Research Design Cartography

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Performative

Performative qualitative research is a type of research where the researcher uses creative, expressive, or artistic forms—like performances, storytelling, theater, spoken word, or movement—to explore and communicate what people think, feel, and experience. Instead of just describing data, performative research often shows it in an expressive way. Think of it as using art to reveal truths about human experience.How it works:

1. Gather real experiences or stories. The researcher collects data through interviews, observations, journals, or personal narratives—just like in other qualitative methods.
2. Transform those experiences into a performance or creative form. This might include: A scripted scene; A monologue based on interview data; A dance representing a social issue; A video or multimedia piece; A public reading or reenactment; etc. The creative performance becomes a way to express the research findings.
3. Use the performance to communicate meaning. The performance helps audiences feel and understand the experience in a deeper way than reading a paper might.
4. Reflect and analyze. The researcher examines how the performance reveals meaning, challenges assumptions, or sparks new insights.

Why do researchers use this?Performative research helps capture emotions, identities, and social issues that are hard to express through traditional writing. It can make invisible experiences more visible, and it invites the audience to understand the research with their senses, not just their mind. Imagine taking real stories about students feeling pressure at school and turning them into a short play. The play doesn’t just report the problem—it brings it to life.That’s the heart of performative qualitative research.

Correlational Research Design

Like descriptive research, correlational research does not manipulate variables. Instead, the researcher measures variables to determine whether a relationship exists between them.The key difference is that correlational studies focus on the relationships among variables—specifically, whether they are positive, negative, or show no correlation:

• Positive correlation: Both variables move in the same direction. Example: “As a person lifts more weights, their muscle mass increases.”

• Negative correlation: Variables move in opposite directions. Example: “As a waiter drops more trays, their tips decrease.”

• Zero correlation: No relationship exists. Example: “The number of muscular waiters is unrelated to tip amount.”

Although correlations may appear causal, they do not prove cause and effect. A correlational study can show that two variables are related, but not that one directly causes the other.

Quasi-Experimental Quantitative Research Design

In a quasi-experimental design, researchers aim to identify cause-and-effect relationships between variables. For example, a study might find that students who study one hour daily tend to earn higher test scores. Here, study time is the independent variable, and test scores are the dependent variable—the outcome that changes in response to the independent variable.Unlike a true experiment, a quasi-experimental study does not use random assignment. Participants are grouped based on existing characteristics or non-random criteria. While control groups are not always required, they are often included to strengthen the study’s conclusions.

Post-positivist Worldview

A post-positivist worldview is a way of thinking about research that builds on positivism but adds an important twist:Post-positivists believe that we can try to understand reality through scientific methods, but we can never know it with complete certainty. In other words, they agree that an objective reality exists, but they recognize that humans—and even scientific tools—have limitations.Key Ideas:

1. There is a real world, but we can’t observe it perfectly. Post-positivists believe in one reality, but admit that researchers can never fully capture it without some error or bias.
2. Research should still be scientific and systematic. They use experiments, measurements, and statistics—just like positivists—but they are more cautious about their conclusions.
3. Objectivity is a goal, not a guarantee. Instead of pretending to be perfectly objective, post-positivists try to reduce bias through careful design, peer review, and transparent methods.
4. Evidence is always “probable,” not absolute. Post-positivists avoid saying “This proves X.” Instead, they say things like “The evidence suggests…” or “The data supports…”
5. Cause and effect still matter. They look for patterns and explanations, but accept that results might change with better tools, more data, or new perspectives.

Action Research

Action Research is a qualitative research design where the researcher is not just observing a problem—they are actively trying to improve it while studying it. Think of it like being both a scientist and a problem-solver at the same time. You study your own practice, performance, approach, etc. Here’s how it works:

1. Identify a problem in a real-world setting. Action research is often used by teachers, coaches, or community leaders who want to fix or improve something in their own environment. For example:
1. “Why aren’t my students participating in group discussions?”
2. “How can I improve the recycling program at school?”
2. Develop a plan to address the problem. The researcher chooses an action or strategy to try—like a new teaching method, a new schedule, or a new communication tool.
3. Implement the action and collect data. While trying the new strategy, the researcher observes what happens, interviews participants, and gathers evidence to see whether the change is working.
4. Reflect, adjust, and try again if needed. Based on what they learn, the researcher improves the plan and repeats the cycle. Action research is often done in cycles: Plan → Act → Observe → Reflect → (Repeat)
5. Share what you have learned. The final result is both a solution to a real issue and a deeper understanding of why the solution worked (or didn’t work).

