Liquidación de la sociedad de gananciales

This section discusses the overall approach to research adopted in this study.

4.3.1 PositivismVersusInterpretivism

Positivist research involves formulating propositions (hypotheses) based on theory. Positivism suggests that truth is objective and that the truth of a proposition can be tested against data (Orlikowski & Robey, 1991). In tests against data, a proposition can be proved to be wrong, but a proposition cannot be proved to be correct. A proposition that was not demonstrated to be false in more and in a greater variety of tests is seen as supported by data and is treated as being true. The results of positivist research can be generalizable: the researcher may be able to state the circumstances in which the propositions tested in the research are expected to be true, independent of anyone’s subjective judgment.

Operationalize 

constructs

Select content 

source Sample content

Test hypotheses State hypotheses Code content Make inferences Coding  scheme

Interpretivist research aims at achieving an understanding of the social world from the perspectives of the researchers and of the research participants. Interpretivist research emphasizes social interaction, language, consciousness, and shared meaning (Boland, 1985; Myers, 1997). Interpretivism does not assume the existence of an objective truth, but rather allows multiple perspectives with respect to the same social reality to coexist; rather than trying to determine the “true” perspective, an interpretivist researcher

attempts to capture and to faithfully report the perspectives of all important stakeholders. Rather than claiming to avoid bias due to subjective judgments, an interpretivist researcher recognizes the possibility of bias in interpreting the results and provides sufficient information for the reader of the research to understand the nature of the possible bias. Interpretivist research does not claim generalizability; it is up to the reader of the research to decide if the research outcomes are applicable to the reader’s context. Some of the methodologists describe interpretivist research in terms of knowledge construction—knowledge is constructed in a dialogue between the researchers and the research participants (Kvale, 1995). Yet, the emphasis on knowledge construction in interpretivist research is not universal; for example, the highly influential introduction to grounded theory by Corbin and Strauss (2008) relies very little on the knowledge construction metaphor (although the knowledge

construction view of interpretivist research is positively mentioned in the introduction, Corbin and Strauss, p. 10).

In this study the research questions were formulated as hypotheses, thus suggesting the use of the positivist paradigm. The hypothesized effects of knowledge construction on perceived information quality and on information integrity were tested against

empirical data.

The positivist research stance adopted in the research method relates to formulating the research design of the present study. At the same time, I adopt a social constructivist view of discussion forum dynamics (see section 2.5) and I rely on knowledge

construction as a concept capturing the important aspects of such dynamics (see sections 1.5, 2.7, and 3.2.1). Thus, I take a view that describing discussion forum dynamics in terms of knowledge construction, with the resulting transcript reflecting the knowledge construction dynamics, is a useful and widely accepted way to make sense of such dynamics. However, I do not take an interpretivist approach to studying

knowledge construction, but rather operationalize the knowledge construction construct to measure it and to test hypotheses involving it.

There is no contradiction in relying on the knowledge construction metaphor in

describing the target phenomenon, and not relying on the same metaphor in formulating the research design—modelling the target phenomenon and modelling the research design are two separate issues. Indeed, the richest understanding of a given social phenomenon is likely to be achieved by addressing the phenomenon by a variety of methods, relying on different paradigms (Creswell, 1998). One can rely on

interpretivist research to understand the rich perspectives of the contributors on

knowledge construction in health support group online discussions. This would offer a rich and deep understanding of the phenomenon, but the research would be vulnerable to claims that the results lack objectivity. Positivist research, including the approach adopted by the present study, is reductionist—complex interactions in the discussion are projected onto a small set of variables, and the richness of the data is not fully taken advantage of. The results, however, can be seen as more objective and thus having greater relevance beyond the immediate research participants. In the long run, it is desirable that knowledge construction in health support group online discussions is studied by a variety of methods; this, however, is hardly feasible to achieve in a single study. In the present study, I opted for a positivist approach in an expectation that if the results are found interesting and significant by the broader research community,

interpretivist studies would follow.

