qualitative research words examples

18 Qualitative Research Examples

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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qualitative research examples and definition, explained below

Qualitative research is an approach to scientific research that involves using observation to gather and analyze non-numerical, in-depth, and well-contextualized datasets.

It serves as an integral part of academic, professional, and even daily decision-making processes (Baxter & Jack, 2008).

Methods of qualitative research encompass a wide range of techniques, from in-depth personal encounters, like ethnographies (studying cultures in-depth) and autoethnographies (examining one’s own cultural experiences), to collection of diverse perspectives on topics through methods like interviewing focus groups (gatherings of individuals to discuss specific topics).

Qualitative Research Examples

1. ethnography.

Definition: Ethnography is a qualitative research design aimed at exploring cultural phenomena. Rooted in the discipline of anthropology , this research approach investigates the social interactions, behaviors, and perceptions within groups, communities, or organizations.

Ethnographic research is characterized by extended observation of the group, often through direct participation, in the participants’ environment. An ethnographer typically lives with the study group for extended periods, intricately observing their everyday lives (Khan, 2014).

It aims to present a complete, detailed and accurate picture of the observed social life, rituals, symbols, and values from the perspective of the study group.


The key advantage of ethnography is its depth; it provides an in-depth understanding of the group’s behaviour, lifestyle, culture, and context. It also allows for flexibility, as researchers can adapt their approach based on their observations (Bryman, 2015)	There are issues regarding the subjective interpretation of data, and it’s time-consuming. It also requires the researchers to immerse themselves in the study environment, which might not always be feasible.

Example of Ethnographic Research

Title: “ The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity “

Citation: Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Overview: This study by Evans (2010) provides a rich narrative of young adult male identity as experienced in everyday life. The author immersed himself among a group of young men, participating in their activities and cultivating a deep understanding of their lifestyle, values, and motivations. This research exemplified the ethnographic approach, revealing complexities of the subjects’ identities and societal roles, which could hardly be accessed through other qualitative research designs.

Read my Full Guide on Ethnography Here

2. Autoethnography

Definition: Autoethnography is an approach to qualitative research where the researcher uses their own personal experiences to extend the understanding of a certain group, culture, or setting. Essentially, it allows for the exploration of self within the context of social phenomena.

Unlike traditional ethnography, which focuses on the study of others, autoethnography turns the ethnographic gaze inward, allowing the researcher to use their personal experiences within a culture as rich qualitative data (Durham, 2019).

The objective is to critically appraise one’s personal experiences as they navigate and negotiate cultural, political, and social meanings. The researcher becomes both the observer and the participant, intertwining personal and cultural experiences in the research.


One of the chief benefits of autoethnography is its ability to bridge the gap between researchers and audiences by using relatable experiences. It can also provide unique and profound insights unaccessible through traditional ethnographic approaches (Heinonen, 2012).	The subjective nature of this method can introduce bias. Critics also argue that the singular focus on personal experience may limit the contributions to broader cultural or social understanding.

Example of Autoethnographic Research

Title: “ A Day In The Life Of An NHS Nurse “

Citation: Osben, J. (2019). A day in the life of a NHS nurse in 21st Century Britain: An auto-ethnography. The Journal of Autoethnography for Health & Social Care. 1(1).

Overview: This study presents an autoethnography of a day in the life of an NHS nurse (who, of course, is also the researcher). The author uses the research to achieve reflexivity, with the researcher concluding: “Scrutinising my practice and situating it within a wider contextual backdrop has compelled me to significantly increase my level of scrutiny into the driving forces that influence my practice.”

Read my Full Guide on Autoethnography Here

3. Semi-Structured Interviews

Definition: Semi-structured interviews stand as one of the most frequently used methods in qualitative research. These interviews are planned and utilize a set of pre-established questions, but also allow for the interviewer to steer the conversation in other directions based on the responses given by the interviewee.

In semi-structured interviews, the interviewer prepares a guide that outlines the focal points of the discussion. However, the interview is flexible, allowing for more in-depth probing if the interviewer deems it necessary (Qu, & Dumay, 2011). This style of interviewing strikes a balance between structured ones which might limit the discussion, and unstructured ones, which could lack focus.


The main advantage of semi-structured interviews is their flexibility, allowing for exploration of unexpected topics that arise during the interview. It also facilitates the collection of robust, detailed data from participants’ perspectives (Smith, 2015).	Potential downsides include the possibility of data overload, periodic difficulties in analysis due to varied responses, and the fact they are time-consuming to conduct and analyze.

Example of Semi-Structured Interview Research

Title: “ Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review “

Citation: Puts, M., et al. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Overview: Puts et al. (2014) executed an extensive systematic review in which they conducted semi-structured interviews with older adults suffering from cancer to examine the factors influencing their adherence to cancer treatment. The findings suggested that various factors, including side effects, faith in healthcare professionals, and social support have substantial impacts on treatment adherence. This research demonstrates how semi-structured interviews can provide rich and profound insights into the subjective experiences of patients.

4. Focus Groups

Definition: Focus groups are a qualitative research method that involves organized discussion with a selected group of individuals to gain their perspectives on a specific concept, product, or phenomenon. Typically, these discussions are guided by a moderator.

During a focus group session, the moderator has a list of questions or topics to discuss, and participants are encouraged to interact with each other (Morgan, 2010). This interactivity can stimulate more information and provide a broader understanding of the issue under scrutiny. The open format allows participants to ask questions and respond freely, offering invaluable insights into attitudes, experiences, and group norms.


One of the key advantages of focus groups is their ability to deliver a rich understanding of participants’ experiences and beliefs. They can be particularly beneficial in providing a diverse range of perspectives and opening up new areas for exploration (Doody, Slevin, & Taggart, 2013).	Potential disadvantages include possible domination by a single participant, groupthink, or issues with confidentiality. Additionally, the results are not easily generalizable to a larger population due to the small sample size.

Example of Focus Group Research

Title: “ Perspectives of Older Adults on Aging Well: A Focus Group Study “

Citation: Halaweh, H., Dahlin-Ivanoff, S., Svantesson, U., & Willén, C. (2018). Perspectives of older adults on aging well: a focus group study. Journal of aging research .

Overview: This study aimed to explore what older adults (aged 60 years and older) perceived to be ‘aging well’. The researchers identified three major themes from their focus group interviews: a sense of well-being, having good physical health, and preserving good mental health. The findings highlight the importance of factors such as positive emotions, social engagement, physical activity, healthy eating habits, and maintaining independence in promoting aging well among older adults.

5. Phenomenology

Definition: Phenomenology, a qualitative research method, involves the examination of lived experiences to gain an in-depth understanding of the essence or underlying meanings of a phenomenon.

The focus of phenomenology lies in meticulously describing participants’ conscious experiences related to the chosen phenomenon (Padilla-Díaz, 2015).

In a phenomenological study, the researcher collects detailed, first-hand perspectives of the participants, typically via in-depth interviews, and then uses various strategies to interpret and structure these experiences, ultimately revealing essential themes (Creswell, 2013). This approach focuses on the perspective of individuals experiencing the phenomenon, seeking to explore, clarify, and understand the meanings they attach to those experiences.


An advantage of phenomenology is its potential to reveal rich, complex, and detailed understandings of human experiences in a way other research methods cannot. It encourages explorations of deep, often abstract or intangible aspects of human experiences (Bevan, 2014).	Phenomenology might be criticized for its subjectivity, the intense effort required during data collection and analysis, and difficulties in replicating the study.

Example of Phenomenology Research

Title: “ A phenomenological approach to experiences with technology: current state, promise, and future directions for research ”

Citation: Cilesiz, S. (2011). A phenomenological approach to experiences with technology: Current state, promise, and future directions for research. Educational Technology Research and Development, 59 , 487-510.

Overview: A phenomenological approach to experiences with technology by Sebnem Cilesiz represents a good starting point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

6. Grounded Theory

Definition: Grounded theory is a systematic methodology in qualitative research that typically applies inductive reasoning . The primary aim is to develop a theoretical explanation or framework for a process, action, or interaction grounded in, and arising from, empirical data (Birks & Mills, 2015).

In grounded theory, data collection and analysis work together in a recursive process. The researcher collects data, analyses it, and then collects more data based on the evolving understanding of the research context. This ongoing process continues until a comprehensive theory that represents the data and the associated phenomenon emerges – a point known as theoretical saturation (Charmaz, 2014).


An advantage of grounded theory is its ability to generate a theory that is closely related to the reality of the persons involved. It permits flexibility and can facilitate a deep understanding of complex processes in their natural contexts (Glaser & Strauss, 1967).	Critics note that it can be a lengthy and complicated process; others critique the emphasis on theory development over descriptive detail.

Example of Grounded Theory Research

Title: “ Student Engagement in High School Classrooms from the Perspective of Flow Theory “

Citation: Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158–176.

Overview: Shernoff and colleagues (2003) used grounded theory to explore student engagement in high school classrooms. The researchers collected data through student self-reports, interviews, and observations. Key findings revealed that academic challenge, student autonomy, and teacher support emerged as the most significant factors influencing students’ engagement, demonstrating how grounded theory can illuminate complex dynamics within real-world contexts.

7. Narrative Research

Definition: Narrative research is a qualitative research method dedicated to storytelling and understanding how individuals experience the world. It focuses on studying an individual’s life and experiences as narrated by that individual (Polkinghorne, 2013).

In narrative research, the researcher collects data through methods such as interviews, observations , and document analysis. The emphasis is on the stories told by participants – narratives that reflect their experiences, thoughts, and feelings.

These stories are then interpreted by the researcher, who attempts to understand the meaning the participant attributes to these experiences (Josselson, 2011).


The strength of narrative research is its ability to provide a deep, holistic, and rich understanding of an individual’s experiences over time. It is well-suited to capturing the complexities and intricacies of human lives and their contexts (Leiblich, Tuval-Mashiach, & Zilber, 2008).	Narrative research may be criticized for its highly interpretive nature, the potential challenges of ensuring reliability and validity, and the complexity of narrative analysis.

Example of Narrative Research

Title: “Narrative Structures and the Language of the Self”

Citation: McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative . American Psychological Association.

Overview: In this innovative study, McAdams et al. (2006) employed narrative research to explore how individuals construct their identities through the stories they tell about themselves. By examining personal narratives, the researchers discerned patterns associated with characters, motivations, conflicts, and resolutions, contributing valuable insights about the relationship between narrative and individual identity.

8. Case Study Research

Definition: Case study research is a qualitative research method that involves an in-depth investigation of a single instance or event: a case. These ‘cases’ can range from individuals, groups, or entities to specific projects, programs, or strategies (Creswell, 2013).

The case study method typically uses multiple sources of information for comprehensive contextual analysis. It aims to explore and understand the complexity and uniqueness of a particular case in a real-world context (Merriam & Tisdell, 2015). This investigation could result in a detailed description of the case, a process for its development, or an exploration of a related issue or problem.


