Quantitative and Qualitative Approaches to Data Collection: Mixed Methods

It has been mentioned (Denscombe, 2003) that the survey strategy allows for the collection of many different types of data, included in which are data that can be counted, and data that need to be interpreted. Simply, these can be described as quantitative data and qualitative data, and approaches of these kinds have been well documented in the literature.

Defining the objective of

the survey Determining

the sample group Writing the questionnaire Administering the questionnaire Pilot study Interpretat ion of the results Main study

63

Quantitative research has been defined by Punch (2005) as empirical work in which the data gathered appear as numbers, and Collis and Hussey (2003) note that this mode of operation measures variables or counts instances of a particular phenomenon. Therefore, a study that gathers measurable information about any subject falls into the category of quantitative research (Hancock, 1998), and relies on systematic non-human instrumentation and statistical analysis. Traditionally, positivists have depended upon such an approach (Maykut and Morehouse, 1994), using methods of data collection that deal with numbers and anything that is measurable, so that ultimately they can confirm existing propositions, or predict future behaviour.

In contrast, qualitative research is interpretive. It rejects the notion of measuring a phenomenon by counting, and instead uses interpretive techniques to get to the heart of the meaning, rather than the frequency of social phenomena (Van Maanen, 1983). The key here is the reference to ‘social’ since this type of research recognises the need to interpret data from the perspective of those who form the research population. Indeed it has been described by Bryman (1998:46) as “an approach to the study of the social world which seeks to describe and analyze the culture and behaviour of humans and their groups from the point of view of those being studied”. It is argued (De Vaus, 2002:5) that qualitative data provide rich insights into real-life situations and are more able [than quantitative data] to make sense of behaviour within its wider context”.

Positivists have criticised qualitative approaches to research as non-scientific, and consequently, it is suggested (Yardley, 2000) that a number of conditions should be met when conducting qualitative research, these being: Sensitivity to context - in terms of related theory, epistemological commitment of the research, and socio- cultural context of data collection; Commitment, rigour, transparency and coherence – in terms of researcher engagement with the study, completeness of data collection and analysis, careful description of the research process and intellectual coherence of the arguments presented through the analysis; and Impact and importance - in terms of substance and worth of the work in relation to earlier theory and the specific issues being explored.

64

It is not only qualitative research that attracts criticism, however; indeed, both approaches have strengths and weaknesses. That said, they have both survived in research work for many years, and it is clear that certain studies are better pursued using one approach, while others fare better with the other. Dey (1993) has tabulated the differences between quantitative and qualitative approaches as shown in Table 4.3.

Table 4.3: Distinctions between Quantitative and Qualitative Approaches

Quantitative Approaches Qualitative Approaches

Based on meanings derived from numbers

Collecting results in numerical and standardised data

Analysis conducted through the use of diagrams and statistics

Based on meanings expressed through words

Collecting results in non-standardised data requiring classification into categories

Analysis conducted through the use of conceptualisation

Source: Dey (1993)

It is clear from Table 4.3 that these two approaches are useful for different kinds of research study, and as noted by Oppeneheim (1992), the eventual choice of whether to pursue qualitative or quantitative data depends upon the suitability of the data to meet the research objectives. He makes the point that in fact, no single method can be claimed to be better than another because of the inherent benefits and shortcomings of each. And, he suggests that a researcher can adopt both approaches within the same study in order to reap the advantages of both, and counteract the disadvantages of the other. This constitutes a mixed methods strategy, which allows for data obtained from different and disparate sources (i.e. in the form of numbers and words) to be ‘triangulated’.

According to several researchers (Bryman, 1990; Denzin. 1989; Punch, 2005; 1998), ‘triangulation’ is the combination of research strategies in order to

65

investigate the same research problem using different approaches, and this allows for the validity of the conclusions reached to be strengthened. The concept can be traced back to Campbell and Fiske (1959) who refer to it as a method that can demonstrate how a hypothesis can survive when considered from different methods of testing; and later, Fielding and Fielding (1986) described it as a concept associated with orienteering, whereby bearings are taken from two landmarks in order to locate oneself at their intersection. The end aim of triangulation is, therefore, to increase confidence in the findings, and this is believed to occur through the use of both quantitative and qualitative data, an approach which is referred to as mixed methods.

It is noted by Creswell (2005) that the mixed methods approach in social science research is relatively new, that it involves the collection, analysis, and combination of qualitative and quantitative data within a single study, thereby permitting triangulation of the data. That said, several other researchers (Creswell, 1994; Miles and Huberman, 1994; Brannen, 1992; Brewer and Hunter, 1989; Bryman, 1998) have reported the value that the ability to triangulate data can bring to a research study and advocate this as a component of sound research design. Moreover, the use of mixed methods is believed to overcome the weaknesses of a single approach (Polit and Beck, 2004), since there is much less opportunity for critics to be sceptical about the findings reached when a hypothesis or proposal is supported by conclusions arrived at from multiple types of data. Further, it has also been argued (Brannen, 2000), that by using mixed methods in one study, it is possible for a researcher to gain insights which could not have emerged simply by adopting one approach.

It must, however, be recognised that a mixed methods approach can be complex, and that time-constraints may preclude such a strategy. There is also the possibility that the results from one method might not agree with those from another method (Mason, 1996). That said, even in such circumstances, it is argued (Ghauri et al, 1995) that having the ability to triangulate data is still worthwhile, since different results can generate a better appreciation of the research topic. By using the questionnaire to gain insight from a range of Libyan students all following a similar process, and then by discussing (via an interview approach)

66

the issues associated with PhD study as seen by government officials, the methods used in this study allow for a suitable mix of perspective which sheds light on the precise issue being studied.