on research subjects
Because of its fixed format, helps to eliminate variation in the questioning process.

Disadvantages –

Precludes personal contact with respondents, perhaps causing the investigator to gain insufficient knowledge about participants in a study.
Does not allow respondents to qualify ambiguous questions
If the prepared instrument does not arouse respondent emotions (i.e., when the questionnaire is too impersonal) valid responses might not be elicited.
Poorly worded or direct questions might arouse antagonism or inhibitions on the part of respondents
Difficulty in obtaining responses from a representative cross section of the target population
Because opinionated respondents might be more likely than other subjects to complete and return it, use of a questionnaire might lead to non-response bias

Types of Question

Factual questions normally pertain to respondent’s ages, education, library experience, memberships in professional organizations, or any other pertinent personal data needed in the study.
Opinion and Attitude Question – When the purpose of a survey is to obtain information about respondent’s beliefs. Feelings, values, and related concepts, opinion and attitude questions can be used
Information question – In some types of survey research, investigators might attempt to determine how respondents know about a given topic and how or when their research subjects gained certain knowledge.
Self – perception question – These questions are about the self-perceptions of respondents in a given topic or area.
Standard of action question – In some types of surveys, investigators might attempt to determine how respondents will act in certain circumstances or how subjects feel about a new development or forthcoming event.
Projective questions- At times, questions are used that allow respondents to answer inquiries in an indirect manner by imposing their personal feelings, attitudes, or beliefs on another person or group of persons.

Types of questionnaire –

Questions can also be classified, on the basis of form and method of response, into two major categories:

Closed form (i.e., yes or no) and

Open (i.e., inviting free responses)

Ways of Administering a Questionnaire

Collective Administration – One of the best way of administering a questionnaire is to obtain a captive audience such as students in classroom, people attending a function
Administration in a public places – Sometimes you can administer a questionnaire in a public place such as a shopping Center, health center, hospital, school or pub, it is dependent upon the type of study population
The mailed questionnaire – The most common approach to collecting information is to send the questionnaire to prospective respondents by mail
Records and Secondary Data
Examples of sources:

files/records

computer databases

industry or government reports

other reports or prior evaluations

census data and household survey data

electronic mailing lists and discussion groups

documents (budgets, organizational charts, policies and procedures, maps, monitoring reports)
newspapers and television reports

OBSERVATION

The study is most commonly used specially in behavioral sciences. In observation the interviewer collects the data about the subjects only by observing his/her activities, while the person being observed may or may not know that he is being observed for his activities.

Observations can also be made in natural settings as well as in artificially created environments. It serves a formulated research purpose, is systematically planned and recorded and is subjected to checks and controls on validity and reliability. Observational research are mainly unstructured.

Observation examples,

See what is happening

traffic patterns
land use patterns
layout of city and rural areas
quality of housing
condition of roads
conditions of buildings
who goes to a health clinic

Observation is Helpful when

need direct information
trying to understand ongoing behavior
there is physical evidence, products, or outputs than can be observed
need to provide alternatives when other data collection is infeasible or inappropriate. It is free from biases if done properly.

TYPES –

Natural Observation (Newton’s apple example of gravity).
Contrived (Staged) Observation
Quantitative observation
Qualitative observation
Participation Observation
Subjective or Objective Observation
Direct or indirect Observation
Structured or unstructured Observation
Longitudinal or Cross-sectional Observation

FOCUS GROUPS

Type of qualitative research where small homogenous groups of people are brought together to informally discusses specific topics under the guidance of a moderator.
Purpose: to identify issues and themes, not just interesting information, and not “counts”.

Focus Groups Are Inappropriate when: language barriers are insurmountable evaluator has little control over the situation trust cannot be established
free expression cannot be ensured confidentiality cannot be assured

DIARIES AND SELF-REPORTED CHECKLISTS

. Use when you want to capture information . . about events in people’s daily lives . .Participants capture experiences in real-time . not later in a questionnaire
. Used to supplement other data collection Cross between a questionnaire and a diary
. The evaluator specifies a list of behaviors or events and asks the respondents to complete the checklist
. Done over a period of time to capture the event or behavior More quantitative approach than diary

EXPERT JUDGMENT

Use of experts, one-on-one or as a panel. E.g., Government task forces, Advisory Groups
Can be structured or unstructured
Issues in selecting experts

Selecting Experts

Area of expertise
Diverse perspective
Diverse political view
Dive technical expertise

Delphi Technique

Advantage and Challenges of Delphi Technique

Advantages
Advantages Allows participants to remain anonymous
Is inexpensive
Is free of social pressure, personality influence, and individual dominance Is conducive to independent thinking Allows sharing of information

Challenges
May not be representative
Has tendency to eliminate extreme positions
Requires skill in written communication
Requires time and participant commitmen

Case Studies

A case study is usually an in-depth description of a process, experience, or structure of a single institution, individual, a group or an event.

