Exploring 10 popular research designs: a quick guide

Dr Lynette Pretorius

Contact details

Dr Lynette Pretorius is an award-winning educator and researcher in the fields of academic language, literacy, research skills, and research methodologies. 

In research, the design chosen plays a pivotal role in determining how data are collected, analysed, and interpreted. Each design provides a unique lens through which researchers can explore their questions, offering distinct advantages and limitations. Below, I summarise ten common research designs, spanning qualitative, quantitative, and mixed methods approaches.

Action Research

Action research is a collaborative and iterative approach that seeks to solve real-world problems while simultaneously generating knowledge. Action research is characterised by its participatory nature, where researchers and participants collaborate to identify problems and implement solutions. This collaborative process ensures that the research is deeply rooted in the needs and realities of the community or organisation being studied. By involving stakeholders in every step, action research not only increases the relevance of the findings but also empowers participants by giving them ownership of the process. This makes it particularly impactful in settings like schools, where teachers and administrators can actively contribute to shaping educational practices.

What sets action research apart is its cyclical nature. Unlike traditional research, where data are collected and analysed in a linear fashion, action research involves continuous cycles of planning, acting, observing, and reflecting. Another important feature of action research is its adaptability. As new insights emerge, the research design can be adjusted to address unforeseen challenges or opportunities. This flexibility allows for iterative learning and continuous improvement, fostering a more dynamic and responsive research environment. This makes it particularly well-suited for environments where ongoing change is necessary, such as schools or businesses aiming to improve their operations or outcomes. However, this adaptability also introduces challenges, particularly in maintaining rigour and objectivity. Balancing the need for scientific validity with the practical demands of real-world problem-solving requires careful planning and reflective practice, often making the role of the researcher one of facilitator as much as investigator.

Autoethnography

I have previously written another blog post which explains autoethnography in detail. In essence, autoethnography is a research design that combines the study of personal experience with broader social and cultural analysis. In this approach, the researcher uses their own life as the primary source of data, reflecting on their personal experiences to explore larger cultural or societal issues. Researchers are the participants in their own studies and the stories which are told often explore transformative experiences for the researcher, frequently taking the form of epiphanies that significantly influenced the author’s worldview. By blending autobiography and ethnography, autoethnography allows researchers to provide an insider’s perspective on their own social context, making it a powerful tool for examining how individual identity and experiences are shaped by—and in turn, shape—cultural norms, values, and power dynamics.

One of the strengths of autoethnography is its ability to highlight marginalised voices or experiences that are often overlooked in traditional research. It provides a platform for self-reflection and critical analysis, allowing researchers to connect their individual stories to larger collective experiences. However, the highly personal nature of this research design also presents challenges. Balancing subjectivity with academic rigour requires careful reflection to avoid the research becoming overly introspective or self-indulgent. Autoethnographers must navigate the fine line between personal storytelling and scholarly analysis, ensuring that their narrative contributes meaningfully to the understanding of broader social or cultural issues. Despite these challenges, autoethnography remains a powerful approach for exploring the intersection of the personal and the political, offering rich, emotionally resonant insights into the complexities of human experience.

Note that autoethnography can be done by one researcher or by a group of researchers. When done together, this type of autoethnography is called collaborative autoethnography. Collaborative autoethnography is particularly pertinent when examining complex social phenomena, such as marginalisation and the pursuit of social justice, as it facilitates the inclusion of multiple perspectives and voices. In this way, the individual voices of the researchers work together to illuminate common themes or experiences.

Case Study

Case study research is particularly effective for exploring complex phenomena in depth and within their real-life context. The case study design focuses on an in-depth examination of a ‘case,’ which could be an individual, group, organisation, or event. Case studies can be either descriptive, exploring what is happening, or explanatory, seeking to understand why and how something occurs. They often use multiple data sources—such as interviews, observations, and documents—to provide a comprehensive understanding of the case. Unlike other designs that seek to generalise findings across large populations, case studies focus on the intricacies of a ‘case’. The depth of focus of a case study also presents limitations—namely, the findings from a single case may not be applicable to other contexts. Despite this, case studies are often used as a stepping stone for further research, providing in-depth insights that can inform broader studies.

