Unit 2- Research Aptitude (UGC NET Paper I).pdf

UGC NET Paper I - Research Aptitude 1
Research
Aptitude
Paper 1: Unit - II
UNIVERSITY GRANTS COMMISSION
GENERAL PAPER ON TEACHING & RESEARCH APTITUDE
K.THIYAGU, Assistant Professor, Department of Education, Central University of Kerala, Kasaragod

Research Aptitude
Paper 1: Unit - II
K.THIYAGU, Assistant Professor, Department of Education,
Central University of Kerala, Kasaragod

Unit – ii: Research Aptitude
Research: Meaning, Types, and Characteristics,
Positivism and Post-positivistic approach to research.
Methods of Research: Experimental, Descriptive,
Historical, Qualitative and Quantitative methods.
Steps of Research.
Thesis and Article writing: Format and styles of
referencing.
Application of ICT in research.
Research Ethics.

UGC NET
Question Types
• Simple MCQ
• Double Statement (Statement I & II)
• Multiple Statements Questions
• Match the Following
• Order Questions
• Assertion & Reason
Model Question Format:
https://testmoz.com/13692742

Meaning of Research
The term research includes two words, specifically 're' and
'search’.
By and large, 're' signifies again and 'search' signifies to
discover.
As indicated by Creswell, 'research is a procedure of steps
used to gather and analyse information to increase our
understanding of a particular topic or issue’.

Research
Research is a detailed and careful study of something to find out more
information about it.
Research is a systematic inquiry to describe, explain, predict, and control
the observed phenomenon.
Research is a systematic and methodical process of inquiry aimed at
discovering, interpreting, and revising facts, events, behaviors, or theories.
It involves the collection, analysis, and interpretation of data to answer
specific questions or solve problems, ultimately contributing to the body of
knowledge in a particular field.

Research - Acronym
• Rational way of thinking
R =
• Expert and exhaustive treatment
E =
• Search and solution
S =
• Exactness
E =
• Analysis
A =
• Relationship of facts
R =
• Critical observation, careful planning, constructive attitude.
C =
• Honesty and hardworking
H = UGC NET Paper I - Research Aptitude 7

Research Objectives
Investigate some existing situation or problem.
Build or make another method or framework.
Generate new knowledge.
Explore and analyse more general issues.
Offer a solution to a problem.
Review and synthesize the existing knowledge.

Research Characteristics
Objectivity Reliability Validity Accuracy Credibility Generalizability
Empirical
Research
Systematics Controlled
Factors
Cyclical Logical Replicable

• It means research with no inclination. (Avoid
Bias).
a. Objectivity
• Reliability with regards to research is
consistency. (verifiability).
b. Reliability
• Validity in research mainly stands for accuracy
of procedures, research instruments, tests, etc
c. Validity
• It is firmly identified with legitimacy.
(Precision)
d. Accuracy

• It is the utilization of best wellspring of data and
the best techniques in the exploration. (Trade-off
between primary data and secondary data).
e. Credibility
• The sample considered is the representative of the
whole population so the findings should also be
applicable to the whole population.
f. Generalizability
• It is based on real-life experiences, direct
experiences or observation by the researcher.
g. Empirical research
• Each research should follow a definite procedure.
h. Systematic

•In research, various factors may affect the outcome
and some are taken as controlled factors, whereas
the others are tested for the possible outcome.
i. Controlled factors
•Research is a repetitive procedure since it begins
with an issue and finishes with an issue.
j. Cyclical
•The statement, great research is coherent, infers that
examination is guided by the standards of sensible
thinking.
k. Logical
•This characteristic allows the results of the research
to be confirmed by repeating the study and after that
building a sound basis for making decisions.
l. Replicable

Characteristics of Scientific Method
13
UGC NET Paper I - Research Aptitude

Aims of research as a scientific activity

Types of Validity
i. Internal validity: With higher internal validity, a researcher is able to
establish a better casual relationship between two or more variables.
ii. External validity: It means external factors that can affect the study
must be controlled.
iii. Face validity: By valid, we mean that the survey and questionnaire
accurately measure what they are supposed to measure.
iv. Content validity: The indicator measures all aspects of the construct
and not just a part of it.
v. Criterion validity: The indicator corresponds with and is predictive of
measurements using related indicators.
vi. Construct validity: The indicator measures the construct in a manner
that is convergent with other measures in terms of direction.

