The reflection–reflexion continuum

Qualitative studies are commonly challenged for their validity and reliability or trustworthiness due to the potential inconsistency in the data analysis process. The criticism relates to the role and awareness of the researcher as the core data

interpreter or data analyser, regardless of their experience in doing research. Novice researchers, particularly those who are conducting doctoral research, usually face a self-disagreement problem with their own interpretation of qualitative data in different timeframes of their study, as they are constantly in the process of building knowledge and understanding of their field of study along the doctoral research journey. This problem, if left unsolved, might impair the confidence of researchers and become a barrier to their data analysis task. However, this problem of instability and inconsistency could be solved if the qualitative data analysis involves a

81 turn could make the varied analysis outcomes become a strength of qualitative

studies.

A model called ‗the reflection–reflexion continuum‘ was developed and adapted to solve the problem of the inconsistency and instability of the outcome of qualitative data analysis in this research (see Figure 4.3). The model was used to juxtapose the change of roles when a particular dataset was analysed or interpreted in different timeframes: when the data were raw data, after the data were processed and became information, and after the information was interpreted and became knowledge. The role also changed in different stages of the research —as beginning researcher; as informed educational researcher. The continuum divided the differences between the act of reflection and the act of reflexion in terms of their influence on the research outcomes. The former consists of personal past experience, knowledge, skills and attitudes in educational research and the field of study; the latter involves the roles played as a doctoral student, an educational researcher and a specialist in the field of research.

Figure 4.3: The reflection–reflexion continuum

In the development of this model, two key concepts—reflection and reflexion were compared, as shown in Table 4.2. Reflection is defined as serious consideration about research activities, especially one that is related to data analysis and results interpretation; while reflexion is the account of research activities that is recorded as

82 a response to stimulus without serious thought. Both reflection and reflexion share similarities in terms of flexibility: positive stimulus or past events increase the control over meta-analysis and meta-interpretation; while negative stimulus or past events limit the control. The control includes the choice of the methods and depth of analysis and interpretation. The fundamental difference between these two concepts lies in the temporal basis. Reflection is based on events in the past, which means it is asynchronous with the research activities that are under consideration. In contrast, reflexion happens immediately after encountering the stimulus of research activities. In other words, reflexion is synchronous with real-time events. With this

comparison, this thesis attempts to revitalise the term ‗reflexion‘, which has been regarded as an archaic spelling of reflection by The Oxford Dictionary of English (2005). Besides, since ‗meta‘ is ‗a prefix placed before a word in order to describe properties about the original word‘ (A Dictionary of the Internet 2009), meta- reflection is reflection about reflection, while meta-reflexion is reflexion that is based on reflexion. However, as meta-reflection and meta-reflexion are based on the range of their associated reflection or reflexion, a hypothetical compound, denoted in grey colour in the continuum was drawn to represent the conceptual, rather than physical, boundary.

It is worth mentioning that the concept of reflexion must not be confused with an ambiguous concept ‗reflexivity‘. Although both reflexion and reflexivity share an identical root word ‗reflex‘, reflexivity emphasizes the importance of self-awareness, political / cultural consciousness, and ownership of one‘s perspective (Patton 2002). Indeed, as the existing meanings of reflexivity in social sciences do not suit the context of the continuum, the need to revitalise ‗reflexion‘ is reinforced. Meanwhile, Hertz‘s (1997) explanation on being reflexive echoed the characteristics of reflexion in qualitative analysis. According to Hertz (1997), being reflexive involves self- questioning and self-understanding, which relates to an ongoing self-examination of what one knows and how one knows about a particular experience while

simultaneously living in the moment.

Both reflection and reflexion are further divided into two opposing domains in the continuum, by referring to the degree of the researcher‘s physical control. The degree of physical control is associated with the extent of manipulation one could

83 have upon the quality and quantity of data. Unlike quantitative studies, the collection of qualitative data is generally cross-sectional, i.e. linked to phenomena that

happened in a specific, defined section of time. While recognising events that took place during data collection are not reversible in natural settings, three core

activities: analysing raw data, interpreting processed data, and constructing

knowledge are indeed revisable in qualitative studies. During the revisiting of data analysis process, positive events or stimuli like helpful research participants, acquiral of effective analysis methods or motivation given by peers allows room for

improving the quality of research outcomes (as in quadrants A and B); while negative events or stimulus such as difficult participants, insufficiency of resources or the loss of mental support, would restrict the yield of research outcomes (in quadrants C and D).

The main function of the reflection–reflexion continuum in qualitative data analysis is to act as a framework for classifying research outcomes, which could contribute to the attainment of a saturation state in the data analysis process, in turn justifying the trustworthiness of the research findings.

Table 4.2: Comparison between reflection and reflexion

Reflection Reflexion

Root word Reflect Reflex

Definition Serious consideration about research activities, especially one that is related to data analysis and interpretation.

Account upon research activities that is recorded as a response to a stimulus without serious thought.

Temporal basis

Based on events in the past. Based on stimulus encountered in real-

time. Relationship

with stimulus

Passive, delayed and asynchronous. Active, immediate and synchronous.

Degree of physical control

Reflection or meta-reflection on positive past events could increase the flexibility of meta-analysis and meta- interpretation.

Reflexion or meta-reflexion on positive stimulus could increase the flexibility of meta-analysis and meta-

interpretation. Reflection or meta-reflection on

negative past events might limit the flexibility of meta-analysis and meta- interpretation.

Reflection or meta-reflexion on negative stimulus events might limit the flexibility of meta-analysis and meta-interpretation.

84 The proposed model was developed based on a comparative analysis of the role played by reflection and meta-reflection in this study and on a review of a similar role undertaken by reflection in a completed doctoral research study, which aimed to explore the experience of Asian students in the UK in a natural setting (Tan & Wu 2010). Both of these studies intended to answer research questions using mixed methods, and their main approach is qualitative. They also shared an exploratory nature in natural settings. Based on these commonalities, the design of the studies were compared and contrasted to juxtapose the similarities and differences in terms of their mixed method nature, data collection methods, data analysis methods and the conduct of reflection and meta-reflection along the doctoral journeys. The

juxtaposition is meant to extract the elements of reflection and reflexion in the studies and to map those elements into a model that could justify their value in the research process.

Besides analysing two doctoral studies, the development of the model also gained inspiration through the research methodology literature. According to Gibbs (2007), the quality of qualitative analysis depends on its claimed objectivity—its freedom from bias or partiality. A constant proposal for safeguarding the quality of qualitative research is to include reflexivity components in one‘s research (Gray 2009). Thus, Patton‘s (2002) triangulated inquiry model was used to direct the interpretation of qualitative data, in which the analyses were conducted from three perspectives: the inquirer or the researcher, the inquired participants, and the key stakeholders of the research (see Figure 4.4). Each of the perspectives took predetermined reflexive screens into consideration during the analysis, which could be culture, age, gender, class, social status, education, family, political praxis, language and value. While these directions may assist researchers to increase the number of perspectives targeting the research issues, they may not help the researchers‘ interpretation reach a saturation state over time, hence justifying the need for a mechanism that focuses on how the reflection and reflexion could be structured to make interpretation stable, consistent, persistent if not saturated. To resolve this challenge in the current

research, a mixed methods research design model, followed by an evolutive spiral- segregated case study research design model were developed. The following sections of this chapter explain the design and development of these models.

85 Figure 4.4: Triangulated inquiry model. Source: Patton 2002