The distinction between single-case and multiple-case designs lies in the scope and focus of the research. A single-case design centres around an in-depth examination of one particular case, which is often chosen because it is either unique, critical, or illustrative of a broader phenomenon. This design is beneficial when the case is exceptional or offers significant insight into a rare or novel situation. In contrast, a multiple-case design involves studying several cases to compare and contrast findings across different contexts or instances. Multiple-case designs offer more robust evidence, as they allow researchers to identify patterns or variations across cases, increasing the potential for generalising findings to a broader population or set of circumstances.

Document or Policy Analysis

Document or policy analysis is a qualitative research design that involves systematically reviewing and interpreting existing documents to extract meaningful data relevant to a research question. These documents can range from government reports, personal letters, and organisational records to media articles, policy documents, and historical texts. It involves examining the formulation, implementation, and outcomes of documents or policies by analysing relevant data, understanding stakeholder perspectives, and evaluating the potential impacts of various options. Researchers use document analysis to identify patterns, themes, or trends within written materials, which can offer valuable insights into social, political, or organisational contexts. One of the strengths of document analysis is that it allows researchers to access data that is already available, making it a relatively unobtrusive approach that does not require direct interaction with participants.

This research design is particularly useful when studying past events, policies, or organisational practices, as documents can provide a rich historical or contextual backdrop. Additionally, document analysis can be used in conjunction with other research designs, such as case studies, to triangulate findings and enhance the depth of the research. However, one of the challenges of this design is assessing the credibility, bias, or completeness of the documents. Researchers must critically evaluate the sources to ensure that the information is reliable and relevant to their study. Despite these challenges, document analysis remains a valuable tool for exploring existing written records and uncovering insights that may not be easily accessible through other research designs.

Ethnography

Ethnography is a deeply immersive research design that involves the researcher becoming part of the community or environment they are studying. This approach allows researchers to gather first-hand insights into the social dynamics, practices, and beliefs of a group from the inside. Rather than relying on external observation or second-hand accounts, ethnographers immerse themselves among their participants, often for extended periods. This enables them to capture the complexities of human behaviour in its natural setting, offering a nuanced understanding of cultural practices and social interactions.

One of the unique aspects of ethnography is its emphasis on the participants’ perspectives. By prioritising the voices and experiences of the people being studied, ethnographers aim to represent the world as seen through the eyes of the participants. However, this approach also raises challenges, particularly around maintaining objectivity and managing the researcher’s role in influencing the group they are observing. Ethnography requires careful ethical considerations, such as gaining informed consent and respecting privacy, given the often intimate nature of the research. Despite these challenges, the rich, contextual insights that ethnography provides make it a powerful approach for understanding the lived experiences of individuals within their cultural and social environments.

Experimental and Quasi-Experimental Design

Experimental research is a highly controlled design that seeks to establish cause-and-effect relationships by manipulating one or more independent variables and observing their impact on dependent variables. This research design typically involves two groups: an experimental group that receives the treatment or intervention and a control group that does not. By randomly assigning participants to these groups, researchers can minimise bias and ensure that differences in outcomes are directly attributable to the variable being tested, rather than external factors. This randomisation strengthens the internal validity of the experiment.

Quasi-experimental designs are similar to experimental research but differ in one key aspect: they lack the random assignment of participants to experimental and control groups. In cases where randomisation is either impractical or unethical—such as in educational settings or when studying pre-existing groups—quasi-experimental designs provide a valuable alternative. While researchers still manipulate an independent variable and observe its effect on a dependent variable, the absence of randomisation means that there may be pre-existing differences between groups. As a result, researchers must account for these differences when analysing the outcomes, often using statistical methods to control for confounding variables.

Grounded Theory

Grounded theory is a qualitative research design designed to generate theory directly from the data rather than testing an existing hypothesis or using a pre-existing theoretical framework. Unlike more traditional research approaches, grounded theory allows the theory to emerge naturally through the iterative process of data collection and analysis. Researchers continuously compare new data with previously gathered information. This ongoing comparison enables them to identify recurring patterns, concepts, and categories, which are then refined into a coherent theoretical framework. Grounded theory is particularly useful when studying processes, interactions, or behaviours where existing theories do not exist or may not fully explain the phenomena.

