Ask five people to define “educational research” and you will likely get five different answers. One might describe it as classroom experiments testing new teaching methods, another as large-scale surveys tracking dropout rates, and a third as computer scientists building an app to help children with dyslexia. All three are correct. That is the nature of this field: it does not sit inside one subject or one age group. It stretches across every level of schooling, every curriculum area, and now, every new technology that touches a classroom.

For anyone studying education seriously, understanding this scope is not just an academic exercise. It shapes what questions get asked, which problems get funded, and how policies like the National Education Policy (NEP) 2020 get shaped by evidence rather than guesswork. Let us break down exactly where the boundaries of this field lie, and where they are still expanding.

Table of Contents

Classification by levels of education

One of the simplest ways to organise educational research is by the stage of education it examines. A question that matters deeply for a five-year-old learning the alphabet is often irrelevant for a postgraduate student writing a thesis. So researchers typically divide their work by level.

Research at the school level

Primary and secondary education research usually looks at foundational literacy and numeracy, classroom pedagogy, textbook design, and assessment patterns. In India, this work is closely tied to institutions like the National Council of Educational Research and Training, which was set up to study and improve teaching practices, develop model textbooks, and coordinate research across states so that school education stays consistent in quality. Much of what appears in a school syllabus, or how a chapter is structured, traces back to research conducted at this level.

Research in higher education

Once you move to colleges and universities, the research questions shift. Instead of foundational literacy, the focus turns to enrolment patterns, employability, curriculum relevance, and access for underrepresented groups. The All India Survey on Higher Education, run by the Ministry of Education, is one of the largest sources of this kind of data in the country. It tracks metrics like the Gross Enrolment Ratio and gender parity across institutions every year. Government data has shown that PhD enrolment in India rose sharply between 2014-15 and 2021-22, more than doubling over that period, which itself has become a subject of research into why more students are pursuing doctoral study and what support systems they need.

This level-based classification matters because policies designed for school children rarely translate well to university students, and vice versa. A researcher studying rote memorisation in a Class 5 classroom is working in a completely different world from one studying research supervision practices at the PhD level, even though both technically fall under “educational research.”

Curriculum areas in educational research

Beyond levels, research is also organised by subject or curriculum area. Each academic discipline brings its own teaching challenges, and researchers who specialise in one area often develop deep, subject-specific expertise that a generalist would miss.

Language education

Language education research examines how students acquire reading and writing skills, how bilingual or multilingual classrooms function, and how mother-tongue instruction affects comprehension. In the Indian context, this becomes especially significant given the sheer number of languages spoken across states and NEP 2020’s emphasis on instruction in regional languages during the early years. Researchers in this space study everything from vocabulary acquisition to the cognitive load of switching between languages in a single classroom.

Science education

Science education research asks a different set of questions: How do students form misconceptions about scientific concepts? Does inquiry-based learning, where students investigate a problem hands-on rather than memorising facts, actually improve retention? This area has grown substantially as India pushes for stronger STEM outcomes, with researchers studying everything from laboratory access in rural schools to the effectiveness of practical demonstrations over textbook-only teaching.

Teacher education

No curriculum area matters more than the one focused on teachers themselves, since their preparation directly shapes every other subject. A recent scoping review of teacher research in higher education found that pedagogy and curriculum design together accounted for well over half of all research focus areas studied, ahead of topics like reflective practice or student support. This tells us something important: even within teacher education, the biggest research energy still goes toward the basics of how to teach and what to teach, rather than peripheral concerns.

Teacher education research in India also increasingly examines in-service training quality, since a large share of practising teachers were trained years or decades ago under older frameworks and now need continuous upskilling to keep pace with revised curricula.

Emerging areas in educational research

Some areas of educational research did not exist in any meaningful form a generation ago. Two of the fastest-growing ones today are educational technology and special or inclusive education, both of which have been pushed to the forefront by NEP 2020.

Educational technology

EdTech research covers everything from the design of learning apps to the use of artificial intelligence for adaptive assessments. NEP 2020 explicitly frames technology not as a peripheral add-on but as a systemic enabler meant to make learning more universal, inclusive, and future-ready. This has opened up a wide research agenda: Does a smartboard actually improve comprehension compared to a chalkboard? Do adaptive learning platforms genuinely personalise instruction, or do they just automate the same worksheet at different speeds? Researchers are also studying the digital divide, since access to devices and reliable internet remains uneven between urban and rural India, which directly affects how much EdTech interventions can actually help.