Types of Research

Types of research
(Fundamental,
Applied and Action)
Criteria
(On the basis)
Types
Objectives Fundamental Research Applied Research Action Research
Nature of Data Qualitative Research Quantitative Research
Nature of Findings Explanatory Research Exploratory Research Descriptive Research
Experimental Manipulations Experimental Non-Experimental
Approach involved Longitudinal Research Cross sectional research
17

Types of Scientific Method (Exploratory, Explanatory and Descriptive)
18

Descriptive vs Analytical
Descriptive Research Analytical Research
It answers questions such as ‘what is’ or
‘what was’ i.e describes the problem.
In this researcher use facts to explain
‘why it has occurred’ or ‘how it
occurred’
It includes survey and fact-finding
enquiries with adequate interpretation.
It attempts to make critical evaluation of
the material.
Example: Analysing the trend of rising
coronavirus cases.
Example: analysing the reason behind
the rise in coronavirus cases.
Classification of Research based on Objectives

Fundamental Research Applied Research
It makes addition to existing knowledge
It is used to find out solutions to existing
problems.
It is used to discover new things or any
invention.
It is used in application.
It is extensive in nature. It is intensive in nature.
Fundamental vs Applied
Classification of Research on Basis of Application

Deductive Research Inductive Research
It is also termed as top-down or general-
to-specific.
It is termed as bottom-up approach.
In this, theory is tested with the help of
available information.
in this, theories are formulated, news
ideas are explored.
It begins with hypothesis It begins with research questions.
Deductive vs Inductive
Classification of Research on Basis of Logic

Structured Research Unstructured Research
Everything that is part of research is
predetermined such as objective, design,
sample, and questions.
In this, flexibility is allowed because it is
not predetermined for formulating
research.
It is more appropriate to determine the
extent of problem.
It is more appropriate to explore the
nature of problem.
It is used in quantitative research. It is used in qualitative research.
Structured vs Unstructured

Qualitative Research Quantitative Research
It is inductive in nature and deals with
phenomena’s quality.
It is deductive in nature and deals with
phenomena’s quantity.
In this, sample size is small. In this, sample size is larger.
It tells about why. It tells about how much or how many.
Qualitative vs Quantitative
Classification of Research on the Basis of Process

Conceptual Research Empirical Research
It is used by philosophers and thinkers to
develop new concepts or for
reinterpretation.
It relies on experience or observation
alone.
It is related to some abstract idea or
theory.
In this, the researcher must formulate a
working hypothesis.
It is based on theoretical approach. It is based on Experimental approach.
Conceptual vs Empirical

Innovative Research Incremental Research
It deals with the innovation of new ideas,
new technology, or a new technique to
solve a problem.
In this, improvement or extension of
something occurs on exiting thing.
Example: Research for Coronavirus vaccine
Example: Research conducted by a
company to improve the product.
Innovative vs Incremental

Ex Post Facto Research
Ex post facto study or after-the-fact research
is a category of research design in which the
investigation starts after the fact has
occurred without interference from the
researcher.
Historical Research
It is similar to Ex Post Facto Research
and usually focusses on the historical
aspect of an issue.

Positivism and
Post Positivism Approach to
Research

Positivist Paradigm
The term positivism was coined by the French philosopher Auguste Comte in the
19th century & reflected through by Francis Bacon, John Locke, Isaac Newton.
The term positivist has no negative connotation.
In philosophy, positivism mainly adheres to the idea that ‘factual’ knowledge gained
through observation is trustworthy.
Positivism relies upon quantifiable perceptions that prompted measurable
examinations.
Here, the role of the researcher is limited to collect data collection and interpretation in
an objective way.
Positivists usually adopt the deductive approach, the concentration is on facts.
The researcher is independent that means maintaining minimal interaction with
participants and research is purely objective & the world is external.
There is one reality, knowable within probability.

