Anderson (2010) noted that qualitative research is often criticized as biased, small scale, ancedotal, and/or lacking rigor; however, when it is carried out properly it is unbiased, in depth, valid, reliable, credible and rigorous. In qualitative research, there needs to be a way of assessing the
‘‘extent to which claims are supported by convincing evidence. Although the terms reliability and validity traditionally have been associated with quantitative research, increasingly they are being seen as important concepts in qualitative research as well. Examining the data for reliability and validity assesses both the objectivity and credibility of the research.
The study held the view that validity related to honesty and genuineness of the research data, while reliability related to reproducibility and stability of the data. The validity of research findings referered to the extent to which the findings was accurate representation of the phenomena it intended to represent. The reliability of the study refers to the reproducibility of the findings.
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Johnson (1997) noted that discussions of the term ‘validity’ and ‘reliability’ have traditionally been attached to the quantitative research. This view was expressed by some positivists that the basic epistemological and ontological assumptions of quantitative and qualitative research are incompatible. However, the study expressed that qualitative researchers regard validity and reliability in terms of research that is plausible; credible; trustworthy and defensible.
Johnson (1997) presented some strategies usually adopted in qualitative research to address the issue of validity and reliability as shown in the Table 3.2:
149 Table 3.2.: Validity and Reliability Strategies
Strategy Description
Researcher as ‘Detective’ A metaphor characterizing the qualitative researcher as he or she searches for evidence about causes and effects. The researcher develops an understanding of the data through careful consideration of potential causes and effects and by systematically eliminating
‘rival’ explanations or hypotheses until the final
‘case’ is made beyond reasonable doubt.
Extended fieldwork Qualitative researcher collects data in the field over an extended period of time.
Low interference descriptors The use of description phrased very close the participants’ accounts and researchers’ field notes.
For example, verbatim (direct quotations) are a commonly used type of low interference descriptors.
Triangulation ‘cross-checking’ information and conclusions
through the use of multiple procedures of sources.
Data triangulation The use of multiple data sources to help understand a phenomenon.
Method triangulation The use of multiple research methods to study a phenomenon.
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Table 3.2: Validity and Reliability Strategies Cont’d
Strategy Description
Investigator triangulation The use of multiple researchers in collecting and interpreting the data.
Theory triangulation The use of multiple theories and perspectives to help interpret and explain the data.
Participant feedback The feedback and discussion of the researcher’s interpretation and conclusions with the actual participants for verification and insight.
Strategy Description
Peer review Discussion of the researcher’s interpretation and
conclusions with other people. This will be in two folds – ‘disinterested peer’ and ‘interested peer’. The disinterested peer should be skeptical and play the devil’s advocate; challenging the researcher to provide solid evidence for any interpretations or conclusions. Discussion with interested peers who are familiar with the research can also help provide useful challenges and insights.
Reflexivity This involves awareness and ‘critical
self-reflection’ by the researcher on his or her potential biases and predispositions as these may affect the research process and conclusions.
Pattern matching Predicting a series of results that form a ‘pattern’ and then determining the degree to which the actual results fit the predicted pattern.
Source: Johnson (1997).
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Bell (2012) opined that sound measurement must meet the tests of validity and reliability. These attributes were regarded as two major considerations in evaluating research instrument. Cane, O’Connor and Michie (2012) described validity as the extent to which an instrument measures what it actually wishes to measure while Cohen et al (2011) described reliability as the accuracy and precision of a measurement procedure. Thus, Cronbach alpha test was used to test the reliability of the questionnaire. The Cronbach’s alpha reliability coefficient measure the reliability of the 5-point Likert type scale used for the study. This is one of the most commonly used reliability coefficient. The Alpha is based on the “internal consistency” of research instrument.
That is, it is based on the average correlation of items within the instrument. If a test were perfectly reliable, this correlation would be 1.00. If the test were totally unreliable, the correlation would be zero. The Cronbach’s alpha was computed using the following formula:
var / cov 1) (k 1
var / cov α k
−
= +
Where k is the number in the scale, cov is the average covariance between items, and var is the average variance of the items. Bell (2012) noted that if the items are standardized to have the same variance, the formula could be simplified to;
r 1) (k 1
r α k
−
= +
Where r is the average correlation between items k is the number in the scale
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Statistical Package for Social Sciences (SPSS) software was used to compute the Cronbach’s test using the 5-point Likert.