Special and inclusive education

Special education research has expanded rapidly as policy attention has shifted toward children with disabilities and other historically excluded groups. According to government data, roughly 22.6 lakh children with special needs were enrolled from pre-primary to Class 12 as per UDISE+ figures for 2021-22, and NEP 2020 has pushed for a “whole school” approach that includes resource centres, trained special educators, and accessible teaching materials. Researchers in this area study which classroom accommodations genuinely help, how early identification of learning difficulties can be improved, and whether current teacher training programmes adequately prepare general classroom teachers, not just special educators, to support diverse learners.

At the same time, independent analyses have pointed out gaps in implementation. One academic review of NEP 2020’s inclusion agenda noted that the policy has been welcomed for its progressive language on equity, even as researchers flag pitfalls in how well those intentions translate into ground-level practice. This tension between policy ambition and classroom reality is itself a rich and ongoing area of study, not a settled question.

Why this expanding scope matters

Educational research today looks very different from what it did even fifteen years ago. It has moved from being primarily concerned with school-level pedagogy to encompassing higher education access, subject-specific learning science, and rapidly evolving technological and inclusion-focused questions. For students of educational research, this expanding scope is actually good news. It means there is no shortage of unexplored territory, whether your interest lies in analysing how a Class 3 student learns to read, how a university structures its PhD programmes, or how an AI-powered app might help a child with a learning disability keep pace with classmates.

What connects all of these areas is a shared goal: using systematic evidence, rather than assumption, to make education work better for the people inside it.

What do you think? Which of these areas, levels of education, curriculum-specific research, or emerging fields like EdTech and inclusive education, feels most urgent for India right now? And do you think research is keeping pace with how quickly classrooms themselves are changing?

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References
  1. http://riemysore.ac.in/national-council-educational-research-and-training-ncert
  2. https://aishe.gov.in/
  3. https://www.pib.gov.in/PressReleasePage.aspx?PRID=1999713&reg=48&lang=2
  4. https://www.sciencedirect.com/science/article/pii/S266637402400075X
  5. https://www.orfonline.org/expert-speak/five-years-of-nep-2020-and-the-promise-of-edtech
  6. https://dsel.education.gov.in/inclusive-education
  7. https://www.tandfonline.com/doi/full/10.1080/13603116.2023.2295907

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Educational Research

1 Introduction to Educational Research

  1. Knowledge: Nature and Types
  2. Sources of Knowledge
  3. Nature and Conceptions of Social Reality
  4. Purposes of Research
  5. What is Educational Research?
  6. Scope of Educational Research
  7. Types of Studies in Educational Research

2 Knowledge Generation- Historical Perspective – I

  1. Sources of Knowledge
  2. Scientific Method
  3. Let Us Sum Up

3 Knowledge Generation- Historical Perspective – II

  1. Positivistic Paradigm
  2. Limitations of the Positivistic Paradigm
  3. Alternative Approaches to Development of Social Science Inquiry
  4. Emergence of Field Methods
  5. Review (Rethinking) of Concepts and Constructs

4 Approaches to Educational Research- Assumptions, Scope and Limitations

  1. Nature of Educational Phenomena
  2. Conceptions of Viewing Reality
  3. The Objective and Subjective Views of Reality
  4. The Nature of Knowledge and Knowing
  5. The Nature of Human Agency
  6. Methodology
  7. Limitations of the Approaches

5 Descriptive Research

  1. Meaning and Nature of Descriptive Survey Research
  2. Types of Descriptive Survey Studies
  3. Steps of Conducting Descriptive Research
  4. Context and Relevance of Descriptive Studies in Educational Research

6 Experimental Research – I

  1. Characteristics of Experimental Research
  2. Experimental Design
  3. Validity of Experimental Design
  4. Controls in an Experiment
  5. Let Us Sum Up

7 Experimental Research – II

  1. Types of Experimental Design
  2. Pre-experimental Designs
  3. True Experimental Designs
  4. Quasi-Experimental Designs
  5. Steps in Experimental Research

8 Qualitative Research

  1. Definition of Qualitative Research
  2. Characteristics of Qualitative Research
  3. Reasons for Conducting Qualitative Research
  4. Types of Qualitative Methods
  5. Context of Qualitative Methods
  6. Common Steps of Conducting Qualitative Studies
  7. Verification of Trustworthiness of Qualitative Research

