Bryman (2016) suggests that research is disciplined inquiry which must be not only conducted but also reported so that its systematic and logical premises can be intently critiqued. This disciplined inquiry does not rely on surface plausibility or eloquence, authority or status of the researcher (Bryman, 2016). Selltiz et al. (2017) write research as a disciplined inquiry emphasizes the systematic nature of research in drawing logical and testable conclusions; regardless of the research paradigm the researcher uses to explore a given study. This essay revolves around the concepts of quantitative and qualitative approaches of research with respect to their distinguishing characteristics, strengths and limitations. Besides, this essay will explore the concepts underlying research ethics before concluding with an overview summary of this presentation.
Quantitative research refers to the systematic examination of social phenomena with the help of statistical tools and mathematical theories to initiate accumulate and process the scientific knowledge base. In addition, quantitative research offers “generalizable” results and according to Hammersley (2016) is characterised by testing of hypothesis, application of large samples, deductive orientation and in-depth and structured data collection tools. Hammersley (2016) suggested quantitative approaches ask standardised questions which limit responses to predetermined categories, therefore rendering it less breadth and depth. This is advantageous since makes responses measurable because respondents’ responses are sorts of limited questions which consequently allows for statistical aggregation and comparison of data. In addition, rigour in quantitative studies is usually conducted through a comprehensive explanation, allowing replication and accuracy. This in-depth rigour help practitioners and researchers to stay confident that the claims and knowledge contained in research are transferable to their area of practice.
Qualitative research refers to a form of social science study which gathers and operates with data in non-numerical form and aim to process comprehensive meaning from these data to effectively comprehend social life and meaning through the comprehensive study of intended places or populations. As an alternative option for quantitative method, qualitative research is differentiated from quantitative research on four main premises; holistic rather than particularistic, researcher-centred rather than variable-centred, depth as opposed to breadth, insider as opposed to outsider (Resnik, 2011). Qualitative methods allows examination into selected issue in great depth with more attention granted to context, detail and nuance, and therefore data gathering is not limited by predetermined set of questions.
(Haggerty (2016) suggests that researchers) ought not caught inside the polarising distinction saying; "All quantitative data is based upon qualitative judgments; and all qualitative data can be described and manipulated numerically pg. 13”
Mixed methods refer to a research methodology involving collection, analysing and incorporating quantitative methodologies such as surveys and experiments, and qualitative such as interviews, and focus group (Creswell, and Clark, 2017).
Quantitative research gathers data from current and relevant sources harnessing sampling techniques, online polls, surveys, and prepared questionnaires to extract numerical data for further synthesis to obtain meaningful conclusions (O’Leary 2017). The major aim of carrying out a quantitative study is to establish a link between independent and dependent variables within a presented population or area (Moule, and Hek, 2011). Quantitative research designs can either be experimental or descriptive. Descriptive research articulates relationships between variables whereas experimental studies establish causality (Taylor, Bogdan, and DeVault, 2015).
Dove et al. (2016) proposed that quantitative research focuses on logic and numbers. This kind of study equally concentrates in numeric and constant data and convergent reasoning as opposed to divergent reasoning. This means that the researcher begins exploring a given topic, based on a set of hypothesis, or research questions he/she is set to approve. This kind of study therefore concentrates on the generation of various ideas concerning the study problem in a spontaneous and disciplined manner (Taylor, Bogdan, and DeVault, 2015).
Based on the design, qualitative research is defined by three major designs; naturalistic, emergent and purposeful designs. Naturalistic refers to surveying the concrete world conditions as they appear naturally without manipulating or controlling any condition. The researcher is open to whatever outcome which unfolds and therefore there are no predetermined findings or constraints. Emergent design refers to acceptance of adapting inquiry to chances to undertake new discourses of knowledge discovery as they arise. Lastly, purposeful qualitative design refers to the application of case studies as selected to provide useful insights and manifestations to the area of study (Flick 2018).
Flick (2018) noted that personal experience with target audience or phenomena under investigation is essential in seeking to understand the phenomena under exploration. This is because the personal experiences provide first-hand information for developing more accurate conclusions.
Lastly, data analysis in qualitative research may take different orientations such as inductive analysis, or holistic analysis. Inductive analysis is where the researcher immerses in the details and particulars of the collected information to unravel key relationships, interrelationships, and themes and begin to explore, and confirm the findings under the guidance of analytical precepts as opposed to rules (Polgar, and Thomas, 2013). On the other hand, holistic design subjects the entire subject under study into a sophisticated system which is more than its basic components. The aim is on system dynamics and advanced interdependencies which may not be reduced in any sensible manner to cause and effect linkages or discrete variables (Taylor, Bogdan, and DeVault, 2015).
Quantitative Research
By utilizing mathematical, computational and statistical tools, quantitative research creates a projectable result applicable to the broader population under study. A small study can be used to represent a large population which may not only be fast in data collection, but also economically viable (Metcalf, and Crawford, 2016).
The samples of quantitative research sometimes can be randomized which therefore minimizes elements of bias from gaining entry into the study (Russell, R.M., 2013). The randomness induces an additional advantage since data supplied quantitatively can be statistically applied to the entire population group under experimentation (Russell, 2013).