Post – Positivism
What we should carry out research in social sciences in ways that are similar to the methods
within the natural sciences.
Two people observe the same event but understand it differently, based upon their own
experiences and beliefs.
Objectivity can be achieved by using multiple measurements, observations and triangulating
the data to gain a more clear comprehension of what’s going on as a general rule.
Since the inception of the 21st century, the focus of research shifted from ‘reality’ to ‘critical
reality’.
Physicists like Werner Heisenberg and Niels Bohr focused on this reality.
This approach was called up as post-positivism, which it describes as a less strict form of
positivism.
Post positivists support the idea that social scientists and natural scientists share the same goals
for research and employ similar methods of investigation.
It tends to be distinguished from positivism as indicated by whether the attention is on
hypothesis verification(positivism) or on theory misrepresentation(post-positivism).

Research Process / Steps

1. Selecting the research area.
2. Formulating research aim, objectives and research questions or
developing hypotheses.
3. Conducting the literature review
4. Selecting methods of data collection
5. Collecting the primary data
6. Data analysis
Research
Process
7. Reaching conclusions

Research
Steps

Steps of Scientific Method

Formats and styles of
Referencing of a Research Report

Referencing
Style

Scales of
Measurement

Quantifiable
Nominal
Ordinal
Interval
Ratio
-
Equal Intervals Absolute Zero
X
X X
X
X
Scale
of
Measurement Characteristics
X
- -
- -
-

Variables,
Samples and Tools

Variables
The quantity or condition
that can change
(anything that has a quantity or quality
that varies)
55

Types of Variables
Dependent Variables
A variable that relies on and can be
changed by other factors that are
measured
Confounding Variables
Extra variables that the researcher
did not account for that can
disguise another variable's effects
and show false correlation
Qualitative Variables
Non-numerical values or groupings
Moderating Variables
A variable that changes the
relationship between dependent
and independent variables by
strengthening or weakening the
intervening variable's effect.
02
04
06
08
Independent Variables
A variable that stands alone
Extraneous Variables
Factors that affect the dependent
variable but that the researcher did
not originally consider when
designing the experiment
Quantitative Variables
Data sets that involve numbers or
amounts.
Intervening Variables
A theoretical variable used to
explain a cause or connection
between other study variables
01
03
05
07
07
Control Variables
Characteristics that are constant and
do not change during a study
09
Composite Variables
Two or more variables combined
to make a more complex variable
08

Nominal Variables
A nominal variable is one that
describes a name, label or
category without natural
order.
Eg: Gender, Locality.
Ordinal Variables
An ordinal variable is a variable whose
values are defined by an order relation
between the different categories.
Eg: Excellent,Very Good, Good, Bad
Continuous Variables
It can assume an infinite number
of real values within a given
interval.
Eg: Height,Weight
Discrete Variables
It can assume only a finite number of
real values within a given interval.
Eg: the range is 0 to 10, and the score is
always given to one decimal
Eg, Siblings a person, number of
students in the classroom, number of
times exercised in a week
CategorialVariables Quantitative /
NumericVariable

Some other Variables
Dummy Variable
This is a variable that takes on
only two values, typically 0 and
1, and is used to represent
categorical variables in
statistical analyses.
Eg:
0 = Female, 1 = Male
1 = Rural, 2 = Urban
Latent Variable
This is a variable that cannot
be directly observed or
measured but is inferred from
other variables.
Latent variables are often used
in psychological or social
research to represent
constructs such as personality
traits, attitudes, or beliefs.
Moderator – Mediator
Variable
This is a variable that acts both as
a moderator and a mediator.
It can moderate the relationship
between the independent and
dependent variables and also
mediate the relationship between
the independent and dependent
variables.
Moderator-mediator variables
are often used in complex
statistical analyses.
Extraneous Variable
This is a variable that has no
relationship with the
independent or dependent
variable but can affect the
outcome of the study.
It can be controlled through
random assignment or statistical
techniques.

