Research is undertaken to understand and examine some concepts, phenomena or hypothesis based on the interests of the researcher. The reliability, validity, and quality of research significantly depend on the reliability of the study design and the approaches used for the collection of data (Yeasmin & Rahman, 2012). According to Turner, Cardinal, and Burton (2015), more often than not, most research and data collection methods individually prove inefficient and flawed. However, so as to enhance the trustworthiness and strength of research, scholars opted to strategically combine at least two research methods hence mixed research designs were coined based on the idea of methodological triangulation. Johnson and Onwuegbuzie (2004) .
defined triangulation as the simultaneous deployment of at least two research methods when conducting a study. The methods are selected based on the convergence, corroboration, and complementarity of the research question when evaluating the same phenomenon. Johnson & Onwuegbuzie (2004) argue that mixed research methods (triangulation) elevate the cogency and dependability of findings of a investigation as the method promotes wide-ranging and corroborative integration of but not limited to the qualitative and quantitative data collection, analysis, and interpretation. Therefore, this paper aims to discuss the benefits of using triangulation methods in studies.
Overview of Mixed Research Methods
Johnson & Onwuegbuzie (2004) note that for a long time, social and physical researchers have engaged is enthusiastic debates on the paradigms of qualitative and quantitative research methodologies. Social scientists argue that social observation and opinions of people should be perceived as entities just like physical phenomenon are treated by physical scientists. On the hand, physical scientist rejects the social scientists’ idea of treating social observation as entities because they are not scalable.
Nonetheless, both methods are useful and they can be used complementarily. The idea of methodological triangulation was coined so as to bridge the gap between qualitative and quantitative research methods as well as integrate other methods when conducting studies (Yeasmin & Rahman, 2012; Turner, Cardinal, & Burton, 2017). Johnson & Onwuegbuzie (2004) argues that mixed research designs are an invaluable promise to researchers as it would help them achieve reliable and valid study findings as well as help in bridging the schism between the qualitative and quantitative research methods among other relevant methods. Triangulation was also postulated to bridge the gap between interviewer and observer’s biasness hence equally promoting the validity of a study.
Triangulation can be undertaken in two forms namely within- and between-method. The former uses of diverse data collection formats within the single method such as combining interviews and questionnaires in a qualitative study. The latter infers to the use of different research methodologies to investigate the same phenomena such as combining qualitative and quantitative methods. Triangulation is argued to allow researchers to recognize and appreciate the strengths and weakness of the different research techniques at their disposal hence leveraging in the corroboration and complementary of studies (Johnson & Onwuegbuzie, 2004; Yeasmin & Rahman, 2012).
The approach of mixed methods research allows researchers to have a big and comprehensive picture of the phenomena and its findings. Conversely, as alluded earlier it increases on the validity and checks the readability of the studies as well as. Nonetheless, the method is argued to be comprehensive hence time-consuming and quite expensive.
Johnson and Onwuegbuzie (2004) indicate that triangulation is conceptualized in seven primary stages. The first stage focuses on data reduction where the qualitative methods for instances are reduced through exploratory thematic analysis while descriptive statistics reduces the quantitative data. The second phase is data display which infers to pictorial description data using but not limited to graphs, tables, charts, lists, and matrices. Thirdly, data transformation stage allows conversion of qualitative data into narrative data (qualitized) or numerical codes that can be qualitatively scrutinized or statistically quantized (Johnson & Onwuegbuzie, 2004).
Data correlation as the fourth step encompass correlating of either qualitized data and quantitative data or quantized data with qualitative data. The fifth phase is data consolidation which involves combining and consolidating qualitative and quantitative statistics to either create fused or new datasets or variables. Data comparison which is the second last stage, it involves comparing of the qualitatively and quantitively analyzed data while in the last stage (data integration) the analyzed data is interpreted either separately or converged from which discussion and conclusions are drawn. An additional step referred as legitimation is often undertaken to assess the validity and trustworthiness of both the methods used in the study and their subsequent interpretations and conclusions.
