that research characteristics

Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

MSc Health Psychology Graduate

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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Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

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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. 

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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4.2 Definitions and Characteristics of Qualitative Research

Qualitative research aims to uncover the meaning and understanding of phenomena that cannot be broken down into measurable elements. It is based on naturalistic, interpretative and humanistic notions. 5 This research method seeks to discover, explore, identify or describe subjective human experiences using non-statistical methods and develops themes from the study participants’ stories. 5 Figure 4.1 depicts major features/ characteristics of qualitative research. It utilises exploratory open-ended questions and observations to search for patterns of meaning in collected data (e.g. observation, verbal/written narrative data, photographs, etc.) and uses inductive thinking (from specific observations to more general rules) to interpret meaning. 6 Participants’ voice is evident through quotations and description of the work. 6 The context/ setting of the study and the researcher’s reflexivity (i.e. “reflection on and awareness of their bias”, the effect of the researcher’s experience on the data and interpretations) are very important and described as part of data collection. 6 Analysis of collected data is complex, often involves inductive data analysis (exploration, contrasts, specific to general) and requires multiple coding and development of themes from participant stories. 6

Reflexivity- avoiding bias/Role of the qualitative researcher

Qualitative researchers generally begin their work with the recognition that their position (or worldview) has a significant impact on the overall research process. 7 Researcher worldview shapes the way the research is conducted, i.e., how the questions are formulated, methods are chosen, data are collected and analysed, and results are reported. Therefore, it is essential for qualitative researchers to acknowledge, articulate, reflect on and clarify their own underlying biases and assumptions before embarking on any research project. 7 Reflexivity helps to ensure that the researcher’s own experiences, values, and beliefs do not unintentionally bias the data collection, analysis, and interpretation. 7 It is the gold standard for establishing trustworthiness and has been established as one of the ways qualitative researchers should ensure rigour and quality in their work. 8 The following questions in Table 4.1 may help you begin the reflective process. 9

Table 4.1: Questions to aid the reflection process

Philosophical underpinnings to qualitative research

Qualitative research uses an inductive approach and stems from interpretivism or constructivism and assumes that realities are multiple, socially constructed, and holistic. 10 According to this philosophical viewpoint, humans build reality through their interactions with the world around them. 10 As a result, qualitative research aims to comprehend how individuals make sense of their experiences and build meaning in their lives. 10 Because reality is complex/nuanced and context-bound, participants constantly construct it depending on their understanding. Thus, the interactions between the researcher and the participants are considered necessary to offer a rich description of the concept and provide an in-depth understanding of the phenomenon under investigation. 11

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

Characteristics of research

• Empirical - based on observations and experimentation
• Systematic - follows orderly and sequential procedure.
• Controlled - all variables except those that are tested/experimented upon are kept constant.
• Employs hypothesis - sheeshable process
• Analytical - There is critical analysis of all data used so that there is no error in their interpretation
• Objective, Unbiased, & Logical - all findings are logically based on empirical.
• Employs quantitative or statistical methods - data are transformed into numerical measures and are treated statistically.
• Thinking Scientifically
• Writing discipline specific research papers
• Wikipedia: Research
• Wikibooks: Research Methods

Bibliography

• Feigenbaum, Edward A.; McCorduck, Pamela (1983). The fifth generation: Artificial intelligence and Japan's computer challenge to the world . ISBN  978-0-201-11519-2 .  
• Kendal, Simon; Creen, Malcolm (2006-10-04). An Introduction to Knowledge Engineering . ISBN  978-1-84628-475-5 .  
• Russell, Stuart Jonathan; Norvig, Peter (1995). Artificial Intelligence: A Modern Approach . ISBN  0-13-103805-2 .  

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What is Research? Definition, Types, Methods and Process

By Nick Jain

Published on: July 25, 2023

Table of Contents

What is Research?

Types of research methods, research process: how to conduct research, top 10 best practices for conducting research in 2023.

Research is defined as a meticulous and systematic inquiry process designed to explore and unravel specific subjects or issues with precision. This methodical approach encompasses the thorough collection, rigorous analysis, and insightful interpretation of information, aiming to delve deep into the nuances of a chosen field of study. By adhering to established research methodologies, investigators can draw meaningful conclusions, fostering a profound understanding that contributes significantly to the existing knowledge base.

This dedication to systematic inquiry serves as the bedrock of progress, steering advancements across sciences, technology, social sciences, and diverse disciplines. Through the dissemination of meticulously gathered insights, scholars not only inspire collaboration and innovation but also catalyze positive societal change.

In the pursuit of knowledge, researchers embark on a journey of discovery, seeking to unravel the complexities of the world around us. By formulating clear research questions, researchers set the course for their investigations, carefully crafting methodologies to gather relevant data. Whether employing quantitative surveys or qualitative interviews, data collection lies at the heart of every research endeavor. Once the data is collected, researchers meticulously analyze it, employing statistical tools or thematic analysis to identify patterns and draw meaningful insights. These insights, often supported by empirical evidence, contribute to the collective pool of knowledge, enriching our understanding of various phenomena and guiding decision-making processes across diverse fields. Through research, we continually refine our understanding of the universe, laying the foundation for innovation and progress that shape the future.

Research embodies the spirit of curiosity and the pursuit of truth. Here are the key characteristics of research:

• Systematic Approach: Research follows a well-structured and organized approach, with clearly defined steps and methodologies. It is conducted in a systematic manner to ensure that data is collected, analyzed, and interpreted in a logical and coherent way.
• Objective and Unbiased: Research is objective and strives to be free from bias or personal opinions. Researchers aim to gather data and draw conclusions based on evidence rather than preconceived notions or beliefs.
• Empirical Evidence: Research relies on empirical evidence obtained through observations, experiments, surveys, or other data collection methods. This evidence serves as the foundation for drawing conclusions and making informed decisions.
• Clear Research Question or Problem: Every research study begins with a specific research question or problem that the researcher aims to address. This question provides focus and direction to the entire research process.
• Replicability: Good research should be replicable, meaning that other researchers should be able to conduct a similar study and obtain similar results when following the same methods.
• Transparency and Ethics: Research should be conducted with transparency, and researchers should adhere to ethical guidelines and principles. This includes obtaining informed consent from participants, ensuring confidentiality, and avoiding any harm to participants or the environment.
• Generalizability: Researchers often aim for their findings to be generalizable to a broader population or context. This means that the results of the study can be applied beyond the specific sample or situation studied.
• Logical and Critical Thinking: Research involves critical thinking to analyze and interpret data, identify patterns, and draw meaningful conclusions. Logical reasoning is essential in formulating hypotheses and designing the study.
• Contribution to Knowledge: The primary purpose of research is to contribute to the existing body of knowledge in a particular field. Researchers aim to expand understanding, challenge existing theories, or propose new ideas.
• Peer Review and Publication: Research findings are typically subject to peer review by experts in the field before being published in academic journals or presented at conferences. This process ensures the quality and validity of the research.
• Iterative Process: Research is often an iterative process, with findings from one study leading to new questions and further research. It is a continuous cycle of discovery and refinement.
• Practical Application: While some research is theoretical in nature, much of it aims to have practical applications and real-world implications. It can inform policy decisions, improve practices, or address societal challenges.

These key characteristics collectively define research as a rigorous and valuable endeavor that drives progress, knowledge, and innovation in various disciplines.

Research serves as a cornerstone for knowledge discovery, innovation, and decision-making. Understanding the various types of research methods is crucial for selecting the most appropriate approach to answer your research questions effectively. This guide delves into the major research methods, their applications, and tips on choosing the best one for your study.

1. Quantitative Research: Unlocking the Power of Numbers

Quantitative research is centered around collecting numerical data and employing statistical techniques to draw conclusions. This type of research is often used to measure variables, identify patterns, and establish causal relationships.

• Purpose: Surveys are utilized to collect data from a large audience to identify trends and generalize findings.
• Method: Employ structured questionnaires with closed-ended questions.
• Example: Businesses conduct customer satisfaction surveys to understand consumer preferences and make informed decisions.
• Experiments:
• Purpose: Experiments are designed to test hypotheses by manipulating variables in a controlled setting.
• Method: Use experimental and control groups to establish cause-and-effect relationships.
• Example: In scientific research, experiments are conducted to evaluate the effectiveness of a new drug treatment.
• Observational Studies:
• Purpose: Observational studies involve watching and recording subjects without interference, providing insights into natural behaviors.
• Method: Systematically observe and document phenomena.
• Example: Wildlife researchers use observational studies to study animal behaviors in their natural habitats.
• Secondary Data Analysis:
• Purpose: Re-analyze existing datasets to extract new insights, saving time and resources.
• Method: Utilize pre-existing data from sources such as government databases or academic publications.
• Example: Economists analyze census data to examine employment trends and economic growth.

2. Qualitative Research: Exploring the Depths of Human Experience

Qualitative research focuses on understanding the intricacies of human experiences, beliefs, and social phenomena. It provides rich, in-depth insights and interpretations that numbers alone cannot capture.

• Interviews:
• Purpose: Conduct in-depth interviews to explore individual perspectives and gain insights into complex topics.
• Method: Use semi-structured or unstructured interviews to allow participants to share their thoughts freely.
• Example: Healthcare researchers interview patients to understand their experiences and emotional responses to treatments.
• Focus Groups:
• Purpose: Gather diverse opinions and insights from group discussions on specific topics.
• Method: Facilitate guided conversations with selected participants.
• Example: Marketing teams conduct focus groups to test new product concepts and gather feedback.
• Ethnography:
• Purpose: Immerse in a culture or community to understand their practices, values, and social dynamics.
• Method: Engage in long-term observation and interaction within the community.
• Example: Anthropologists conduct ethnographic research to study cultural rituals and traditions.
• Case Studies:
• Purpose: Provide an in-depth examination of a single subject, event, or organization to uncover insights and identify patterns.
• Method: Use multiple data sources to gain comprehensive knowledge.
• Example: Business analysts study successful startups to identify strategies for growth and innovation.

3. Mixed-Methods Research: Bridging the Gap

Mixed-methods research combines qualitative and quantitative approaches to gain a deeper insight into complex problems. This integration allows researchers to benefit from both numerical data and narrative insights.

• Purpose: Leverage the strengths of both quantitative and qualitative data.
• Method: Employ a combination of surveys, interviews, and other techniques.
• Example: Educational researchers use mixed methods to evaluate student performance through test scores and personal interviews.

4. Cross-Sectional Studies: Snapshot of a Moment

Cross-sectional studies analyze data from a population at a specific point in time to identify patterns, correlations, or differences between variables.

• Purpose: Provide a snapshot of a population’s characteristics and relationships.
• Method: Collect data simultaneously from multiple subjects.
• Example: Public health researchers conduct cross-sectional studies to assess disease prevalence in a community.

5. Longitudinal Studies: Observing Change Over Time

Longitudinal studies track the same subjects over an extended period, providing valuable insights into changes, trends, and long-term effects.

• Purpose: Examine changes and developments over time.
• Method: Collect data from the same participants at multiple intervals.
• Example: Psychologists conduct longitudinal studies to understand cognitive development from childhood to adulthood.

6. Action Research: Solving Real-World Problems

Action research involves collaboration with stakeholders to identify and address practical issues, aiming for immediate impact and improvement.

• Purpose: Implement solutions and drive change in real-world settings.
• Method: Engage participants actively in the research process.
• Example: Educators conduct action research to enhance teaching methods and student engagement.