Independent
(A variable that we can control)
Cause
X Y
Independent Variable (IV)
also called
exposure,
explanatory,
manipulated variables 60
This is the variable that is manipulated by the researcher. It is
also known as the predictor variable, as it is used to predict
changes in the dependent variable.

Dependent
(A variable that we can observe or measure)
Effects
X Y
Dependent Variable (IV)
also called
outcome,
explained,
response variable 61
This is the variable that is measured or observed to determine the effects
of the independent variable. It is also known as the outcome variable, as it
is the variable that is affected by the independent variable.

Z: Confounding, Mediating and Moderating Variables
X Y
Z ?
62

Confounding Variables
X Y
Z
Confounder Both X and Y are affected by Z
Subject
Interest
Hours
of Study
Exam
Score
63
This is a variable that can affect the relationship between the independent
variable and the dependent variable. It is a variable that is not being studied
but could impact the results of the study.
Eg: In a study on the effects of a new drug
on a disease, a confounding variable could
be the patient’s age, as older patients may
have more severe symptoms.

Mediating Variable
X Y
Z
Mediator A part of the association between X and Y goes through Z
Practice
Problems
Hours
of Study
Exam
Score
64
This is a variable that explains the relationship between the independent variable and the dependent variable.
It is a variable that comes in between the independent and dependent variables and is affected by the
independent variable, which then affects the dependent variable.
Eg. In a study on the relationship between exercise and
weight loss, the mediating variable could be metabolism, as
exercise can increase metabolism, leading to weight loss.

Moderating Variable
X Y
Z
Moderator Z affects the association between X and Y
Tiredness
Hours
of Study
Exam
Score
65
This is a variable that affects the strength or direction of the relationship between the independent variable
and the dependent variable. It is a variable that influences the effect of the independent variable on the
dependent variable.
Eg: In a study on the effects of caffeine on cognitive performance, the moderator variable could be age, as older adults may be
more sensitive to the effects of caffeine than younger adults.

Path model
diagrams for
mediator,
confounding, and
moderator
variables.
66

Dichotomous
Variable
Gender: Male and female
Locality: Rural and Urban
Pregnant and non pregnant
Alive and dead
Literate and illiterate
Trichotomous
Variable
Residence:
Urban, semi urban and
rural
Religion:
Hindu, Muslim, and
Christianity
Multiple
Variables
Blood groups: A,B,AB and O
68

Concept of Universe and Sample
70

Techniques of Sampling
(Probability and Non-probability Sampling)
71

Tools & Techniques of
Research
74

Tool Constructions - Steps
Final Draft
Reliability & Validity
Reliability: Test retest, Split Half, Cronbach Validity: Face, Content, etc.
Pilot Study
Item Analysis Accept / Reject Statements
Preliminary Draft
Overlapping items – modified (Guide & investigator) Number of statement, scales, (Preliminary Draft)
Item Writing
Positive & Negative Statements Cover the content / dimensions
Planning
Study of books, articles & Experts Discussion List out the Statement
75

Tools of Research in Education
Inquiry
Forms
Questionnaire
Checklist
Score-card
Schedule
Rating scale
Opinionnaire
Attitude scale
Observation Interview Sociometry
Psychological
Test
Achievement
Aptitude
Intelligence
Interest
inventory
Personality
Measures
76

Test-Retest
Reliability
Same Test
Same Sample
Different Times
78
Test-Retest Reliability:
Used to assess the consistency of a measure from one time to another.
(or) The consistency of a measure evaluated over time.