Imagine you want to improve how your club runs meetings. You try a new approach, observe how people respond, analyze the results, adjust your strategy, and test it again. That’s action research—learning and improving at the same time.

Concurrent Mixed Research Design

A Concurrent Mixed Research Design is a type of study where the researcher collects quantitative data (numbers) and qualitative data (stories or explanations) at the same time, rather than one after the other.Think of it like listening to two songs playing in harmony—you hear them together, and they help you understand the full meaning of the music. Here’s how it works:

1. Conduct two studies at the same time. For example, a researcher might conduct a correlational study (quantitative) and a case study (qualitative) during the same week, to study the same phenomenon.
2. Analyze each type of data separately. The numbers are analyzed statistically, while the interviews or observations are analyzed for themes or patterns.
3. Bring the two sets of results together to see if they align.

The researcher compares and combines the findings to see how they support, contradict, or deepen each other. This design is especially useful when you want a complete, well-rounded understanding of a problem—getting both the measurable facts and the human explanations all at once.

Grounded Theory

Grounded Theory is a qualitative research design used when a researcher wants to develop a new theory about how something works—based on real data collected from people’s experiences.Think of it as building a theory from the ground up, instead of starting with a theory and trying to prove it. Here’s how it works:

1. Collect data without a fixed theory in mind. The researcher interviews people, observes situations, or analyzes documents to understand a process, behavior, or experience.
2. Look for patterns and recurring ideas. As the researcher reviews the data, they highlight important phrases, actions, or explanations. These become “codes.”
3. Organize the codes into categories. As more data is collected, the researcher starts seeing relationships between ideas—like stages, causes, or conditions that shape the experience.
4. Develop a theory that explains the process. After comparing data again and again, the researcher builds a theory that shows how something happens and why.

Grounded Theory is like watching a bunch of puzzle pieces being poured onto a table. Instead of starting with the picture on the box, you examine the shapes, colors, and edges until a picture naturally forms. The theory you create is grounded in the real experiences of the people you studied.

Pragmatic Worldview

A pragmatic worldview is a way of thinking about research that focuses on what works best for answering the question—rather than sticking to one strict philosophy or method. Pragmatists aren’t concerned with whether reality has one truth (like positivists) or many truths (like constructivists). Instead, they care about solving problems, finding useful answers, and using whatever methods get the job done.Key Ideas:

1. “Use the method that works.” Pragmatists don’t believe any one method is superior. They choose quantitative, qualitative, or mixed methods depending on what will produce the most helpful results.
2. The research question comes first. A pragmatist starts by asking: “What am I trying to understand or solve?” Then they pick methods that fit the goal—kind of like choosing the right tool from a toolbox.
3. Truth is judged by usefulness. For pragmatists, something is “true” if it helps explain a problem or supports better decision-making, even if it isn’t perfect or final.
4. Real-world application matters. Pragmatists prefer research that: solves real problems; improves practice; helps people make better choices; has practical impact
5. Flexibility is a strength. Pragmatists might run surveys, conduct interviews, observe behavior, or combine methods—all in one study—if it leads to better insights.

Experimental Design

A true experiment tests cause-and-effect relationships by manipulating an independent variable and measuring its impact on a dependent variable. It is often considered the “gold standard” of research because it allows researchers to infer causality. Experiments can occur in laboratories or real-world settings.Key Features

• Manipulation: Researcher controls the treatment or intervention.
• Random assignment: Participants are randomly placed in either the experimental group (receives treatment) or control group (does not).
• Control: Random assignment helps eliminate outside factors, strengthening causal conclusions.

Example

• Researchers might test whether childcare subsidies increase maternal employment by randomly assigning some participants to receive subsidies and others not to.

Sampling

• Random sampling improves generalizability, though convenience sampling is still common.
• Participants are ideally randomly selected and assigned to reduce bias.

Sequential Exploratory Mixed Research Design

A Sequential Exploratory Mixed Research Design is a type of study where the researcher collects qualitative data first (the ideas, stories, or observations) and quantitative data second (the numbers), in order to build a deeper understanding of a topic. Here’s how it works:

1. Start with Qualitative Data (the deep exploration). You might interview people, observe a situation, or analyze open-ended responses. This helps you explore a topic, discover themes, or identify patterns you didn’t expect.
2. Then collect Quantitative Data (the numbers). After you understand the ideas from your qualitative phase, you design a survey, experiment, or measurement tool to test whether those ideas hold true for a larger group.
3. Finally, connect the two phases.