One of the major advantages of grounded theory is its flexibility. Since it does not require researchers to adhere to a rigid hypothesis or framework from the start, the design allows for the exploration of unexpected insights that may arise during data collection. This makes it a powerful approach for investigating complex or under-researched topics. However, the open-ended nature of grounded theory can also be a challenge, as it requires researchers to be highly reflexive and adaptable throughout the research process. The absence of a pre-set framework means that analysis can be time-consuming, with researchers needing to sift through large amounts of data to construct a meaningful theory that adequately reflects the participants’ experiences and emerging patterns.

Narrative Inquiry

Narrative inquiry is a qualitative research design that focuses on the stories people tell about their personal experiences, aiming to understand how individuals construct meaning in their lives. Unlike other research approaches that may prioritise external observation or objective measurement, narrative inquiry dives into the subjective world of the participant. Researchers collect these narratives through interviews, journals, letters, or even autobiographies, and analyse how individuals structure their stories to make sense of their experiences. This approach is particularly useful in fields where understanding personal identity, life transitions, or cultural contexts requires a close examination of how people frame and interpret their lived experiences.

A key feature of narrative inquiry is its emphasis on the co-construction of meaning between the researcher and the participant. The researcher does not just passively collect stories but actively engages in dialogue, interpreting the narratives while considering how their own perspectives and biases influence the analysis. This collaborative process allows for a richer understanding of the subject matter but also demands a high level of reflexivity from the researcher. Since narratives are shaped by memory, culture, and social influences, researchers must carefully navigate issues of subjectivity, ensuring that the participant’s voice is authentically represented while also providing a critical analysis of how the story fits within broader social or cultural patterns.

Phenomenology

Phenomenology is a qualitative research design that seeks to explore and understand individuals’ lived experiences of a particular phenomenon. Rather than focusing on objective measures or external observations, phenomenology prioritises subjective experience, aiming to uncover the essence of how people perceive, interpret, and make sense of their experiences. Researchers using this design typically collect data through a variety of in-depth methods such as interviews or reflections, allowing participants to describe their personal encounters with the phenomenon in their own words. The goal is to view the experience as closely as possible through the eyes of the individuals who lived it, capturing its richness and complexity without external influence.

While this research design provides deep insights into human consciousness and subjective experience, it can be challenging to generalise the findings due to the intensely personal nature of the data. Nevertheless, phenomenology’s strength lies in its ability to provide a profound, context-rich understanding of how individuals uniquely experience and interpret specific aspects of life, making it invaluable for exploring complex, emotionally charged, or abstract phenomena.

Survey Research

Survey research is a widely utilised design in both quantitative and qualitative research that involves gathering data from a large group of respondents, typically through structured questionnaires. This approach is highly versatile, allowing researchers to collect information about a wide range of topics, including attitudes, behaviours, preferences, and demographic characteristics. One of the main advantages of survey research is its ability to gather data from a broad population efficiently, making it possible to identify trends, correlations, or patterns within large datasets. Surveys can be administered in various formats, such as online, by phone, or in person, providing flexibility in how researchers reach their target audience.

However, the quality and reliability of the data collected through surveys depend heavily on the survey’s design. Well-constructed surveys require carefully worded questions that avoid bias and confusion, and they must be designed to ensure that respondents understand and can accurately answer the questions. Another challenge is ensuring a high response rate, as low participation can skew results and affect the study’s representativeness. Despite these limitations, survey research remains a powerful tool in fields like marketing, social sciences, public health, and education, where large-scale data collection is necessary to inform policies, identify trends, or make generalisations about a population’s characteristics or behaviours.

You can also learn more about research designs and methods by watching the videos below.

Questions to ponder

How does the nature of the research question influence the decision to use a particular research design?

How do ethical concerns shape the choice of research design?

What types of research questions are best suited for case study research, and how do these differ from questions better addressed through autoethnography?