In order to answer a combination of ‘what’ and ‘why’ questions, case studies generally involve a mix of quantitative (i.e., surveys, usage statistics, etc.) and qualitative (i.e., interviews, focus groups, extant document analysis, etc.) data collection techniques.

Most often, the researcher will analyze quantitative data first and then use qualitative strategies to look deeper into the meaning of the trends identified in the numerical data.

Characteristics

Under this method, the researcher can take one single social unit or more of such units for his study purpose; he may even take a situation to study the same comprehensively. Generalization results less.
Generally the study extends over a long period of time (longitudinal) to ascertain the natural history of the unit so to obtain enough information for drawing correct inferences.

Sociometric Technique

Quantitative tools which are designed to measure social relationships, typically used in education studies to understand group clusters and characteristics and for evaluating the extent and types of students’ popularity within classrooms.

A systematic method for graphically representing individuals as points/nodes and the relationships between them as lines/arcs.

Most prevalent technique (Descriptive) – SURVEY

Most notably technique – Questionnaire

Historical Research

• Many things have happened before the researcher came on the scene. In case information about these events is to be brought forward, the only approach is to conduct HISTORICAL RESEARCH.

• In such instances the researcher must depend on the observations made by others who lived before him and also information recorded in different types of sources.

• History is a systematic explanation of what man has done to himself, to others and to his surroundings over accidentally or by design.

• The historian is unable to control the conditions of observation; he only interprets relationships without manipulating independent variables.

• Present historical investigations primarily aim for critical search for the truth.

Procedure of historical research

Selecting and delimiting the problem.
Reviewing the literature.
Identification of the data.
Formulation of the hypothesis that explain relationships among historical factors.
Selection and development of the tools.
Selection of the samples.
Collecting and classifying source materials.
Criticizing source materials.
Formulating tentative conclusions.
Interpreting and presenting the facts or findings.

Collecting and classifying source materials –
Historical data is mainly classified into two categories:

i) Primary sources

Primary sources provide first-hand information and they involve only single mind. The description is provided by an individual who has witnessed the event.

ii) Secondary sources

They are not first-hand accounts. They are not written by those who have directly witnessed the event. Secondary sources are descriptions of primary sources. They involve more than one mind.

Primary Sources

Official records
Personal records
Oral Statements
Pictorial records
Published materials
Physical remains
Printed materials
Mechanical records

Secondary Sources

Books
Encyclopedia
Newspaper articles
Interviews

Criticizing Source materials
Historians are always suspicious about the authenticity and reliability of the information gathered from different sources because the researcher has not personally witnessed the event. Historical evidence is derived from data by the process of criticism.

i) External criticism

Through external criticism the researcher determines the identity and character of the author and time place and circumstances of document origination. It refers to the evaluation of the authenticity of the evidence.

The following questions are asked in external criticism:
Who is the author?
Was the document written by the ghost author or by another person?
What were the qualifications of the author?
Is the particular equipment, piece of apparatus, costume etc. authentic?

ii) Internal Criticism

In this, historians are concerned with the meaning and the accuracy of statements included in the documents.

The following questions are asked in internal criticism:
Is the author writing seriously?
Is the meaning of the terms same?
How soon after the event the document was written?
Is the author expressing his real belief?

Philosophical Research

Philosophical research is a school of wisdom and a school of wonder.
It is something to do with our thought, experience and intellect. It is contrasted with science, which is empirical, analytical and objective.

WHY to use Philosophical Research?

It rests on rational, descriptive and analytical approaches.

It is based on logical thinking.

It is a way of getting dependable generalization through a systematic and disciplined examination of the question raised by observation.

Scientists do not repose much confidence in it because it lacks empirical proof.

In philosophical research examination is based on the available facts and on the frames of references i.e., sets of beliefs, values and assumptions.

It reflects to know better something in sure sense we already know.

Observation, experience, and logical reasoning are crucial to analyzing facts and synthesizing conclusions.

Philosophical method is based on critical thinking on a level of extensive generalizations beyond the realm of fact-finding science.

Synthesis is the underlying principle of the philosophic technique, and analysis that of scientific technique.