Parallel Forms Reliability
One major problem
with this approach is
that you have to be
able to generate lots of
items that reflect the
same construct.
Furthermore, this
approach makes the
assumption that the
randomly divided
halves are parallel or
equivalent. Even by
chance this will
sometimes not be the
case.
79
Parallel-Forms Reliability:
• Used to assess the consistency of the results of two tests constructed in the same way from the same
content domain.
• The reliability of two tests constructed the same way, from the same content.
Two Tests
Same Sample
At a same Times

Split-Half Reliability
• The parallel forms approach is
very similar to the split-half
reliability described below.
• The major difference is that
parallel forms are constructed
so that the two forms can be
used independent of each
other and considered
equivalent measures.
• With split-half reliability we
have an instrument that we
wish to use as a single
measurement instrument and
only develop randomly split
halves for purposes of
estimating reliability.
80
Internal Consistency Reliability:
• Used to assess the consistency of results across items within a test. (or)
• The consistency of results across items, often measured with Cronbach’s Alpha.
Single Test
Split halves

Average Inter-item Correlation
We first compute the
correlation between each
pair of items, as
illustrated in the figure.
In the example, we find an
average inter-item
correlation of .90 with the
individual correlations
ranging from .84 to .95.
81

This approach also uses the inter-
item correlations. In addition, we
compute a total score for the six
items and use that as a seventh
variable in the analysis.
The figure shows the six item-to-
total correlations at the bottom of
the correlation matrix. They range
from .82 to .88 in this sample
analysis, with the average of these
at .85.
Average Item total Correlation
82

Cronbach's Alpha (a)
83

Inter-Rater/Observer Reliability
84
Inter-Rater or Inter-Observer Reliability:
• Used to assess the degree to which different raters/observers give consistent estimates of the same
phenomenon. (or)
• The degree to which different raters/observers give consistent answers or estimates

Logical Statistical
Face Content Predictive
Construct
Concurrent
Validity
Consistency
Reliability Objectivity
86

Face Validity
(Logical Validity)
It refers to the transparency or relevance of a test as it
appears to test participants.
In other words, a test can be said to have face validity if it
"looks like" it is going to measure what it is supposed to
measure.
Eg: if a test is prepared to measure whether students can
perform multiplication, and the people to whom it is shown
all agree that it looks like a good test of multiplication
ability, this demonstrates face validity of the test.
E.g. A test of Mathematics should have numerical questions,
and
87

Content validity (also known as logical validity) refers to the extent to which a measure
represents all facets of a given construct.
For example, a depression scale may lack content validity if it only assesses
the affective dimension of depression but fails to take into account
the behavioral dimension.
Content validity is important primarily for measures of achievement
The test maker first determines the widely accepted goals of instruction in the subject
and then prepares a blueprint for the test. Test content is drawn from the course
content and weighted according to the weightage of the objectives of the course and the
course content.
Content Validity
(Logical Validity)
88

Infers that the test produces similar results
to a previously validated test
e.g.
VO2
max
Incremental
Treadmill Protocol
with expired gas
analysis
Multi-Stage Fitness
(Beep) Test
Concurrent Validity
(Statistical Validity)
89
Concurrent validity is evaluated by showing how
well the test scores correspond to already
accepted measure of performance or status made
at the same time.
Example
• Scores of a test of knowledge of basic
concepts in Geography can be validated
against the teachers' ratings of the students
on this aspect.
• Intelligence test were first validated against
school grades, teacher’s rating etc.
• A newly constructed test of intelligence may
be validated by finding its correlation with
another already existing well accepted test in
this area.
• In this cases, a correlation coefficient
between the two sets of measures is
calculated as an index of validity.

Infers that the test provides a valid
reflection of future performance using
a similar test
Can performance during
test A be used to predict
future performance in
test B?
A B
Predictive Validity
(Statistical Validity)
90
We may be interested in using a test
to predict some future outcome.
Example:
• A test of aptitude for teaching may
be used to admit students to
teacher’s training college and be
expected to predict success at the
job as teachers
• A clerical aptitude test may be used
to predict success on the job as
clerks.