Case study research is ideal for a holistic, in-depth investigation, making complex phenomena understandable and allowing for the exploration of contexts and activities where it is not feasible to use other research methods (Crowe et al., 2011).	Critics of case study research often cite concerns about the representativeness of a single case, the limited ability to generalize findings, and potential bias in data collection and interpretation.

Example of Case Study Research

Title: “ Teacher’s Role in Fostering Preschoolers’ Computational Thinking: An Exploratory Case Study “

Citation: Wang, X. C., Choi, Y., Benson, K., Eggleston, C., & Weber, D. (2021). Teacher’s role in fostering preschoolers’ computational thinking: An exploratory case study. Early Education and Development , 32 (1), 26-48.

Overview: This study investigates the role of teachers in promoting computational thinking skills in preschoolers. The study utilized a qualitative case study methodology to examine the computational thinking scaffolding strategies employed by a teacher interacting with three preschoolers in a small group setting. The findings highlight the importance of teachers’ guidance in fostering computational thinking practices such as problem reformulation/decomposition, systematic testing, and debugging.

Read about some Famous Case Studies in Psychology Here

9. Participant Observation

Definition: Participant observation has the researcher immerse themselves in a group or community setting to observe the behavior of its members. It is similar to ethnography, but generally, the researcher isn’t embedded for a long period of time.

The researcher, being a participant, engages in daily activities, interactions, and events as a way of conducting a detailed study of a particular social phenomenon (Kawulich, 2005).

The method involves long-term engagement in the field, maintaining detailed records of observed events, informal interviews, direct participation, and reflexivity. This approach allows for a holistic view of the participants’ lived experiences, behaviours, and interactions within their everyday environment (Dewalt, 2011).


A key strength of participant observation is its capacity to offer intimate, nuanced insights into social realities and practices directly from the field. It allows for broader context understanding, emotional insights, and a constant iterative process (Mulhall, 2003).	The method may present challenges including potential observer bias, the difficulty in ensuring ethical standards, and the risk of ‘going native’, where the boundary between being a participant and researcher blurs.

Example of Participant Observation Research

Title: Conflict in the boardroom: a participant observation study of supervisory board dynamics

Citation: Heemskerk, E. M., Heemskerk, K., & Wats, M. M. (2017). Conflict in the boardroom: a participant observation study of supervisory board dynamics. Journal of Management & Governance , 21 , 233-263.

Overview: This study examined how conflicts within corporate boards affect their performance. The researchers used a participant observation method, where they actively engaged with 11 supervisory boards and observed their dynamics. They found that having a shared understanding of the board’s role called a common framework, improved performance by reducing relationship conflicts, encouraging task conflicts, and minimizing conflicts between the board and CEO.

10. Non-Participant Observation

Definition: Non-participant observation is a qualitative research method in which the researcher observes the phenomena of interest without actively participating in the situation, setting, or community being studied.

This method allows the researcher to maintain a position of distance, as they are solely an observer and not a participant in the activities being observed (Kawulich, 2005).

During non-participant observation, the researcher typically records field notes on the actions, interactions, and behaviors observed , focusing on specific aspects of the situation deemed relevant to the research question.

This could include verbal and nonverbal communication , activities, interactions, and environmental contexts (Angrosino, 2007). They could also use video or audio recordings or other methods to collect data.


Non-participant observation can increase distance from the participants and decrease researcher bias, as the observer does not become involved in the community or situation under study (Jorgensen, 2015). This method allows for a more detached and impartial view of practices, behaviors, and interactions.	Criticisms of this method include potential observer effects, where individuals may change their behavior if they know they are being observed, and limited contextual understanding, as observers do not participate in the setting’s activities.

Example of Non-Participant Observation Research

Title: Mental Health Nurses’ attitudes towards mental illness and recovery-oriented practice in acute inpatient psychiatric units: A non-participant observation study

Citation: Sreeram, A., Cross, W. M., & Townsin, L. (2023). Mental Health Nurses’ attitudes towards mental illness and recovery‐oriented practice in acute inpatient psychiatric units: A non‐participant observation study. International Journal of Mental Health Nursing .

Overview: This study investigated the attitudes of mental health nurses towards mental illness and recovery-oriented practice in acute inpatient psychiatric units. The researchers used a non-participant observation method, meaning they observed the nurses without directly participating in their activities. The findings shed light on the nurses’ perspectives and behaviors, providing valuable insights into their attitudes toward mental health and recovery-focused care in these settings.

11. Content Analysis

Definition: Content Analysis involves scrutinizing textual, visual, or spoken content to categorize and quantify information. The goal is to identify patterns, themes, biases, or other characteristics (Hsieh & Shannon, 2005).

Content Analysis is widely used in various disciplines for a multitude of purposes. Researchers typically use this method to distill large amounts of unstructured data, like interview transcripts, newspaper articles, or social media posts, into manageable and meaningful chunks.

When wielded appropriately, Content Analysis can illuminate the density and frequency of certain themes within a dataset, provide insights into how specific terms or concepts are applied contextually, and offer inferences about the meanings of their content and use (Duriau, Reger, & Pfarrer, 2007).


The application of Content Analysis offers several strengths, chief among them being the ability to gain an in-depth, contextualized, understanding of a range of texts – both written and multimodal (Gray, Grove, & Sutherland, 2017) – see also: .	Content analysis is dependent on the descriptors that the researcher selects to examine the data, potentially leading to bias. Moreover, this method may also lose sight of the wider social context, which can limit the depth of the analysis (Krippendorff, 2013).

Example of Content Analysis

Title: Framing European politics: A content analysis of press and television news .

Citation: Semetko, H. A., & Valkenburg, P. M. (2000). Framing European politics: A content analysis of press and television news. Journal of Communication, 50 (2), 93-109.

Overview: This study analyzed press and television news articles about European politics using a method called content analysis. The researchers examined the prevalence of different “frames” in the news, which are ways of presenting information to shape audience perceptions. They found that the most common frames were attribution of responsibility, conflict, economic consequences, human interest, and morality.

Read my Full Guide on Content Analysis Here

12. Discourse Analysis

Definition: Discourse Analysis, a qualitative research method, interprets the meanings, functions, and coherence of certain languages in context.

Discourse analysis is typically understood through social constructionism, critical theory , and poststructuralism and used for understanding how language constructs social concepts (Cheek, 2004).

Discourse Analysis offers great breadth, providing tools to examine spoken or written language, often beyond the level of the sentence. It enables researchers to scrutinize how text and talk articulate social and political interactions and hierarchies.

Insight can be garnered from different conversations, institutional text, and media coverage to understand how topics are addressed or framed within a specific social context (Jorgensen & Phillips, 2002).


Discourse Analysis presents as its strength the ability to explore the intricate relationship between language and society. It goes beyond mere interpretation of content and scrutinizes the power dynamics underlying discourse. Furthermore, it can also be beneficial in discovering hidden meanings and uncovering marginalized voices (Wodak & Meyer, 2015).	Despite its strengths, Discourse Analysis possesses specific weaknesses. This approach may be open to allegations of subjectivity due to its interpretive nature. Furthermore, it can be quite time-consuming and requires the researcher to be familiar with a wide variety of theoretical and analytical frameworks (Parker, 2014).

Example of Discourse Analysis

Title: The construction of teacher identities in educational policy documents: A critical discourse analysis

Citation: Thomas, S. (2005). The construction of teacher identities in educational policy documents: A critical discourse analysis. Critical Studies in Education, 46 (2), 25-44.

Overview: The author examines how an education policy in one state of Australia positions teacher professionalism and teacher identities. While there are competing discourses about professional identity, the policy framework privileges a narrative that frames the ‘good’ teacher as one that accepts ever-tightening control and regulation over their professional practice.

Read my Full Guide on Discourse Analysis Here

13. Action Research

Definition: Action Research is a qualitative research technique that is employed to bring about change while simultaneously studying the process and results of that change.

This method involves a cyclical process of fact-finding, action, evaluation, and reflection (Greenwood & Levin, 2016).

Typically, Action Research is used in the fields of education, social sciences , and community development. The process isn’t just about resolving an issue but also developing knowledge that can be used in the future to address similar or related problems.

The researcher plays an active role in the research process, which is normally broken down into four steps:

developing a plan to improve what is currently being done
implementing the plan
observing the effects of the plan, and
reflecting upon these effects (Smith, 2010).


Action Research has the immense strength of enabling practitioners to address complex situations in their professional context. By fostering reflective practice, it ignites individual and organizational learning. Furthermore, it provides a robust way to bridge the theory-practice divide and can lead to the development of best practices (Zuber-Skerritt, 2019).	Action Research requires a substantial commitment of time and effort. Also, the participatory nature of this research can potentially introduce bias, and its iterative nature can blur the line between where the research process ends and where the implementation begins (Koshy, Koshy, & Waterman, 2010).

Example of Action Research

Title: Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing

Citation: Ellison, M., & Drew, C. (2020). Using digital sandbox gaming to improve creativity within boys’ writing. Journal of Research in Childhood Education , 34 (2), 277-287.

Overview: This was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Read my Full Guide on Action Research Here

14. Semiotic Analysis

Definition: Semiotic Analysis is a qualitative method of research that interprets signs and symbols in communication to understand sociocultural phenomena. It stems from semiotics, the study of signs and symbols and their use or interpretation (Chandler, 2017).

In a Semiotic Analysis, signs (anything that represents something else) are interpreted based on their significance and the role they play in representing ideas.

This type of research often involves the examination of images, sounds, and word choice to uncover the embedded sociocultural meanings. For example, an advertisement for a car might be studied to learn more about societal views on masculinity or success (Berger, 2010).


The prime strength of the Semiotic Analysis lies in its ability to reveal the underlying ideologies within cultural symbols and messages. It helps to break down complex phenomena into manageable signs, yielding powerful insights about societal values, identities, and structures (Mick, 1986).	On the downside, because Semiotic Analysis is primarily interpretive, its findings may heavily rely on the particular theoretical lens and personal bias of the researcher. The ontology of signs and meanings can also be inherently subject to change, in the analysis (Lannon & Cooper, 2012).

Example of Semiotic Research

Title: Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia

Citation: Symes, C. (2023). Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia. Semiotica , 2023 (250), 167-190.

Overview: This study examines school badges in New South Wales, Australia, and explores their significance through a semiotic analysis. The badges, which are part of the school’s visual identity, are seen as symbolic representations that convey meanings. The analysis reveals that these badges often draw on heraldic models, incorporating elements like colors, names, motifs, and mottoes that reflect local culture and history, thus connecting students to their national identity. Additionally, the study highlights how some schools have shifted from traditional badges to modern logos and slogans, reflecting a more business-oriented approach.

15. Qualitative Longitudinal Studies

Definition: Qualitative Longitudinal Studies are a research method that involves repeated observation of the same items over an extended period of time.

