Critical realism was used as an under-labourer for this qualitative comparative case study. In this study, inductive and abductive modes of inference were used (Danermark et al., 2002). The use of critical realist analysis inductive and abductive analysis) were used to probe shaping generative mechanisms. Critical realists use four modes of inferences which are deduction, induction, abduction and retrodiction. Abductive analysis is concerned with the emergence of themes from the data, when one uses theoretical lenses to make sense of the data moving from the concrete to the abstract (Mukute, 2010a). In this study, abduction was based on the lenses of Bernstein’s pedagogic device, classification and framing as well as Moll’s model of curriculum responsiveness. Bhaskar’s position practice system and laminated system of emergence (Bhaskar, 2010). Abduction relies heavily on theories as mediators for deriving explanations.
According to Danermark et al. (2002) abduction is an inference where description and recontextualisation is the central element, in order to understand something in a different context.
Retrodictive analysis was concerned with establishing explanations of what qualities must exist for something to be possible (in this case curriculum responsiveness). Retrodiction posits that events are explained through identifying and hypothesizing causal powers and mechanisms that produce them (Marks & O' Mahoney, 2014). Causality is mediated by contextual conditions because causal powers may only result in an event occurring under certain conditions. Table 5 below adapted from Danermark et al. (2002, pp. 80-81) presents the four modes of inference.
144 Table 5: Four modes of inference
Deduction Induction Abduction Retrodiction (Also
referred to as Retroduction) Fundamental
Structure/ Thought operations
To derive logically valid conclusions form
given premises.
To derive knowledge of
individual phenomena from
universal laws
Draw universally valid conclusions from a number of instances. See similarities in a
number of observations (identification of
patterns of data)
Interpret and recontextualise
individual phenomena within a
conceptual framework (theory)or
set of ideas.
Understanding something in a new
conceptual framework
From a description and analysis of concrete phenomena,
reconstruct the basis conditions for these phenomena to be what they are. By way of thought
operations and counterfactual
thinking.
Central Issue What are the logical conditions for the
premise?
What is the element common for a number of observed
entities?
What meaning is given to something interpreted within a particular conceptual
framework?
What qualities must exist for something to
be possible?
Strength Provides rules and guidance for
logical derivations and investigations of
the logical validity in all
argument
Provides guidance in connection with
empirical generalisations
Provides guidance for interpretive processes by which to ascribe meaning to events in
relation to a larger context
Provides knowledge of transfactual conditions, structures and mechanisms that
cannot always be observed in the
domain of the empirical Limitation Deduction does
not say anything new about reality beyond what is
already in the premises.
Inductive inference can never be either
analytically or empirically certain (internal limitations
of induction)
There are no fixed criteria from which it
is possible to assess in a definite way the
validity of an abductive conclusion
There are no fixed criteria from which it
would be possible to assess in a definite way the validity of a
retrodictive conclusion
Apart from the four modes of inference presented in table 5 above, the researcher used thematic analysis for analysing data from semi-structured interviews, focus group interviews and observations. Thematic analysis is informed by the realist philosophy (Vaismoradi, Turunen, &
Bondas, 2013). Thematic analysis refers to a method of identifying, analysing and reporting patterns (themes) in data and examining commonality, differences and relationships in the data (Braun & Clarke, 2006; Gibson & Brown, 2009). Thematic analysis works well with narrative materials, breaking text into small units of content. It involves identifying common threads in the data sets and condensing them into analysable units by creating categories from the data (Coffey
145
& Atkinson, 1996; Miles & Huberman, 1994 ). The process was done separately for the two colleges under study. This was to avoid losing case specific data in the preliminary analysis.
Commonality is established by pulling together all material across a data set that has something in common. These common elements can also be analysed further. Differences are identified across the data set focusing on the relevance of the differences to the themes being examined (Gibson & Brown, 2009). Identifying commonality as well as differences ultimately allows a researcher to establish the relationship of the data.
The use of thematic analysis allows for the context influencing data to be apparent. Having collected data, the researcher started the process by familiarising with the data through reading and re-reading responses from the data sets. This led to the allocation of codes on the data sets.
In order to reduce the data into more manageable sets summarising the main issues, the identified codes were reduced into a few clusters. Data collection and analysis were done concurrently as it is suggested that the process of data collection, analysis and report writing are not distinct steps but rather are interlinked and often go on simultaneously (Cohen, Mannion, & Morrison, 2011;
Creswell, 2013; Dey, 1995).
According to Alhojailan (2012) the use of thematic analysis is befitting in qualitative studies in that it allows for interpretation of data which is consistent with the data collected from respondents. Through thematic analysis, the factors that influence VET curriculum responsiveness at the colleges under study, for example, can be identified. Having analysed the data from the two cases separately, a data matrix was used to enable a cross-case analysis that allowed for a comparison of factors influencing VET curriculum responsiveness at the two colleges. The data matrix was used for data display purposes which enables the visualization of data and conclusion drawing (Miles & Huberman, 1994 ). In some cases the researcher utilised actual quotations from the respondents where necessary. The data matrix used in this study is in appendix 11. The following table presents a summary of data analysis.
146 Table 6:Summary of data analysis