Infers not only that the test is
measuring what it is supposed to, but
also that it is capable of detecting
what should exist, theoretically
Therefore relates to hypothetical or
intangible constructs
e.g.
Team Rivalry
Sportsmanship.
Construct Validity
(Logical / Statistical Validity)
91
Sometimes questions like the following
are asked
§ What does this test mean or signify?
§ What does the score tell us about the
individual?
§ These questions are related with
construct validity of the test.
The terms ‘construct’ is used in
psychology to refer to something that is
not observable but is literally
‘constructed’ by the investigator to
summarize or account for the regularities
or relationships that he observes in
behaviour.

Factorial Validity
Factorial validity is, in a way, extension of the construct
validity.
The intercorrelations of a large number of tests are
examined and if possible accounted for in terms of a much
smaller number of more general ‘factors’ or trait categories.
Sometimes 3 or 4 factors may account for the
intercorrelations among 15 to 20 test.
The factorial validity of a test is defined by its correlation
with a factor, called factor loading.
92

Statistical
Analysis

Graph

Parametric & Non-Parametric Test

Application of ICT Tools in
Research
(ICT Applications in Research)
K.THIYAGU,
Assistant Professor, Department of Education,

ICT tools are mainly used by researchers
for its ability
to ease knowledge –gathering process
and
to enhance resource development.

Digital tools helps the researcher in the following way:
Identify research articles and appropriate information
sources through searching various online tools
Literature survey & Critically analyses known information
for further reading
Data collection process (Manage and collect the data)
Data analysis tools for both quantitative and qualitative
analysis
Referencing
Report preparation
CC-BY-NC-SA 105

ICT
Tools
Search Engine
Connect &
Communicate
with experts
and researchers
Free Digital
Library
Data Analysis
Referencing
Write & Publish
Research
Papers

Application
of ICT
Pre-data Analysis
Data Analysis
Post-data analysis

Application of ICT in
Pre-Data Analysis

Pre-Data
Analysis
Literature
Search
Literature
Tracking
Data
Collection

Literature Search
• https://scholar.google.com/
Google Scholar
• https://www.researchgate.net/
Research Gate
• https://www.academia.edu/
Academia
• https://www.semanticscholar.org/
Semantic Scholar
• https://scinapse.io/
Scinapse
• https://eric.ed.gov/
Eric
• https://pubmed.ncbi.nlm.nih.gov/
PubMed
• https://doaj.org/
DOAJ
• https://www.lens.org/
Lens
• https://login.webofknowledge.com/
Web of Knowledge

Famous Database for Research articles
AMS
Annual Revices
EBSCO
Elsevier
Indian Citation Index
Indian Journals
JSTOR
PsycINFO
SpringerLink
ProQuest
Academic Search Premier
Teacher Reference Center
PubPsych
Research Gate
Scopus
ERIC
PubMed
IEEE Xplore
Science Direct
DOAJ
Google Scholar
J-Gate
ORCID
Paperity
Publons
SpringerLink
Web of Science

Theses & Dissertations Database
PQDT Open: https://pqdtopen.proquest.com/search.html
MIT Theses: http://dspace.mit.edu/handle/1721.1/7582
Stanford University Libraries: https://library.stanford.edu/
UColorado Libraries: https://www.colorado.edu/libraries/
FAS Theses & Dissertations: https://dash.harvard.edu/handle/1/4927603
EBSCO Open Dissertations: https://biblioboard.com/opendissertations/
EThOS e-theses: https://ethos.bl.uk/Home.do
UNSW Library: https://www.library.unsw.edu.au/
Open Access Theses: https://oatd.org/
Shodhganga (Reservoir of Indian Theses): https://shodhganga.inflibnet.ac.in/

Literature
Tracking
Mendely
Zotero
EndNote
Literature Tracking: Sort, classify and store
EasyBib

