RESEARCH METHODOLOGY
3.11 Data Analysis
Data analysis is the systematic elicitation process of incorporating the mass of
collected data. Undertaking data collection and analysis in a systematic and well-
planned manner, it is possible to analyze data rigorously and to draw verifiable
conclusions (Marshall and Rossman, 1999; Denzin and Lincoln, 2003).
Altinay and Paraskevas (2008) define qualitative data analysis as:
“... the conceptual interpretation of the dataset as a whole, using specific analytic strategies to convert the raw data into logical description and explanation of the phenomenon” (Altinay and Paraskevas, 2008:167).
As my research project was a qualitative inquiry based on inductive reasoning
derived from meanings expressed through words and experiences, the collected
data was interpreted through conceptualization and categorization (Bogdan and
Biklen, 1992; Marshall and Rossman, 1999; Denzin and Lincoln, 2003).
It was my view that action research improves the quality of human interaction, is
participatory, and methodologically eclectic, seeking to understand the process of
change within systems and using feedback from data in an ongoing cyclical
process (Altrichter et al., 1993; Cohen et al., 2000). In my research project,
action research was undertaken in order to create an action plan for the
development of the Distance Education Institute based on EUA Standards by
focusing on the roles of tutors to facilitate communication in constructing
knowledge.
In respect to the nature of action research and the focus of my research project,
different experiences and meaning were collected by multiple data collection
techniques within an ongoing cyclical process (Hubbard and Power, 1993). As
voluminous data can be gathered in qualitative inquiry, paying attention to how
data were verified and building a coherent interpretation was essential
throughout. Therefore collected data were managed through triangulation to
underpin data organization, theme development and interpretation (Saunders et
al., 2000). I also balanced efficiency and design flexibility by focusing on a
series of action and data collection techniques that would produce valid and
reliable findings (Marshall and Rossman, 1999).
Content Analysis
Management and analysis of qualitative data from multiple data collection
research tool used to determine the presence of certain words or concepts within
texts or sets of texts in relation to the focus, I quantified and analyzed the
presence of meanings and relationships of concepts and then made inferences.
This provided a way of managing qualitative data that was less time consuming,
and costly, compared to other data collection techniques by allowing me to
conduct what can be called “desk research” without any disruptions, and
produced data in a permanent form, ready and collected for analysis. Therefore,
having easy access to research participants, being a worker researcher and having
capabilities in the field, using content analysis in qualitative data analysis, and
being strategic in action enabled me to handle my project, particularly in
managing the data collection and analysis process.
I broke down manageable categories on a variety of themes indicated by the
content analysis employed in my project (Fraenkel and Wallen, 2000).
Dimensions of organizational climate, the four hats” of metaphors of
pedagogical, social, managerial and technical roles of tutors, the five stage model
of Salmon, the roles of tutors within online socialization, and the quality and
characteristics of online tutors were considered key themes in the data analysis.
Within an inductive approach to qualitative data analysis, coding,
conceptualization and ordering were undertaken. I categorized the themes of
each action in order to conceptualize and order the collected data. Conceptual
analysis identifies in a text the existence and the frequency of concepts, whether
in simple words or in phrases.
In this analysis, I chose a concept for examination and then looked at the
related to this concept in order to create a whole picture for the research findings
(Altinay and Paraskevas, 2008).
My qualitative research inquiry consisted of the following series of actions. The
data collection process and analysis were conducted simultaneously. The first
step was evaluating the organizational climate of the Distance Education Institute
regarding communication flow. For this, I used focus groups. The focus groups
enabled the sharing of experiences in a negotiated atmosphere among the
institute’s members. In addition, the focus groups supported the preliminary
training of the members about the importance of communication. The targeted
group were online tutors who delivered online courses from different
departments.
Focus groups was the right choice of data collection technique as it allowed
collective voices to reveal detailed evidence on social situations and meanings
from participants’ own experiences without consuming excessive time (Denzin
and Lincoln, 2003). Furthermore, compared to individual interviews, focus
groups provided the advantage of uncovering the interactive processes occurring
among the participants. The data from the records were kept and analyzed using
content analysis and converting qualitative data to quantitative based on my
categories. In the qualitative data analysis from the focus group, content analysis
was used in interpreting results. Thematic analysis was also employed in that a
concept was chosen for examination, and the analysis then involved quantifying
and tallying its presence in the focus group discussions.
In the second step of my research, I used in-depth interviews to gather data on
how the current roles of the tutors and the new roles of the tutors differed from
Exploratory in-depth interviews consisting of open-ended questions gave a
chance to the participants to explore their experiences, thoughts and
recommendations regarding my process.
Similar to the focus groups, in-depth face to face conversations between me and
the participants were analyzed by conceptual analysis. Qualitative data analysis
is the conceptual interpretation of the dataset as a whole, using specific analytic
strategies to convert the raw data into logical description and explanation of the
phenomenon under study. In other words, data analysis is all about making sense
of what the data say about the research focus. In this respect, conceptual analysis
was the right choice for qualitative analysis to interpret the findings based on
themes and categories.
Self-reports of the online tutors were used to report changes in the performances
of online tutors in their roles in relation to their own point of view. As
mentioned, the target group were online tutors who voluntarily and purposefully
participated in my research project. The self-reports provided primary data for
the qualitative research, providing in-depth, large amounts of data in which
participants reported on their experiences, thoughts and perceptions in relation to
the specific focus.
The self-reports were produced through questionnaires with open ended. Similar
to the focus groups, the interview conversations and qualitative documents were
analyzed through content analysis based on the selection of themes as in
conceptual analysis.
Furthermore, self-reports were obtained from online students as qualitative data
in order to evaluate the performances of online tutors in their roles and examine
the self-reports of the online students using conceptual analysis. During my
research process, I kept a diary and notes about my observations and reflections
at every step of my actions as an insider researcher (Rowley, 2003).
Triangulation
I analyzed the qualitative data in my project by reducing and rearranging the
voluminous amount of data into a more manageable and comprehensible form
based on certain patterns, categories, themes. Multiple data collection techniques
enabled triangulation, which is a classic method of seeking convergence of
results and compensating for the weaknesses of individual data collection
techniques as well as better comprehending a phenomenon being explored
(Creswell, 1994; Bryman, 2004).
The multiple data collection techniques and triangulation were shaped by the
nature of my work-based project, and by its approach and focus. Data from the
focus groups, in-depth interviews, self-reports and researcher diary were
triangulated, increasing the validity and reliability of my research outcomes and
results. Figure 2 below shows the approach to triangulation in my research
project (Hubbard and Power, 1993; Creswell, 1994; Cohen et al., 2000,
Silverman, 2000; Denzin and Lincoln, 2003; Bryman, 2004).
Data Collection Techniques
Research Theory, Practice Diary Actions
The final step was to prepare a handbook on communication practices in the
institute, showing how to teach online courses in terms of online pedagogy and
evaluating the sustainability of my research project through feedback from online
tutors. This secured the outcome of my project by stressing the harmonic picture
of triangulated data in my project.