Building Theory from the Ground Up, Explained

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Building Theory from the Ground Up

Research Methods in Psychology · Chapter 6: Qualitative Research MethodsSection 6.4 · lesson 38 of 9411 min · free with a free account

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In this lesson

Letting theoretical accounts emerge from systematic engagement with data.

  • Define grounded theory and its inductive logic
  • Apply open, axial and selective coding
  • Use constant comparison, theoretical sampling and memos
  • Judge saturation and the quality of a theory

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Qualitative Research Methods

Building Theory from the Ground Up

Most research you have studied so far starts with a theory, and then goes looking for data. Grounded theory runs the other way. It starts with the data, and builds the theory afterwards. That sounds simple. Doing it well takes a set of very specific disciplines. This section walks through those disciplines, one at a time. By the end you will be able to define grounded theory, and explain its inductive logic. You will apply three levels of coding to qualitative material: open, axial, and selective. You will use constant comparison, theoretical sampling, and memo writing. And you will know how to judge whether a grounded theory is any good. That last question has a more concrete answer than you might expect.

Theory From Data

Theory That Begins With Data

Start with the sequence that most quantitative research follows. You begin with a theory. You derive hypotheses from it. You collect data, and the theory is then supported, refined, or rejected. The theory comes first, and the data arrive to judge it. Grounded theory reverses that sequence completely. The researcher enters the field with a question, not with a framework. The theoretical account is built up inductively, from the data themselves. Which is where the name comes from. The theory is called grounded because it grows out of the material participants provided. Close, systematic engagement with that material is what does the work. Nothing is imposed on the evidence from outside. That is the whole claim.

Glaser And Strauss

Where the Approach Came From

The approach has a specific origin, and it was an argument as much as a method. Grounded theory was developed in the nineteen sixties, by two sociologists. Barney Glaser and Anselm Strauss. They were reacting to something they saw in the social sciences of the time. An overemphasis on theory testing, and a corresponding neglect of theory construction. There was plenty of machinery for checking whether an idea survived contact with data. Far less for producing the idea in the first place. Since then, the approach has split into several streams. Glaserian, Straussian, and constructivist variants. They differ in their philosophical commitments, and in their analytical procedures. The constructivist variant, for instance, stresses the researcher's part in co-constructing the analysis. What unites them all is one conviction. Systematic qualitative analysis can produce theory, not merely description.

Defining Features

Six Features That Mark the Approach

Six features define the approach. Take them as a set, because they hold each other up. First, inductive logic. Theory is built up from data, rather than tested against them. Second, concurrent collection and analysis, which is the one people underestimate. Data collection and analysis proceed at the same time, each shaping the other. Third, constant comparison. Every new piece of data is compared with what has already been coded. Fourth, theoretical sampling. Later sources are chosen because they will develop the emerging theory. Fifth, memo writing. The researcher keeps ongoing analytical notes as ideas emerge. Sixth, saturation. Collection ends when additional cases produce no new categories or insights. Now look again at that second feature, because it changes the shape of the whole project. In most designs, data are collected first and analyzed afterwards. Grounded theory interleaves them deliberately. Early analysis shapes what gets collected next. New data then refine the analysis, and the account emerges from the evidence instead of being imposed on it.

Three Coding Levels

Coding: From Data to Theory

Coding is the central analytic activity in grounded theory. The researcher reads the data closely, and attaches labels to small segments. Those labels are the codes. A segment might be a line of transcript, or a moment recorded in field notes. Codes are then organized into categories, and the categories grow more abstract as work proceeds. The standard Straussian approach marks three levels of coding. Open coding comes first. It breaks the material into small labeled pieces. Axial coding groups those pieces into categories, and looks for relationships among them. Selective coding identifies a core category, and uses it to integrate everything else. Read that sequence as a movement from concrete to abstract. Each level is more integrative than the last, and each one depends on the last.

Open Coding

Breaking the Data into Concepts

Open coding is the closest the analysis ever gets to the raw material. The researcher reads transcripts or field notes line by line. The question at each segment is simple. What is happening here? Each piece is then labeled with a concept. Crucially, the codes are kept close to the data. Often that means using the participants' own words, which is called an in vivo code. An in vivo code preserves the participant's language, instead of translating it into yours. The output of open coding is a long list of concepts. They capture what is being said and done right across the material. It is not organized yet, and it is not meant to be. Organizing comes next.

Axial And Selective

From Categories to a Core

Axial coding is where the scattered list becomes a structure. The researcher regroups the open codes into categories. Then asks how those categories relate to one another. Which codes belong together? What are the central conditions and contexts? What strategies do people use, and what consequences follow? By the end of axial coding you have an organized set of categories, not a list. Selective coding takes the final step. It identifies a core category, the central concept that the rest of the theory organizes around. That core is then used to integrate the analysis into a coherent theoretical story. The test is whether every major category links to the core in a clear, explainable way. If a category will not link, the analysis is not finished yet.