Data Collections Tools
• https://www.google.com/forms/about/
Google Forms
• https://www.office.com/launch/forms
Microsoft Forms
• https://www.surveymonkey.com/
Survey Monkey
• https://www.zoho.com/forms/
Zoho Forms
• https://www.typeform.com/
Type form
• https://www.cognitoforms.com/
Cognito Forms

Data Analysis

Quantitative
Qualitative
Application of
ICT in data
analysis

Quantitative Data Analysis
SPSS
R
MATLAB
SAS
GraphPad
Microsoft Excel

Free Statistical Software
JASP: https://jasp-stats.org/
Jamovi: https://www.jamovi.org/
OpenStat: https://openstat.info/OpenStatMain.htm
SalStat-2: https://www.salstat.com/
SOFA (Statistics Open For All): https://www.sofastatistics.com/home.php
PSPP: https://www.gnu.org/software/pspp/
Statext: https://www.statext.com/
MicrOsiris: https://www.microsiris.com/
Gnumeric: http://www.gnumeric.org/
Tanagra (Data Mining): https://eric.univ-lyon2.fr/~ricco/tanagra/en/tanagra.html
AM Statistical Software: https://am.air.org/

Qualitative Data Analysis
Nvivo
ATLAS.ti
MAXQDA
Transana
• CAT (Coding Analysis Toolkit): https://cat-help.texifter.com/
• Weft QDA: https://weft-qda.en.uptodown.com/

Post Data Analysis

References and Bibliography Compilation
•Endnote
•Zotero
•Mendeley

Article and Thesis Discussion
• Academia.edu
• ResearchGate

Plagiarism Detection
• Grammarly
• Article Checker
• Turnitin
• Duplichecker

Ethical Considerations
in
Quantitative &
Qualitative Research
K.THIYAGU, Assistant Professor, Department of Education, Central University of Kerala, Kasaragod
Research
Ethics

Quantitative Research
• Data that are analyzed are in the form of
numbers.
• Eg: Behaviors are counted, correct answers or
errors are counted, and other types of measures
are recorded in terms of quantity.
• Quantitative research involves both experimental
and nonexperimental research.

Qualitative Research
• Data that are recorded in narrative
descriptions, not numbers.
• Methods to observe and describe
conditions rather than control them.
Basic Ethical Principle for Qualitative Researchers is
this:
Do not tamper with the natural setting under study.

Research
Ethics
Accuracy
Credibility
Confidential
Transparency
Honesty
Protecting
Authenticity
Originality
Plagiarism

Accuracy

Accuracy / Carefulness
Avoid careless errors
and negligence;
Carefully and critically
examine your own work
Keep good records of
research activities,
such as data collection,
research design, and
correspondence with
agencies or journals.

Credibility

Credibility
• Proper Citations
• Acknowledgement

Confidential

Confidential
Protect confidential
communications,
such as papers or
grants submitted for
publication,
personnel records,
trade or military secrets,
and patient records.

Protecting

Protection
• When conducting research on
human subjects, minimize harms
and risks and maximize benefits;
• Take special precautions with
vulnerable populations;
• Respect human dignity, privacy,
and autonomy;

Transparency

Transparency/
Openness
Share data,
results, ideas,
tools,
resources.
Be open to
criticism and
new ideas.

Honesty

Honestly report data,
results, methods and
procedures, and
publication status.
Do not deceive
colleagues,
research sponsors,
or
the public.
Do not fabricate,
falsify,
or
misrepresent data.

Authenticity

Authenticity
Data should authentic
Information should be authentic
Proper references

Originality

Originality
Ideas should be fresh
Innovative work
Novel work

Plagiarism

Plagiarism
Plagiarism is the act of passing
off somebody else’s ideas,
thoughts, pictures, theories,
words, or stories as your own.

Research Aptitude
NET BUREAU
Unit - II
K.THIYAGU, Assistant Professor, Department of Education,

Unit 2- Research Aptitude (UGC NET Paper I).pdf

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