7. Case-Control Studies: Uncovering Causes and Risks

Case-control studies compare individuals with a particular outcome (cases) to those without it (controls) to identify potential causes or risk factors.

• Purpose: Identify factors linked to specific outcomes or diseases.
• Method: Analyze historical data between cases and controls.
• Example: Epidemiologists conduct case-control studies to investigate potential causes of rare diseases.

8. Descriptive Research: Painting a Picture

Descriptive research aims to provide detailed descriptions and summaries of phenomena without manipulating variables, offering a clear picture of a subject.

• Purpose: Describe characteristics, behaviors, or patterns.
• Method: Use surveys, observations, or case studies.
• Example: Sociologists use descriptive research to document urban population demographics.

9. Correlational Research: Understanding Relationships

Correlational research examines the relationship between two or more variables to identify patterns, associations, or correlations without inferring causation.

• Purpose: Identify patterns and associations between variables.
• Method: Use statistical analysis to determine correlation coefficients.
• Example: Researchers study the correlation between physical activity levels and mental well-being.

10. Grounded Theory: Building Theories from Data

Grounded theory is an approach where theories are developed based on systematically gathered and analyzed data, allowing concepts and frameworks to emerge organically.

• Purpose: Develop theories grounded in empirical evidence.
• Method: Use iterative data collection and analysis.
• Example: Social scientists build theories on workplace motivation through employee interviews and observations.

11. Surveys and Questionnaires: Collecting Direct Feedback

Surveys and questionnaires are structured tools used to collect specific information directly from a target population, providing valuable data for various purposes.

• Purpose: Gather targeted data and opinions from respondents.
• Method: Administer standardized questions to a sample population.
• Example: Market researchers use surveys to gather feedback on consumer preferences and trends.

12. Meta-Analysis: Synthesizing Evidence

Meta-analysis is a powerful statistical technique that combines the results of multiple studies on a similar topic to draw robust conclusions and insights.

• Purpose: Synthesize existing research findings for stronger conclusions.
• Method: Aggregate and analyze data from numerous studies.
• Example: Medical researchers perform meta-analysis to assess the overall effectiveness of treatment across multiple clinical trials.

Choosing the Right Research Method

Selecting the appropriate research method is crucial for achieving valid and reliable results. Consider the following factors when deciding on a research approach:

• Research Objectives: Clearly define your goals and questions to guide method selection.
• Data Type: Determine whether you need quantitative, qualitative, or mixed-methods data.
• Resources: Evaluate available time, budget, and technology.
• Ethical Considerations: Ensure compliance with ethical standards in data collection and analysis.

By understanding these diverse research methodologies and strategically employing best practices, researchers can effectively communicate their findings and contribute to the broader field of knowledge.

Learn more: What is Research Design?

Conducting research involves a systematic and organized process that follows specific steps to ensure the collection of reliable and meaningful data. The research process typically consists of the following steps:

Step 1. Identify the Research Topic

Choose a research topic that interests you and aligns with your expertise and resources. Develop clear and focused research questions that you want to answer through your study.

Step 2. Review Existing Research

Conduct a thorough literature review to identify what research has already been done on your chosen topic. This will help you understand the current state of knowledge, identify gaps in the literature, and refine your research questions.

Step 3. Design the Research Methodology

Determine the appropriate research methodology that suits your research questions. Decide whether your study will be qualitative , quantitative , or a mix of both (mixed methods). Also, choose the data collection methods, such as surveys, interviews, experiments, observations, etc.

Step 4. Select the Sample and Participants

If your study involves human participants, decide on the sample size and selection criteria. Obtain ethical approval, if required, and ensure that participants’ rights and privacy are protected throughout the research process.

Step 5. Information Collection

Collect information and data based on your chosen research methodology. Qualitative research has more intellectual information, while quantitative research results are more data-oriented. Ensure that your data collection process is standardized and consistent to maintain the validity of the results.

Step 6. Data Analysis

Analyze the data you have collected using appropriate statistical or qualitative research methods . The type of analysis will depend on the nature of your data and research questions.

Step 7. Interpretation of Results

Interpret the findings of your data analysis. Relate the results to your research questions and consider how they contribute to the existing knowledge in the field.

Step 8. Draw Conclusions

Based on your interpretation of the results, draw meaningful conclusions that answer your research questions. Discuss the implications of your findings and how they align with the existing literature.

Step 9. Discuss Limitations

Acknowledge and discuss any limitations of your study. Addressing limitations demonstrates the validity and reliability of your research.

Step 10. Make Recommendations

If applicable, provide recommendations based on your research findings. These recommendations can be for future research, policy changes, or practical applications.

Step 11. Write the Research Report

Prepare a comprehensive research report detailing all aspects of your study, including the introduction, methodology, results, discussion, conclusion, and references.

Step 12. Peer Review and Revision

If you intend to publish your research, submit your report to peer-reviewed journals. Revise your research report based on the feedback received from reviewers.

Make sure to share your research findings with the broader community through conferences, seminars, or other appropriate channels, this will help contribute to the collective knowledge in your field of study.

Remember that conducting research is a dynamic process, and you may need to revisit and refine various steps as you progress. Good research requires attention to detail, critical thinking, and adherence to ethical principles to ensure the quality and validity of the study.

Learn more: What is Primary Market Research?

Best practices for conducting research remain rooted in the principles of rigor, transparency, and ethical considerations. Here are the essential best practices to follow when conducting research in 2023:

1. Research Design and Methodology

• Carefully select and justify the research design and methodology that aligns with your research questions and objectives.
• Ensure that the chosen methods are appropriate for the data you intend to collect and the type of analysis you plan to perform.
• Clearly document the research design and methodology to enhance the reproducibility and transparency of your study.

2. Ethical Considerations

• Obtain approval from relevant research ethics committees or institutional review boards, especially when involving human participants or sensitive data.
• Prioritize the protection of participants’ rights, privacy, and confidentiality throughout the research process.
• Provide informed consent to participants, ensuring they understand the study’s purpose, risks, and benefits.

3. Data Collection

• Ensure the reliability and validity of data collection instruments, such as surveys or interview protocols.
• Conduct pilot studies or pretests to identify and address any potential issues with data collection procedures.

4. Data Management and Analysis

• Implement robust data management practices to maintain the integrity and security of research data.
• Transparently document data analysis procedures, including software and statistical methods used.
• Use appropriate statistical techniques to analyze the data and avoid data manipulation or cherry-picking results.

5. Transparency and Open Science

• Embrace open science practices, such as pre-registration of research protocols and sharing data and code openly whenever possible.
• Clearly report all aspects of your research, including methods, results, and limitations, to enhance the reproducibility of your study.

6. Bias and Confounders

• Be aware of potential biases in the research process and take steps to minimize them.
• Consider and address potential confounding variables that could affect the validity of your results.

7. Peer Review

• Seek peer review from experts in your field before publishing or presenting your research findings.
• Be receptive to feedback and address any concerns raised by reviewers to improve the quality of your study.

8. Replicability and Generalizability

• Strive to make your research findings replicable, allowing other researchers to validate your results independently.
• Clearly state the limitations of your study and the extent to which the findings can be generalized to other populations or contexts.

9. Acknowledging Funding and Conflicts of Interest

• Disclose any funding sources and potential conflicts of interest that may influence your research or its outcomes.

10. Dissemination and Communication

• Effectively communicate your research findings to both academic and non-academic audiences using clear and accessible language.
• Share your research through reputable and open-access platforms to maximize its impact and reach.

By adhering to these best practices, researchers can ensure the integrity and value of their work, contributing to the advancement of knowledge and promoting trust in the research community.

Learn more: What is Consumer Research?

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Qualities of Qualitative Research: Part I

Many important medical education research questions cry out for a qualitative research approach: How do teacher characteristics affect learning? Why do learners choose particular specialties? How is professionalism influenced by experiences, mentors, or the curriculum? The medical paradigm, the “hard” science most often taught in medical schools, usually employs quantitative approaches. 1 As a result, clinicians 5 be less familiar with qualitative research or its applicability to medical education questions. For these why types of questions, qualitative or mixed qualitative and quantitative approaches 5 be more appropriate and helpful. 2 Thus, we wish to encourage submissions to the Journal of Graduate Medical Education that are for qualitative purposes or use qualitative methods.

This editorial is the first in a series of two, and it will provide an introduction to qualitative approaches and compare features of quantitative and qualitative research. The second editorial will review in more detail the approaches for selecting participants, analyzing data, and ensuring rigor and study quality in qualitative research. The aims of the editorials are to enhance readers' understanding of articles using this approach and to encourage more researchers to explore qualitative approaches.

Theory and Methodology

Good research follows from a reasonable starting point, a theoretical concept or perspective. Quantitative research uses a positivist perspective in which evidence is objectively and systematically obtained to prove a causal model or hypothesis; what works is the focus. 3 Alternatively, qualitative approaches focus on how and why something works, to build understanding. 3 In the positivist model, study objects (eg, learners) are independent of the researchers, and knowledge or facts are determined through direct observations. Also, the context in which the observations occur is controlled or assumed to be stable. In contrast, in a qualitative paradigm researchers might interact with the study objects (learners) to collect observations, which are highly context specific. 3

Qualitative research has often been differentiated from quantitative as hypothesis generating rather than hypothesis testing . 4 Qualitative research methods “explore, describe, or generate theory, especially for uncertain and ‘immature’ concepts; sensitive and socially dependent concepts; and complex human intentions and motivations.” 4 In education, qualitative research strives to understand how learning occurs through close study of small numbers of learners and a focus on the individual. It attempts to explain a phenomenon or relationship. Typically, results from qualitative research have been assumed to apply only to the small groups studied, such that generalizability of the results to other populations is not expected. For this reason, qualitative research is considered to be hypothesis generating, although some experts dispute this limitation. 5 table 1 presents a comparison of qualitative and quantitative approaches.

Quantitative Versus Qualitative Research

When Qualitative Studies Make Sense

Qualitative studies are helpful to understand why and how; quantitative studies focus on cause and effect, how much, and numeric correlations. Qualitative approaches are used when the potential answer to a question requires an explanation, not a straightforward yes/no. Generally, qualitative research is concerned with cases rather than variables, and understanding differences rather than calculating the mean of responses. 4 In-depth interviews, focus groups, case studies, and open-ended questions are often employed to find these answers. A qualitative study is concerned with the point of view of the individual under study. 6

For example, the changes in duty hours for residents in 2003 have generated many quantitative research articles, which have counted and correlated the changes in numbers of procedures, patient safety parameters, resident test results, and resident sleep hours. However, to determine why residents still sleep about the same number of hours since 2003, one could start from a qualitative framework in order to understand residents' decisions regarding sleep. Similarly, to understand how residents perceive the influence of resident work hour restrictions on aspects of professionalism, a qualitative study would start with the learners rather than by measuring and correlating scores on professionalism assessments. Because learning takes place in social environments characterized by complex interactions, the quantitative “cause and effect” model is often too simplistic. 7

A variety of ways to collect information are available to researchers, such as observation, field notes, reflexive journals, interviews, focus groups, and analysis of documents and materials; table 2 provides examples of these methods. Interviews and focus groups are usually audiorecorded and transcribed for analysis, whereas observations are recorded in field notes by the observer.

Potential Data Sources for Qualitative Research 8

After data collection, accepted methods are employed to interpret the data. Researchers review the observations and report their impressions in a structured format, with subsequent analysis also standardized. table 3 provides one example of an analysis plan. Strategies to ensure rigor in data collection and trustworthiness of the data and data analysis will be discussed in the second editorial in the series.

