NTA NET 2021 || Unit 9 Educational Management, Administration and Leadership|| L2

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NTA NET 2021 || Unit 9 Educational Management, Administration and Leadership|| L2

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NTA NET 2021 || Unit 9 Educational Management, Administration and Leadership|| L2

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In this lecture we will discuss part of
Unit 6: Research in Education
a) Meaning and Scope of Educational Research, Meaning and steps of
Scientific Method, Characteristics of Scientific Method (Replicability,
Precision, Falsifiability and Parsimony), Types of Scientific Method
(Exploratory, Explanatory and Descriptive), Aims of research as a
scientific activity: Problem-solving, Theory Building and Prediction,
Types of research (Fundamental, Applied and Action), Approaches to
educational research (Quantitative and Qualitative), Designs in
educational research (Descriptive, Experimental and Historical)
b) Variables: Meaning of Concepts, Constructs and Variables, Types of
Variables (Independent, Dependent, Extraneous, Intervening and
Moderator), Hypotheses – Concept, Sources, Types (Research,
Directional, Non-directional, Null), Formulating Hypothesis,
Characteristics of a good hypothesis, Steps of Writing a Research
Proposal, Concept of Universe and Sample, Characteristics of a good
Sample, Techniques of Sampling (Probability and Non-probability
Sampling), Tools of Research – Validity, Reliability and Standardisation
of a Tool, Types of Tools (Rating scale, Attitude scale, Questionnaire,
Aptitude test and Achievement Test, Inventory), Techniques of
Research (Observation, Interview and Projective Techniques)
c) Types of Measurement Scale (Nominal, Ordinal, Interval and Ratio),
Quantitative Data Analysis – Descriptive data analysis (Measures of
central tendency, variability, fiduciary limits and graphical presentation
of data), Testing of Hypothesis (Type I and Type II Errors), Levels of
Significance, Power of a statistical test and effect size, Parametric
Techniques, Non- Parametric Techniques , Conditions to be satisfied
for using parametric techniques, Inferential data analysis, Use and
Interpretation of statistical techniques: Correlation, t-test, z-test,
ANOVA, chi-square (Equal Probability and Normal Probability
Hypothesis). Qualitative Data Analysis – Data Reduction and
Classification, Analytical Induction and Constant Comparison, Concept
of Triangulation
d) Qualitative Research Designs: Grounded Theory Designs (Types,
characteristics, designs, Steps in conducting a GT research, Strengths
and Weakness of GT) – Narrative Research Designs (Meaning and key
Characteristics, Steps in conducting NR design), Case Study (Meaning,
Characteristics, Components of a CS design, Types of CS design,
Steps of conducting a CS research, Strengths and weaknesses),
Ethnography (Meaning, Characteristics, Underlying assumptions, Steps
of conducting ethnographic research, Writing ethnographic account,
Strengths and weaknesses), Mixed Method Designs: Characteristics,
Types of MM designs (Triangulation, explanatory and exploratory
designs), Steps in conducting a MM designs, Strengths and weakness
of MM research.

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