Unlike a snapshot perspective, this method aims to piece together individual histories and examine the influences and impacts of change (Neale, 2019).

Qualitative Longitudinal Studies provide an in-depth understanding of change as it happens, including changes in people’s lives, their perceptions, and their behaviors.

For instance, this method could be used to follow a group of students through their schooling years to understand the evolution of their learning behaviors and attitudes towards education (Saldaña, 2003).


One key strength of Qualitative Longitudinal Studies is its ability to capture change and continuity over time. It allows for an in-depth understanding of individuals or context evolution. Moreover, it provides unique insights into the temporal ordering of events and experiences (Farrall, 2006).	Qualitative Longitudinal Studies come with their own share of weaknesses. Mainly, they require a considerable investment of time and resources. Moreover, they face the challenges of attrition (participants dropping out of the study) and repeated measures that may influence participants’ behaviors (Saldaña, 2014).

Example of Qualitative Longitudinal Research

Title: Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study

Citation: Hackett, J., Godfrey, M., & Bennett, M. I. (2016). Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study. Palliative medicine , 30 (8), 711-719.

Overview: This article examines how patients and their caregivers manage pain in advanced cancer through a qualitative longitudinal study. The researchers interviewed patients and caregivers at two different time points and collected audio diaries to gain insights into their experiences, making this study longitudinal.

Read my Full Guide on Longitudinal Research Here

16. Open-Ended Surveys

Definition: Open-Ended Surveys are a type of qualitative research method where respondents provide answers in their own words. Unlike closed-ended surveys, which limit responses to predefined options, open-ended surveys allow for expansive and unsolicited explanations (Fink, 2013).

Open-ended surveys are commonly used in a range of fields, from market research to social studies. As they don’t force respondents into predefined response categories, these surveys help to draw out rich, detailed data that might uncover new variables or ideas.

For example, an open-ended survey might be used to understand customer opinions about a new product or service (Lavrakas, 2008).

Contrast this to a quantitative closed-ended survey, like a Likert scale, which could theoretically help us to come up with generalizable data but is restricted by the questions on the questionnaire, meaning new and surprising data and insights can’t emerge from the survey results in the same way.


The key advantage of Open-Ended Surveys is their ability to generate in-depth, nuanced data that allow for a rich, . They provide a more personalized response from participants, and they may uncover areas of investigation that the researchers did not previously consider (Sue & Ritter, 2012).	Open-Ended Surveys require significant time and effort to analyze due to the variability of responses. Furthermore, the results obtained from Open-Ended Surveys can be more susceptible to subjective interpretation and may lack statistical generalizability (Fielding & Fielding, 2008).

Example of Open-Ended Survey Research

Title: Advantages and disadvantages of technology in relationships: Findings from an open-ended survey

Citation: Hertlein, K. M., & Ancheta, K. (2014). Advantages and disadvantages of technology in relationships: Findings from an open-ended survey. The Qualitative Report , 19 (11), 1-11.

Overview: This article examines the advantages and disadvantages of technology in couple relationships through an open-ended survey method. Researchers analyzed responses from 410 undergraduate students to understand how technology affects relationships. They found that technology can contribute to relationship development, management, and enhancement, but it can also create challenges such as distancing, lack of clarity, and impaired trust.

17. Naturalistic Observation

Definition: Naturalistic Observation is a type of qualitative research method that involves observing individuals in their natural environments without interference or manipulation by the researcher.

Naturalistic observation is often used when conducting research on behaviors that cannot be controlled or manipulated in a laboratory setting (Kawulich, 2005).

It is frequently used in the fields of psychology, sociology, and anthropology. For instance, to understand the social dynamics in a schoolyard, a researcher could spend time observing the children interact during their recess, noting their behaviors, interactions, and conflicts without imposing their presence on the children’s activities (Forsyth, 2010).


The predominant strength of Naturalistic Observation lies in : it allows the behavior of interest to be studied in the conditions under which it normally occurs. This method can also lead to the discovery of new behavioral patterns or phenomena not previously revealed in experimental research (Barker, Pistrang, & Elliott, 2016).	The observer may have difficulty avoiding subjective interpretations and biases of observed behaviors. Additionally, it may be very time-consuming, and the presence of the observer, even if unobtrusive, may influence the behavior of those being observed (Rosenbaum, 2017).

Example of Naturalistic Observation Research

Title: Dispositional mindfulness in daily life: A naturalistic observation study

Citation: Kaplan, D. M., Raison, C. L., Milek, A., Tackman, A. M., Pace, T. W., & Mehl, M. R. (2018). Dispositional mindfulness in daily life: A naturalistic observation study. PloS one , 13 (11), e0206029.

Overview: In this study, researchers conducted two studies: one exploring assumptions about mindfulness and behavior, and the other using naturalistic observation to examine actual behavioral manifestations of mindfulness. They found that trait mindfulness is associated with a heightened perceptual focus in conversations, suggesting that being mindful is expressed primarily through sharpened attention rather than observable behavioral or social differences.

Read my Full Guide on Naturalistic Observation Here

18. Photo-Elicitation

Definition: Photo-elicitation utilizes photographs as a means to trigger discussions and evoke responses during interviews. This strategy aids in bringing out topics of discussion that may not emerge through verbal prompting alone (Harper, 2002).

Traditionally, Photo-Elicitation has been useful in various fields such as education, psychology, and sociology. The method involves the researcher or participants taking photographs, which are then used as prompts for discussion.

For instance, a researcher studying urban environmental issues might invite participants to photograph areas in their neighborhood that they perceive as environmentally detrimental, and then discuss each photo in depth (Clark-Ibáñez, 2004).


Photo-Elicitation boasts of its ability to facilitate dialogue that may not arise through conventional interview methods. As a visual catalyst, it can support interviewees in articulating their experiences and emotions, potentially resulting in the generation of rich and insightful data (Heisley & Levy, 1991).	There are some limitations with Photo-Elicitation. Interpretation of the images can be highly subjective and might be influenced by cultural and personal variables. Additionally, ethical concerns may arise around privacy and consent, particularly when photographing individuals (Van Auken, Frisvoll, & Stewart, 2010).

Example of Photo-Elicitation Research

Title: Early adolescent food routines: A photo-elicitation study

Citation: Green, E. M., Spivak, C., & Dollahite, J. S. (2021). Early adolescent food routines: A photo-elicitation study. Appetite, 158 .

Overview: This study focused on early adolescents (ages 10-14) and their food routines. Researchers conducted in-depth interviews using a photo-elicitation approach, where participants took photos related to their food choices and experiences. Through analysis, the study identified various routines and three main themes: family, settings, and meals/foods consumed, revealing how early adolescents view and are influenced by their eating routines.

Features of Qualitative Research

Qualitative research is a research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

Some key features of this method include:

Naturalistic Inquiry: Qualitative research happens in the natural setting of the phenomena, aiming to understand “real world” situations (Patton, 2015). This immersion in the field or subject allows the researcher to gather a deep understanding of the subject matter.
Emphasis on Process: It aims to understand how events unfold over time rather than focusing solely on outcomes (Merriam & Tisdell, 2015). The process-oriented nature of qualitative research allows researchers to investigate sequences, timing, and changes.
Interpretive: It involves interpreting and making sense of phenomena in terms of the meanings people assign to them (Denzin & Lincoln, 2011). This interpretive element allows for rich, nuanced insights into human behavior and experiences.
Holistic Perspective: Qualitative research seeks to understand the whole phenomenon rather than focusing on individual components (Creswell, 2013). It emphasizes the complex interplay of factors, providing a richer, more nuanced view of the research subject.
Prioritizes Depth over Breadth: Qualitative research favors depth of understanding over breadth, typically involving a smaller but more focused sample size (Hennink, Hutter, & Bailey, 2020). This enables detailed exploration of the phenomena of interest, often leading to rich and complex data.

Qualitative vs Quantitative Research

Qualitative research centers on exploring and understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

It involves an in-depth approach to the subject matter, aiming to capture the richness and complexity of human experience.

Examples include conducting interviews, observing behaviors, or analyzing text and images.

There are strengths inherent in this approach. In its focus on understanding subjective experiences and interpretations, qualitative research can yield rich and detailed data that quantitative research may overlook (Denzin & Lincoln, 2011).

Additionally, qualitative research is adaptive, allowing the researcher to respond to new directions and insights as they emerge during the research process.

However, there are also limitations. Because of the interpretive nature of this research, findings may not be generalizable to a broader population (Marshall & Rossman, 2014). Well-designed quantitative research, on the other hand, can be generalizable.

Moreover, the reliability and validity of qualitative data can be challenging to establish due to its subjective nature, unlike quantitative research, which is ideally more objective.


	Research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013)	Research method dealing with numbers and statistical analysis (Creswell & Creswell, 2017)
	Interviews, text/image analysis (Fugard & Potts, 2015)	Surveys, lab experiments (Van Voorhis & Morgan, 2007)
	Yields rich and detailed data; adaptive to new directions and insights (Denzin & Lincoln, 2011)	Enables precise measurement and analysis; findings can be generalizable; allows for replication (Ali & Bhaskar, 2016)
	Findings may not be generalizable; labor-intensive and time-consuming; reliability and validity can be challenging to establish (Marshall & Rossman, 2014)	May miss contextual detail; depends heavily on design and instrumentation; does not provide detailed description of behaviors, attitudes, and experiences (Mackey & Gass, 2015)

Compare Qualitative and Quantitative Research Methodologies in This Guide Here

In conclusion, qualitative research methods provide distinctive ways to explore social phenomena and understand nuances that quantitative approaches might overlook. Each method, from Ethnography to Photo-Elicitation, presents its strengths and weaknesses but they all offer valuable means of investigating complex, real-world situations. The goal for the researcher is not to find a definitive tool, but to employ the method best suited for their research questions and the context at hand (Almalki, 2016). Above all, these methods underscore the richness of human experience and deepen our understanding of the world around us.

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Quant or Qual Research? 27 Words to Help You Decide

Figure 1: The 27 primarily quant, qual, and mixed-method keywords.

Quantitative Words

Qualitative words, mixed-use words.

Question	Quant	Qual
Why aren’t people paying their bills via the mobile app?		X
What do users expect when they click the icon?		X
Which entry points and menu locations do users prefer?	X
Learn users? thoughts about online shopping.		X
How likely are people to recommend the new app?	X
Do users understand how to make the player full screen?	X	X
Which prescription order form is easier to use?	X
Which icons are preferred?	X
What are the first impressions people have of the homepage?		X

Table 1: Ten examples of quant and qual research questions with keywords.