Iterative Team Process to Interpret Data 8

In contrast to quantitative methods, subjective responses are critical findings, both in participant responses and observer reactions. The unique or outlier response has value in contributing to understanding the experience of others, and thus individual responses are not lost in the aggregation of findings or in the development of research group consensus. 2 , 4 Qualitative methods acknowledge the “myth of objectivity” between researcher and subjects of study. 7 In fact, the researcher is unlikely to be a purely detached observer.

Ethical Issues

As qualitative researchers usually attempt to study subjects and interactions in their “natural settings,” ethical issues frequently arise. Because of the sensitive nature of some discussions as well as the relationship between researchers and participants, informed consent is often required. The very reason for doing qualitative research—to discover why and how, particularly for thorny topics—can lead to potential exposure of sensitive opinions, feelings, and personal information. Thus, consideration of how to protect participants from harm is essential from the very onset of the study.

Quality Assessment

Qualitative researchers need to show that their findings are credible. As with quantitative approaches, a strong research project starts with a basic review of existing knowledge: a solid literature search. However, in contrast to quantitative approaches, most qualitative paradigms do not look to find a single “truth,” but rather multiple views of a context-specific “reality.” The concepts of validity and reliability originally evolved from the quantitative tradition, and therefore their accepted definitions are considered inadequate for qualitative research. Instead, concepts of precision, credibility, and transferability are key aspects of evaluating a qualitative study. 9

Although some experts find that reliability has little relevance to qualitative studies, others propose the term “dependability” as the analogous metric for this type of research. Dependability is gained though consistency of data, which is evaluated through transparent research steps and research findings. 9 , 10 Trustworthiness and rigor are terms used to establish credible findings. One technique often used to enhance trustworthiness and rigor is triangulation, in which multiple data sources (eg, observation, interviews, and recordings), multiple analytic methods, or multiple researchers are used to study the question. 9 The overall goal is to minimize and understand potential bias while ensuring the researcher's “truthfulness” of interpretation. 9

A potentially helpful appraisal checklist for qualitative studies, developed by Coté and Turgeon, 11 is found in table 4 . This appraisal checklist has not been examined systematically. table 5 includes a list of terms commonly used in qualitative research. Approaches to ensure rigor and trustworthiness in qualitative research will be addressed in greater detail in Part 2.

Sample Quality Appraisal Checklist for Qualitative Studies 11 , a

Commonly Used Terms in Qualitative Research 8

Both quantitative and qualitative approaches have strengths and weaknesses; medical education research will benefit from each type of inquiry. The best approach will depend on the kind of question asked, and the best methods will be those most appropriate to the question. 4 To learn more about this topic, the references below are a useful start, as is talking to colleagues engaged in qualitative research at your institution or in your specialty.

Gail M. Sullivan, MD, MPH, is Editor-in-Chief, Journal of Graduate Medical Education; and Joan Sargeant, PhD, is Professor in the Division of Medical Education, Dalhousie University, Halifax, Nova Scotia, Canada.

What is Research Design? Characteristics, Types, Process, & Examples

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Ever felt like a hamster on a research wheel fast, spinning with a million questions but going nowhere? You've got your topic; you're brimming with curiosity, but... what next? So, forget the research rut and get your papers! This ultimate guide to "what is research design?" will have you navigating your project like a pro, uncovering answers and avoiding dead ends. Know the features of good research design, what you mean by research design, elements of research design, and more.

What is Research Design?

Before starting with the topic, do you know what is research design? Research design is the structure of research methods and techniques selected to conduct a study. It refines the methods suited to the subject and ensures a successful setup. Defining a research topic clarifies the type of research (experimental, survey research, correlational, semi-experimental, review) and its sub-type (experimental design, research problem, descriptive case-study).

There are three main types of designs for research:

1. Data Collection

2. Measurement

3. Data Analysis

Elements of Research Design 

Now that you know what is research design, it is important to know the elements and components of research design. Impactful research minimises bias and enhances data accuracy. Designs with minimal error margins are ideal. Key elements include:

1. Accurate purpose statement

2. Techniques for data collection and analysis

3. Methods for data analysis

4. Type of research methodology

5. Probable objections to research

6. Research settings

7. Timeline

8. Measurement of analysis

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Characteristics of Research Design

Research design has several key characteristics that contribute to the validity, reliability, and overall success of a research study. To know the answer for what is research design, it is important to know the characteristics. These are-

1. Reliability

A reliable research design ensures that each study’s results are accurate and can be replicated. This means that if the research is conducted again under the same conditions, it should yield similar results.

2. Validity

A valid research design uses appropriate measuring tools to gauge the results according to the research objective. This ensures that the data collected and the conclusions drawn are relevant and accurately reflect the phenomenon being studied.

3. Neutrality

A neutral research design ensures that the assumptions made at the beginning of the research are free from bias. This means that the data collected throughout the research is based on these unbiased assumptions.

4. Generalizability

A good research design draws an outcome that can be applied to a large set of people and is not limited to the sample size or the research group.

Research Design Process

What is research design? A good research helps you do a really good study that gives fair, trustworthy, and useful results. But it's also good to have a bit of wiggle room for changes. If you’re wondering how to conduct a research in just 5 mins , here's a breakdown and examples to work even better.

1. Consider Aims and Approaches

Define the research questions and objectives, and establish the theoretical framework and methodology.

2. Choose a Type of Research Design

Select the suitable research design, such as experimental, correlational, survey, case study, or ethnographic, according to the research questions and objectives.

3. Identify Population and Sampling Method

Determine the target population and sample size, and select the sampling method, like random, stratified random sampling, or convenience sampling.

4. Choose Data Collection Methods

Decide on the data collection methods, such as surveys, interviews, observations, or experiments, and choose the appropriate instruments for data collection.

5. Plan Data Collection Procedures

Create a plan for data collection, detailing the timeframe, location, and personnel involved, while ensuring ethical considerations are met.

6. Decide on Data Analysis Strategies

Select the appropriate data analysis techniques, like statistical analysis, content analysis, or discourse analysis, and plan the interpretation of the results.

What are the Types of Research Design?

A researcher must grasp various types to decide which model to use for a study. There are different research designs that can be broadly classified into quantitative and qualitative.

Qualitative Research

Qualitative research identifies relationships between collected data and observations through mathematical calculations. Statistical methods validate or refute theories about natural phenomena. This research method answers "why" a theory exists and explores respondents' perspectives.

Quantitative Research

Quantitative research is essential when statistical conclusions are needed to gather actionable insights. Numbers provide clarity for critical business decisions. This method is crucial for organizational growth, with insights from complex numerical data guiding future business decisions.

Qualitative Research vs Quantitative Research

While researching, it is important to know the difference between qualitative and quantitative research. Here's a quick difference between the two:

The research types can be further divided into 5 categories:

1. Descriptive Research

Descriptive research design focuses on detailing a situation or case. It's a theory-driven method that involves gathering, analysing, and presenting data. This approach offers insights into the reasons and mechanisms behind a research subject, enhancing understanding of the research's importance. When the problem statement is unclear, exploratory research can be conducted.

2. Experimental Research

Experimental research design investigates cause-and-effect relationships. It’s a causal design where the impact of an independent variable on a dependent variable is observed. For example, the effect of price on customer satisfaction. This method efficiently addresses problems by manipulating independent variables to see their effect on dependent variables. Often used in social sciences, it involves analysing human behaviour by studying changes in one group's actions and their impact on another group.

3. Correlational Research

Correlational research design is a non-experimental technique that identifies relationships between closely linked variables. It uses statistical analysis to determine these relationships without assumptions. This method requires two different groups. A correlation coefficient between -1 and +1 indicates the strength and direction of the relationship, with +1 showing a positive correlation and -1 a negative correlation.

4. Diagnostic Research

Diagnostic research design aims to identify the underlying causes of specific issues. This method delves into factors creating problematic situations and has three phases: 

• Issue inception
• Issue diagnosis
• Issue resolution

5. Explanatory Research

Explanatory research design builds on a researcher’s ideas to explore theories further. It seeks to explain the unexplored aspects of a subject, addressing the what, how, and why of research questions.

Benefits of Research Design

After learning about what is research design and the process, it is important to know the key benefits of a well-structured research design:

1. Minimises Risk of Errors: A good research design minimises the risk of errors and reduces inaccuracy. It ensures that the study is carried out in the right direction and that all the team members are on the same page.

2. Efficient Use of Resources: It facilitates a concrete research plan for the efficient use of time and resources. It helps the researcher better complete all the tasks, even with limited resources.

3. Provides Direction: The purpose of the research design is to enable the researcher to proceed in the right direction without deviating from the tasks. It helps to identify the major and minor tasks of the study.

4. Ensures Validity and Reliability: A well-designed research enhances the validity and reliability of the findings and allows for the replication of studies by other researchers. The main advantage of a good research design is that it provides accuracy, reliability, consistency, and legitimacy to the research.

5. Facilitates Problem-Solving: A researcher can easily frame the objectives of the research work based on the design of experiments (research design). A good research design helps the researcher find the best solution for the research problems.

6. Better Documentation: It helps in better documentation of the various activities while the project work is going on.

That's it! You've explored all the answers for what is research design in research? Remember, it's not just about picking a fancy method – it's about choosing the perfect tool to answer your burning questions. By carefully considering your goals and resources, you can design a research plan that gathers reliable information and helps you reach clear conclusions. 

Frequently Asked Questions

What are the key components of a research design, how can i choose the best research design for my study, what are some common pitfalls in research design, and how can they be avoided, how does research design impact the validity and reliability of a study, what ethical considerations should be taken into account in research design.

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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Home → Research

What is research- characteristics, importance, and objectives.

In this article, I will share the characteristics, importance, and objectives of the research…

Table of Contents

What is Research??

Research is a process through which an individual or the researcher helps to search the definite or useful information from the number of respondents to evaluate or solve the problem-related questions. In fact, research is an art of scientific investigation or technique.

In other words, some people say that research is a systematized effort to gain knowledge and it is a process of collecting, evaluating, and interpreting information to answer questions.

Characteristics of Research:

The characteristics of research include various points such as:-

1. Research should be controlled-

It should be controlled because of the relation between two or more variables are affected by each other (whether it is internal or external). If the research is not controllable, then it will not be able to design a particular research report .

2. Research should be rigorous-

It should be rigorous because it helps to follow the procedures to find out the answers related questions which are relevant and appropriate in nature. The research information consists of two types of sciences such as physical and social sciences. These two sciences are also varied from each other.

3. Research should be systematic-

Research should be systematic because if a researcher wants to do a perfect research design or process then it will have to evaluate or obtained the necessary information from the market in a systematic manner. It takes various steps to do a perfect or systematic research process and all the steps of procedures are interlinked to each other.

4. Research should be valid-

It means the information which is collected by the researcher can be the correct and verifiable by yourself (i.e,  researcher himself). If our collected information is fair or valid, then our research will also be ethical in nature.

5. Research should be empirical-

This means that any conclusion drawn is totally based upon ethical or hard evidence gathered information collected from observations and real-life experiences.

6. The foundation of knowledge-

Research is the foundation of knowledge for the purpose of knowledge and an important source for providing guidelines or norms for solving different social, business, or governmental problems. It is a variety of formal training which enables us to understand the new developments in one’s field in an efficient way.