The quantitative results help you confirm, check, or expand on what you discovered earlier during the qualitative phase.Think of it like starting with a conversation to learn what people think, and then creating a questionnaire to see if many others think the same way. You begin by exploring, and then you measure.

Transformative Worldview

A transformative worldview is a way of thinking about research that focuses on social change, fairness, and giving a voice to groups who are often ignored or marginalized. Researchers who use this worldview believe that research should do more than just “observe” the world—it should help improve it. Key Ideas:

1. Research should challenge injustice. Transformative researchers study issues like inequality, discrimination, and power imbalances. They believe research can help expose unfair systems and support positive change.
2. The voices of marginalized groups matter. Instead of focusing on the most powerful or visible groups, transformative research listens closely to people who are often left out—such as minorities, people with disabilities, low-income communities, or other underrepresented groups.
3. The researcher works with the community, not on it. Transformative research is often collaborative. The researcher and participants work together to decide what to study, how to study it, and what solutions to propose.
4. Knowledge is connected to power. Transformative thinkers believe that the way we ask questions—and who gets to answer them—can either reinforce or challenge inequality.
5. The goal is real, meaningful change. The research is meant to inspire action—such as new policies, programs, resources, or awareness that improves people’s lives.

Constructivist Worldview

A constructivist worldview is a way of thinking about research that says people don’t just discover reality—they create or construct their own understanding of it based on their experiences, culture, and interactions with others.In other words, constructivists believe there isn’t just one truth. Instead, different people can experience the same situation in different ways—and all of those perspectives matter.Key Ideas:

1. Reality is shaped by people’s experiences. Unlike positivists (who look for one objective truth), constructivists think truth is personal and subjective. Two people can have totally different experiences of the same event—and both are valid.
2. The researcher is part of the process. The researcher doesn’t try to be a “neutral outsider.” Instead, they interact with participants and learn from them, almost like joining their world for a moment.
3. Focus on meaning, understanding, and interpretation. Constructivists want to know:
1. How do people make sense of this?
2. What does this experience mean to them?
3. How do their backgrounds shape their views?
4. Qualitative methods are often used. Because constructivists care about personal experiences and perspectives, they use interviews, observations, stories, and discussions to understand people’s viewpoints.
5. Multiple truths can exist at the same time. A constructivist researcher doesn’t try to find “the one correct answer,” but instead tries to understand the many ways people see the world.

Positivist Worldview

A positivist worldview is a way of thinking about research that believes the best way to understand the world is through objective facts, measurement, and scientific testing—kind of like how scientists study chemistry or physics.Positivists think that reality exists independently of our opinions, and that we can discover truth by observing it carefully and using tools like numbers, experiments, and statistics.Key Ideas:

1. There is a single, discoverable truth. Positivists believe that the world works in predictable ways, and if you study it scientifically, you can uncover the correct answers.
2. Research should be objective. This means the researcher should avoid letting their feelings or personal beliefs influence the study. Think: neutral scientist in a lab coat.
3. Use measurable, observable data. Positivists prefer things they can test, count, or measure—surveys, experiments, numerical data, tests, and statistics.
4. Cause and effect matter. They look for patterns and laws that explain how things work. A positivist wants to know things like:
1. “Does X cause Y?”
2. “If we change this variable, what happens?”
5. Experiments and quantitative methods are preferred.
6. Because they give clear, precise, and replicable answers.

Causal-Comparative Research Design

Causal-comparative research (also called ex post facto research) explores the causes or effects of events that have already happened. For example, researchers might study how a new diet has affected children who are already following it. This design is common in education, sociology, and health research. Researchers may use it to: a) Examine the effects of participating in a group; b) Explore the causes of participation in a group; c) Investigate the consequences of a change within a group.While this approach helps identify relationships between variables, it cannot prove causation because the researcher cannot control or manipulate the original event. Typical steps include:

• Identify a phenomenon and its possible causes or effects.
• Formulate a research problem and hypotheses.
• Select comparison groups.
• Match groups on relevant variables to control for differences.
• Choose instruments and collect data.
• Compare the groups to analyze results.

Causal-comparative studies are similar to correlational studies, but they compare two or more groups, often using categorical variables, while correlational studies measure relationships among variables within a single group.