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Home » 500+ Qualitative Research Titles and Topics

500+ Qualitative Research Titles and Topics

Table of Contents

Qualitative research is a methodological approach that involves gathering and analyzing non-numerical data to understand and interpret social phenomena. Unlike quantitative research , which emphasizes the collection of numerical data through surveys and experiments, qualitative research is concerned with exploring the subjective experiences, perspectives, and meanings of individuals and groups. As such, qualitative research topics can be diverse and encompass a wide range of social issues and phenomena. From exploring the impact of culture on identity formation to examining the experiences of marginalized communities, qualitative research offers a rich and nuanced perspective on complex social issues. In this post, we will explore some of the most compelling qualitative research topics and provide some tips on how to conduct effective qualitative research.

Qualitative Research Titles

Qualitative research titles often reflect the study’s focus on understanding the depth and complexity of human behavior, experiences, or social phenomena. Here are some examples across various fields:

“Understanding the Impact of Project-Based Learning on Student Engagement in High School Classrooms: A Qualitative Study”
“Navigating the Transition: Experiences of International Students in American Universities”
“The Role of Parental Involvement in Early Childhood Education: Perspectives from Teachers and Parents”
“Exploring the Effects of Teacher Feedback on Student Motivation and Self-Efficacy in Middle Schools”
“Digital Literacy in the Classroom: Teacher Strategies for Integrating Technology in Elementary Education”
“Culturally Responsive Teaching Practices: A Case Study in Diverse Urban Schools”
“The Influence of Extracurricular Activities on Academic Achievement: Student Perspectives”
“Barriers to Implementing Inclusive Education in Public Schools: A Qualitative Inquiry”
“Teacher Professional Development and Its Impact on Classroom Practice: A Qualitative Exploration”
“Student-Centered Learning Environments: A Qualitative Study of Classroom Dynamics and Outcomes”
“The Experience of First-Year Teachers: Challenges, Support Systems, and Professional Growth”
“Exploring the Role of School Leadership in Fostering a Positive School Culture”
“Peer Relationships and Learning Outcomes in Cooperative Learning Settings: A Qualitative Analysis”
“The Impact of Social Media on Student Learning and Engagement: Teacher and Student Perspectives”
“Understanding Special Education Needs: Parent and Teacher Perceptions of Support Services in Schools

Health Science

“Living with Chronic Pain: Patient Narratives and Coping Strategies in Managing Daily Life”
“Healthcare Professionals’ Perspectives on the Challenges of Rural Healthcare Delivery”
“Exploring the Mental Health Impacts of COVID-19 on Frontline Healthcare Workers: A Qualitative Study”
“Patient and Family Experiences of Palliative Care: Understanding Needs and Preferences”
“The Role of Community Health Workers in Improving Access to Maternal Healthcare in Rural Areas”
“Barriers to Mental Health Services Among Ethnic Minorities: A Qualitative Exploration”
“Understanding Patient Satisfaction in Telemedicine Services: A Qualitative Study of User Experiences”
“The Impact of Cultural Competence Training on Healthcare Provider-Patient Communication”
“Navigating the Transition to Adult Healthcare Services: Experiences of Adolescents with Chronic Conditions”
“Exploring the Use of Alternative Medicine Among Patients with Chronic Diseases: A Qualitative Inquiry”
“The Role of Social Support in the Rehabilitation Process of Stroke Survivors”
“Healthcare Decision-Making Among Elderly Patients: A Qualitative Study of Preferences and Influences”
“Nurse Perceptions of Patient Safety Culture in Hospital Settings: A Qualitative Analysis”
“Experiences of Women with Postpartum Depression: Barriers to Seeking Help”
“The Impact of Nutrition Education on Eating Behaviors Among College Students: A Qualitative Approach”
“Understanding Resilience in Survivors of Childhood Trauma: A Narrative Inquiry”
“The Role of Mindfulness in Managing Work-Related Stress Among Corporate Employees: A Qualitative Study”
“Coping Mechanisms Among Parents of Children with Autism Spectrum Disorder”
“Exploring the Psychological Impact of Social Isolation in the Elderly: A Phenomenological Study”
“Identity Formation in Adolescence: The Influence of Social Media and Peer Groups”
“The Experience of Forgiveness in Interpersonal Relationships: A Qualitative Exploration”
“Perceptions of Happiness and Well-Being Among University Students: A Cultural Perspective”
“The Impact of Art Therapy on Anxiety and Depression in Adult Cancer Patients”
“Narratives of Recovery: A Qualitative Study on the Journey Through Addiction Rehabilitation”
“Exploring the Psychological Effects of Long-Term Unemployment: A Grounded Theory Approach”
“Attachment Styles and Their Influence on Adult Romantic Relationships: A Qualitative Analysis”
“The Role of Personal Values in Career Decision-Making Among Young Adults”
“Understanding the Stigma of Mental Illness in Rural Communities: A Qualitative Inquiry”
“Exploring the Use of Digital Mental Health Interventions Among Adolescents: A Qualitative Study”
“The Psychological Impact of Climate Change on Young Adults: An Exploration of Anxiety and Action”
“Navigating Identity: The Role of Social Media in Shaping Youth Culture and Self-Perception”
“Community Resilience in the Face of Urban Gentrification: A Case Study of Neighborhood Change”
“The Dynamics of Intergenerational Relationships in Immigrant Families: A Qualitative Analysis”
“Social Capital and Economic Mobility in Low-Income Neighborhoods: An Ethnographic Approach”
“Gender Roles and Career Aspirations Among Young Adults in Conservative Societies”
“The Stigma of Mental Health in the Workplace: Employee Narratives and Organizational Culture”
“Exploring the Intersection of Race, Class, and Education in Urban School Systems”
“The Impact of Digital Divide on Access to Healthcare Information in Rural Communities”
“Social Movements and Political Engagement Among Millennials: A Qualitative Study”
“Cultural Adaptation and Identity Among Second-Generation Immigrants: A Phenomenological Inquiry”
“The Role of Religious Institutions in Providing Community Support and Social Services”
“Negotiating Public Space: Experiences of LGBTQ+ Individuals in Urban Environments”
“The Sociology of Food: Exploring Eating Habits and Food Practices Across Cultures”
“Work-Life Balance Challenges Among Dual-Career Couples: A Qualitative Exploration”
“The Influence of Peer Networks on Substance Use Among Adolescents: A Community Study”

Business and Management

“Navigating Organizational Change: Employee Perceptions and Adaptation Strategies in Mergers and Acquisitions”
“Corporate Social Responsibility: Consumer Perceptions and Brand Loyalty in the Retail Sector”
“Leadership Styles and Organizational Culture: A Comparative Study of Tech Startups”
“Workplace Diversity and Inclusion: Best Practices and Challenges in Multinational Corporations”
“Consumer Trust in E-commerce: A Qualitative Study of Online Shopping Behaviors”
“The Gig Economy and Worker Satisfaction: Exploring the Experiences of Freelance Professionals”
“Entrepreneurial Resilience: Success Stories and Lessons Learned from Failed Startups”
“Employee Engagement and Productivity in Remote Work Settings: A Post-Pandemic Analysis”
“Brand Storytelling: How Narrative Strategies Influence Consumer Engagement”
“Sustainable Business Practices: Stakeholder Perspectives in the Fashion Industry”
“Cross-Cultural Communication Challenges in Global Teams: Strategies for Effective Collaboration”
“Innovative Workspaces: The Impact of Office Design on Creativity and Collaboration”
“Consumer Perceptions of Artificial Intelligence in Customer Service: A Qualitative Exploration”
“The Role of Mentoring in Career Development: Insights from Women in Leadership Positions”
“Agile Management Practices: Adoption and Impact in Traditional Industries”

Environmental Studies

“Community-Based Conservation Efforts in Tropical Rainforests: A Qualitative Study of Local Perspectives and Practices”
“Urban Sustainability Initiatives: Exploring Resident Participation and Impact in Green City Projects”
“Perceptions of Climate Change Among Indigenous Populations: Insights from Traditional Ecological Knowledge”
“Environmental Justice and Industrial Pollution: A Case Study of Community Advocacy and Response”
“The Role of Eco-Tourism in Promoting Conservation Awareness: Perspectives from Tour Operators and Visitors”
“Sustainable Agriculture Practices Among Smallholder Farmers: Challenges and Opportunities”
“Youth Engagement in Climate Action Movements: Motivations, Perceptions, and Outcomes”
“Corporate Environmental Responsibility: A Qualitative Analysis of Stakeholder Expectations and Company Practices”
“The Impact of Plastic Pollution on Marine Ecosystems: Community Awareness and Behavioral Change”
“Renewable Energy Adoption in Rural Communities: Barriers, Facilitators, and Social Implications”
“Water Scarcity and Community Adaptation Strategies in Arid Regions: A Grounded Theory Approach”
“Urban Green Spaces: Public Perceptions and Use Patterns in Megacities”
“Environmental Education in Schools: Teachers’ Perspectives on Integrating Sustainability into Curricula”
“The Influence of Environmental Activism on Policy Change: Case Studies of Grassroots Campaigns”
“Cultural Practices and Natural Resource Management: A Qualitative Study of Indigenous Stewardship Models”

Anthropology

“Kinship and Social Organization in Matrilineal Societies: An Ethnographic Study”
“Rituals and Beliefs Surrounding Death and Mourning in Diverse Cultures: A Comparative Analysis”
“The Impact of Globalization on Indigenous Languages and Cultural Identity”
“Food Sovereignty and Traditional Agricultural Practices Among Indigenous Communities”
“Navigating Modernity: The Integration of Traditional Healing Practices in Contemporary Healthcare Systems”
“Gender Roles and Equality in Hunter-Gatherer Societies: An Anthropological Perspective”
“Sacred Spaces and Religious Practices: An Ethnographic Study of Pilgrimage Sites”
“Youth Subcultures and Resistance: An Exploration of Identity and Expression in Urban Environments”
“Cultural Constructions of Disability and Inclusion: A Cross-Cultural Analysis”
“Interethnic Marriages and Cultural Syncretism: Case Studies from Multicultural Societies”
“The Role of Folklore and Storytelling in Preserving Cultural Heritage”
“Economic Anthropology of Gift-Giving and Reciprocity in Tribal Communities”
“Digital Anthropology: The Role of Social Media in Shaping Political Movements”
“Migration and Diaspora: Maintaining Cultural Identity in Transnational Communities”
“Cultural Adaptations to Climate Change Among Coastal Fishing Communities”

Communication Studies

“The Dynamics of Family Communication in the Digital Age: A Qualitative Inquiry”
“Narratives of Identity and Belonging in Diaspora Communities Through Social Media”
“Organizational Communication and Employee Engagement: A Case Study in the Non-Profit Sector”
“Cultural Influences on Communication Styles in Multinational Teams: An Ethnographic Approach”
“Media Representation of Women in Politics: A Content Analysis and Audience Perception Study”
“The Role of Communication in Building Sustainable Community Development Projects”
“Interpersonal Communication in Online Dating: Strategies, Challenges, and Outcomes”
“Public Health Messaging During Pandemics: A Qualitative Study of Community Responses”
“The Impact of Mobile Technology on Parent-Child Communication in the Digital Era”
“Crisis Communication Strategies in the Hospitality Industry: A Case Study of Reputation Management”
“Narrative Analysis of Personal Stories Shared on Mental Health Blogs”
“The Influence of Podcasts on Political Engagement Among Young Adults”
“Visual Communication and Brand Identity: A Qualitative Study of Consumer Interpretations”
“Communication Barriers in Cross-Cultural Healthcare Settings: Patient and Provider Perspectives”
“The Role of Internal Communication in Managing Organizational Change: Employee Experiences”