 Importance or Objectives of the Research:

Research objectives help to identify the full purpose or attention of your research with the type of basic questions that will be noted. Explaining your research objectives means explaining what do I need to investigate and evaluate. The importance of research is also known as the objectives of the research . It includes various points such as:-

[ Q . What are the objectives of the research and What is the importance of research ??]…

1. To find out the real facts-

As we know, every type of research has its own object but the basic aim of the research is always to find out or obtained the information from the markets and societies and their number of respondents. A researcher evaluates or finds the real or exact information for our problem-related questions.

2. To achieve the new thoughts-

In this objective of the research , anybody can find new thoughts from the research. Research is the process of finding the exact information through proper observation, optimization, and experiments.

These are the scientific methods to find out or evaluate the information which is very necessary for evaluating the problem task.

3. To evaluate the information-

The first aim of the research is to find out the information and then evaluate them in an appropriate or efficient manner so that they can easily design the research problem and solve them also.

A researcher evaluates the information through various scientific approaches and methods, statistical analysis and procedures, and another type of tables and graphs.

4. To test a hypothesis-

In this objective of the research , the researcher does the causal relationship between the variables (it can also be said that the hypothesis testing research studies). The hypothesis testing study represents the number of actions like these terms:

(a) Making a formal statement,

(b) Selecting a significance level,

(c) Deciding the distribution use,

(d) Selecting a random sample and computing an appropriate value,

(e) Calculation of the probability,

(f) Comparing the probability.

5. To design or implement the research-

After the collection of all information, the researcher prepares the structure of a research design for the company so that they can easily describe or identify the structure of a particular research theme. The research designs can be broadcasted into two forms such as experimental designs and non-experimental designs.

After the structure of the research design, the researcher implements them in a problem and find out the optimum factor to solve them.

6. To improve the understanding-

In this objectives of the research , the researcher helps to improve the understanding of a particular topic by asking what else needs to be evidenced before the research is purposeful, or what knowledge could be assembled from a more focused investigation, or scrutiny of the existing findings.

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Literature Searching

Characteristics of a good research question

The first step in a literature search is to construct a well-defined question.  This helps in ensuring a comprehensive and efficient search of the available literature for relevant publications on your topic.  The well-constructed research question provides guidance for determining search terms and search strategy parameters.

A good or well-constructed research question is:

• Original and of interest to the researcher and the outside world
• It is clear and focused: it provides enough specifics that it is easy to understand its purpose and it is narrow enough that it can be answered. If the question is too broad it may not be possible to answer it thoroughly. If it is too narrow you may not find enough resources or information to develop a strong argument or research hypothesis.  
• The question concept is researchable in terms of time and access to a suitable amount of quality research resources.
• It is analytical rather than descriptive.  The research question should allow you to produce an analysis of an issue or problem rather than a simple description of it.  In other words, it is not answerable with a simple “yes” or “no” but requires a synthesis and analysis of ideas and sources.
• The results are potentially important and may change current ideas and/or practice
• And there is the potential to develop further projects with similar themes

The question you ask should be developed for the discipline you are studying. A question appropriate for Physical Therapy, for instance, is different from an appropriate one in Sociology, Political Science or Microbiology .

The well-constructed question provides guidance for determining search terms and search strategy parameters. The process of developing a good question to research involves taking your topic and breaking each aspect of it down into its component parts. 

One well-established way that can be used both for creating research questions and developing strategies is known as PICO(T). The PICO framework was designed primarily for questions that include clinical interventions and comparisons, however other types of questions may also be able to follow its principles.  If the PICO framework does not precisely fit your question, using its principles can help you to think about what you want to explore even if you do not end up with a true PICO question.

References/Additional Resources

Fandino W. (2019). Formulating a good research question: Pearls and pitfalls.   Indian journal of anaesthesia ,  63 (8), 611–616. 

Vandenbroucke, J. P., & Pearce, N. (2018). From ideas to studies: how to get ideas and sharpen them into research questions .  Clinical epidemiology ,  10 , 253–264.

Ratan, S. K., Anand, T., & Ratan, J. (2019). Formulation of Research Question - Stepwise Approach .  Journal of Indian Association of Pediatric Surgeons ,  24 (1), 15–20.

Lipowski, E.E. (2008). Developing great research questions. American Journal of Health-System Pharmacy, 65(17) , 1667–1670.

FINER Criteria

Another set of criteria for developing a research question was proposed by Hulley (2013) and is known as the FINER criteria. 

FINER stands for:

Feasible – Writing a feasible research question means that it CAN be answered under objective aspects like time, scope, resources, expertise, or funding. Good questions must be amenable to the formulation of clear hypotheses.

Interesting – The question or topic should be of interest to the researcher and the outside world. It should have a clinical and/or educational significance – the “so what?” factor. 

Novel – In scientific literature, novelty defines itself by being an answer to an existing gap in knowledge. Filling one of these gaps is highly rewarding for any researcher as it may represent a real difference in peoples’ lives.

Good research leads to new information. An investigation which simply reiterates what is previously proven is not worth the effort and cost. A question doesn’t have to be completely original. It may ask whether an earlier observation could be replicated, whether the results in one population also apply to others, or whether enhanced measurement methods can make clear the relationship between two variables.  

Ethical – In empirical research, ethics is an absolute MUST. Make sure that safety and confidentiality measures are addressed, and according to the necessary IRB protocols.

Relevant – An idea that is considered relevant in the healthcare community has better chances to be discussed upon by a larger number of researchers and recognized experts, leading to innovation and rapid information dissemination.

The results could potentially be important and may change current ideas and/or practice.

Cummings, S.R., Browner, W.S., & Hulley, S.B. (2013). Conceiving the research question and developing the study plan. In: Designing clinical research (Hulley, S. R. Cummings, W. S. Browner, D. Grady, & T. B. Newman, Eds.; Fourth edition.). Wolters Kluwer/Lippincott Williams & Wilkins. Pp. 14-22.    

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Research | Meaning, Types, Characteristics, Positivism

Research: Meaning, Types and Characteristics

When you say that you are undertaking a research study to find answers to a question, you are implying that the process;

• is being undertaken within a framework of a set of philosophies (approaches);
• uses procedures, methods, and techniques that have been tested for their validity and reliability ;
• is designed to be unbiased and objective .

Philosophies mean approaches, e.g., qualitative, quantitative, and the academic discipline in which you have been trained.

Validity means that correct procedures have been applied to find answers to a question.

Reliability refers to the quality of a measurement procedure that provides repeatability and accuracy.

Unbiased and objective means that you have taken each step in an unbiased manner and drawn each conclusion to the best of your ability and without introducing your own vested interest.

(Bias is a deliberate attempt to either conceal or highlight something).

Adherence to the three criteria mentioned above enables the process to be called ‘research’.

However, the degree to which these criteria are expected to be fulfilled varies from discipline to discipline and so the meaning of ‘research’ differs from one academic discipline to another.

The difference between research and non-research activity is, in the way we find answers: the process must meet certain requirements to be called research. We can identify these requirements by examining some definitions of research.

The word research is composed of two syllables, “ re” and “ search.” “ re” is a prefix meaning again, a new or over again and “ search” is a verb meaning to examine closely and carefully, to test and try, or to probe. Together they form a noun describing a careful, systematic, patient study and investigation in some field of knowledge, undertaken to establish facts or principles.

Research is a structured enquiry that utilizes acceptable scientific methodology to solve problems and create new knowledge that is generally applicable.

Scientific methods consist of systematic observation, classification and interpretation of data.

Characteristics of Research

Research is a process of collecting, analyzing and interpreting information to answer questions. But to qualify as research, the process must have certain characteristics: it must, as far as possible, be controlled, rigorous, systematic, valid and verifiable, empirical and critical.

Controlled – in real life there are many factors that affect an outcome. The concept of control implies that, in exploring causality in relation to two variables (factors), you set up your study in a way that minimizes the effects of other factors affecting the relationship. This can be achieved to a large extent in the physical sciences (cookery, bakery), as most of the research is done in a laboratory. However, in the social sciences (Hospitality and Tourism) it is extremely difficult as research is carried out on issues related to human beings living in society, where such controls are not possible. Therefore, in Hospitality and Tourism, as you cannot control external factors, you attempt to quantify their impact.

Rigorous -you must be scrupulous in ensuring that the procedures followed to find answers to questions are relevant, appropriate and justified. Again, the degree of rigour varies markedly between the physical and social sciences and within the social sciences.

Systematic -this implies that the procedure adopted to undertake an investigation follow a certain logical sequence. The different steps cannot be taken in a haphazard way. Some procedures must follow others.

Valid and verifiable -this concept implies that whatever you conclude on the basis of your findings is correct and can be verified by you and others.

Empirical -this means that any conclusion drawn are based upon hard evidence gathered from information collected from real-life experiences or observations.

Critical -critical scrutiny of the procedures used and the methods employed is crucial to a research enquiry . The process of investigation must be foolproof and free from drawbacks. The process adopted and the procedures used must be able to withstand critical scrutiny.

For a process to be called research, it is imperative that it has the above characteristics.

Types of Research

Research can be classified from three perspectives:

• Application of research study
• Objectives in undertaking the research
• Inquiry Mode employed

Based on Application:

From the point of view of the application, there are two broad categories of research:

• Pure Research
• Applied Research,

Pure research (Fundamental) involves developing and testing theories and hypotheses that are intellectually challenging to the researcher but may or may not have a practical application at the present time or in the future. The knowledge produced through pure research is sought in order to add to the existing body of research methods.

Applied research (Action Research) is done to solve specific, practical questions; for policy formulation, administration and understanding of a phenomenon. It can be exploratory but is usually descriptive . It is almost always done on the basis of basic research.

Applied research can be carried out by academic or industrial institutions. Often, an academic institution such as a university will have a specific applied research program funded by an industrial partner interested in that program.

Based on Objectives:

From the viewpoint of objectives, research can be classified as

• Descriptive
• Correlational
• Explanatory
• Exploratory

Descriptive research attempts to describe systematically a situation, problem, phenomenon, service or programme, or provides information about, say, the living condition of a community, or describes attitudes towards an issue.

Correlational research attempts to discover or establish the existence of a relationship/ interdependence between two or more aspects of a situation.

Explanatory research attempts to clarify why and how there is a relationship between two or more aspects of a situation or phenomenon.

Exploratory research is undertaken to explore an area where little is known or to investigate the possibilities of undertaking a particular research study ( feasibility study pilot study).

In practice, most studies are a combination of the first three categories.

Based on Inquiry Mode:

From the process adopted to find the answer to re search questions; the two approaches are:

• Structured approach
• Unstructured approach

Structured approach: The structured approach to inquiry is usually classified as quantitative research . Everything that forms the research process- objectives, design, sample, and the questions that you plan to ask of respondents- is predetermined. It is more appropriate to determine the extent of a problem, issue or phenomenon by quantifying the variation.

e.g . how many people have a particular problem? How many people hold a particular attitude?

Unstructured approach: The unstructured approach to inquiry is usually classified as qualitative research . This approach allows flexibility in all aspects of the research process.

It is more appropriate to explore the nature of a problem, issue or phenomenon without quantifying it. The main objective is to describe the variation in a phenomenon, situation or attitude.

e,g, description of an observed situation, the historical enumeration of events, an account of different opinions different people have about an issue, description of working condition in a particular industry.

Both approaches have their place in research. Both have their strengths and weaknesses.

In many studies, there is a combination of both qualitative and quantitative approaches.

For example, suppose you have to find the types of cuisine/accommodation available in a city and the extent of their popularity.