Constant Comparison

Every New Case Tests the Categories

Constant comparison is the habit that keeps categories honest. Each new piece of data gets compared with everything already coded. Two questions drive it. Does this incident fit an existing category, or does it suggest a new one? And does this code apply equally well in different contexts? Notice what that prevents. A category cannot be applied loosely, because every new case is tested against it. The rhythm of comparison sharpens categories, and exposes inconsistencies. It pushes the analysis toward greater precision, case by case. It is a slow discipline, and it is the reason the categories can be trusted at the end.

Sampling And Memos

Letting the Analysis Drive the Sampling

Theoretical sampling asks a different question from ordinary sampling. Not what the plan said in advance, but what the developing theory now needs. If a category seems thin, the researcher seeks cases that will elaborate it. If a category seems too neat, the researcher seeks cases that might challenge it. That second move is the interesting one. You go looking for trouble on purpose. Sampling decisions are driven by the analysis itself. Not by a fixed plan set before fieldwork began. Memos run alongside all of this. A memo is an analytical note, written while the project is still unfolding. Emerging ideas, comparisons among codes, hunches about relationships, reflections on where the analysis is going. Memos are not field notes. They are theoretical reflections in their own right. Some grounded theorists describe the final theory as the systematic organization of the memos they accumulated.

Theoretical Saturation

Knowing When to Stop

Every qualitative researcher meets the same question eventually. When do I stop collecting data? Grounded theory has a specific answer, and it is not a number. Theoretical saturation is the point at which additional data produce no new categories. No new properties, and no new insights. The account has become comprehensive enough that further data merely confirm what is understood. Saturation, not a predetermined sample size, is the criterion for ending collection. So the amount of data you gather is an outcome of the analysis, not a decision made up front. In practice, saturation is judged with reference to specific categories. A researcher might be saturated on one category, while still seeking fresh data to elaborate another. So saturation is rarely a single moment. It arrives category by category.

Strengths And Limitations

What Grounded Theory Can and Cannot Do

Now the honest accounting. What grounded theory does well, and what it cannot do. It generates new theory, rather than testing theory that already exists. It stays close to participants' own perspectives and language. It produces rich, well-grounded theoretical accounts. It suits relatively unexplored topics, where existing theory is thin. And it encourages disciplined, transparent analytical reasoning. The limitations are just as specific. It cannot test pre-existing hypotheses. For that you need a different design. It is highly time-intensive, particularly because collection and analysis run together. It is difficult to learn well, and it requires sustained training and supervision. It is less suitable when robust theory already exists and the goal is testing. And the different schools give conflicting guidance on procedure, which a beginner has to navigate.

Quality Criteria

Fit, Work, Relevance, Modifiability

Finally, how a grounded theory gets judged. It inherits the trustworthiness criteria introduced in section six point one. Credibility, transferability, dependability, confirmability, and reflexivity. Then it adds four standards of its own. Fit. The theory should fit the data closely, capturing what participants actually said and did. Work. It should explain the phenomenon coherently. Relevance. It should illuminate something the people it describes recognize as meaningful. And modifiability. It should stay open to revision as new data or new contexts appear. But one test matters more than all four. Is the theory actually grounded in the data? An account that reads beautifully, but cannot be traced back to specific incidents and codes, has lost its evidentiary base. So strong writing keeps the link between data and theory visible, through quotation and a clear analytical narrative.

About Research Methods in Psychology at UPI Study

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FAQ

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About Building Theory from the Ground Up

What is grounded theory and who developed it?
Grounded theory is a qualitative approach that builds theory inductively from data rather than testing a theory chosen in advance. Sociologists Barney Glaser and Anselm Strauss developed it in the 1960s, reacting against social science's emphasis on testing theories rather than generating them. It has since split into Glaserian, Straussian, and constructivist versions, which share the view that systematic qualitative analysis can produce theory.
What are open, axial, and selective coding?
They are the three levels of coding in the Straussian version of grounded theory, moving from concrete to abstract. Open coding breaks data into small labeled pieces, line by line, often using participants' own words as in vivo codes. Axial coding groups those codes into categories and examines how they relate. Selective coding identifies a core category and integrates every other category around it into a coherent theory.
What is the constant comparative method?
The constant comparative method means comparing each new piece of data with everything already coded. The researcher asks whether a new incident fits an existing category or suggests a new one, and whether a code applies equally well across contexts. This testing sharpens categories, exposes inconsistencies, and prevents codes from being applied loosely. In grounded theory, data collection and analysis proceed together, so comparison continues throughout the study.
What is theoretical sampling in grounded theory?
Theoretical sampling means choosing later participants or sources based on what the emerging theory needs, rather than following a plan fixed in advance. If a category seems thin, the researcher seeks cases that will elaborate it; if it seems too neat, the researcher seeks cases that might challenge it. Analytical memos written throughout the project record the developing ideas that guide these sampling decisions.

About the Research Methods in Psychology course

How many college credits is Research Methods in Psychology?
Research Methods in Psychology (Psychology 111) carries a NCCRS credit recommendation for 3 semester credits. ACE and NCCRS have over 2,100 cooperating colleges that will consider accepting credits; the final decision is with the universities.
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