Steps in philosophical research – By JOHN DEWEY

The occurrence of a felt difficulty.
Defining the research problem.
Occurrence of the suggested explanations, solution, guess hypothesis, etc.
A rational idea is developed by the collection of ideas.
Formulation of a concluding belief through experimental verification of the hypothesis.
Philosophical data would be largely qualitative, its in-depth analysis would be necessary.
It is basically focused on ideals, ideas, values, value systems, morals, ethics, and relationships.

Branches of Philosophy:

1) Metaphysics – The study of the nature of reality or things.

– Why does man play?
– What should we teach?
– Who should teach?
– What are exercise science, physical education, and kinesiology?
– What is the competition?

2) Axiology – The study of the origin, nature, methods, and limits of knowledge

– How do we know?
– What do we know?
– How do we know that what we know is what we know?
– How do we learn through education, through sport, through play?

3) Epistemology – The study of values: Aesthetics & Ethics

– What do we value?
– What is beautiful? Ugly?
– Why do we cheat?
– What is the value of education?
– What is of the value of exercise & fitness?

4) Logics – The study of the nature of exact thought

– seldom studied in the sports world but methods are used in analysis
– induction: particulars to general
– deduction: general to particular
– Syllogism: if p = q & q =r then p = r.

Examples of Schools of Philosophy:

Idealism: the world of the mind
Realism: the world of nature & science
Pragmatism: the world of experience

Meta Analysis

A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analysis can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error.

The aim then is to use approaches from statistics to drive a pooled estimate closest to the unknown. It is an objective approach, unlike a narrative review.

Purpose of meta-analysis

Like any other research procedure, a meta-analysis involves the section of an important problem to address.
However, a meta-analysis involves two steps lacking in the typical literature review.

A definitive methodology is reported concerning the decisions in a literature analysis.
The results of various studies are quantified to a standard metric called effect size that allows the use of statistical techniques as a means of analysis.

Effect size –

🞭 Effect size is a statistical concept that measures the strength of the relationship between two variables on a numerical scale. In statistics, an effect size is a quantitative measure of the magnitude of a phenomenon

🞭 For example, the average height difference between males and females.

🞭 In a meta-analysis, the effect size is concerned with studying different studies and then combining all the studies into a single analysis. When combining all the study results then their difference and relationship can be understood by Effect Size.

🞭 The formula of Effect size –There are three formulas given by –

Step of meta-analysis-

🞭 Research problem
🞭 Systematic review
🞭 Data extraction
🞭 Calculate effect size
🞭 Standardization and weighting studies
🞭 Apply the appropriate statistical technique
🞭 Report all these steps and the outcomes in a review paper.

Difference between meta-analysis and review of literature

🞭 A literature review cites the conclusions of previous studies in order to provide a historic overview of a particular field of research.

🞭 A meta-analysis also contains a summary of previous research, but in addition, it compiles data from multiple studies, performs statistical analysis on this aggregate data, and then draws new conclusions from the results of this analysis.

Difference between meta-analysis and systematic review

🞭Basically, a systematic review is a method used to describe trends in the research field by calculating how many studies have used certain research methodologies, where they were carried out, etc…

Whereas a meta-analysis combines RESULTS from those studies in a new statistical framework to test hypotheses.

Both methods can be used together, which is advantageous as many systematic reviews, while great for getting a feel for the research field, are difficult to publish in high-impact journals as they often do not test any real hypotheses.

Research Proposal and preparation of research report

Keys of Research

What is research? How is research?
Why is research? When is research? Where is research?

Research proposal

A research proposal is a concise and coherent summary of your proposed research.
A synopsis consisting of logical and systematic planning of research.
A blueprint or an outline indicating the boundary of the study.
A research proposal is a document proposing a research project, generally in the sciences or academia.

The main purpose of a research proposal is to show that the problem proposed to investigate is significant enough to warrant the investigation, the planned method to use is suitable and feasible, and the results are likely to prove fruitful and will make an original contribution.

The research proposal contains the definition, scope, methodology, and significance of the study or problem.

Research report

Documentation prepared by an investigator, analyst, scholar, researcher, or research team.
An account that describes in detail an investigated event, situation, or occurrence.
A prepared result of observation or inquiry.
A thesis or dissertation is organized into different chapters or units.
A rational description of empirical data gathered through actual testing and measurements.

Steps in research report writing

Logical analysis of the subject-matter
Logical development
Chronological development
Preparation of the final outline
Preparation of the rough draft
Rewriting and polishing
Preparation of the final bibliography and Writing the final draft.