Types of cuisine are the qualitative aspect of the study as finding out about them entails a description of the culture and cuisine

The extent of their popularity is the quantitative aspect as it involves estimating the number of people who visit a restaurant serving such cuisine and calculating the other indicators that reflect the extent of popularity.

Positivism and Post-Positivism Approach

Positivism:.

Positivism argues for the existence of a true and objective reality that can be studied by applying the methods and principles of natural sciences and scientific inquiry. It maintains that “the object of study is independent of researchers; knowledge is discovered and verified through direct observations or measurements of phenomena; facts are established by taking apart a phenomenon to examine its component parts.” According to this paradigm, the role of the researcher is to provide material for the development of laws by testing theories.

Positivists believe in five principles which include

• Phenomenalism (knowledge confirmed by the senses can be regarded as knowledge),
• Deductivism (the purpose of theory is to generate hypotheses that can be tested to make laws),
• Inductivism (the gathering of facts provides the basis for laws and knowledge),
• Objectivism (science should be value-free) and
• Scientific statements

Post positivism:

Post Positivism is considered a contemporary paradigm that developed as a result of the criticism of positivism. Like positivists, post positivists also believe in the existence of a single reality, however, they acknowledge that reality can never be fully known and efforts to understand reality are limited owing to the human beings’ sensory and intellectual limitations.

The aim of post positivist research is also a prediction and explanation. Like positivists, post positivists also strive to be objective, neutral and ensure that the findings fit with the existing knowledge base. However, unlike positivists, they acknowledge and spell out any predispositions that may affect the objectivity

Positivism and post positivism was precluded from use in this study for several reasons. Firstly, research conducted under both of these paradigms is usually quantitative where a hypothesis is tested while the researcher remains objective and separate from the area of investigation.

Ref – Kumar, R. (2019). Resarch methodology: A step-by-step guide for beginners . Sage Publications Limited. https://www.ukessays.com/essays/psychology/rsearch-on-positivism-and-post-positivism-psychology-essay.php

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10 Qualities of a Good Researcher: Quest for Excellence

• Post author By admin
• November 9, 2023

Discover the essential 10 qualities of a good researcher! Uncover the traits that drive success in the world of research. Learn what it takes to excel in the quest for knowledge and innovation

Suppose a vast landscape of knowledge, uncharted and waiting to be discovered. Research is the compass guiding us through this territory, and at the helm of every great exploration stands a good researcher.

But what sets them apart? It’s not just knowledge; it’s a unique set of qualities that propel them towards understanding.

In this journey, we’ll uncover the very essence of a good researcher. We’ll delve into the top 10 qualities that define them. From unquenchable curiosity to unwavering perseverance, these qualities are the secret sauce behind their success in academia and exploration.

Whether you’re already treading the path of research or gearing up for the adventure, understanding and embracing these qualities will transform you into a research dynamo. So, let’s embark on this quest to unravel what makes a good researcher tick.

Table of Contents

10 Qualities of a Good Researcher

Check out the 10 qualities of a good researcher:-

1. Inquisitiveness: The Craving for Knowledge

Think of a good researcher as that friend who’s always full of questions. They’re the eternal curious cats of the academic world, forever wondering, forever seeking, and forever hungry for knowledge. It’s like they have a built-in “Why?” button that never switches off.

A good researcher’s inquisitiveness is like the spark that lights up a dark room. It’s what pushes them to ask the questions no one else has thought of and venture into uncharted territories. They’re the ultimate seekers, the champions of “What if?” and “Why not?” It’s this insatiable curiosity that keeps their research fresh, exciting, and always on the hunt for more knowledge.

2. Patience: Sifting Through Data

Imagine a good researcher as a treasure hunter in the vast desert of data. Research can sometimes feel like slogging through quicksand – slow, meticulous, and demanding. But here’s the thing: good researchers have an incredible treasure map, and it’s called “patience.”

They understand that research isn’t a race; it’s a journey. It’s about sifting through tons of data, the way a prospector pans for gold. Every grain of information matters, and they’re willing to invest the time needed to collect, analyze, and interpret data accurately.

This patience isn’t about twiddling thumbs; it’s about meticulously building the puzzle of knowledge, piece by piece. They understand that no detail is too small to be overlooked, and in the end, it’s these small pieces that complete the big picture.

Good researchers don’t rush; they savor the journey, knowing that the best discoveries often lie in the details. They are the patient architects of knowledge, and it’s their patience that ensures that no gem of information goes undiscovered.

3. Attention to Detail: Devil in the Details

In research, it’s the little things that matter most. A good researcher understands this like no other. They’re the ones who spot the faintest footprints in the sand and the almost invisible fingerprints on the glass because they know that in research, the devil truly lies in the details.

For them, every piece of information is a precious puzzle piece. They’re like puzzle enthusiasts, and they’re determined to find and fit every piece perfectly. Because, in their world, even the tiniest detail holds the potential to make or break a study.

In a realm where precision reigns supreme, good researchers are the vigilant guardians of information. They’re the ones who make sure no stone is left unturned, no detail is too minor, and it’s this unwavering attention to detail that transforms their research into something truly extraordinary.

4. Critical Thinking: Questioning the Norm

Let’s picture a good researcher as the ultimate rebel of the research realm. They don’t just follow the herd; they’re the ones breaking the mold, challenging established theories, and stirring up the intellectual pot. Their secret weapon? It’s called critical thinking.

Critical thinking is like their sidekick, the Watson to their Holmes. It’s their power to look at information with a discerning eye, to cut through the noise, and make informed judgments. Good researchers? They’ve got critical thinking in their toolkit, and they’re not afraid to use it.

They’re not content with nodding along to the norm. No, they’re the ones who dare to ask, “Why?” and “What if?” They’re the Sherlock Holmes of academia, seeking the hidden clues that others might overlook. They’re the explorers who venture beyond the boundaries of convention.

For them, curiosity isn’t just a casual interest; it’s a full-blown investigation. They’re the skeptics, the truth-seekers, and the challengers of the status quo. Because they know that the road to enlightenment is paved with skepticism and paved with profound insights.

In a world where knowledge is the ultimate treasure, good researchers are the rebels with a cause. They’re the ones who question, challenge, and redefine the norm, making the pursuit of knowledge a thrilling adventure.

5. Organization: Chaos to Clarity

Let’s paint a mental picture of a good researcher as the master organizer of the research universe. Picture this: researchers often find themselves wading through mountains of data, like explorers in an information jungle.

But what sets good researchers apart is their exceptional skill in turning chaos into clarity through one magic word – organization.

These researchers are like the conductors of a grand symphony, where data plays the melodious tunes. They understand that without a meticulously organized score, the music may fall into chaos.

This is why they keep their work structured and well-organized. It’s like having a treasure map to navigate through the data wilderness.

For them, organization isn’t just a preference; it’s a necessity. It ensures that every piece of data, every note in the symphony, can be easily accessed and referenced when needed. It’s the librarian’s skill of categorizing, labeling, and arranging knowledge in a way that makes sense.

In a world where data can be overwhelming, good researchers are the navigators who chart the course from chaos to clarity. They bring order to the information realm, making sure that every piece of data finds its place in the grand mosaic of knowledge.

6. Effective Communication: Sharing Insights

Imagine a good researcher as not just a discoverer of hidden treasures but also a gifted storyteller. Research isn’t merely about uncovering the unknown; it’s about sharing those discoveries with the world. Good researchers possess a unique superpower – effective communication.

They are the bards of academia, able to weave intricate tales of data and insight. It’s not enough to gather knowledge; they understand the importance of conveying it to their peers and the wider community. They’re like skilled translators, turning complex data into understandable narratives.

For them, research isn’t a solitary endeavor but a communal one. They can articulate their findings, transforming raw data into gems of wisdom. They speak not just to fellow researchers but to anyone who seeks understanding.

In a world where information is abundant but understanding can be scarce, good researchers are the bridges that connect data to meaning. They’re the ones who bring clarity to complexity, ensuring that their discoveries benefit not just themselves but all who thirst for knowledge.

7. Ethical Integrity: The Moral Compass

Picture a good researcher as a moral compass, always pointing in the direction of what’s right. In their world, there’s no room for ethical shortcuts; they’re the guardians of integrity, setting the highest standards.

Ethical conduct is their unwavering principle, not a mere guideline. These researchers tread the path of knowledge with profound respect for all beings, be it humans, animals, or the environment.

They understand that research isn’t just about facts and figures; it’s about the impact on the world.

They are the ethical warriors who ensure that every discovery is made with the utmost respect for boundaries. They’re the ones who hold the torch of integrity, even when the road gets dark and uncertain.

In a world where ethical dilemmas can cloud the way, good researchers are the beacons of moral clarity. They remind us that the pursuit of knowledge should always be illuminated by the light of ethics, leaving a positive and lasting legacy.

8. Adaptability: Rolling with Research’s Twists

Now, picture a good researcher as the ultimate research ninja. They know that in the world of research, surprises are the name of the game. What makes them exceptional? Their uncanny ability to adapt.

In their world, every research project is like a thrilling rollercoaster ride. They’re fully aware that not everything will go as planned.

But instead of dreading the unexpected, they welcome it with open arms. It’s not about dodging hurdles; it’s about using them as springboards for new discoveries.

Adaptability is their secret weapon. They don’t panic when faced with unexpected twists and turns; they thrive on them. They’re the daredevils of research, excited by the idea that every surprise brings a chance for a breakthrough.

They understand that research isn’t a linear path; it’s an expedition full of surprises. Good researchers approach each twist and turn as a new opportunity to learn, grow, and uncover the unknown.

9. Perseverance: Never Giving Up

Now, picture a good researcher as the indomitable hero of the research saga. The journey to groundbreaking discoveries is no walk in the park; it’s an epic adventure filled with obstacles and trials. What makes a good researcher extraordinary? Their unshakable perseverance.

In their world, setbacks are not dead ends; they are the very soil in which success takes root. They grasp that the path to pioneering research is not a sprint but a demanding marathon.

When confronted with challenges, they don’t retreat; they roll up their sleeves and forge ahead with unwavering resolve.

In their universe, perseverance is the North Star guiding them through the darkest nights of research. It’s the fire that keeps them warm when faced with the chilling winds of doubt.

They understand that every stumble is a lesson, every hurdle is an opportunity, and every fall is a chance to rise even higher.

In a realm where remarkable discoveries are born from sheer determination, good researchers are the embodiment of perseverance.

They don’t just weather the storms of research; they harness them to soar to new heights of understanding and innovation.

10. Problem-Solving Skills: Creative and Determined Issue Resolution

Think of a good researcher as a maverick in the world of problem-solving. They possess an innate ability to tackle research-related issues with a unique blend of creativity and unwavering determination. They’re not just issue-spotters; they’re issue-solvers.

In their realm, challenges aren’t roadblocks; they’re opportunities for innovation. Whether it’s deciphering a complex data conundrum, navigating unexpected research detours, or confronting formidable roadblocks, they approach each problem with a dash of unconventional thinking.

Their toolkit isn’t limited to traditional solutions; it includes a healthy dose of creativity. They know that sometimes the most extraordinary answers emerge from unconventional thinking.

When faced with adversity, they don’t back down; they dive headfirst into the challenge, armed with resourcefulness and an unyielding spirit.

In the world of research, where every obstacle conceals a chance for a groundbreaking discovery, these good researchers are the daring explorers.

They turn problems into springboards, propelling the journey of knowledge and unveiling new insights along the way.

What is the qualities of good researcher?