Empirical Benefits and Challenges in Triangulation
According to De Lisle (2011), there has been an increasing interest in the deployment of mixed research methodologies in research as well as finding the best ways and alternatives to systematically integrate qualitative and quantitative methods. Several studies have investigated the strengths and weaknesses of triangulation while many others have employed the techniques in investigating several phenomena. For instance, Almalki (2016), Dos Santos et al. (2017) and Perone and Tucker (2003) evaluated the benefits and challenges integrating qualitative and quantitative data in mixed research methodlogy in while Ammenwerth, Iller, and Mansmann (2003).
investigated whether triangulation can benefit evaluation studies. Dang’s (2015) study on the perception of educational stakeholders in vocational training and education in Vietnam used a triangulation method. Turner, Cardinal and Burton (2015) article provide a framework and roadmap for mixed research designs. On the other hand, De Lisle’s (2011) article discussed lesson drawn from the application of qualitatively based mixed methods research in Tobago and Trinidad.
De Lisle (2011) points out that qualitatively anchored approaches to mixed method research provide an invaluable and extensive potential of creating new ways of comprehending the contexts and complexities of social experiences. De Lisle (2011) argued that despite mixed research method being central in education studies, the implementation of the method has been faced with significant challenges. Many studies that used the triangulation method failed to provide a clear and satisfactory rationale to why they preferred the method whereas some used expansion and complementarity to justify the use of the method. Nonetheless, it was noted that the definition of triangulation or mixed research method was skewedly captured. In instances of diversity and complexity, the lack of coherent variation and understanding of samples results in the phenomenon in question being poorly captured. De Lisle’s (2011).
analysis of the studies in the study area revealed that even though mixed methods are critical in research, it is not only a matter of collecting qualitative and quantitative data but it is vital to take into account the philosophical assumptions inherent in each method to avoid making inept conclusions. The study also emphasized the vitality of corroboration between qualitative and quantitative teams as it promotes the ability to integrate the methods. The author also found out that the mixed methods often resulted in different but insightful surmises.
On the other hand, Almalki (2016) aimed to examine whether mixed methods research that uses qualitative and quantitative data had potential positive impacts on investigative studies despite the limitations of the method. Almalki found that the skills of the researcher are the first potential limitation of mixed research designs as they inhibit the validity and reliability of a study. Researchers skills significantly influence their ability to effectively use mixed method research. Secondly, it was noted that researchers often face a dire challenge in choosing the aptest method for their studies. This finding resonates with De Lisle (2011).
observation that mixed methods research is not only a matter of collecting qualitative and quantitative data but choosing the most appropriate method to examine the phenomena under study. Almalki (2016) and De Lisle (2011) argue that in order to effectively used the triangulation method, it is vital for the researcher to synthesize the main typologies of the method. There are four primary typologies of mixed method research namely QUAN inferring to quantitively designed studies, QUAL – qualitative studies, quan – quantitatively data compared to qualitized data, and qual – qualitative data compared to quantized data (Dos Santos, et al., 2017; Almalki, 2016; De Lisle, 2011).
Dos Santos et al. (2017) study collected quantitative data from 106 nurses using Brazilian version of Nursing Work Index-Revised (B-NWI-R) to collection their description on work environment whole qualitative data were collected using in-depth interviews from 63 respondents. For instance, the study’s autonomy findings recorded an average B-NWI-R rate of 2.07 indicating that the working environment and culture of the hospital supported nursing autonomy. The qualitative data from the interviews indicated that the administrators support nurses counselling; a combination of the quantitative and qualitative findings gives a big picture and in-depth grasp of the working environment of the nurses.
Dos Santos et al. (2017) note that the use of mixed-research methods allows them to identify the divergence and convergence of qualitative and quantitative data and how they complementarily contributed to the study findings and discussion. However, they noted that the validity and reliability of the method depend on the ability of the researcher to pinpoint the limitations and potentialities of the method as per the research question and objectives.
Just like Dos Santos et al. (2017), Dang (2015) employed a mixed method technique that involved three methods in assessing the perceptions of different stakeholders in the Vietnamese education system on the VET (vocational education and training programs). Questionnaires were used to collect quantitative data (quantized), open-ended interviewed collected qualitative data on students’ perceptions towards the VET programs while a nominal group technique was used to collect data on the other key stakeholders.
The methods were triangulated from data collection to interpretation which revealed that VET industries and providers significantly impacted the VET programs and sector. Dang (2015) selected the method with a belief that it would provide a clear and substantive evidence on the research hypothesis. Figure 1 below shows an illustration of the triangulation method adopted by Dang (2015). Dang (2015) study concluded that combination of various research methods, theories, observations, and empirical materials considerably leverages the researcher’s ability to overcome intrinsic biases, weakness, and challenges incurred when using a single method. Thus, triangulation helped in the confirmation of results by converging multiple perspectives.
