As earlier hinted, this study is based on mixed methods research design. Mixed methods design combines quantitative and qualitative research methods to generate new knowledge (Stange et al., 2006). Surveys research, as one of the two popular strategies of inquiry associated with quantitative research and positivist perspectives (the other being experimental or quasi- experimental methods) is integrated with semi-structured interviews of phenomenological research method. Historically, this strategy of combining research methods is credited to
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Campbell and Fiske (1959) in their effort to study validity of psychological traits. In spite of the fact that researchers had been using more than one methods of inquiry, these researchers were the first to truly announce a “multimethod matrix” and by so doing popularized this strategy. It has been an established research method in the past few decades to mix methodologies more commonly, by combining field methods (e.g. observations and interviews) with conventional surveys (Creswell, 2003). However the emergence of mixed methods in behavioural and social sciences, according to Tashakkori and Teddie (2003, p. 697), began in the 1980s. The rationale behind a combination of quantitative and qualitative approaches, to which this current study takes a cue, is that all methods have their limitations and through a combination of approaches the weaknesses hold the possibility of cancelling out the biases in the other. Otherwise, it is meant to capture the best of both approaches. As expected of a mixed methods approach, the researcher sees the strength in the methodology in order to address the research questions and theoretical perspective at different levels. Due to the evolving nature of the concept of new communication technologies and journalism, mixed methods is useful for developing and testing a new instrument, to explain or interpret a concept and ultimately to explore a phenomenon. According to Creswell (2003, p. 21), a researcher following mixed methods bases “the inquiry on the assumption that collecting diverse types of data best provides an understanding of a research problem.” This research shares this assumption.
4.3.1 Mixed Methods: Characteristics
A number of characteristic are associated with the mixed methods research design. For instance, in mixed methods the research problems can become research questions and/or hypotheses as dictated by researcher’s prior knowledge, literature or the research process. Sample size can vary depending on the methods used while data gathering can involve any technique available to researchers. More so, interpretation of data is continual and can shape phases of the research process. Creswell (2003, p. 211) however suggests a systematic framework for conducting mixed methods research. This framework involves a combination of four-grid decision and six-point strategy. The first and second decisions to take involve chosen the sequence of data gathering and determining which of the modes should take priority over the other during data collection as well as during analysis. The next is to determine what the integration stage would involve. And lastly, is the decision which involves determining whether the analysis will be theory-driven or not. Creswell (2003) goes further to highlight six
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mixed methods design strategies: sequential explanatory, sequential exploratory, sequential transformative, concurrent triangulation, concurrent nested, and concurrent transformative.
These strategies have further been summarised into three basic divisions of mixed methods strategies. The first is the “sequential procedures”; in which a researcher uses one method to expand the other; not minding which method comes first. Upon completion of one method, the researcher launches the other in order to examine the phenomenon from an emerging perspective. The second mixed methods strategy is termed “concurrent procedures” and with this strategy, the researcher launches the methods being mixed at the same time. The goal here is to provide a detailed analysis of the research problem. For instance, quantitative and qualitative data are collected at the same time during the study and the information generated from the data is used for the overall interpretation of the results. This mixed methods strategy involves what is called “nesting” of one form of the data with another (Creswell, 2003). This may involve using the numeric or non-numeric data to assess the different levels of units in an organisation or to analysis different questions altogether. The last but not the least is called “transformative procedure”. This strategy involves a researcher working under the guidance of a theoretical framework that encapsulates both the qualitative and quantitative approaches to data collection. It equally entails evaluating the theoretical perspectives of the study at different levels of analysis. The current study employed concurrent procedures to mixed methods. The rationale for the choice of this approach was borne out of the nature of the research as underscored by limited funding and time of completion. Be that as it may, for an exploratory study concurrent procedures provide an avenue to maximise the limited resources to achieve a detailed analysis of the research.
4.3.2 Deploying Mixed Methods for the Study
In line with the mixed methods concurrent tradition, I began the study with broad surveys which gathered both the quantitative and qualitative at the same time and places. The quantitative data were obtained using adapted scales in relation to technology adoption and journalistic role conceptions. The numeric data collected would be used to explore the phenomenon of technology use among Nigerian broadcast journalists and also to determine the relationship between adoption variables and journalists role conceptions. It would also be used to explore the dimension of interactivity in Nigerian radio programming with the use of interactive and non-interactive technologies. The qualitative approach produced non numeric data which were collected from the research participants. The general strategy for the mixed methods approach therefore follows concurrent data gathering and analytic procedures in
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which quantitative and qualitative data were used as a means of providing a comprehensive analysis of the research problem. Since the data are collected at the same time, it is better that the analyses follow sooth in order for easy integration of the information in the interpretation of the overall results.
In spite of this uniqueness, the mixed methods research design has its own weaknesses as pointed out in literature on research methods (Creswell, 2003). For instance, some researchers have noticed that mixed methods designs can generate unequal evidence, thereby jeopardizing the research aim and objectives. When data are not collected concurrently, it may also lead to time wasting.