A case study, according to Yin (1993, 1994), should not be confused with the similar strategy of ethnography. Ethnographic methods are largely derived from cultural anthropology. In studying organisations such as schools, these methods might help the researcher to extract cultural and social knowledge and identify actions and instruments that participants utilise in their everyday life (Prasad, 1997; Schwartzmann, 1993). Yin (1994) distinguished ethnographies from case studies in that the former takes a long period of time to conduct and requires very detailed observational evidence. Case studies, by contrast, are conducted within a defined period of time and do not necessarily imply the use of ethnographic techniques. Researchers conducting case studies need not even visit the organisation under study; they could collect their data by consulting secondary sources or interviewing respondents telephonically or by e-mail.
Furthermore, a case study is an empirical inquiry that investigates a contemporary phenomenon within its real-life context, and this approach may have the boundaries between the phenomenon under study and its context in the ‗messy‘ realm where the boundaries of context and phenomenon overlap and/or are poorly defined. That was the case with this research in which the school and technology boundaries overlap and extend beyond the schools‘ walls and into the homes. Yin (1994, p. 13) stipulated that ―the case study allows an investigation to retain the holistic and meaningful characteristics of real-life events such as individual life cycles, organisational and managerial processes, neighbourhood change, international relations and the maturation of industries.‖ Therefore, the case study approach is especially useful in situations where contextual conditions of the events being studied are critical and where the researcher has no control over the events as they unfold. The case study, as a research strategy, should therefore encompass specific techniques for collecting and analysing data, directed by clearly
102 stated theoretical assumptions. Furthermore, data should be collected from different sources and its integrity should be ensured.
Within case study methodology a case can be classified as being singular or multiple. Accordingly, Smith (1988) and Yin (1994) described that the single case study approach is best used when the case is:
i. unique or critical, or when the researcher is able to access a previously remote phenomenon;
ii. critical to testing a well formulated theory, and
iii. a pilot or exploratory study that is representative of a larger population.
Several case study researchers, such as Herriott and Firestone (1983) and Stake (1994) considered that evidence collected from multiple case studies is more rigorous and complete than if it is only collected for a single case study because of triangulation. It is for this reason that a multiple school case study approach was adopted for the current study.
Another important case study requirement indicated by Lincoln and Guba (1985) recommended that case study research should establish ―trustworthiness‖ in order to verify the findings as worthy. They proposed that researchers should question themselves on ―truth‖, ―value‖, ―applicability‖, ―consistency‖ and ―neutrality‖, in addressing issues in relation to the terms of conventional research methods of ―internal validity, external validity, reliability, and objectivity‖ (p. 290). Further to this approach, Burns (1997) contended that the effort required to produce trustworthy findings that provide authentic understanding might be more time- consuming and rigorous than expected (p. 383). Whilst Isaac and Michael (1997) claimed that case study data-gathering mechanisms were similar to other data gathering methods, except that ―the characterization is distinctly different‖ (p. 221), and case study mechanisms seek to produce findings that are ―credible‖, ―transferable‖, ―dependable‖ and ―confirmable‖ (p. 221).
103
Triangulation as a research strategy
As discussed, rigor and validity are major concerns of researchers (de Laine, 1997; Schwandt, 2001) and triangulation is a means of ensuring research integrity (Wiersma, 1995). Triangulation is a method used to study the same phenomenon (e.g. digital technology use and decision-making) from more than one source, to provide ―rich‖ data (Dootson, 1995; Kushner & Morrow, 2003; Maggs-Rapport, 2000). Triangulation seeks to examine data from multiple sources to strengthen interpretations. By examining data from different sources and collected by different methods, findings can be corroborated across data sets, minimizing potential biases and so giving greater confidence in the findings. For example, data triangulation assumes that if data is collected from multiple sources, researcher bias is reduced. Moreover, triangulation of data from different sources and standpoints increases the validity of that data by verifying the repeatability of the observation and its interpretation by the researcher. Carter (1990) avowed that triangulation of data collection methods not only increased internal validity but also minimized researcher bias. He also postulated that ―no single method can hope to capture the complexity of…life‖ (p. 276) and so a mixed-methods approach utilising triangulation offers a better solution as a research method. In order to maximize a mixed-methods approach, leading researchers in this field (Cohen, Manion, & Morrison, 2000; Patton, 2002; Silverman, 1993; Tobin, Kahle, & Fraser, 1990; Tobin & Fraser, 1998; Woods, 1995; Yin, 1994) have suggested that triangulation can be achieved by:
i. using different data sources (data triangulation);
ii. using two or more investigators (investigator triangulation);
iii. using different perspectives to interpret data (theory triangulation), and iv. using multiple methods to gather data (methodological triangulation).
Using the above triangulation and using mixed-methods can result in one of three possible outcomes (Erzberger & Prein, 1997):
104 i. qualitative and quantitative results may converge (results lead to the same
conclusion);
ii. qualitative and quantitative results may relate to different aspects of the phenomena, but are complimentary (each supplements the other);
iii. quantitative and qualitative results may be divergent (results contradict each other).
Cohen et al. (2000) and Yin (1994) each ascertained that multiple data sources increased reliability and trustworthiness of a study‘s findings and also identified relevant similarities and difference associated within the data. The difficultly is that multiple data sources and techniques can create multiple interpretations. For instance, in this study, many actors (teachers, principals, students and parents/guardians) were asked about digital technology use and school decision- making, at different times and in different educational settings. In order to find consensus from different data sources Giddens (1984) recommended that the researcher needs to look for consensus and conflict within the data. Giddens (1984) related that researchers should look for commonalities and differences, and these need to be noted in order for the researcher to gain a deeper understanding of the study, although one interpretation or experience may not be any more ‗real‘ or ‗truer‘ than the next. The triangulation approaches previously mentioned (Cohen, Manion, & Morrison, 2000; Silverman, 1993; Yin, 1994) have been termed triangulation of time, place and person (Denzin, 1997) which Giddens‘ (1984) termed contextuality.