Ethnography

An Ethnography is a type of qualitative research design where the researcher tries to understand a group of people by immersing themselves in that group’s everyday life. The goal is to learn about the group’s culture—its beliefs, behaviors, traditions, language, routines, and ways of thinking.Think of it like being a detective, but instead of solving a mystery, you’re trying to understand what life is really like inside a particular community. Here’s how it works:

1. Immerse yourself in the group or community. The researcher spends extended time with the group—weeks, months, or even longer—observing and sometimes participating in their daily activities.
2. Take detailed notes and gather data.They observe behaviors, listen to conversations, interview members, collect artifacts (like photos or documents), and write field notes to capture what they see and hear.
3. Look for cultural patterns. The researcher analyzes the data to discover what is important to the group—values, shared beliefs, routines, roles, and unspoken rules.
4. Describe the culture from the inside out. The final result is a rich, detailed account that helps readers understand the group’s worldview and the meaning behind their actions.

Imagine joining a school club, sports team, or online gaming community not just to participate, but to understand its culture—how people communicate, what they value, and what makes the group unique. That’s what ethnographers do, but with a lot of structure, observation, and analysis.

Embedded Mixed Research Design

An Embedded Mixed Research Design is a type of study where one kind of data—either qualitative (stories, ideas) or quantitative (numbers)—is the main focus of the research, and the other type is added in to “support” or “enhance” it.Think of it like a main dish with a side dish: one is the center of the meal, and the other helps make it better. Here’s how it works:

1. Choose a primary method. Some studies are mainly quantitative (surveys, experiments, statistics). Others are mainly qualitative (interviews, observations, open-ended responses). This primary method drives the study.
2. Add a secondary method inside the first one.The researcher includes a smaller set of the other type of data within the main method to help clarify, explain, or deepen understanding. For example:
1. In a mostly quantitative study, the researcher might add a few interviews to explain surprising survey results.
2. In a mostly qualitative study, the researcher might collect a small amount of numerical data to support or compare with themes.
3. Interpret the results together.

Even though the study has one main method, the extra “embedded” data helps strengthen the conclusions by giving more insight or evidence. Imagine you’re watching a movie (the main method) but also looking at behind-the-scenes clips (the embedded method) to better understand how the movie was made. The main story stays the same, but the extra details help you see the full picture.

Sequential Explanatory Mixed Research Design

A Sequential Explanatory Mixed Research Design is a research approach that uses both numbers and stories, but in a specific order to help a researcher deeply understand a problem. Here’s how it works:

1. First, you collect and analyze quantitative data — the numbers. This might include surveys with rating scales, test scores, or any data you can measure.
2. Then, you collect and analyze qualitative data — the explanations. This might involve interviews, open-ended questions, or observations that help you understand why the numbers look the way they do.
3. Finally, you connect the two sets of results to get a fuller picture. The ideas you discover from the qualitative phase help you explain or make sense of the patterns you found in the quantitative phase.

Think of it like this: You start by noticing what is happening (the numbers), and then you go talk to people to understand why it’s happening (the explanations). This design is especially helpful when you want strong, reliable data but also want the human story behind it.

Narrative Research Design

A Narrative qualitative research design is a way of doing research that focuses on people’s stories—the experiences they share, the events that shaped them, and the meanings they make from those events. Think of it like creating a detailed biography, but with a research purpose. Here’s how it works:

1. Start by collecting someone’s story. The researcher gathers information through interviews, journals, letters, conversations, or other personal materials. The goal is to understand someone’s life experience in their own words.
2. Look for key events, turning points, and themes. The researcher organizes the story so the important moments stand out—what happened, how it happened, and why it mattered to the person.
3. Re-tell the story with explanation and insight. The researcher helps put the pieces together, showing how the person’s experiences connect to a bigger question or issue. This is not just storytelling; it’s analysis.
4. Connect the individual story to the larger world.

Narrative research often shows how one person’s experience represents something bigger—such as how students overcome obstacles, how families adapt to change, or how someone’s identity develops over time.Imagine sitting down with someone and asking them to tell you the story of an important part of their life. Narrative research turns that story into a source of knowledge, helping us understand people more deeply and see the world through their eyes.

Factorial Design

A factorial design is an experimental research design that studies two or more independent variables (factors) at the same time to see how they individually and jointly affect a dependent variable.

• Each factor can have two or more levels (e.g., low/high, treatment/no treatment).
• Researchers can examine main effects (the impact of each factor alone) and interaction effects (how factors combine to influence outcomes).
• Factorial designs are efficient because they test multiple variables simultaneously rather than in separate experiments.