Under quantitative research, conducted study is anonymous meaning the identity if respondents are hidden for confidential purpose. The respondents are therefore more prone to provide actual information. The researcher normally applies quantitative data when exploring sensitive topics requiring elements of anonymity. The respondents are not necessarily expected to provide actual details about themselves during data collection. This reduces chances of data falsification on the conception that respondents were ashamed to disclose particular issues openly
Qualitative Research
Qualitative research is characterized by various strengths. First, qualitative research studies may provide vital insights concerning human personality, behaviour and emotional traits which quantitative studies might not address. The prospects if qualitative data integrates information about user behaviours, desires, need, use cases, routines and different information which are fundamental in human psychology studies (Hewitt-Taylor 2017).
Besides, qualitative research is highly flexible, therefore allowing the researcher to react to data as it emerges during the study period (Oh, 2014). Therefore, qualitative research presumes a form of naturalistic observation including ethnography or structured interviews and therefore the researcher must observe and record opinions, characteristics, patterns, behaviours and other relevant information required. This is advantageous since it provides more accurate findings and conclusions.
In addition, events under study can be perceived in their proper context (more holistically) thus increasing accuracy in drawing out empirical conclusions. Qualitative research is also effective in situations requiring detailed understanding. The researcher studies in the field, and is able to interact with all study variables, and extract details deemed relevant to the study (Dove et al., 2016).
Quantitative Approaches
Quantitative methods are limiting in that the researcher may not get back to the respondents after they have filled in the survey in case they wanted to due to financial, time and other resource constraints (O'Brien, and Saldanha, 2014). In addition, the concept of anonymity conceals yet another limitation in that if surveys provide questionable or incomplete results, the verification if data becomes a challenge. If many respondents give similar responses, it might skew the data in a way which cannot apply to the general population, thus leading unrepresented or unstudied scenarios (Robson and McCartan 2016).
Jensen (2013) maintains quantitative research creates the possibility for unnatural environment. When conducting quantitative research, the study may be conducted in an unnatural setting which may lead into the generation of deviant results, from those that would have been obtained in the natural setting. For instance, studies dealing physical phenomena such as temperature measurement may greatly vary from place to place; therefore requiring studies to be done in-situ or else results elsewhere will greatly vary (Jensen, 2013).
Qualitative research is it is not generalizable based on small sample sizes and the subjective form of the study (Ryen 2016). The study is guided by clear objectives which guides the entire study. The personal nature of data gathering may subject the entire study into bias and personal skews and overgeneralized data which may consequently induce an inaccurate study (Ryen 2016). Besides, data rigidity is difficult to assess and demonstrate because personal vies are normally the foundation of the data collected qualitatively. It becomes difficult to substantiate collective information (Hewitt-Taylor, 2017)
Data collection may be time consuming based on the nature of detailed requirements during data collection (Robson, and McCartan, 2016). Sorting this data to extract the most relevant information may be time-consuming. In addition, qualitative data extracts important findings but which may be difficult to present and express. What a researcher denotes from the data may be different from what an external observer denotes from the data. This may lead to misinterpretation of the entire study (Hewitt-Taylor, 2017).
Research ethics encompass requirements on daily work, safeguarding the dignity of respondents, and the publication of the data accrued from research (van Raan, 2013). Research ethics provides a code of conduct inspiring the whole research process. This code applies in data collection, data storage, data analysis, and treatment of confidential information (Silverman 2016). There are four major areas research ethics focuses namely; autonomy, beneficence, nonmaleficence and justice.
Respect for autonomy obliges researchers to respect decision of participants who are autonomous-minded. van Raan, (2013) suggests three conditions for autonomy to prevail on respondents with capacity to choose namely; absence of controlling effects determining their actions, understanding and intentionality. As a researcher, it is vital to obtain consent, protect confidential information, respect privacy and always tell the truth to actualize this ethic (van Raan, 2013).
The principle of beneficence demands that researchers have a moral duty to behave for the benefit of others. The aim of the research should not intend to harm but help in accruing knowledge for practice. The researcher should therefore strive to balance benefits and harms connected with research (Battiste 2016).
Nonmaleficence principle suggests a researcher has moral responsibility not to induce harm on others (first do no harm). This ethic reinforces regulations such as do not offend, do not disable, do not cause suffering or pain or do not kill, while in the process of executing research. Lastly, justice principle obliges researchers to fairly disseminate risks, benefits, costs and resources while under research study. This ethic suggests researchers should treat research stakeholders equally, according to individuals need, effort, merit and contribution (Terrell, 2012).
Continue your journey with our comprehensive guide to Mixed Methods in Research Analysis.
As discussed herein, research is a systematic study of materials and sources in the quest to derive facts and draw empirical conclusion. This quest employs elements of critical and creative thinking in deriving facts which can consequently inspire conclusions. Both qualitative and quantitative researches are commonly used methodologies in research. As discussed above, quantitative data is a systematic study of phenomena through collection of quantifiable data and undertaking statistical and mathematical techniques, while qualitative research is a form of social science study which gathers and operates with data in non-numerical form and aims to interpret meaning from this information to effectively understand social life through the study of targeted places or populations. These two methodologies are characterized by distinct strengths and weaknesses; which the researcher ought to grasp alongside other aspects of research ethics to come up with effective research conclusion.
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