Information Technology

“User Experience Design in Augmented Reality Applications: A Qualitative Study of Best Practices”
“The Human Factor in Cybersecurity: Understanding Employee Behaviors and Attitudes Towards Phishing”
“Adoption of Cloud Computing in Small and Medium Enterprises: Challenges and Success Factors”
“Blockchain Technology in Supply Chain Management: A Qualitative Exploration of Potential Impacts”
“The Role of Artificial Intelligence in Personalizing User Experiences on E-commerce Platforms”
“Digital Transformation in Traditional Industries: A Case Study of Technology Adoption Challenges”
“Ethical Considerations in the Development of Smart Home Technologies: A Stakeholder Analysis”
“The Impact of Social Media Algorithms on News Consumption and Public Opinion”
“Collaborative Software Development: Practices and Challenges in Open Source Projects”
“Understanding the Digital Divide: Access to Information Technology in Rural Communities”
“Data Privacy Concerns and User Trust in Internet of Things (IoT) Devices”
“The Effectiveness of Gamification in Educational Software: A Qualitative Study of Engagement and Motivation”
“Virtual Teams and Remote Work: Communication Strategies and Tools for Effectiveness”
“User-Centered Design in Mobile Health Applications: Evaluating Usability and Accessibility”
“The Influence of Technology on Work-Life Balance: Perspectives from IT Professionals”

Tourism and Hospitality

“Exploring the Authenticity of Cultural Heritage Tourism in Indigenous Communities”
“Sustainable Tourism Practices: Perceptions and Implementations in Small Island Destinations”
“The Impact of Social Media Influencers on Destination Choice Among Millennials”
“Gastronomy Tourism: Exploring the Culinary Experiences of International Visitors in Rural Regions”
“Eco-Tourism and Conservation: Stakeholder Perspectives on Balancing Tourism and Environmental Protection”
“The Role of Hospitality in Enhancing the Cultural Exchange Experience of Exchange Students”
“Dark Tourism: Visitor Motivations and Experiences at Historical Conflict Sites”
“Customer Satisfaction in Luxury Hotels: A Qualitative Study of Service Excellence and Personalization”
“Adventure Tourism: Understanding the Risk Perception and Safety Measures Among Thrill-Seekers”
“The Influence of Local Communities on Tourist Experiences in Ecotourism Sites”
“Event Tourism: Economic Impacts and Community Perspectives on Large-Scale Music Festivals”
“Heritage Tourism and Identity: Exploring the Connections Between Historic Sites and National Identity”
“Tourist Perceptions of Sustainable Accommodation Practices: A Study of Green Hotels”
“The Role of Language in Shaping the Tourist Experience in Multilingual Destinations”
“Health and Wellness Tourism: Motivations and Experiences of Visitors to Spa and Retreat Centers”

Qualitative Research Topics

Qualitative Research Topics are as follows:

Understanding the lived experiences of first-generation college students
Exploring the impact of social media on self-esteem among adolescents
Investigating the effects of mindfulness meditation on stress reduction
Analyzing the perceptions of employees regarding organizational culture
Examining the impact of parental involvement on academic achievement of elementary school students
Investigating the role of music therapy in managing symptoms of depression
Understanding the experience of women in male-dominated industries
Exploring the factors that contribute to successful leadership in non-profit organizations
Analyzing the effects of peer pressure on substance abuse among adolescents
Investigating the experiences of individuals with disabilities in the workplace
Understanding the factors that contribute to burnout among healthcare professionals
Examining the impact of social support on mental health outcomes
Analyzing the perceptions of parents regarding sex education in schools
Investigating the experiences of immigrant families in the education system
Understanding the impact of trauma on mental health outcomes
Exploring the effectiveness of animal-assisted therapy for individuals with anxiety
Analyzing the factors that contribute to successful intergenerational relationships
Investigating the experiences of LGBTQ+ individuals in the workplace
Understanding the impact of online gaming on social skills development among adolescents
Examining the perceptions of teachers regarding technology integration in the classroom
Analyzing the experiences of women in leadership positions
Investigating the factors that contribute to successful marriage and long-term relationships
Understanding the impact of social media on political participation
Exploring the experiences of individuals with mental health disorders in the criminal justice system
Analyzing the factors that contribute to successful community-based programs for youth development
Investigating the experiences of veterans in accessing mental health services
Understanding the impact of the COVID-19 pandemic on mental health outcomes
Examining the perceptions of parents regarding childhood obesity prevention
Analyzing the factors that contribute to successful multicultural education programs
Investigating the experiences of individuals with chronic illnesses in the workplace
Understanding the impact of poverty on academic achievement
Exploring the experiences of individuals with autism spectrum disorder in the workplace
Analyzing the factors that contribute to successful employee retention strategies
Investigating the experiences of caregivers of individuals with Alzheimer’s disease
Understanding the impact of parent-child communication on adolescent sexual behavior
Examining the perceptions of college students regarding mental health services on campus
Analyzing the factors that contribute to successful team building in the workplace
Investigating the experiences of individuals with eating disorders in treatment programs
Understanding the impact of mentorship on career success
Exploring the experiences of individuals with physical disabilities in the workplace
Analyzing the factors that contribute to successful community-based programs for mental health
Investigating the experiences of individuals with substance use disorders in treatment programs
Understanding the impact of social media on romantic relationships
Examining the perceptions of parents regarding child discipline strategies
Analyzing the factors that contribute to successful cross-cultural communication in the workplace
Investigating the experiences of individuals with anxiety disorders in treatment programs
Understanding the impact of cultural differences on healthcare delivery
Exploring the experiences of individuals with hearing loss in the workplace
Analyzing the factors that contribute to successful parent-teacher communication
Investigating the experiences of individuals with depression in treatment programs
Understanding the impact of childhood trauma on adult mental health outcomes
Examining the perceptions of college students regarding alcohol and drug use on campus
Analyzing the factors that contribute to successful mentor-mentee relationships
Investigating the experiences of individuals with intellectual disabilities in the workplace
Understanding the impact of work-family balance on employee satisfaction and well-being
Exploring the experiences of individuals with autism spectrum disorder in vocational rehabilitation programs
Analyzing the factors that contribute to successful project management in the construction industry
Investigating the experiences of individuals with substance use disorders in peer support groups
Understanding the impact of mindfulness meditation on stress reduction and mental health
Examining the perceptions of parents regarding childhood nutrition
Analyzing the factors that contribute to successful environmental sustainability initiatives in organizations
Investigating the experiences of individuals with bipolar disorder in treatment programs
Understanding the impact of job stress on employee burnout and turnover
Exploring the experiences of individuals with physical disabilities in recreational activities
Analyzing the factors that contribute to successful strategic planning in nonprofit organizations
Investigating the experiences of individuals with hoarding disorder in treatment programs
Understanding the impact of culture on leadership styles and effectiveness
Examining the perceptions of college students regarding sexual health education on campus
Analyzing the factors that contribute to successful supply chain management in the retail industry
Investigating the experiences of individuals with personality disorders in treatment programs
Understanding the impact of multiculturalism on group dynamics in the workplace
Exploring the experiences of individuals with chronic pain in mindfulness-based pain management programs
Analyzing the factors that contribute to successful employee engagement strategies in organizations
Investigating the experiences of individuals with internet addiction disorder in treatment programs
Understanding the impact of social comparison on body dissatisfaction and self-esteem
Examining the perceptions of parents regarding childhood sleep habits
Analyzing the factors that contribute to successful diversity and inclusion initiatives in organizations
Investigating the experiences of individuals with schizophrenia in treatment programs
Understanding the impact of job crafting on employee motivation and job satisfaction
Exploring the experiences of individuals with vision impairments in navigating public spaces
Analyzing the factors that contribute to successful customer relationship management strategies in the service industry
Investigating the experiences of individuals with dissociative amnesia in treatment programs
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Qualitative Research Questions

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How to write qualitative research questions.

11 min read Here’s how to write effective qualitative research questions for your projects, and why getting it right matters so much.

What is qualitative research?

Qualitative research is a blanket term covering a wide range of research methods and theoretical framing approaches. The unifying factor in all these types of qualitative study is that they deal with data that cannot be counted. Typically this means things like people’s stories, feelings, opinions and emotions , and the meanings they ascribe to their experiences.

Qualitative study is one of two main categories of research, the other being quantitative research. Quantitative research deals with numerical data – that which can be counted and quantified, and which is mostly concerned with trends and patterns in large-scale datasets.

What are research questions?

Research questions are questions you are trying to answer with your research. To put it another way, your research question is the reason for your study, and the beginning point for your research design. There is normally only one research question per study, although if your project is very complex, you may have multiple research questions that are closely linked to one central question.

A good qualitative research question sums up your research objective. It’s a way of expressing the central question of your research, identifying your particular topic and the central issue you are examining.

Research questions are quite different from survey questions, questions used in focus groups or interview questions. A long list of questions is used in these types of study, as opposed to one central question. Additionally, interview or survey questions are asked of participants, whereas research questions are only for the researcher to maintain a clear understanding of the research design.

Research questions are used in both qualitative and quantitative research , although what makes a good research question might vary between the two.

In fact, the type of research questions you are asking can help you decide whether you need to take a quantitative or qualitative approach to your research project.

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

Writing research questions is very important in both qualitative and quantitative research, but the research questions that perform best in the two types of studies are quite different.

Quantitative research questions

Quantitative research questions usually relate to quantities, similarities and differences.

It might reflect the researchers’ interest in determining whether relationships between variables exist, and if so whether they are statistically significant. Or it may focus on establishing differences between things through comparison, and using statistical analysis to determine whether those differences are meaningful or due to chance.

How much? This kind of research question is one of the simplest. It focuses on quantifying something. For example:

How many Yoruba speakers are there in the state of Maine?

What is the connection?

This type of quantitative research question examines how one variable affects another.

For example:

How does a low level of sunlight affect the mood scores (1-10) of Antarctic explorers during winter?

What is the difference? Quantitative research questions in this category identify two categories and measure the difference between them using numerical data.

Do white cats stay cooler than tabby cats in hot weather?

If your research question fits into one of the above categories, you’re probably going to be doing a quantitative study.

Qualitative research questions

Qualitative research questions focus on exploring phenomena, meanings and experiences.