Example: A study tests how teaching method (lecture vs. interactive) and study time (short vs. long) each affect student performance—and whether the effect of study time depends on the teaching method.

Single-Case Design

A single-case (or single-subject) design focuses on one participant or a small group, measuring behavior or outcomes repeatedly over time. It is often used in psychology, education, and clinical research to evaluate interventions.

• The researcher observes a baseline (before treatment), applies an intervention, and continues observing to see if changes occur.
• This design shows whether the intervention directly affects the individual’s behavior.
• Common formats include AB, ABA, and multiple-baseline designs.

Example: A therapist measures a child’s disruptive behavior before, during, and after a behavioral intervention to determine if the treatment reduces incidents.

Case Study

A Case Study is a qualitative research design where the researcher takes an in-depth look at one specific case—usually a person, group, organization, event, program, or situation—to understand it deeply and in detail.Think of it like zooming in with a camera until you can see every important part of the subject. Here’s how it works:

1. Choose a “case” that is worth studying. This could be: one student, one classroom, one school club, one community event, one unique situation, etc. The case is selected because it’s meaningful or can teach us something important.
2. Collect lots of different types of data.The researcher gathers information through interviews, observations, documents, videos—whatever helps them understand the case from multiple angles.
3. Study the case deeply and holistically. Instead of focusing on just one part, the researcher examines the whole context: the people involved, the environment, the history, the challenges, and the outcomes.
4. Describe and analyze what makes the case important.

The researcher explains what happened, why it happened, and what we can learn from it. Sometimes the case even reveals patterns that could apply to similar situations elsewhere.Imagine investigating one student’s successful science project—not to judge it, but to understand how they worked, why they succeeded, and what others could learn from their process. That’s the heart of a Case Study: deep understanding of one real example.

Pre-Experimental Design

A basic, exploratory design used to test the potential effects of an intervention before a full experiment.

• No control group or random assignment
• Observes outcomes after a treatment
• Cannot confirm causation

Common types:

• One-shot case study – One group observed after treatment
• One-group pretest–posttest – Measured before and after treatment
• Static-group comparison – Two groups, only one receives treatment

Purpose: To test feasibility, pilot methods, or gather early data when full experimental control isn’t possible.

Quantitative Descriptive Research Design

This research design is suitable when you want to measure variables and identify associations between them. However, it cannot determine cause-and-effect relationships. Because this approach is observational, your role as the researcher is to observe and record, not to manipulate variables. Descriptive research is therefore often called an observational study. Common types include:

• Case study: Data are collected from a single subject.
• Case series: Data are gathered from several subjects.
• Cross-sectional study: Variables are analyzed within a sample at one point in time to identify non-causal relationships. Prospective (cohort or longitudinal) study: Variables are measured at the start of a study and outcomes are analyzed later—sometimes years afterward (e.g., studying diet and heart disease over 30 years).
• Case-control study: Researchers compare subjects with a specific trait to those without it; often called a retrospective study.

• Because the researcher only observes, a hypothesis may not be developed in advance. Instead, it often emerges after data collection and analysis.

Phenomenology & Phenomenography

Phenomenography is also a qualitative design, but it focuses on studying the different ways people understand or think about a phenomenon, not their lived emotional experience of it.Think of it as mapping the different perspectives people have about the same thing.How it works:

1. The researcher collects interviews, open-ended responses, or discussions about a topic (e.g., “What does good teamwork mean?” or “What does learning look like?”).
2. They look for the various ways people describe or make sense of the phenomenon.
3. The goal is to group these different understandings into categories.
4. Researchers show the range of how people think—not which one is correct.

In short:Phenomenography asks “What are the different ways people understand this?”

Phenomenology is a qualitative research design that focuses on understanding the deep, lived experiences of people.Researchers want to know: What is it like to experience this phenomenon?Think of it as trying to get inside someone’s mind to understand how they feel, think, and make sense of a specific experience. How it works:

1. The researcher interviews people who have personally experienced the phenomenon (e.g., anxiety before a big exam, losing a friend, learning a new la nguage).
2. They listen closely to the emotions, memories, and meanings people describe.
3. They identify the essential themes—what those experiences have in common.
4. The goal is to describe the essence of the experience, like a deep, emotional snapshot of what it means to live through it.

In short: Phenomenology asks “What is the experience like?”