Conversely, Perone and Tucker (2003) hypothesized that an integration of QUAN (quan) and QUAL (qual) research methods would significantly enhance the capacity to determine and understand the desires of both transit users and non-users. The qualitative and quantitative data were collected and analyzed independently but integrated during interpretation and discussion. Perone and Tucker (2003) note that they combined the two methods because of the concordance where the qualitative data was aimed at finding and understanding the motivation for the users and non-users while quantitative data vindicated the patterns of usage. Combination of the two methods provided the scholar with a comprehensive grasp of the factors influencing the use of transit by simultaneously investigating of the motivation and demographic patterns of transit usage; therefore, making a detailed and informed decision as opposed if the study would have been undertaken separately.
Ammenwerth, Iller, and Mansmann (2003) as many other researchers were interested in determining and understanding whether evaluation studies would tap into the benefits of the triangulation technique. Therefore, they adopted a mixed method design to investigate the impacts of computerized nursing documentation systems in healthcare systems. A quantitative process was used to gather data on the attitudes of nurses towards the computerized system; questionnaires based on Nickell, Bowman, Lowery and .
Chin and Ohmann scales were used to assess nurses’ attitudes. Qualitative method aimed to understand the reasons for the different attitudes towards the computerized systems in the word; data was collected using interviews. In Ward C (paediatrics) and D (dermatology), the results indicated negative attitudes which were justified by interviews that indicated the system did not save time, there were many documents in the two wards, and lack of motivation among others. Basing on these findings, if the study was conducted by one method, it would not have been possible to compare the findings and comprehends the research problem. Ammenwerth, Iller, and Mansmann (2003) concluded that triangulation is an indispensable method for evaluation studies however accurate use of the method depends considerably on the use of support evaluation methods, methodological, and training experience of the researcher.
In summation, all through the articles discussed above, it is evident that triangulation is a panacea to challenges and limitation posed by the use of individual research methods. Most research methods are flawed when independently used in a study but a mixed method ensures the method used to complement each other thus increasing the dependability and validity of the study. It is crystal clear that the method provides a comprehensive and fuller understanding of the studied phenomena and equally supports interdisciplinary researches. Nevertheless, the dependability and soundness of the method depend on the skills and experience of the researcher and the ability to select appropriate complimentary methods. triangulation significantly enhance the validity and reliability of studies regardless of the discipline stemming from social sciences to physical sciences.
References
Almalki, S. (2016). Integrating Quantitative and Qualitative Data in Mixed Methods Research–Challenges and Benefits. Journal of Education and Learning, 5(3), 288-296.
Ammenwerth, E., Iller, E., & Mansmann, U. (2003). Can evaluation studies benefit from triangulation? A case study. International journal of medical informatics, 70(2-3), 237-248.
Dang, V. H. (2015). A mixed method approach enabling the triangulation technique: Case study in Vietnam. World Journal of Social Science, 2(2), 1-13.
De Lisle, J. (2011). The benefits and challenges of mixing methods and methodologies: Lessons learnt from implementing qualitatively led mixed methods research designs in Trinidad and Tobago. Caribbean Curriculum, 18, 87–120.
Dos Santos, J. L., Erdmann, A. L., Meirelles, B. H., Lanzoni, G. M., Cunha, V. P., & Ross, R. (2017). Integrating Quantitative and Qualitative Data in Mixed Methods Research. Texto & Contexto-Enfermagem, 26(3), 1-9.
Johnson, R. B., & Onwuegbuzie, A. J. (2004). Mixed Methods Research: A Research Paradigm Whose Time Has Come. Educational Researcher, 33(4), 14-26.
Perone, J. S., & Tucker, L. (2003). An exploration of triangulation of methodologies: Quantitative and qualitative methodology fusion in an investigation of perceptions of transit safety (Report Number: NCTR-416-08.1, 416-08.2). Tampa, FL: College of Engineering, University of South Florida.
Turner, S. F., Cardinal, L. B., & Burton, R. M. (2017). Research design for mixed methods: A triangulation-based framework and roadmap. Organizational Research Methods, 20(2), 243-267.
Yeasmin, S., & Rahman, K. F. (2012). Triangulation’research method as the tool of social science research. BUP journal, 1(1), 154-163.
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