Unlike quantitative research, qualitative research isn’t about finding causal relationships between variables. So although qualitative research questions might touch on topics that involve one variable influencing another, or looking at the difference between things, finding and quantifying those relationships isn’t the primary objective.

In fact, you as a qualitative researcher might end up studying a very similar topic to your colleague who is doing a quantitative study, but your areas of focus will be quite different. Your research methods will also be different – they might include focus groups, ethnography studies, and other kinds of qualitative study.

A few example qualitative research questions:

What is it like being an Antarctic explorer during winter?
What are the experiences of Yoruba speakers in the USA?
How do white cat owners describe their pets?

Qualitative research question types

Marshall and Rossman (1989) identified 4 qualitative research question types, each with its own typical research strategy and methods.

Exploratory questions

Exploratory questions are used when relatively little is known about the research topic. The process researchers follow when pursuing exploratory questions might involve interviewing participants, holding focus groups, or diving deep with a case study.

Explanatory questions

With explanatory questions, the research topic is approached with a view to understanding the causes that lie behind phenomena. However, unlike a quantitative project, the focus of explanatory questions is on qualitative analysis of multiple interconnected factors that have influenced a particular group or area, rather than a provable causal link between dependent and independent variables.

Descriptive questions

As the name suggests, descriptive questions aim to document and record what is happening. In answering descriptive questions , researchers might interact directly with participants with surveys or interviews, as well as using observational studies and ethnography studies that collect data on how participants interact with their wider environment.

Predictive questions

Predictive questions start from the phenomena of interest and investigate what ramifications it might have in the future. Answering predictive questions may involve looking back as well as forward, with content analysis, questionnaires and studies of non-verbal communication (kinesics).

Why are good qualitative research questions important?

We know research questions are very important. But what makes them so essential? (And is that question a qualitative or quantitative one?)

Getting your qualitative research questions right has a number of benefits.

It defines your qualitative research project Qualitative research questions definitively nail down the research population, the thing you’re examining, and what the nature of your answer will be.This means you can explain your research project to other people both inside and outside your business or organization. That could be critical when it comes to securing funding for your project, recruiting participants and members of your research team, and ultimately for publishing your results. It can also help you assess right the ethical considerations for your population of study.
It maintains focus Good qualitative research questions help researchers to stick to the area of focus as they carry out their research. Keeping the research question in mind will help them steer away from tangents during their research or while they are carrying out qualitative research interviews. This holds true whatever the qualitative methods are, whether it’s a focus group, survey, thematic analysis or other type of inquiry.That doesn’t mean the research project can’t morph and change during its execution – sometimes this is acceptable and even welcome – but having a research question helps demarcate the starting point for the research. It can be referred back to if the scope and focus of the project does change.
It helps make sure your outcomes are achievable

Because qualitative research questions help determine the kind of results you’re going to get, it helps make sure those results are achievable. By formulating good qualitative research questions in advance, you can make sure the things you want to know and the way you’re going to investigate them are grounded in practical reality. Otherwise, you may be at risk of taking on a research project that can’t be satisfactorily completed.

Developing good qualitative research questions

All researchers use research questions to define their parameters, keep their study on track and maintain focus on the research topic. This is especially important with qualitative questions, where there may be exploratory or inductive methods in use that introduce researchers to new and interesting areas of inquiry. Here are some tips for writing good qualitative research questions.

1. Keep it specific

Broader research questions are difficult to act on. They may also be open to interpretation, or leave some parameters undefined.

Strong example: How do Baby Boomers in the USA feel about their gender identity?

Weak example: Do people feel different about gender now?

2. Be original

Look for research questions that haven’t been widely addressed by others already.

Strong example: What are the effects of video calling on women’s experiences of work?

Weak example: Are women given less respect than men at work?

3. Make it research-worthy

Don’t ask a question that can be answered with a ‘yes’ or ‘no’, or with a quick Google search.

Strong example: What do people like and dislike about living in a highly multi-lingual country?

Weak example: What languages are spoken in India?

4. Focus your question

Don’t roll multiple topics or questions into one. Qualitative data may involve multiple topics, but your qualitative questions should be focused.

Strong example: What is the experience of disabled children and their families when using social services?

Weak example: How can we improve social services for children affected by poverty and disability?

4. Focus on your own discipline, not someone else’s

Avoid asking questions that are for the politicians, police or others to address.

Strong example: What does it feel like to be the victim of a hate crime?

Weak example: How can hate crimes be prevented?

5. Ask something researchable

Big questions, questions about hypothetical events or questions that would require vastly more resources than you have access to are not useful starting points for qualitative studies. Qualitative words or subjective ideas that lack definition are also not helpful.

Strong example: How do perceptions of physical beauty vary between today’s youth and their parents’ generation?

Weak example: Which country has the most beautiful people in it?

Related resources

Qualitative research design 12 min read, primary vs secondary research 14 min read, business research methods 12 min read, mixed methods research 17 min read, market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, request demo.

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Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

Surveys : List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

Interviews : Asking open-ended questions verbally to respondents.
Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

Use quantitative research if you want to confirm or test something (a theory or hypothesis )
Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

Average scores ( means )
The number of times a particular answer was given
The correlation or causation between two or more variables
The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
Thematic analysis : Closely examining the data to identify the main themes and patterns
Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

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MSc, Health Psychology, University of Nottingham

Lauren obtained an MSc in Health Psychology from The University of Nottingham with a distinction classification.

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Associate Editor for Simply Psychology

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Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Qualitative research is a type of research methodology that focuses on gathering and analyzing non-numerical data to gain a deeper understanding of human behavior, experiences, and perspectives.

It aims to explore the “why” and “how” of a phenomenon rather than the “what,” “where,” and “when” typically addressed by quantitative research.

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research involves researchers interpreting data to identify themes, patterns, and meanings.

Qualitative research can be used to:

Gain deep contextual understandings of the subjective social reality of individuals
To answer questions about experience and meaning from the participant’s perspective
To design hypotheses, theory must be researched using qualitative methods to determine what is important before research can begin.

Examples of qualitative research questions include:

How does stress influence young adults’ behavior?
What factors influence students’ school attendance rates in developed countries?
How do adults interpret binge drinking in the UK?
What are the psychological impacts of cervical cancer screening in women?
How can mental health lessons be integrated into the school curriculum?

Characteristics

Naturalistic setting.

Individuals are studied in their natural setting to gain a deeper understanding of how people experience the world. This enables the researcher to understand a phenomenon close to how participants experience it.

Naturalistic settings provide valuable contextual information to help researchers better understand and interpret the data they collect.

The environment, social interactions, and cultural factors can all influence behavior and experiences, and these elements are more easily observed in real-world settings.

Reality is socially constructed

Qualitative research aims to understand how participants make meaning of their experiences – individually or in social contexts. It assumes there is no objective reality and that the social world is interpreted (Yilmaz, 2013).

The primacy of subject matter

The primary aim of qualitative research is to understand the perspectives, experiences, and beliefs of individuals who have experienced the phenomenon selected for research rather than the average experiences of groups of people (Minichiello, 1990).

An in-depth understanding is attained since qualitative techniques allow participants to freely disclose their experiences, thoughts, and feelings without constraint (Tenny et al., 2022).

Variables are complex, interwoven, and difficult to measure

Factors such as experiences, behaviors, and attitudes are complex and interwoven, so they cannot be reduced to isolated variables , making them difficult to measure quantitatively.

However, a qualitative approach enables participants to describe what, why, or how they were thinking/ feeling during a phenomenon being studied (Yilmaz, 2013).

Emic (insider’s point of view)

The phenomenon being studied is centered on the participants’ point of view (Minichiello, 1990).

Emic is used to describe how participants interact, communicate, and behave in the research setting (Scarduzio, 2017).

Interpretive analysis

In qualitative research, interpretive analysis is crucial in making sense of the collected data.

This process involves examining the raw data, such as interview transcripts, field notes, or documents, and identifying the underlying themes, patterns, and meanings that emerge from the participants’ experiences and perspectives.

Collecting Qualitative Data

There are four main research design methods used to collect qualitative data: observations, interviews, focus groups, and ethnography.

Observations

This method involves watching and recording phenomena as they occur in nature. Observation can be divided into two types: participant and non-participant observation.

In participant observation, the researcher actively participates in the situation/events being observed.

In non-participant observation, the researcher is not an active part of the observation and tries not to influence the behaviors they are observing (Busetto et al., 2020).

Observations can be covert (participants are unaware that a researcher is observing them) or overt (participants are aware of the researcher’s presence and know they are being observed).

However, awareness of an observer’s presence may influence participants’ behavior.

Interviews give researchers a window into the world of a participant by seeking their account of an event, situation, or phenomenon. They are usually conducted on a one-to-one basis and can be distinguished according to the level at which they are structured (Punch, 2013).

Structured interviews involve predetermined questions and sequences to ensure replicability and comparability. However, they are unable to explore emerging issues.

Informal interviews consist of spontaneous, casual conversations which are closer to the truth of a phenomenon. However, information is gathered using quick notes made by the researcher and is therefore subject to recall bias.

Semi-structured interviews have a flexible structure, phrasing, and placement so emerging issues can be explored (Denny & Weckesser, 2022).

The use of probing questions and clarification can lead to a detailed understanding, but semi-structured interviews can be time-consuming and subject to interviewer bias.

Focus groups

Similar to interviews, focus groups elicit a rich and detailed account of an experience. However, focus groups are more dynamic since participants with shared characteristics construct this account together (Denny & Weckesser, 2022).

A shared narrative is built between participants to capture a group experience shaped by a shared context.

The researcher takes on the role of a moderator, who will establish ground rules and guide the discussion by following a topic guide to focus the group discussions.

Typically, focus groups have 4-10 participants as a discussion can be difficult to facilitate with more than this, and this number allows everyone the time to speak.

Ethnography

Ethnography is a methodology used to study a group of people’s behaviors and social interactions in their environment (Reeves et al., 2008).

Data are collected using methods such as observations, field notes, or structured/ unstructured interviews.

The aim of ethnography is to provide detailed, holistic insights into people’s behavior and perspectives within their natural setting. In order to achieve this, researchers immerse themselves in a community or organization.

Due to the flexibility and real-world focus of ethnography, researchers are able to gather an in-depth, nuanced understanding of people’s experiences, knowledge and perspectives that are influenced by culture and society.

In order to develop a representative picture of a particular culture/ context, researchers must conduct extensive field work.

This can be time-consuming as researchers may need to immerse themselves into a community/ culture for a few days, or possibly a few years.

Qualitative Data Analysis Methods

Different methods can be used for analyzing qualitative data. The researcher chooses based on the objectives of their study.

The researcher plays a key role in the interpretation of data, making decisions about the coding, theming, decontextualizing, and recontextualizing of data (Starks & Trinidad, 2007).

Grounded theory

Grounded theory is a qualitative method specifically designed to inductively generate theory from data. It was developed by Glaser and Strauss in 1967 (Glaser & Strauss, 2017).