A very similar stance was adopted by Schellens and Valcke in two studies. Schellens and Valcke (2005), in a study of educational science freshmen contributions to a discussion group, confirmed the hypothesis that higher levels of participation result in higher levels of knowledge construction. Schellens and Valcke (2006), in another study of educational science freshmen contributions to a discussion group, confirmed the hypothesis that at the end of the discussion period the levels of knowledge

constructions are higher than at the beginning (and thus, the contributors improve their knowledge construction skills over the discussion period). These studies, similarly to the present study, conceptualized technology mediated interactions in terms of knowledge construction, operationalized knowledge construction, and tested

further, recent studies that have conceptualized discussion forum dynamics as knowledge construction, measured knowledge construction, and statistically tested hypotheses regarding how knowledge construction relates to other constructs (and thus, relied on positivism in research design, but conceptualized discussion forum dynamics in terms of social constructivism) are the studies by De Wever, Van Keer, Schellens, and Valke (2009, 2010) and by Rienties et al. (2012) discussed in section 6.3.1.1.

4.3.2 QuantitativeResearchVersusQualitativeResearch

Quantitative research involves representing social reality using quantities and

mathematical relationships. Quantitative research is often associated with the positivist paradigm because quantitative research offers a way to test hypotheses—by applying inferential statistics to measured quantities. In quantitative research hypotheses regarding causal relationships can be investigated by applying inferential statistics to test relationships between variables (Sale, Lohfeld, & Brazil, 2002).

Qualitative research involves working with rich data, such as texts and observations, which allows researchers to construct new understandings of the underlying social reality. Qualitative research is primarily used in conjunction with the interpretivist research paradigm (Sale et al., 2002).

This study relied on quantitative research to test the research hypotheses stated in section 1.6. In this study, the effects of knowledge construction on perceived

information quality and information integrity were investigated by operationalizing the constructs as variables, followed by using inferential statistics to investigate the

relationships between these variables.

4.3.3 ExplanatoryResearchVersusExploratoryResearch

Exploratory research involves investigating little-understood phenomena and

generating hypotheses for further research (Marshall & Rossman, 2010). Exploratory research is conducted in areas where the theory is either not available or is weak.

Explanatory research focuses on testing theories (Marshall & Rossman, 2010). Explanatory research is conducted in areas where there is sufficient understanding of social phenomena, and thus the theory is relatively strong.

This study was to a large degree exploratory, because it addressed the effects of

knowledge construction on perceived information quality and information integrity; no study has attempted this in the past.

4.3.4 ApproachtoDataCollection

The most common approaches to data collection in quantitative research are experiment, survey, and content analysis.

An experiment requires changing the values of independent variables to compare outcomes (i.e. changing the level of knowledge construction to observe the effects of knowledge construction on information quality). Researchers modify the values of independent variables to observe the changes in response variables. In the present study, the use of an experiment as a research technique was not feasible because of the difficulty in controlling the level of knowledge construction. Because discussions at communities of practice occur naturally, and communities of practice are self-

regulating, an attempt to control such a discussion would destroy the ecological validity of the study.

Both surveys and content analysis include studying populations, but in surveys the populations are of human participants, and in content analysis the populations are of documents. Information quality is a property of a document, and the level of knowledge construction, as conceptualized in this study, is a property of the dialogue captured in a document. Neither information quality nor knowledge construction can be assessed by surveying the document contributors. Therefore, a survey was not an option.

Content analysis involves sampling documents, coding documents to measure

constructs (such as the dimensions of knowledge construction, perceived information quality, and information integrity), and testing hypotheses regarding relationships between the constructs. As content analysis involves working with authentic documents, the results of content analysis have high ecological validity. Moreover,

content analysis was feasible to execute within the time and financial constraints of this study.

In view of the considerations presented in this section, this study used content analysis.

One drawback associated with using content analysis is that, unlike experiments, content analysis does not distinguish causes from effects. However, as in this study information is generated via discussion (and not the other way round), it appears more plausible that various aspects of the discussion (such as the level of knowledge

construction) affect the quality of the resulting information, rather than the other way round.

Compared to collecting data from the contributors directly (as in a survey), the drawback of using content analysis was that ultimately the results of the content analysis were used to make abductive inferences about the context of the content generation and use. These contexts involved both contributors and lurkers. Thus, more insightful results could have been obtained by combining content analysis with a survey, as in Newman et al. (1997) and Kanuka and Anderson (2007). However, this was not possible, as contact details of the initial contributors (and, particularly, of lurkers) were not available. Moreover, there were concerns that disrupting discussions by including contributors within the scope of the research would result in harm. Therefore, the option of combining content analysis with a survey was considered, but rejected, and the research was limited to conducting content analysis.