Principles of research report writing

Selectiveness, Comprehensiveness Accuracy, Objectivity, Clarity, Preciseness, Simplicity, Proper, Language, Reliability Proper, Format, Attractive

Structure of research report writing

The Preliminary materials (front materials)
The Main Body (Text of the thesis or dissertation)
The Supplementary or References (back materials)

The Preliminary materials

Title Page
Approval or Certificate Page
Declaration
Dedication
Vita
Acknowledgment
Table of Contents
List of Tables
List of Illustrations

The main Body

I. INTRODUCTION

Statement of problem
Objectives of study
Hypothesis
Delimitations of study
Limitation of study
Definition and Explanation of Operational Terms
Significance of the study

II. REVIEW OF RELATED LITERATURE

The major part of developing the research problem.
The readings that have already been published about the problem.
Past research is invaluable in planning new research.
Provides background information and critique of previous research done.
Pointing out the weakness, conflicts, and areas needed for the investigation.
A basis of inductive reasoning leads to the statement of the problem.
Instrumental in the formulation of hypotheses.
Helpful in identifying the methods, design, and statistical tools.

METHODOLOGY

Sources of Data
Selection of the Subjects
Selection of Test
Criterion Measures
Experimental Design
Test Administration
Collection of Data
Analysis and Interpretation of Data

IV. ANALYSIS OF DATA, RESULT, AND DISCUSSION
Statistical Techniques and Level of Significance
Findings
Discussions of findings
Discussions of hypothesis

V. SUMMARY, CONCLUSION, AND RECOMMENDATION

Summary
Conclusion
Recommendation

The Supplementary or References
Bibliography
Appendix
Index

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UGC NET Physical education Unit 8 MCQ Questions

Who authored the book “methods in Social Research”
(A) Wilkinson
(B) CR Kothari
(C) Kerlinger
(D) Goode and Halt

Answer: D

“Research is an organized and systematic enquiry” Defined by
(A) Marshall
(B) P.V. Young
(C) Emory
(D) Kerlinger

Answer: C

Research is a “Scientific undertaking” opined by
(A) Young
(B) Kerlinger
(C) Kothari
(D) Emory

Answer: A

“A systematic step-by-step Procedure following a logical process of reasoning” called
(A) Experiment
(B) Observation
(C) Deduction
(D) Scientific method
Answer: D
Ethical Neutrality is a feature of
(A) Deduction
(B) Scientific method
(C) Observation
(D) Experience
Answer: B
Scientific method is committed to ……………….
(A) Objectivity
(B) Ethics
(C) Proposition
(D) Neutrally

Answer: A

“One of the methods of logical reasoning process” is called
(A) Induction
(B) Deduction
(C) Research
(D) Experiment

Answer: A

An essential Criterion of Scientific study is
(A) Belief
(B) Value
(C) Objectivity
(D) Subjectivity
Answer: C
“Reasoning from general to particular “is called
(A) Induction
(B) deduction
(C) Observation
(D) Experience
Answer: B
“Deduction and induction are a part of system of reasoning” – stated by
(A) Caroline
(B) P.V.Young
(C) Dewey John
(D) Emory
Answer: B
“ A system of systematically interrelated concepts definitions and propositions that are advanced to explain and predict phenomena” … is
(A) Facts
(B) Values
(C) Theory
(D) Generalization
Answer: C
“ A system of systematically interrelated concepts, definitions, and propositions that are advanced to explain and Predict phenomena” defined by
(A) Jack Gibbs
(B) PV Young
(C) Black
(D) Rose Arnold
Answer: B
The theory is “ a set of systematically related propositions specifying the casual relationship among variables” is defined by Black James and
(A) Champion
(B) P.V. Young
(C) Emory
(D) Gibbes
Answer: A
“Empirically verifiable observation” is
(A) Theory
(B) Value
(C) Fact
(D) Statement
Answer: C
Fact is “empirically verifiable observation” — is defined by
(A) Good and Hatt
(B) Emory
(C) P.V. Young
(D) Clever
Answer: A
————- is a “systematically conceptual structure of interrelated elements in some schematic form”
(A) Concept
(B) Variable
(C) Model
(D) Facts
Answer: C
Social Science deals with ………..
(A) Objects
(B) Human beings
(C) Living things
(D) Nonliving things
Answer: B
Science is broadly divided into ……………….
(A) Natural and Social
(B) Natural and Physical
(C) Physical and Mental
(D) Social and Physical
Answer: A
Social Science tries to explain …………. between human activities and natural laws governing them
(A) Causal Connection
(B) reason
(C) Interaction
(D) Objectives
Answer: A
Social Science Research …………….
(A) Problems
(B) Explain
(C) diagnosis
(D) Recommend
Answer – B

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