This methodology aims to develop theories (rather than test hypotheses) that explain a social process, action, or interaction (Petty et al., 2012). To inform the developing theory, data collection and analysis run simultaneously.

There are three key types of coding used in grounded theory: initial (open), intermediate (axial), and advanced (selective) coding.

Throughout the analysis, memos should be created to document methodological and theoretical ideas about the data. Data should be collected and analyzed until data saturation is reached and a theory is developed.

Content analysis

Content analysis was first used in the early twentieth century to analyze textual materials such as newspapers and political speeches.

Content analysis is a research method used to identify and analyze the presence and patterns of themes, concepts, or words in data (Vaismoradi et al., 2013).

This research method can be used to analyze data in different formats, which can be written, oral, or visual.

The goal of content analysis is to develop themes that capture the underlying meanings of data (Schreier, 2012).

Qualitative content analysis can be used to validate existing theories, support the development of new models and theories, and provide in-depth descriptions of particular settings or experiences.

The following six steps provide a guideline for how to conduct qualitative content analysis.

Define a Research Question : To start content analysis, a clear research question should be developed.
Identify and Collect Data : Establish the inclusion criteria for your data. Find the relevant sources to analyze.
Define the Unit or Theme of Analysis : Categorize the content into themes. Themes can be a word, phrase, or sentence.
Develop Rules for Coding your Data : Define a set of coding rules to ensure that all data are coded consistently.
Code the Data : Follow the coding rules to categorize data into themes.
Analyze the Results and Draw Conclusions : Examine the data to identify patterns and draw conclusions in relation to your research question.

Discourse analysis

Discourse analysis is a research method used to study written/ spoken language in relation to its social context (Wood & Kroger, 2000).

In discourse analysis, the researcher interprets details of language materials and the context in which it is situated.

Discourse analysis aims to understand the functions of language (how language is used in real life) and how meaning is conveyed by language in different contexts. Researchers use discourse analysis to investigate social groups and how language is used to achieve specific communication goals.

Different methods of discourse analysis can be used depending on the aims and objectives of a study. However, the following steps provide a guideline on how to conduct discourse analysis.

Define the Research Question : Develop a relevant research question to frame the analysis.
Gather Data and Establish the Context : Collect research materials (e.g., interview transcripts, documents). Gather factual details and review the literature to construct a theory about the social and historical context of your study.
Analyze the Content : Closely examine various components of the text, such as the vocabulary, sentences, paragraphs, and structure of the text. Identify patterns relevant to the research question to create codes, then group these into themes.
Review the Results : Reflect on the findings to examine the function of the language, and the meaning and context of the discourse.

Thematic analysis

Thematic analysis is a method used to identify, interpret, and report patterns in data, such as commonalities or contrasts.

Although the origin of thematic analysis can be traced back to the early twentieth century, understanding and clarity of thematic analysis is attributed to Braun and Clarke (2006).

Thematic analysis aims to develop themes (patterns of meaning) across a dataset to address a research question.

In thematic analysis, qualitative data is gathered using techniques such as interviews, focus groups, and questionnaires. Audio recordings are transcribed. The dataset is then explored and interpreted by a researcher to identify patterns.

This occurs through the rigorous process of data familiarisation, coding, theme development, and revision. These identified patterns provide a summary of the dataset and can be used to address a research question.

Themes are developed by exploring the implicit and explicit meanings within the data. Two different approaches are used to generate themes: inductive and deductive.

An inductive approach allows themes to emerge from the data. In contrast, a deductive approach uses existing theories or knowledge to apply preconceived ideas to the data.

Phases of Thematic Analysis

Braun and Clarke (2006) provide a guide of the six phases of thematic analysis. These phases can be applied flexibly to fit research questions and data.

Phase
1. Gather and transcribe data	Gather raw data, for example interviews or focus groups, and transcribe audio recordings fully
2. Familiarization with data	Read and reread all your data from beginning to end; note down initial ideas
3. Create initial codes	Start identifying preliminary codes which highlight important features of the data and may be relevant to the research question
4. Create new codes which encapsulate potential themes	Review initial codes and explore any similarities, differences, or contradictions to uncover underlying themes; create a map to visualize identified themes
5. Take a break then return to the data	Take a break and then return later to review themes
6. Evaluate themes for good fit	Last opportunity for analysis; check themes are supported and saturated with data

Template analysis

Template analysis refers to a specific method of thematic analysis which uses hierarchical coding (Brooks et al., 2014).

Template analysis is used to analyze textual data, for example, interview transcripts or open-ended responses on a written questionnaire.

To conduct template analysis, a coding template must be developed (usually from a subset of the data) and subsequently revised and refined. This template represents the themes identified by researchers as important in the dataset.

Codes are ordered hierarchically within the template, with the highest-level codes demonstrating overarching themes in the data and lower-level codes representing constituent themes with a narrower focus.

A guideline for the main procedural steps for conducting template analysis is outlined below.

Familiarization with the Data : Read (and reread) the dataset in full. Engage, reflect, and take notes on data that may be relevant to the research question.
Preliminary Coding : Identify initial codes using guidance from the a priori codes, identified before the analysis as likely to be beneficial and relevant to the analysis.
Organize Themes : Organize themes into meaningful clusters. Consider the relationships between the themes both within and between clusters.
Produce an Initial Template : Develop an initial template. This may be based on a subset of the data.
Apply and Develop the Template : Apply the initial template to further data and make any necessary modifications. Refinements of the template may include adding themes, removing themes, or changing the scope/title of themes.
Finalize Template : Finalize the template, then apply it to the entire dataset.

Frame analysis

Frame analysis is a comparative form of thematic analysis which systematically analyzes data using a matrix output.

Ritchie and Spencer (1994) developed this set of techniques to analyze qualitative data in applied policy research. Frame analysis aims to generate theory from data.

Frame analysis encourages researchers to organize and manage their data using summarization.

This results in a flexible and unique matrix output, in which individual participants (or cases) are represented by rows and themes are represented by columns.

Each intersecting cell is used to summarize findings relating to the corresponding participant and theme.

Frame analysis has five distinct phases which are interrelated, forming a methodical and rigorous framework.

Familiarization with the Data : Familiarize yourself with all the transcripts. Immerse yourself in the details of each transcript and start to note recurring themes.
Develop a Theoretical Framework : Identify recurrent/ important themes and add them to a chart. Provide a framework/ structure for the analysis.
Indexing : Apply the framework systematically to the entire study data.
Summarize Data in Analytical Framework : Reduce the data into brief summaries of participants’ accounts.
Mapping and Interpretation : Compare themes and subthemes and check against the original transcripts. Group the data into categories and provide an explanation for them.

Preventing Bias in Qualitative Research

To evaluate qualitative studies, the CASP (Critical Appraisal Skills Programme) checklist for qualitative studies can be used to ensure all aspects of a study have been considered (CASP, 2018).

The quality of research can be enhanced and assessed using criteria such as checklists, reflexivity, co-coding, and member-checking.

Co-coding

Relying on only one researcher to interpret rich and complex data may risk key insights and alternative viewpoints being missed. Therefore, coding is often performed by multiple researchers.

A common strategy must be defined at the beginning of the coding process (Busetto et al., 2020). This includes establishing a useful coding list and finding a common definition of individual codes.

Transcripts are initially coded independently by researchers and then compared and consolidated to minimize error or bias and to bring confirmation of findings.

Member checking

Member checking (or respondent validation) involves checking back with participants to see if the research resonates with their experiences (Russell & Gregory, 2003).

Data can be returned to participants after data collection or when results are first available. For example, participants may be provided with their interview transcript and asked to verify whether this is a complete and accurate representation of their views.

Participants may then clarify or elaborate on their responses to ensure they align with their views (Shenton, 2004).

This feedback becomes part of data collection and ensures accurate descriptions/ interpretations of phenomena (Mays & Pope, 2000).

Reflexivity in qualitative research

Reflexivity typically involves examining your own judgments, practices, and belief systems during data collection and analysis. It aims to identify any personal beliefs which may affect the research.

Reflexivity is essential in qualitative research to ensure methodological transparency and complete reporting. This enables readers to understand how the interaction between the researcher and participant shapes the data.

Depending on the research question and population being researched, factors that need to be considered include the experience of the researcher, how the contact was established and maintained, age, gender, and ethnicity.

These details are important because, in qualitative research, the researcher is a dynamic part of the research process and actively influences the outcome of the research (Boeije, 2014).

Reflexivity Example

Who you are and your characteristics influence how you collect and analyze data. Here is an example of a reflexivity statement for research on smoking. I am a 30-year-old white female from a middle-class background. I live in the southwest of England and have been educated to master’s level. I have been involved in two research projects on oral health. I have never smoked, but I have witnessed how smoking can cause ill health from my volunteering in a smoking cessation clinic. My research aspirations are to help to develop interventions to help smokers quit.

Establishing Trustworthiness in Qualitative Research

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

1. Credibility in Qualitative Research

Credibility refers to how accurately the results represent the reality and viewpoints of the participants.

To establish credibility in research, participants’ views and the researcher’s representation of their views need to align (Tobin & Begley, 2004).

To increase the credibility of findings, researchers may use data source triangulation, investigator triangulation, peer debriefing, or member checking (Lincoln & Guba, 1985).

2. Transferability in Qualitative Research

Transferability refers to how generalizable the findings are: whether the findings may be applied to another context, setting, or group (Tobin & Begley, 2004).

Transferability can be enhanced by giving thorough and in-depth descriptions of the research setting, sample, and methods (Nowell et al., 2017).

3. Dependability in Qualitative Research

Dependability is the extent to which the study could be replicated under similar conditions and the findings would be consistent.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

4. Confirmability in Qualitative Research

Confirmability is concerned with establishing that there is a clear link between the researcher’s interpretations/ findings and the data.

Researchers can achieve confirmability by demonstrating how conclusions and interpretations were arrived at (Nowell et al., 2017).

This enables readers to understand the reasoning behind the decisions made.

Audit Trails in Qualitative Research

An audit trail provides evidence of the decisions made by the researcher regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data.

The researcher must provide a clear rationale to demonstrate how conclusions were reached in their study.

A clear description of the research path must be provided to enable readers to trace through the researcher’s logic (Halpren, 1983).

Researchers should maintain records of the raw data, field notes, transcripts, and a reflective journal in order to provide a clear audit trail.

Discovery of unexpected data

Open-ended questions in qualitative research mean the researcher can probe an interview topic and enable the participant to elaborate on responses in an unrestricted manner.

This allows unexpected data to emerge, which can lead to further research into that topic.

The exploratory nature of qualitative research helps generate hypotheses that can be tested quantitatively (Busetto et al., 2020).

Flexibility

Data collection and analysis can be modified and adapted to take the research in a different direction if new ideas or patterns emerge in the data.