Exceptional researchers are a unique breed, possessing a blend of innate traits and developed skills that set them apart in the world of discovery. Here are the qualities that define an outstanding researcher:

Inherent Curiosity

Exceptional researchers are born with an insatiable curiosity about the world. They perpetually question, driven by an unrelenting thirst for knowledge. This curiosity fuels their exploration of new ideas and their deep dives into complex problems.

Independence and Initiative

They are fiercely independent, unafraid to challenge conventions and think outside the box. This independence empowers them to conduct research with rigor and objectivity, free from preconceived notions.

Critical Thinking

Exceptional researchers are expert critical thinkers. They scrutinize information, identifying biases and assumptions. This skill enables them to draw well-founded conclusions from their research, undeterred by misinformation.

Effective Communication

They are adept communicators, capable of presenting their findings clearly and concisely. Their ability to convey complex ideas is vital for sharing their discoveries with the broader scientific community.

Collaboration Prowess

Collaboration is second nature to them. Exceptional researchers seamlessly collaborate with others to achieve common research objectives. Their skill in teamwork is essential for handling large-scale research projects effectively.

Problem-Solving Expertise

Problem-solving is in their DNA. They spot issues, conceive and test solutions, and rigorously evaluate their effectiveness. This skill is the backbone of conducting thorough research.

In addition to these qualities, exceptional researchers boast an in-depth understanding of their chosen field. They stay abreast of the latest research findings and expertly apply this knowledge to their own work.

Furthermore, they adhere to ethical guidelines that govern research, conducting their inquiries responsibly and ethically.

Armed with these remarkable qualities, exceptional researchers not only expand our comprehension of the world but also contribute to solving critical problems and enhancing the quality of life for all.

What are the 7 major characteristics of research?

Research is a multifaceted endeavor, marked by seven pivotal characteristics that define its essence:

1, Empirical Foundation

At its core, research is grounded in empiricism. It shuns opinions, personal beliefs, and conjecture. Instead, it thrives on data and evidence drawn from real-world observations and experiments, bolstering its conclusions with solid support.

2. Systematic Approach

Research unfolds systematically, adhering to a meticulously designed process. It commences with defining the research question, identifying research methods, collecting data, rigorously analyzing it, and ultimately deriving well-founded conclusions. This systematic journey ensures both rigor and objectivity.

3. Logical Underpinning

Logic forms the backbone of research. It forges conclusions that harmonize seamlessly with the laws of logic, yielding findings that are not only profound but also reliable.

4. Cyclical Nature

Research possesses a cyclical essence. It commences with a question or problem, each exploration invariably begetting new inquiries. This continuous cycle propels researchers toward a deeper understanding of the ever-evolving world.

5. Analytical Rigor

Research demands meticulous data analysis. Researchers employ diverse analytical techniques to uncover patterns, trends, and relationships within the data. This scrutiny unveils the latent significance of the data, facilitating the derivation of meaningful conclusions.

6. Objective Stance

An unwavering objectivity characterizes research. Researchers diligently strive to avoid bias and partiality, ensuring that their personal beliefs or opinions exert no undue influence on their findings.

7. Replicability Standard

Research adheres to a replicability standard. Other researchers should be capable of replicating the study and achieving congruent results. This commitment to replicability bolsters the reliability and validity of research findings.

Incorporating these seven key characteristics, research emerges as a powerful tool for the exploration of the unknown, the validation of hypotheses, and the continuous advancement of knowledge.

What are the 3 important qualities of a good research?

When we delve into the world of outstanding research, we uncover the pillars that set it apart. Imagine these as the main characters in a compelling story:

1. Credibility

This is the unwavering foundation. Exceptional research is built on solid evidence and meticulous reasoning. It follows a rigorous and objective path, supported by thorough data and in-depth analysis.

2. Relevance

Consider this the heart of the matter. Exceptional research doesn’t shy away from addressing pressing questions and challenges.

It aims to contribute significantly to our understanding of the world and has the potential to solve crucial problems.

3. Originality

Think of this as the trailblazer, the innovator. Exceptional research ventures into uncharted territories, offering fresh and unique perspectives.

It doesn’t retrace well-worn paths; instead, it opens new doors to insights that haven’t been explored before.

These are the three pillars of remarkable research, igniting our quest to comprehend our world more deeply, confront significant challenges, and provide solutions that truly enhance our lives and the lives of those around us.

What are the 4 characteristics of a good research?

When we delve into the world of research, we discover the four cornerstones that define what makes research truly exceptional:

Imagine research as a sturdy ship navigating the vast sea of knowledge. What keeps it afloat? Credibility – the anchor of solid evidence and logical reasoning.

It’s about following a rigorous and objective methodology, with findings firmly supported by a wealth of data and meticulous analysis.

Good research is like a compass pointing to the critical questions and challenges that pique the curiosity of the research community and society.

It’s not just an exploration; it’s a journey with a purpose – to deepen our understanding of the world and unravel solutions to the most pressing problems.

Think of research as an explorer venturing into uncharted territory. It doesn’t follow the trodden paths; it forges its own.

Good research doesn’t echo what’s been said before; it blazes new trails, offering fresh insights and unique perspectives.

Effective research is a lighthouse, guiding others through the maze of complexity. Its findings are not buried in jargon or obscured by ambiguity.

They are presented with clarity and conciseness, ensuring that everyone can navigate the discoveries with ease.

These attributes, like the North Star, lead us in the pursuit of knowledge and understanding, casting light on the uncharted waters of research.

In the grand tapestry of knowledge, good researchers stand as the weavers of profound discovery. They embody a unique blend of qualities, shaping the course of understanding and change.

From the inquisitiveness that fuels their journey to the unwavering patience that carries them through the most intricate of labyrinths, these qualities are the compass, the guiding light.

The unquenchable curiosity of a good researcher keeps the embers of exploration burning bright. Patience, the steadfast companion, ensures that no detail remains in obscurity.

Their critical thinking propels them beyond the boundaries of convention, unraveling new layers of understanding.

In the chaos of data, they find serenity through organization, and in the midst of complexity, they wield the sword of effective communication.

Ethical integrity acts as their moral compass, while adaptability embraces the unpredictability of research’s twists.

But it’s perseverance, the indomitable spirit, that carries them through the darkest hours. They recognize that the path to groundbreaking research is often fraught with obstacles, but those obstacles serve as stepping stones to success.

These ten qualities, woven into the very fabric of their being, make good researchers the architects of transformation.

With every study they undertake, they draw closer to unraveling the mysteries of our world, bridging gaps in knowledge, and contributing to the betterment of humanity.

As we celebrate these qualities, we acknowledge the significance of their work. Through their endeavors, we glimpse the limitless potential of human exploration, and we are inspired to never cease questioning, exploring, and, above all, learning.

Frequently Asked Questions

Can anyone become a good researcher.

Yes, with dedication and a willingness to develop these qualities, anyone can become a good researcher.

Why is adaptability crucial for a researcher?

Research is unpredictable, and adaptability allows researchers to navigate unexpected challenges effectively.

What role does ethics play in research?

Ethical integrity is vital in research to ensure the well-being of participants and the integrity of the study.

How do researchers maintain their inquisitiveness?

Researchers stay curious by continually seeking new questions and exploring uncharted territories in their field.

Is critical thinking a natural talent, or can it be developed?

Critical thinking can be developed through practice and a commitment to questioning and evaluating information.

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What is Research? Types, Purpose, Characteristics, Process

• Post last modified: 26 August 2021
• Reading time: 13 mins read
• Post category: Research Methodology

• What is Research?

Research means a systematic and objective study to find facts which can be answers to questions and solutions to problems.

Social sciences Encyclopedia defines research as the manipulation of things, concepts or symbols for the purpose of generalizing to extend, correct as to verify knowledge, whether that knowledge aid in the construction of a theory or in the practice of art.

Table of Content

• 1 What is Research?
• 2.1 Basic or pure research
• 2.2 Applied or practical research
• 3 What is Social Research?
• 4 Purpose of Research
• 5 Characteristics of Research
• 6 Research process

In a different way effort to reach definiteness or certainty, to collect facts and ascertain truth constitute research. In research, we examine facts for truth. When facts are repeatedly examined and tested, truth is established. This leads to certainty and incorporates a generalization which is unique.

Types of Research

Basically, research is classified in two types.

Basic or pure research

Applied or practical research.

Basic or pure research explores broad, inclusive laws, rules, theories and tendencies with precise causation. Pure research is an intellectual response to great questions and seemingly difficult causal complexities.

Theory of gravity (Newton), a theory of relativity (Einstein), and birth of the universe theory (Hoyle and Naralikar theory) are examples of pure research. Such pure research may or may not be practical and socially useful immediately.

Applied or practical research aims at making existing, available knowledge useful in solving present problems of the society and individuals vis-a-vis production, distribution, consumption, and minimization of pain.

What is Social Research?

According to Pauline Young, social research is defined in the following words. “We may define social research as the systematic method of discovering new facts or verifying old facts, through sequence, interrelationship, causal explanations and the natural laws which cover them.

Prof. M. H. Copal, a senior Indian social scientist defined social research as the study of phenomena resulting from an interaction between different human groups in the process of their living together.

This study helps us in generalizing, theorizing and policy planning.

Social research is intrinsically dynamic and involves a large number of variables, some controllable some not so controllable.

As a result, social research involves a process of continuous revision of existing laws, theories, periodic refutation and/or modification of the same laws and theories. Freshly generated or collected data i.e. primary data give us new insights and evidence to arrive at new conclusions.

Purpose of Research

Purpose and functions of social research can be enumerated as below

• Search for truth
• Application of knowledge for better human life.
• Examining phenomena or events for identifying causes and establishing generalizations, and theories about human behaviour.
• Predicting the future on the basis of existing knowledge and study methods.
• Verifying, correlating or modifying existing generalizations or theories, differences of opinion and settling debates if any.

Characteristics of Research

Following are the essential characteristics of an ideal researcher.

• An unquenchable and strong desire to find out the truth
• Ability to identify similarity in diverse situations and diversity in similar Situations
• Curiosity, quest, doubt, patient, slow thinking, willingness to reexamine, discipline, no dogmatism are according to Francis Beacon, essential attributes of a researcher
• insistence for data
• caution in statements
• clear right/understanding
• awareness about multiplicity in varied social interrelations
• According to Carl Pearson, disciplined imagination is the distinguishable characteristics of an ideal researcher
• According to Sidney and Beatrice Web, a researcher must always avoid the influence of his personal biases
• A researcher, according to C. Luther Fry, must possess intellectual honesty and integrity
• According to Spaher and Swanson, a researcher must love his work, have abundant patience and perseverance, insist on authority and correctness of data, posses equity of consideration, thoughtfulness, and broadly responsible and always focused

Research process

To make your research efforts successful and socially meaningful, the whole approach has to be carefully planned and executed step by step in a scientific and logical way. It is, therefore, necessary to explain and present steps and design of any research work carefully.

Following are the steps in research process:

• Explain the objectives of research, present the problem and state the hypothesis/es.
• Elaborate on the research design mainly with reference to methodology of data collection and analysis.
• System of data collection with clear understanding of sampling techniques and/or census approach.
• Description, tabulation, coding, analysis of data and statement of analytical results/findings.
• Interpretation of these findings/results and reaching objective conclusions.
• Attempting reliable prediction.

Selection of the research topic/question is the first critically important step. Practical problems, emerging needs, scientific curiosity, intellectual quest values of life, life experiences are the main sources of research topics or questions.

