Conceptions of Reality in Educational Research: Traditional vs. Radical Perspectives

Ask a physicist and a poet what “reality” means, and you will get two very different answers. Educational researchers face the same divide. Before anyone designs a study, collects data, or writes a single questionnaire item, they must first answer a deeper question: what is real, and how do we know it? This is not a philosophical detour. It decides which methods a researcher trusts, which questions they think are worth asking, and how they interpret whatever data they collect.

Two ways of looking at reality 🔗

In educational research, this debate is usually framed as a contrast between the traditional (positivist) view and the radical (interpretivist) view of reality. Both are legitimate, both have shaped decades of research, and both show up constantly in Indian classrooms, policy reports, and academic journals, often without anyone naming them directly.

The traditional view: Reality as fixed and measurable 🔗

The positivist tradition borrows its assumptions from the natural sciences. It treats reality as something that exists independently of the researcher, waiting to be discovered through careful observation and measurement. A realist ontology holds that a single, objective truth exists out there, and the researcher’s job is simply to uncover it accurately, without letting personal bias creep in.

This view treats learning outcomes, intelligence scores, and dropout rates as things that can be counted, compared, and generalised across large populations. If a study finds that students who receive extra tutoring score higher on a standardised test, positivists would treat this as evidence of a real, replicable relationship between two variables, similar to how a chemist treats the relationship between heat and pressure.

The radical view: Reality as constructed 🔗

The radical or interpretivist tradition rejects the idea that human and social life can be studied the same way as chemicals or planets. Here, reality is not a fixed external fact but something that is built through human meaning-making. This position, sometimes called relativism, holds that reality is subjective and differs from person to person, shaped by individual experience, culture, and context.

For an interpretivist researcher, a “dropout” is not just a statistic. It is a lived experience shaped by a student’s family circumstances, self-perception, relationship with teachers, and sense of belonging in the classroom. No two dropouts mean exactly the same thing, and no single number can fully capture why a child left school.

How these conceptions shape actual research 🔗

This is where the philosophy stops being abstract and starts affecting real research design. The choice of paradigm shapes three things directly: the questions researchers ask, the methods they choose, and how they interpret their data.

The questions researchers ask 🔗

A positivist-leaning researcher tends to ask questions that can be tested and measured: Does a particular teaching method improve test scores? Is there a correlation between attendance and academic performance? An interpretivist researcher asks more open, exploratory questions: How do students experience anxiety before an exam? What does “quality education” mean to a first-generation learner?

The methods researchers choose 🔗

Positivist assumptions naturally lead to quantitative methods, such as surveys, standardised tests, and statistical analysis, because these tools produce numerical, generalisable data. Interpretivist assumptions lead to qualitative methods, such as interviews, classroom observations, and case studies, which capture depth and nuance rather than breadth.

How data gets interpreted 🔗

Even when researchers look at the same numbers, their underlying view of reality changes what they conclude. A drop in national test scores can be read by a positivist as clear evidence of declining learning outcomes. An interpretivist would ask what the test actually measured, whose knowledge it privileged, and whether the number hides more than it reveals. Both readings can be defended, but they lead to very different policy recommendations.

Examples from Indian education 🔗

India’s education sector offers some vivid, real-world illustrations of this paradigm divide in action.

ASER and the numbers debate 🔗

The Annual Status of Education Report, published by Pratham, is a classic example of the positivist approach. It surveys households across rural India and reports hard figures, such as the percentage of Grade 5 students who cannot read a Grade 2-level text. These numbers are treated as an objective snapshot of the “real” state of learning, and they have directly shaped national conversations, including debates that fed into the National Education Policy’s outcomes-based approach and the 2017 amendment to the Right to Education Act that made class-wise learning outcomes mandatory.

National Achievement Survey and its critics 🔗

The National Achievement Survey (NAS) is another large-scale, positivist-style assessment that produces national average scores for language and mathematics across grades. But it has also drawn criticism for being overly focused on metrics, with some researchers arguing that a narrow obsession with numbers has, in certain cases, encouraged schools to manipulate results rather than genuinely improve learning. This criticism is essentially an interpretivist objection: a single score cannot capture the full, messy reality of what happens inside a classroom, and treating it as the whole truth can distort behaviour on the ground.

Foundational literacy research using both lenses 🔗

Recent studies on India’s NIPUN Bharat Mission for foundational literacy and numeracy show both paradigms working together. Researchers have combined student performance data with teacher-reported classroom challenges across states like Tamil Nadu, Uttar Pradesh, and Assam. The numbers reveal patterns of improvement, while the interviews with teachers and administrators reveal why some states, particularly those using local language and context-sensitive approaches, saw better results than others. Neither lens alone would have told the full story.

Balancing perspectives for comprehensive research 🔗

The most useful research in education rarely picks one paradigm and ignores the other completely. Mixed-methods research, which draws on both positivist and interpretivist assumptions, has become increasingly common precisely because it plays to the strengths of both traditions. Quantitative data can establish that a pattern exists at scale, while qualitative data can explain why that pattern exists and how it feels from the inside.

Consider a study on why enrolment drops during the transition from primary to secondary school in a particular Indian state. A purely positivist study might report the dropout percentage and correlate it with variables like household income or distance to school. A purely interpretivist study might interview a handful of families to understand their reasoning. Combined, the researcher gets both the scale of the problem and the human reasons behind it, which is far more useful for designing an actual intervention.

This is why many contemporary researchers treat the positivist-interpretivist divide not as a wall but as a spectrum. Depending on the research question, a study can lean more toward one end or genuinely integrate both, using numbers to identify what is happening and narratives to understand why.

Why this matters beyond the research classroom 🔗

Understanding these conceptions of reality is not just an academic exercise for those studying research methodology. It shapes how policymakers read reports like ASER, how teacher training programmes evaluate their own effectiveness, and how school administrators decide whether a “successful” intervention is one that raises test scores, one that improves student wellbeing, or both. Every time someone cites a statistic to argue a point about Indian education, or dismisses a personal account as “just anecdotal,” they are quietly taking a side in this very old philosophical debate.

What do you think? When you look at debates over falling learning levels in Indian schools, do you find yourself trusting the numbers more, or the lived experiences behind them? And can you think of a school problem in your own experience that a single test score could never fully explain?

References

1. https://researcher.life/blog/article/what-is-a-research-paradigm-types-examples/
2. https://files.eric.ed.gov/fulltext/EJ1080001.pdf
3. https://teachers.institute/contemporary-india-education/impact-research-educational-policy-planning-india/
4. https://www.teacherplus.org/nep-2020-and-learning-outcomes/
5. https://www.tandfonline.com/doi/full/10.1080/13603116.2023.2295907
6. https://www.researchgate.net/publication/393131237_The_Success_of_the_NIPUN_Bharat_Scheme_A_Case_Study_on_Foundational_Literacy_and_Numeracy_in_India