This enables researchers to investigate new opportunities while firmly maintaining their research goals.

Naturalistic settings

The behaviors of participants are recorded in real-world settings. Studies that use real-world settings have high ecological validity since participants behave more authentically.

Limitations

Time-consuming .

Qualitative research results in large amounts of data which often need to be transcribed and analyzed manually.

Even when software is used, transcription can be inaccurate, and using software for analysis can result in many codes which need to be condensed into themes.

Subjectivity

The researcher has an integral role in collecting and interpreting qualitative data. Therefore, the conclusions reached are from their perspective and experience.

Consequently, interpretations of data from another researcher may vary greatly.

Limited generalizability

The aim of qualitative research is to provide a detailed, contextualized understanding of an aspect of the human experience from a relatively small sample size.

Despite rigorous analysis procedures, conclusions drawn cannot be generalized to the wider population since data may be biased or unrepresentative.

Therefore, results are only applicable to a small group of the population.

While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions.

By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.

Extraneous variables

Qualitative research is often conducted in real-world settings. This may cause results to be unreliable since extraneous variables may affect the data, for example:

Situational variables : different environmental conditions may influence participants’ behavior in a study. The random variation in factors (such as noise or lighting) may be difficult to control in real-world settings.
Participant characteristics : this includes any characteristics that may influence how a participant answers/ behaves in a study. This may include a participant’s mood, gender, age, ethnicity, sexual identity, IQ, etc.
Experimenter effect : experimenter effect refers to how a researcher’s unintentional influence can change the outcome of a study. This occurs when (i) their interactions with participants unintentionally change participants’ behaviors or (ii) due to errors in observation, interpretation, or analysis.

What sample size should qualitative research be?

The sample size for qualitative studies has been recommended to include a minimum of 12 participants to reach data saturation (Braun, 2013).

Are surveys qualitative or quantitative?

Surveys can be used to gather information from a sample qualitatively or quantitatively. Qualitative surveys use open-ended questions to gather detailed information from a large sample using free text responses.

The use of open-ended questions allows for unrestricted responses where participants use their own words, enabling the collection of more in-depth information than closed-ended questions.

In contrast, quantitative surveys consist of closed-ended questions with multiple-choice answer options. Quantitative surveys are ideal to gather a statistical representation of a population.

What are the ethical considerations of qualitative research?

Before conducting a study, you must think about any risks that could occur and take steps to prevent them. Participant Protection : Researchers must protect participants from physical and mental harm. This means you must not embarrass, frighten, offend, or harm participants. Transparency : Researchers are obligated to clearly communicate how they will collect, store, analyze, use, and share the data. Confidentiality : You need to consider how to maintain the confidentiality and anonymity of participants’ data.

What is triangulation in qualitative research?

Triangulation refers to the use of several approaches in a study to comprehensively understand phenomena. This method helps to increase the validity and credibility of research findings.

Types of triangulation include method triangulation (using multiple methods to gather data); investigator triangulation (multiple researchers for collecting/ analyzing data), theory triangulation (comparing several theoretical perspectives to explain a phenomenon), and data source triangulation (using data from various times, locations, and people; Carter et al., 2014).

Why is qualitative research important?

Qualitative research allows researchers to describe and explain the social world. The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively.

In qualitative research, participants are able to express their thoughts, experiences, and feelings without constraint.

Additionally, researchers are able to follow up on participants’ answers in real-time, generating valuable discussion around a topic. This enables researchers to gain a nuanced understanding of phenomena which is difficult to attain using quantitative methods.

What is coding data in qualitative research?

Coding data is a qualitative data analysis strategy in which a section of text is assigned with a label that describes its content.

These labels may be words or phrases which represent important (and recurring) patterns in the data.

This process enables researchers to identify related content across the dataset. Codes can then be used to group similar types of data to generate themes.

What is the difference between qualitative and quantitative research?

Qualitative research involves the collection and analysis of non-numerical data in order to understand experiences and meanings from the participant’s perspective.

This can provide rich, in-depth insights on complicated phenomena. Qualitative data may be collected using interviews, focus groups, or observations.

In contrast, quantitative research involves the collection and analysis of numerical data to measure the frequency, magnitude, or relationships of variables. This can provide objective and reliable evidence that can be generalized to the wider population.

Quantitative data may be collected using closed-ended questionnaires or experiments.

What is trustworthiness in qualitative research?

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

Credibility refers to how accurately the results represent the reality and viewpoints of the participants. Transferability refers to whether the findings may be applied to another context, setting, or group.

Dependability is the extent to which the findings are consistent and reliable. Confirmability refers to the objectivity of findings (not influenced by the bias or assumptions of researchers).

What is data saturation in qualitative research?

Data saturation is a methodological principle used to guide the sample size of a qualitative research study.

Data saturation is proposed as a necessary methodological component in qualitative research (Saunders et al., 2018) as it is a vital criterion for discontinuing data collection and/or analysis.

The intention of data saturation is to find “no new data, no new themes, no new coding, and ability to replicate the study” (Guest et al., 2006). Therefore, enough data has been gathered to make conclusions.

Why is sampling in qualitative research important?

In quantitative research, large sample sizes are used to provide statistically significant quantitative estimates.

This is because quantitative research aims to provide generalizable conclusions that represent populations.

However, the aim of sampling in qualitative research is to gather data that will help the researcher understand the depth, complexity, variation, or context of a phenomenon. The small sample sizes in qualitative studies support the depth of case-oriented analysis.

What is narrative analysis?

Narrative analysis is a qualitative research method used to understand how individuals create stories from their personal experiences.

There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.

Researchers can use different methods together to explore a research question.

Some narrative researchers focus on the content of what is said, using thematic narrative analysis, while others focus on the structure, such as holistic-form or categorical-form structural narrative analysis. Others focus on how the narrative is produced and performed.

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What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

How does social media shape body image in teenagers?
How do children and adults interpret healthy eating in the UK?
What factors influence employee retention in a large organisation?
How is anxiety experienced around the world?
How can teachers integrate social issues into science curriculums?

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

Qualitative research approaches
Approach	What does it involve?
Grounded theory	Researchers collect rich data on a topic of interest and develop theories .
	Researchers immerse themselves in groups or organisations to understand their cultures.
	Researchers and participants collaboratively link theory to practice to drive social change.
Phenomenological research	Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences.
Narrative research	Researchers examine how stories are told to understand how participants perceive and make sense of their experiences.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

Observations: recording what you have seen, heard, or encountered in detailed field notes.
Interviews: personally asking people questions in one-on-one conversations.
Focus groups: asking questions and generating discussion among a group of people.
Surveys : distributing questionnaires with open-ended questions.
Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
You take field notes with observations and reflect on your own experiences of the company culture.
You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative data analysis
Approach	When to use	Example
	To describe and categorise common words, phrases, and ideas in qualitative data.	A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps.
	To identify and interpret patterns and themes in qualitative data.	A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity.
	To examine the content, structure, and design of texts.	A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade.
	To study communication and how language is used to achieve effects in specific contexts.	A political scientist could use discourse analysis to study how politicians generate trust in election campaigns.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

Limited generalisability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .

Labour-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organisation to understand its culture.
Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Phenomenological research involves investigating phenomena through people’s lived experiences.
Action research links theory and practice in several cycles to drive innovative changes.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organise your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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18 Qualitative Research Examples - Helpful Professor
Qualitative research is an approach to scientific research that involves using observation to gather and analyze non-numerical, in-depth, and well-contextualized datasets. It serves as an integral part of academic, professional, and even daily decision-making processes (Baxter & Jack, 2008).
What Is Qualitative Research? | Methods & Examples - Scribbr
Qualitative research question examples. How does social media shape body image in teenagers? How do children and adults interpret healthy eating in the UK? What factors influence employee retention in a large organization? How is anxiety experienced around the world? How can teachers integrate social issues into science curriculums? Note.
Quant or Qual Research? 27 Words to Help You Decide
Jeff Sauro, PhD • Jim Lewis, PhD. April 13, 2021. When approaching a UX research project, one of the first things to consider is the method. And UX research has many methods. Methods can be categorized as quantitatively focused (e.g., A/B tests) or qualitatively focused (e.g., interviews).
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Here are some examples across various fields: Education. “Understanding the Impact of Project-Based Learning on Student Engagement in High School Classrooms: A Qualitative Study” “Navigating the Transition: Experiences of International Students in American Universities”
How to write qualitative research questions - Qualtrics XM
A few example qualitative research questions: What is it like being an Antarctic explorer during winter? What are the experiences of Yoruba speakers in the USA? How do white cat owners describe their pets? Qualitative research question types
Glossary of terms used in qualitative research
Puzzled by words like semiotics, snowballing and psychographics? Want to know what a qualitative researcher means by mapping or mental accounting? This glossary, compiled by the AQR, defines and explains many of the words and terms used in the qualitative research industry.
Qualitative vs. Quantitative Research | Differences, Examples ...
When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.
Characteristics of Qualitative Research - Simply Psychology
Examples of qualitative research questions include: How does stress influence young adults’ behavior? What factors influence students’ school attendance rates in developed countries? How do adults interpret binge drinking in the UK? What are the psychological impacts of cervical cancer screening in women?
What is Qualitative Research? Definition, Types, Examples ...
Qualitative research is defined as an exploratory method that aims to understand complex phenomena, often within their natural settings, by examining subjective experiences, beliefs, attitudes, and behaviors. Learn more about qualitative research methods, types, examples and best practices.
What Is Qualitative Research? | Methods & Examples - Scribbr
Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

18 Qualitative Research Examples

Qualitative Research Examples

2. Autoethnography

3. Semi-Structured Interviews

4. Focus Groups

5. Phenomenology

6. Grounded Theory

7. Narrative Research

8. Case Study Research

9. Participant Observation

10. Non-Participant Observation

11. Content Analysis

12. Discourse Analysis

13. Action Research

14. Semiotic Analysis

15. Qualitative Longitudinal Studies

16. Open-Ended Surveys

17. Naturalistic Observation

18. Photo-Elicitation

Features of Qualitative Research

Qualitative vs Quantitative Research

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Quant or Qual Research? 27 Words to Help You Decide

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What is qualitative research?

What are research questions?

Quantitative vs. qualitative research questions

Quantitative research questions

Qualitative research questions

Qualitative research question types

Why are good qualitative research questions important?

Developing good qualitative research questions

1. Keep it specific

2. Be original

3. Make it research-worthy

4. Focus your question

4. Focus on your own discipline, not someone else’s

5. Ask something researchable

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Quantitative data collection methods

Qualitative data collection methods

Quantitative research approach

Qualitative research approach

Mixed methods approach

Analyzing quantitative data

Analyzing qualitative data

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Qualitative Research: Characteristics, Design, Methods & Examples

Qualitative research can be used to:

Examples of qualitative research questions include:

Characteristics

Reality is socially constructed

The primacy of subject matter