Secondly, formation of the hypothesis is the next step. Before we start collecting, tabulating and analyzing data, it is necessary to have ‘a priori’ causal relationship which may explain the phenomenon under study, this is known as hypothesis/es.

A hypothesis/es explain the cause-effect relationship at a logical level. The hypothesis gives us basic concepts on the basis of which we collect data generate data, for empirical evidence.

In formulation of hypothesis, we in a way, organize our research question in a scientific way. The words hypothesis and concepts are explained elaborately in subsequent units.

In formulating research question and research design it is necessary that

• the researcher has advanced in-depth reading in related literature,
• he is fully aware of the current theories and research in related area
• he has close interaction with peers in the field and
• he must possess an inquisitive imaginative scientific mindset.

Thirdly, it is necessary to have a well planned research design. It helps in focussing work, precise explanation of events / questions and most importantly a research design helps in minimization of variance in the research system.

According to R. L. Ackoff there are two types of research design- Ideal Research Design – a design without practical limitation, the other research design is practical / feasible research design. In this, we consider limitations like time, resources availability of data and intellectual skills of the researcher.

Normally a practical research design has four important constituents.

• Sampling Design
• Statistical design
• Observational Design
• Operational Design

In preparing a practical research design, the researcher has to consider following aspects,

i. What is the primary research focus? ii. What is the data required for the research? iii. What are the exact objectives of the research? iv. Sources of data? v. Places to be visited for research vi. Time limits vii. A number of entities to be involved in the research viii. Criteria of sampling ix. Methods of data collection x. Methods of data coding classification and tabulation. xi. Material / financial resources available for research.

Broadly, there are five types of research design, according to Mac-Grant.

i. Controlled experiment ii. Study / case study iii. Survey sample / census iv. Investigation v. Action research

According to Seltiz and others, there are basically three types of research design,

i. Exploratory or formulative ii. Descriptive or diagnostic iii. Studies testing causal hypothesis.

Exploratory research relies heavily on review of literature, review of experience and entities/cases encouraging intuitions or inspiration. This depends heavily on the attitude of scientist, intensity of/or depth of his study/integrative powers of the researcher normally, reaction of indifferent individuals, behaviour of marginal individuals/groups, developmental transition, isolates, deviants and pathological cases and pure cases constitute factors which induce a researcher to explore.

In the case of many social sciences, majority of researchers collect and describe information regarding various groups, communities and sets of experiences consumption patterns, saving habits, investment, likes and dislikes, work culture, price responses, management decisions and practices, entrepreneurial behaviours, business leadership etc are such areas of research.

In the case of studies testing causal hypothesis the main objective of research is to verify an assumed causation, either positively or negatively. In such researches, experimental method is more frequently used.

However, with the passage of time and revolutionary changes in technology of analysis, experimental method is now used, as in natural sciences, in social sciences also. In a very formal way experiment is a way of organizing evidence so as to reach inference about the appropriateness of a hypothesis which essentially is a statement of relationship between a cause (set of causes) and a result (set of results).

In the case of experimental design two approaches are mainly practiced

• after only experiment
• before after experiment.

Business Ethics

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• What is Ethics?
• What is Business Ethics?
• Values, Norms, Beliefs and Standards in Business Ethics
• Indian Ethos in Management
• Ethical Issues in Marketing
• Ethical Issues in HRM
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• What is Corporate Governance?
• What is Ownership Concentration?
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Corporate social responsibility (CSR)

• Theories of CSR
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Lean Six Sigma

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• Lean Techniques for Optimisation Flow
• Failure Modes and Effects Analysis (FMEA)
• What is Process Audits?
• Six Sigma Implementation at Ford
• IBM Uses Six Sigma to Drive Behaviour Change
• Research Methodology

What is Hypothesis?

• Sampling Method
• Research Methods
• Data Collection in Research
• Methods of Collecting Data
• Application of Business Research
• Levels of Measurement
• What is Sampling?

Hypothesis Testing

Research report.

• What is Management?
• Planning in Management
• Decision Making in Management
• What is Controlling?
• What is Coordination?
• What is Staffing?
• Organization Structure
• What is Departmentation?
• Span of Control
• What is Authority?
• Centralization vs Decentralization
• Organizing in Management
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Operations Research

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Operation Management

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• Supply Chain Process Restructuring
• Points of Differentiation
• Re-engineering Improvement in SCM
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• Supply Chain Operations Reference (SCOR) Model
• Customer Service and Cost Trade Off
• Internal and External Performance Measures
• Linking Supply Chain and Business Performance
• Netflix’s Niche Focused Strategy
• Disney and Pixar Merger
• Process Planning at Mcdonald’s

Service Operations Management

• What is Service?
• What is Service Operations Management?
• What is Service Design?
• Service Design Process
• Service Delivery
• What is Service Quality?
• Gap Model of Service Quality
• Juran Trilogy
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• IT Service Operation
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Procurement Management

• What is Procurement Management?
• Procurement Negotiation
• Types of Requisition
• RFX in Procurement
• What is Purchasing Cycle?
• Vendor Managed Inventory
• Internal Conflict During Purchasing Operation
• Spend Analysis in Procurement
• Sourcing in Procurement
• Supplier Evaluation and Selection in Procurement
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• Incoterms in Procurement
• Documents Used in International Procurement
• Transportation and Logistics Strategy
• What is Capital Equipment?
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• E-marketplace and Online Catalogues
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Strategic Management

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• Mission Statement
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• What is Ansoff Matrix?
• Prahalad and Gary Hammel
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• Five Competitive Forces That Shape Strategy
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• Fragmentation and Consolidation Of Industries
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• Resources and Capabilities of Organization
• Role of Leaders In Functional-Level Strategic Management
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Supply Chain

• What is Supply Chain Management?
• Supply Chain Planning and Measuring Strategy Performance
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Top 10 Qualities and Characteristics of a Good Researcher

Year after year, people with different personalities and backgrounds step into the field of research eager to develop the key qualities of a good researcher , only to find themselves faced with anxiety and self-doubt. Becoming a good researcher is a challenging task that requires a combination of skills and attributes as well as time, dedication, and a lot of hard work.   

So what are the qualities of a good researcher and how does one build these must-have characteristics? This article answers this by sharing the top 10 qualities of a good researcher that you must work to develop, strengthen, and apply on your journey to research success.   

Table of Contents

Top 10 qualities of a good researcher  

• Curiosity:  A curious mind and an ability to look at things from different perspectives is what makes a good researcher better. Good researchers are observant about the world around them and open to new ideas and possibilities; they are always asking questions and looking for answers. This ability to see the bigger picture while being curious about the smaller details is what makes a good researcher explore new ideas, test hypotheses, and make new discoveries.
• Critical thinking:  Successful researchers can think critically about the information they gather while reading about new developments in their own and related fields. This is an essential characteristic of a good researcher . Instead of simply accepting existing knowledge as fact, you need to have the ability to analyze and evaluate the validity and reliability of sources, consider alternative explanations for results you observe, and find connections between seemingly unrelated concepts.

• Creativity:  The qualities of a good researcher do not just include curiosity and critical thinking, but also thinking creatively when it comes to problem solving. Nurturing the ability to think outside the box and come up with novel and often unconventional solutions to challenges you face is how to become a better researcher. This allows you to come up with more ground-breaking research studies and results addressing issues that others might easily miss.
• Objectivity:  Nurturing preconceived notions is detrimental to research. Avoid temptations to make unconclusive statements or introduce personal biases into research, which will impact your research and standing in the long run. Remember, building essential qualities of a good researcher means consciously keeping aside personal preferences and biases and applying sound judgement to your work even when under pressure.
• Collaborative spirit:  An important characteristic of a good researcher is being able to work well with others. With a shift toward more collaborative research, successful researchers often connect with and work with peers to come up with innovative approaches to research problems. While sharing ideas and partnering with other researchers can lead to breakthroughs and boost your researcher reputation, it also opens the door for your work to reach and potentially benefit a wider audience.
• Communication skills:  An added strength of a good researcher is being able to communicate your findings clearly and effectively, which is a key contributor to your success. This is applicable when writing your manuscripts, presenting at conferences, as well as when seeking funding for your work. Good researchers can explain their research to both specialists and non-specialists to ensure their work is understood and appreciated by a wider audience.
• Attention to detail:  One of the key qualities of a good researcher is being meticulous in your work. Researchers need to pay attention to every detail, from the design of an experiment to the analysis of data, and further in writing and submitting their manuscript for publication. This crucial characteristic can help you ensure your research is accurate, testable, and reliable, and also gives your manuscripts a better chance of acceptance.
• Time management:  To understand what are the characteristics of a good researcher , first ask yourself if you manage your time well. Most successful researchers organize, prioritize, and optimize their time efficiently, allowing them to not only keep up with their responsibilities but also make time for personal tasks. If you’re being pulled in different directions or overwhelmed with trying to manage your research, stay updated on your research reading, or meeting your writing deadlines, consider honing this skill as a prerequisite to becoming a good researcher.
• Persistence & flexibility:  Research can be a long, difficult process with several hurdles and changes along the way. One of the key requirements to becoming a good researcher is being able to adapt to new technologies and changing circumstances and persevere despite setbacks and challenges that inevitably arise. Developing the qualities of a good researcher means anticipating problems, adjusting plans to tackle challenges head-on, and being patient while moving forward toward achieving your goals.
• Focus on self-care:  Anxiety, stress, and mental health issues are common among academics. Successful researchers are better equipped to manage this by adopting a healthy balanced lifestyle. Understanding what works for you can also improve your efficiency and productivity. Being aware of your strengths and weaknesses and using this to your advantage is key to becoming a good researcher.

In conclusion, perfecting the characteristics of a good researcher is not quick or easy, but by working consistently toward developing or strengthening these essential qualities, you will be well on your way to finding success as a well-established researcher.  

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CUR Releases Updated ‘Characteristics of Excellence in Undergraduate Research’ to Serve as a Roadmap to Building Impactful Undergraduate Research Experiences  

As the leading voice in undergraduate research, the Council on Undergraduate Research (CUR) recognizes the critical need for comprehensive, adaptable guidelines that set the standard for excellence in this field. In 2012, CUR published its first edition of the Characteristics of Excellence in Undergraduate Research ( COEUR ), which contained twelve characteristics that describe a roadmap of best practices. In 2015, COEUR served as a guideline for the establishment of the campus-wide Award for Undergraduate Research Accomplishments (AURA). The 23 campuses that have received this highly sought-after award to date, crafted exemplary undergraduate research programs with sustained metrics of their impact. COEUR has been a critical guide in the success of undergraduate research and a foundation to follow for many institutions globally.  

After ten years, a working group of leaders was appointed by then-CUR President Ruth Palmer to evaluate  COEUR  and update it for the next era. This team of four, Lourdes Echegoyen, Winny Dong, Buffie Longmire-Avital, and Jeanne Mekolichick, with support from one of the original authors Linda Blockus, took the next two years to review, research, seek input, and update these characteristics to then put forward COEUR 2.0 .  

“As an original author of COEUR , I am delighted that we have updated the document.  A lot has changed over the past 12 years, and as the national voice on the practice of undergraduate research, CUR continues to be a proactive leader. This document provides a blueprint for creating and sustaining campus environments where undergraduate research can flourish,” Stated Linda Blockus, Director of Undergraduate Research at the University of Missouri.  

