Is It Possible to Ensure Scientific Rigour When Conducting Quantitative and Qualitative Research - Essay Example

? Is it possible to ensure scientific rigour when conducting quantitative and qualitative research? Submission Introduction Scientific rigour in research is the ability to ensure rigorous validity, cogency, credibility, and believability in the findings of any scientific study. The findings should also be dependable and confirmable in order to build the trust of the users (Kirk & Miller 1986). In the past, studies were often conducted without consideration to scientific rigor, beginning with the objective leading to a general perception that scientific research was a pseudoscience, especially as a result of the method used. It is worth noting that the concepts of validity and reliability of qualitative research have in the past not been well codified as in the case of quantitative research. This paper therefore, looks at the possibility of having a scientific rigour when conducting qualitative and quantitative research (Gery & Ryan 2013). The quality and reliability of any research finding depend on the techniques used in collecting data, sample choices, techniques used in the analysis and the illustration of the chosen techniques. Equally, the researcher needs to develop systematic coding patterns to assist detect deviant cases that would otherwise affect reliability. The Techniques for Collecting Qualitative Data In order to have correct inference, the analysed data must be quality data. This means that techniques of collecting data must be well chosen based on the type of research and the judgements made about the contents. Poor selection of techniques is likely to result into wrong deduction (Meyrick 2006). There are approaches and techniques that can assist to improve the validity and reliability of qualitative data and the research reports. To ensure scientific rigour, four data collection techniques can be used. These are; (1) techniques for indirect observation, (2) direct observation techniques, which is considered not verifiable and unreliable owing to the fact that different observers can observe different results (3) techniques for elicitation and (4) a mixed method that is a combination of the three techniques (Seale 1999). These techniques vary on the level of interaction among the participants, which in turn elicit varied responses that either validates or refutes. Elicitation techniques can also be categorized into types of interviews; structured, semi-structured, unstructured, and mixed elicitation that combines the three. The use of unstructured interviews may be informal or ethnographic. To have control of the results scientific research need to avoid informal interviews but choose the structured and ethnographic techniques, which allows longer questionings and deeper probing (Seale & Silverman 1997). This leads into credibility of the data with ability for proper analysis. This is because the structured and semi-structured interviews are often designed to allow all informants to be examined on a set of similar questions, in order to provide an opportunity of making comparisons of the data across respondents or groups of respondents to improve reliability. In this method, the researcher initiates the interview, asks the specific questions, and determines whether the conversation on a particular topic has meets the research objectives. In this case, the respondent is guided and restricted to the research questions. Data collected is likely to be reliable if there is a level of correlation across the respondents. Structured interviews are majorly employed when the research intends to measure the magnitude of an occurrence and to assist make more accurate comparisons within and across groups (Seale & Silverman 1997).The validity of such structured interviews is founded on the hypothesis that if a systematic and a set of standardized instrument is administered to a group of individuals, the variances in their responses is majorly as a result of their individual differences, but not the difference in the instrument used. Examples of structured interviews techniques that produce valid and reliable data are surveys and questionnaires. In addition, structured interviews may also comprise open-ended and closed-ended questions that stimulate both short and long qualitative and quantitative responses. A mixed technique that comprises the structured, semi-structured, and unstructured techniques can also be used depending on the environment where the research is carried out, since each technique has its advantages. This shows that it is possible to have a scientific rigour in research based on the type of technique used to collect and analyse the quantitative and qualitative data. The research participants in this case need to put more effort in both setting standards for collection of the qualitative and quantitative data are collected, and how best the analysis can be done. Reliability and Validity in Qualitative Research Rigour and validity in findings are important in qualitative research. There are various methods that can be used to ensure scientific rigour when conducting quantitative and qualitative research. These include; Ensuring representativeness of cases; validity is measured when all the cases covered during the collection of data are well represented. This means including all the data collected by both the quantitative and qualitative methods to back the recognition and generalizations of the merits, especially when random samples or statistical figures are used to represent a population, or when theoretical sampling is adopted (Seale & Silverman 1997). Testing hypotheses; this is done during data analysis to avoid any deviation in the data that may contradict emerging hypotheses, the grounded theory and analytic induction. For validity and reliability to be proved, there must be consistency in all aspects of data analysis. This approach is therefore, to collect and analyse qualitative data ensures that generalizations made are supported by adequate evidence. Supporting generalizations by counts of events; this is also known as quasi-statistics used to address the major concerns related to reporting of qualitative data to ensure that no unnecessary attention is paid to insignificant activities, at the expense of the significant ones. Validity testing; to validate the data, face validity, predictive validity and construct validity can be employed to ensure the data collected are factual. The use of ANOVA and ANCOVA that analyses the variance of the collected data helps to assess the significance of variances that exist between the means. This is done by comparing variances of different sets of data when structured techniques are used to collect data. For example, in a study to find out the level of performance based on the instructional method used, comparing the means and variance in the students’ performance in different set of data the validity can be proved by the minimal variation of in the calculated ANOVA. Using computer programmes; these programmes are to assist qualitative analysis of the representative data. Validity and reliability of data is also achieved through objective and comprehensive recording of collected data through the use of audiotapes, notebooks, videotapes and diverse levels of detail in the transcription of data. Scientific Rigour Quantitative Research The reliability of quantitative research is dependent on the technique of collecting data adopted by the researcher. For example, in a quantitative research involving health sector, the use of observation as a technique is not considered an important method of data collection, since it is challenging to carry out observational studies on large samples and arrive at a correct analysis. Equally, quantitative researchers consider observation to be unreliable because different people may record different observations (Seale 1999). Quantitative research may make use of interviews and questionnaires administered to random samples of the population. Usually, closed ended questions such as ‘yes’ or 'no' are preferred to produce simple tabulation in the analysis that provides clear representation of the population. The most important aspect of quantitative research is the reliability of the questionnaire and the interview schedule, as well as the representativeness of the sample used to bring about the validity of the findings (Meyrick 2006). This means that scientific rigour can be achieved in a quantitative research when right samples, interview questions are well structured questionnaires are developed The analysis in quantitative research is often done on written material in a manner that produces reliable and verifiable evidence as well as proper representation of the population (Anderson 2006). The preferred method is content analysis that forces the researchers to establish a set of categories and then compute the number of occurrences falling under each category. The most essential quality is that the set categories must be sufficiently precise to allow diverse coders to get the same results using the same body of material. When these techniques of collecting data and the methods of ensuring reliability and validity of data are employed, it is possible to ensure scientific rigour when conducting quantitative and qualitative research. However, the use of these techniques should be with full regard of their limitations in order to solve the reliability and validity problems usually experienced when determining the scientific rigour. Conclusion Scientific rigour in research is the ability to ensure rigorous validity, credibility, believability and reliability in the findings of any scientific study. The findings should also be dependable and confirmable in order to build the trust of the users (Kirk & Miller 1986). This paper concludes that it is possible to ensure scientific rigour when conducting quantitative and qualitative research. However, the rigour begins with choosing a good data collection technique that improves the validity and reliability of qualitative and quantitative data. The techniques discussed include structured, semi-structured and unstructured techniques. The paper has also looked at the ways to ensure there is validity in the data. Testing of the data helps the researcher to determine the reliability of the findings. Bibliography Anderson, J.D., 2006. Superintendent of Schools Qualitative and Quantitative research, Retrieved on 14 March 2013, http://www.icoe.org/webfm_send/1936 Gery W. and Ryan, 2013. What Are Standards of Rigor for Qualitative Research? Meyrick J., 2006. What is Good Qualitative Research? A First Step towards a Comprehensive Approach to Judging Rigour/Quality, Journal of Health Psychology, SAGE Publications, UK, Retrieved on 14 March 2013 from http://www.wjh.harvard.edu/nsfqual/Ryan%20Paper.pdf Seale Clive and Silverman David, 1997. Ensuring rigour in qualitative research, European Journal of Public Health, Retrieved on 14 March 2013 from http://eurpub.oxfordjournals.org/content/7/4/379.full.pdf Kirk, J., & Miller, M. L. 1986. Reliability and validity in qualitative research, Beverly Hills, Sage Publications. Seale, C. 1999. The quality of qualitative research, London, Sage Publications. Read More