9 Philosophical and Historical Studies

  1. Philosophical Studies
  2. Meaning and Nature of Philosophical Research in Education
  3. Areas of Philosophical Research in Education
  4. Philosophical Inquiry: Main Steps
  5. Historical Research
  6. Relevance and Scope of the Study of Educational History
  7. Main Characteristics of Historical Research
  8. New Trends in Historical Approaches to Education
  9. Enhancing the Importance of Historical Research

10 Identification of Problem and Formulation of Research Questions

  1. Nature of a Problem
  2. Identification of a Research Problem
  3. Sources for Selecting a Research Problem
  4. Definition and Statement of the Problem
  5. Formulation of Research Questions

11 Hypothesis- Nature of Formulation

  1. Meaning of the Hypothesis
  2. Sources of Hypothesis
  3. Types of Hypothesis
  4. Testing of the Hypothesis
  5. Characteristics of a Good Hypothesis
  6. Significance and Importance of a Hypothesis

12 Sampling

  1. Meaning of Population and Sample
  2. Probability Sampling
  3. Non-probability Sampling
  4. Simple Random Sampling
  5. Characteristics of a Good Sample

13 Tools and Techniques of Data Collection

  1. Questionnaire
  2. Rating Scale
  3. Attitude Scales
  4. Check List
  5. Tests
  6. Inventory
  7. Interview
  8. Observation
  9. Documents
  10. Characteristics and Criteria for Selection of a Good Tool

14 Analysis of Quantitative Data (Descriptive Statistical Measures- Selection and Application)

  1. Types of Data
  2. Graphic Representation of Quantitative Data
  3. Measures of Central Tendency or Averages
  4. Measures of Variability or Dispersion
  5. Normal Probability Curve

15 Analysis of Quantitative Data- Inferential Statistics Based on Parametric Tests

  1. Inferential Statistics
  2. Parametric Tests: Uses and Assumptions
  3. Statistical Inference Based on Parametric Tests
  4. Testing the Statistical Significance of the Difference Between Means
  5. Statistical Inference Regarding Pearson’s Coefficient of Correlation
  6. Significance of the Difference Between Pearson’s Coefficients of Correlation of Two Independent Samples

16 Analysis of Quantitative Data- Inferential Statistics Based on Non-Parametric Tests

  1. Non-parametric Tests
  2. Statistical Inference Based on Non-Parametric Tests: Unrelated Samples
  3. Statistical Inference Based on Non-Parametric Tests: Related Samples
  4. Statistical Inference Regarding Correlations Using Non-Parametric Data

17 Analysis of Qualitative Data

  1. Nature of Qualitative Data
  2. Sources of Qualitative Data Collection
  3. Deciding Data Analysis Strategies
  4. Components of Qualitative Data Analysis

18 Data Analysis Techniques in Qualitative Research

  1. Data Analysis Techniques in Qualitative Research
  2. Codification
  3. Categorization and Classification
  4. Content Analysis
  5. Triangulation

19 Computer Data Analysis

  1. What is SPSS?
  2. Get Yourself Acquainted with SPSS
  3. Menu Commands and Sub-commands
  4. Basic Steps in Data Analysis
  5. Defining, Editing and Entering Data
  6. Data File Management Functions
  7. Running a Preliminary Analysis
  8. Understanding Relationship Between Variables
  9. Non-parametric Tests
  10. SPSS Production Facility
  11. Statistical Analysis System (SAS)
  12. NUDIST

20 Writing Proposal / Synopsis

  1. Purpose of Writing a Research Proposal
  2. Research Proposal/Synopsis
  3. Format of a Research Proposal / A Synopsis

21 Methods of Literature Search /Review

  1. Need and Purpose of Literature Search
  2. Types of Literature Search
  3. Steps Involved in Literature Search
  4. Methods of Literature Search
  5. Methods of Review and Their Implications

22 Research Report- Various Components and Structure

  1. Significance of a Research Report
  2. What is a Research Report?
  3. Why to Prepare a Research Report?
  4. Types of Research Reports
  5. Format of a Research Report

23 Scheme of Chapterisation and Referencing

  1. Need for Chapterisation and its Functions
  2. Diversity in Chapterisation
  3. Referencing and Footnotes – Need and Importance
  4. Various Styles of Referencing