In COEUR 2.0 , the authors have made several updates. The number of characteristics has been streamlined from 12 to 11, with the Strategic Planning characteristic now incorporated into the Campus Mission and Culture. Diversity, equity, inclusion, and access have now been strongly emphasized throughout the work, along with highlighting the power of integrating research, scholarly work, and creative inquiry with other high-impact practices, such as community engagement, study abroad, internship, and work-based learning. In addition, separate chapters on these topics have been added to provide the best approaches for research ethics training. Overall, COEUR 2.0 maintains the best practices that support and sustain highly effective undergraduate research environments.  

As described by Winny Dong, one of the 2.0 editors, Professor of Chemical and Materials Engineering, California State Polytechnic University, Pomona, “Working on COEUR 2.0 has been a true pleasure. Not only did it allow me to reacquaint myself with the essential tenets of COEUR , but it also allowed me to envision what those tenets might look like in light of what we have learned about serving students over the past 12 years. I am especially happy to see that inclusive practices have been threaded throughout all of the characteristics in COEUR 2.0 and that a broader set of voices have been included (community colleges, transfer students, non-traditional students, etc.) I hope that others will find that these characteristics of excellence in undergraduate research can help them assess where they are in their journey to provide meaningful undergraduate research for students and be inspired to continue on that journey of reflection and improvement.” 

As a user of COEUR and second edition editor, Buffie Longmire-Avital, Professor of Psychology and Director of the Black Lumen Project at Elon University, explains, “ My faculty career to this point has been at Elon University, an institution that openly embraced COEUR to develop our undergraduate research program. It was a wonderful opportunity to connect with and reflect on the document that has been both directly and indirectly influential to my career as an undergraduate research mentor. COEUR 2.0 centers access, equity, and inclusion in a way that captures not only the diversity that we have in higher education, but also the growing diversity we will have. COEUR 2.0 builds off the conversations, trainings, and efforts CUR and undergraduate research programs have been challenged to engage with. In this version, undergraduate research is an equity driving vehicle not simply a possibility or hope of what it could be. The attention to voices, experiences, and nuanced contexts hopefully not only makes COEUR 2.0 more relatable but provides multiple pathways to excellence in undergraduate research that is accessible to a variety of programs and institutions.” 

In CUR’s experience, successful programs exhibit many of the characteristics enumerated in this document. A sneak peek of these 11 characteristics was showcased in June 2024 at CUR’s Annual ConnectUR conference in College Park, MD. The editors were able to host a working plenary to showcase case studies and walk attendees through the COEUR assessment.  

“ It has been such a wonderful experience working alongside a talented group of URSCI experts to update this important resource guiding our community. Following the positive impact of the first edition, I expect COEUR 2.0 to make an equally important impact in guiding URSCI offices, support, faculty, and programming,” says Jeanne Mekolichick, second edition editor, Professor of Sociology and Associate Provost for Research, Faculty Success & Strategic Initiatives at Radford University. “I’m particularly excited to have DEI infused throughout as these values are foundational to CUR and their treatment in this edition will help folks operationalize at their institutions. I am equally excited to articulate and highlight the connection between the benefits of URSCI and career readiness. Leveraging URSCI for career success has not historically been top of mind for faculty and students. Infusing the URSCI-career readiness connections in COEUR is a valuable next step in providing resources and direction for faculty and programs.” 

Maria T. Iacullo-Bird, CUR 2024-2025 President, Assistant Provost for Research at Pace University, explained, “The newly revised Characteristics of Excellence in Undergraduate Research (COEUR 2.0) provides a masterful pedagogical update that exemplifies CUR’s long-standing intellectual leadership for the undergraduate research community.”  

COEUR 2.0 is published electronically in individual chapters for easy consumption and as a full ePub on our website at www.CUR.org/COEUR2 on August 20, 2024.  

Founded in 1978, the  Council on Undergraduate Research  (CUR) focuses on providing high-quality and collaborative undergraduate research, scholarly, and creative activity. Among the many activities and networking opportunities that CUR provides, the organization also offers support for the professional growth of faculty and administrators through expert-designed institutes, conferences, and a wide-range of volunteer positions. The CUR community, made up of nearly 700 institutions and 13,000 individuals, continues to provide a platform for discussion and other resources related to mentoring, connecting, and creating relationships centered around undergraduate research. CUR’s advocacy efforts are also a large portion of its work as they strive to strengthen support for undergraduate research. Its continued growth in connections with representatives, private foundations, government agencies, and campuses world-wide provides value to its members and gives voice to undergraduate research. CUR is committed to inclusivity and diversity in all of its activities and our community.

CUR focuses on giving a voice to undergraduate research with learning through doing. It provides connections to a multitude of campuses and government agencies, all while promoting networking and professional growth to its community.

By Todd Waggoner

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Methodology

• Descriptive Research | Definition, Types, Methods & Examples

Descriptive Research | Definition, Types, Methods & Examples

Published on May 15, 2019 by Shona McCombes . Revised on June 22, 2023.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when and how   questions , but not why questions.

A descriptive research design can use a wide variety of research methods  to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

Table of contents

When to use a descriptive research design, descriptive research methods, other interesting articles.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when and where it happens.

Descriptive research question examples

• How has the Amsterdam housing market changed over the past 20 years?
• Do customers of company X prefer product X or product Y?
• What are the main genetic, behavioural and morphological differences between European wildcats and domestic cats?
• What are the most popular online news sources among under-18s?
• How prevalent is disease A in population B?

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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. Common uses of surveys include:

• Describing the demographics of a country or region
• Gauging public opinion on political and social topics
• Evaluating satisfaction with a company’s products or an organization’s services

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event or organization). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalizable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

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.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

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

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McCombes, S. (2023, June 22). Descriptive Research | Definition, Types, Methods & Examples. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/methodology/descriptive-research/

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Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics

Invasive dreissenid mussels (Dreissena polymorpha and Dreissena rostriformis bugensis) have altered Great Lakes ecosystems through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict Dreissena spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with Dreissena spp. biomass. Point observations from the 2017 Lake Huron benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for in situ measurements of dreissenid presence and biomass at 119 sites across Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.

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Can we grow veggies designed to combat diabetes? Manitoba researchers hope so

U of m scientists team with remote first nation to grow more nutritious vegetables, teach locals to love them.

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Researchers at the University of Manitoba are working with a northern First Nation to develop vegetables with increased nutritional characteristics that may help combat health conditions like diabetes. But they also have to convince local folks to eat them.

"There's a lot of stigma that we were met with," said Stephanie R. Cook, Opaskwayak Cree Nation (OCN) smart farm operations manager. "People were like, 'Oh … it's artificial, it's fake food.' "

Cook understands this hesitancy, because in her first few months on the job, she was also too scared to eat the produce. Coming from a traditional background, she says she was taught that food comes from the earth, not from a lab.

"It was funny, because the first time I ate it, I was actually surprised at the freshness. You know, normally, coming from the north, you're not used to getting such fresh product unless it's coming from the garden in the summer."

Healthier veggies by way of a vertical 'smart farm'

The vertical smart farm was established by the OCN as a pilot project in 2016 to see if they could grow vegetables faster all year round, providing fresher, less expensive produce to the remote northern community about 520 kilometres northwest of Winnipeg, where it's difficult to grow vegetables year round and expensive to transport and buy them.

• Northern Manitoba First Nation aims to help feed community, fight diabetes with expanded vertical farm project
• Year-round garden provides free fresh vegetables to hundreds on Manitoba's Opaskwayak Cree Nation

The plants are grown hydroponically in stacked layers, without soil, which means a smaller carbon footprint than traditional farming. Blue, red and green LED lights mimic sunshine. Artificial intelligence controls temperature, moisture, carbon dioxide and nutrient levels. 

When the smart farm was first started, it  provided vegetables to OCN families at no cost through food programs at the local health centre, trying to encourage healthier diets. Now, the focus has turned to research. 

Fighting diabetes

OCN has about 4,652 members, about 2,850 of whom live on reserve. Almost half of the adult population on OCN is suffering from type two diabetes, said N. Glen Ross, the executive director of the Opaskwayak Health Authority.

"We were averaging probably about two to three deaths a month based on diabetes-related issues," Ross said.

In an effort to change this, OCN teamed up with Miyoung Suh and her team from the University of Manitoba, and the Canadian Centre for Agri-Food Research in Health and Medicine at the St. Boniface Hospital Albrechtsen Research Centre. Suh has received several grants to support the smart farm and her research there.

The team has experimented with different growing, harvesting and post-harvest processing conditions and found some made the vegetables more nutritious and possibly better at slowing the progression of diabetes. 

"We are trying to mitigate the prevalence of type 2 diabetes using vegetables as a source," said Ruchira Nandasiri, a University of Manitoba food scientist and postdoctoral fellow in Suh's laboratory. 

The smart farm is currently growing cabbage, broccoli and Brussels sprouts for research purposes only.

As part of their work, the team has discovered ways to manipulate the lights and nutrients to stimulate production of antioxidant compounds in the vegetables that impact obesity, blood glucose control, inflammation, blood pressure and heart function, Nandasiri said.

• Manitoba receives $500K funding grant to investigate soaring rates of Type 2 diabetes in kids
• Rate of new Type 2 diabetes diagnosis among Manitoba kids climbed over 50% in last decade, new study finds

They are not genetically modifying the produce, he explained, but rather changing the growing environment.

The vegetables are being fed to obese and diabetic rats by dietitian and PhD student Breanne Semenko, who is studying the rats' health to see how much of an impact the vegetables are having. She hopes to have definitive conclusions later this fall.  

However, early results show compounds such as beta carotene, potassium and manganese are four to 11 times higher in the OCN vegetables than in produce found in grocery stores, Suh said.

It means someone can eat fewer vegetables, but still have the same health benefits, she explained, adding food is a "basic entry point for building healthy communities."

Developing recipes

But now, they must encourage local residents to cook and eat the vegetables. This is a challenge partly because fresh produce is not a regular part of their diet, especially in the winter.

"We want to try and make these vegetables as accessible as possible to individuals in the community," said Semenko. "If you haven't necessarily grown up with continued access to fresh produce, then you may not necessarily know how to utilize them."

So they called on colleagues at Red River College Polytechnic's Prairie Research Kitchen (PRK) to develop culturally-sensitive recipes that are easy to prepare.

• Traditional foods give boost to First Nations battling diabetes
• 'Romaine calm,' hydroponic farm says to northern Manitoba community, we've got you covered

"Our chefs have created a chili with kale growing in the smart farm and cornbread with sage and kale, to go with the chili," said the kitchen's director Mavis McRae. "The goal today is to show how we can cook it up, make it tasty and add to a healthy diet without a lot of extra prep or concerns about taste."

They set up at the shopping mall to hand out the food during the annual Opaskwayak Indigenous Days celebration that takes place from Aug. 13-19. 

Darrell Lathlin was skeptical at first about the green bits in the chili and the green tinge of the cornbread, admitting he didn't even know what kale is.

Still, he gave the samples a thumbs-up. "Tastes more healthy, more natural."

Agnes Cowley said the chili tasted "different" but "nice" and said she'd like to find a way to feed it to her grandchildren, "instead of the junk food they always get, like fries and gravy."

Linda Scott said she was coming back for the recipe later. "I don't know what it is, but I like the taste of it," she said of the kale-infused food. 

The researchers said they were happy with that feedback.

"It's a small movement, right?" Suh said. "We want to get some feedback so then we can further improve this."

The researchers have applied for funding to develop First Nation food products that include the team's vegetables — hoping to create food security in the North and also economic opportunities for the community. 

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