Week 5: Variation and commonality in phenomenographic research methods

Akerlind, G. (2005)

"For researchers in higher education... the test is generally not in its [phenomenography's] theoretical purity, but in its value in producing useful insights into teaching and learning" (Entwhistle, 1997: 129)

Aims and outcomes of phenomenographic research

Aims of research/researcher: to determine not only a set of different meanings but also a logically inclusive structure relating to the different meanings. To explore the range of meanings within a sample group as a group, not the range of meanings for each individual within the group. So for example, no single interview transcript can be understood in isolation from the others and must instead be interpreted within the context of the group of transcripts or meanings as a whole.

Object of study = variation in human meaning, understanding, conceptions (Marton, 1981) and awareness or ways of experiencing a particular phenomenon (Marton & Booth, 1997).

Outcomes = categories of description, i.e. qualitatively different meanings of ways of experiencing the phenomenon and the structural relationships linking these different ways of experiencing. These relationships represent the structure of the outcome space. The assumption of structural relationships between different ways of experiencing is one of the assumptions about the nature of knowledge and how it is acquired that underlies the phenomenographic approach.

• "There is not a real world 'out there' and a subjective world 'in here'. The world [as experienced] is not constructed by the learner, nor is it imposed upon her; it is constituted by an internal relationship between them. (Marton & Booth, 1997: 13)

'Outcome space': the structured set of categories of description put forward by the researcher to represent different ways of experiencing a phenomenon. This provides a way of looking at collective human experience of phenomena holistically, despite the fact that some phenomena may be perceived differently by different people and under different circumstances.

Ideally, the outcomes represent the full range of possible ways of experiencing the phenomenon in question, at this particular point in time, for the population represented by the sample group collectively.

Proposition: that ways of experiencing represent a relationship between the experiencer and the phenomenon being experienced. This leads to the expectation that different ways of experiencing will be logically related through the common phenomena being experienced.

Core assumption: that different categories of description or ways of experiencing a phenomenon are logically related to one another, typically by way of hierarchically inclusive relationships (Marton & Booth, 1997).

Data collection: phenomenographic interviews are typically audio taped and transcribed verbatim, making the transcripts the focus of the analysis. The set of categories or meanings that result from the analysis are not determined in advance, but 'emerge' from the data in relationship with the researcher.

Data analysis

Analysis usually starts with a search for meaning, or variation in meaning, across interview transcripts. This is then followed by a search for structural relationships between meanings. In the early stages the researcher should display a high degree of openness to possible meanings, with subsequent readings focusing more on particular aspects or criteria. The ultimate aim is to shed light on the whole by focusing on different perspectives at different times.

Categories of description begin to be formulated by identifying key qualitative similarities within and differences between the categories. In practical terms, transcripts or selected quotes are grouped and regrouped according to perceived similarities and differences along varying criteria. At times the groupings are made before explicit description of the similarities and differences, while at other times the groupings are made according to tentative descriptions for categories, as a checking and validation procedure.

Things to consider:

1. how much of each transcript is considered at one time during the analysis
2. the emphasis placed on analytic collaboration with other researchers
3. variation in ways of practically managing the large amounts of data involved
4. the degree to which the logical structure of the outcome space is seen as needing to emerge as directly as possible from the data versus more explicitly reflecting the professional judgement of the researcher
5. use of communicative and pragmatic validity checks
6. use of coder and dialogic reliability checks