Theoretical and Methodological Considerations

The literature on research design in educational settings supports the use of mixed methodology case-based techniques for investigating new teaching and learning approaches, or the use of new technologies in education (Creswell & Plano-Clark, 2007; Johnson & Onwuegbuzie, 2004). Therefore, a mixed methodology case-based approach was selected for this study as the study aimed to provide an insight into a new aspect of technology use in the educational environment through exploring students’ experiences of m-learning in a range of different learning environments. A case-based mixed methodology is advantageous as it provides a rich data set and opportunities to explore multiple facets of the learning environment (Teddlie & Tashakkori, 2009). Furthermore, a mixed methodology offers the combined

of a mixed methodology study contribute data that is statistically measurable and supports correlation research, and quantitative data is enhanced by qualitative data collected to support and provide further detail resulting in a comprehensive image of the phenomenon being studied (Teddlie & Tashakkori, 2009). The qualitative

approach, embedded in a mixed methodology, allows for documentation of multiple realities and perspectives, and it supports inductive analysis whereby knowledge of the topic studied is constructed based on analysis of the data (Creswell, 2007).

For this study, a complementary style of analyses was selected, which was informed by the principles of the complementary explorative data analysis (CEDA) research

methodology, initially developed by Sudweeks and Simoff (1999), extended as the complementary explorative multilevel data analysis (CEMDA) by Riva and Galimberti (2001), and further revised by Sudweeks (2004, 2008). CEDA incorporates

complementary use of both qualitative and quantitative methods, depending on the particular research stage or the initial assumptions that need to be taken into

consideration. In this study, the multilevels are represented by the analyses of quantitative and qualitative data gathered from students and lecturers.

4.2.2 Multiple Case Study Approach

Case study research approaches involve exploration of a case, or multiple cases, through detailed data collection via multiple sources of information rich in context, and allows for the investigation of a problem within real-life contexts (Creswell, 1998; Scholz & Tietje, 2002). Yin (2009) defines a case study as:

An empirical inquiry, that investigates a contemporary phenomenon in depth, and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident. (p. 18)

Yin (2003, 2009) recommended the use of case-based methodologies in studies where the behaviour of the participants in the study cannot be manipulated, and where the contextual conditions of the study are relevant to the phenomenon being studied. Similarly, Miles and Huberman (1994, p. 25) define a case as “a phenomenon of some sort occurring in a bounded context”, with the emphasis on establishing the boundary of the case as a unit of analysis in a defined setting, where the context of the case is integral to the case itself.

A multiple case study can be described as a case study incorporating multiple individual cases. According to Yin (2003), multiple case studies can be more robust than a single case study as the inclusion of multiple cases applies a replication logic which strengthens the external validity of the findings, and the result is analogous to conducting multiple single case studies. However, Yin (2003) stresses that a

disadvantage of multiple case studies is the requirement for more resources and time than is needed when conducting a single case study.

This study applies a multiple case study research design to identify students’ and lecturers’ perceptions of m-learning in a variety of courses and university settings. The multiple case study approach was selected for this study as m-learning is a

phenomenon that is difficult to observe and may vary considerably between cases, across settings and within each setting. The multiple-case study approach enabled the researcher to explore similarities and differences within and between cases, and groupings of cases (e.g. by discipline type, or m-learning program).

Stake (2005) summarised the conceptual responsibilities of a qualitative case researcher as:

1. bounding the case and conceptualising the object of the study;

2. selecting phenomena, themes, or issues;

3. seeking patterns of data to develop the issues;

4. triangulating key observations and bases for interpretation; 5. selecting alternative interpretations to pursue; and

6. developing assertions or generalisations about the case. (p.459)

In all types of research validity, and reliability are important considerations. A primary strategy to ensure validity and reliability in case-based research is

triangulation of data types and sources (e.g. surveys, interviews, focus groups). Stake (1995, 2004) defines triangulation as working towards substantiating an interpretation, or clarifying meanings and, additionally, as a means of identifying different realities. Stake (2004) stresses that triangulation is not a single step, but should be a continuous process undertaken throughout the study. Triangulation of multiple data sets is recommended as it can both confirm or contradict results (Creswell & Plano-Clark, 2007), and verify the repeatability of an observation or interpretation (Stake, 2004). For example, in practice, validation of qualitative data analysis can be achieved by independent coding of data and comparison of emerging themes and categories by multiple researchers, or by double coding, where the researcher returns and codes the same data set and compares the results (Miles & Huberman, 1984).

To facilitate triangulation of results, multiple data collection is recommended (Yin, 2009). As only one point of contact with students was feasible in this study, due to limited access, an online survey gathering both qualitative and quantitative data from

students was designed. In addition, a survey was administered to lecturers of the selected units.

According to Stake (1995) and Yin (2003), findings of case studies can be generalisable. Yin (2003) states that this generalisability can be made to theoretical propositions, rather than to populations or universes, and employing a multiple case methodology for a study supports generalisability across cases. Case studies can be applied for either a literal replication (predicting similar results), or for a theoretical replication (predicting contrasting results with predictable reasons). Generalisations, based on case study findings, are assertions of enduring value and are context free implying transferability to different contexts (Lincoln & Guba, 2000).

The generalisability and transferability of case study outcomes support the application of case-based studies for theory building (e.g. Eckstein, 2000; Eisenhardt, 1989;

Eisenhardt & Graebner, 2007; Yin, 1989 ). In describing the use of case studies for theory building, Eisenhardt (1989) recommended prior specification of potential constructs identified in the literature to shape the initial design of theory building research as this provides firmer empirical grounding for the research and emergent theory. However, Eisenhardt (1989) stressed that, though the research problem and potentially important variables can be formulated with reference to literature, researchers should avoid thinking about specific relationships between variables and theories, particularly at the outset of the process to avoid bias or limiting the findings. Eisenhardt (1989) also highlighted that, when building theory from cases studies, it is important to select cases that are likely to replicate or extend the emergent theory, and to choose extreme and/or polar cases.

Therefore, in this m-learning study of students using tablet or laptop computers, there was a deliberate selection of polar cases for comparison: cases where students were participating in a laptop program; and cases where no program was in place thus students provided their own laptops. For theory building, Eisenhardt (1989)

recommended four to ten cases; therefore, after examining various units in different universities, seven suitable cases were selected for inclusion in the study. The case studies from Edith Cowan University, Charles Darwin University, and Murdoch

University were purposively selected by meeting the criteria of above average student laptop use or participation in a laptop/tablet program. Initially, several units meeting the required criteria were identified at each institution. Where multiple units included the same cohort of students, only one of the units was selected for inclusion in the study. Unit coordinators for these units were contacted individually with a request for their unit(s) to be included in the study as cases.

4.3 Research Design