Triangulation

1. Triangulation

2. Triangulation is a powerful technique that facilitates validation of data through cross verification from more than two sources. In particular, it refers to the application and combination of several research methodologies in the study of the same phenomenon.[2] • By combining multiple observers, theories, methods, and empirical materials, researchers can hope to overcome the weakness or intrinsic biases and the problems that come from single method, single-observer and single-theory studies. http://en.wikipedia.org/wiki/Triangulation_(social_science)

3. Triangulation Techniques • Data Triangulation • Investigator Triangulation • Theory Triangulation • Methodological Triangulation

4. Mixed methods research • A style of research that uses procedures for conducting research that are typically applied in both quantitative and qualitative studies • The purpose of these designs is to build upon the synergy and strength that exists between quantitative and qualitative methods in order to more fully understand a given phenomenon than is possible using either quantitative or qualitative methods alone

5. Mixed methods provides a clearer picture of what is happening in the real world. • Quantitative data give you some numbers to work with. • Qualitative data give you an explanation of the numbers. • Together they provide a way of triangulating data to confirm findings.

6. The research problem itself determines the choice of a design and method • Using surveys to identify specific groups of students and conducting focus groups with them to understand their views • A series of interviews are conducted to ascertain the critical issues bothering students, and a survey of the student body is conducted using these issues as variables

7. Quantitative research Deductive approach generalizable Causal relationships Identify and test hypotheses Random selection of participants Qualitative research Inductive approach Participant’s perspectives Describing and understanding relationships Emerging questions Purposive sampling A Quick Review

8. Inductive Reasoning Deductive Reasoning

9. Mixed methods is not that different from other methods Identifying a research problem Reviewing the literature Identifying a purpose and stating questions Views of knowledge Assumptions Collecting data Analyzing and interpreting data Reporting and evaluating the study

10. Preliminary Design Considerations (Morse, 1991) Which model did we use?

11. Parsimonious Designs (Creswell & Plano Clark, 2007) QUANPre-test Data & Results QUANPost-test Data & Results Interpretation qualProcess Intervention QUANData & Results QUALData & Results Interpretation Concurrent Mixed Methods Designs Triangulation Design Embedded Design

12. qualData & Results QUANData & Results Interpretation Following up quanData & Results QUALData & Results Interpretation Building to QUANIntervention Trial Before-interventionqual After-intervention qual Interpretation Sequential Designs Mixed Methods Designs Explanatory Design Exploratory Design Sequential Embedded Design

14. MIXED METHODS RESEARCH: A discussion paper JULIA BRANNEN Institute of Education, University of London Writing up mixed methods research What models are there for writing up mixed methods research? The answer is that there is a lack of exemplary studies that demonstrate different ways of writing up evidence based on different methods. This is unsurprising since, as we have noted, this is not straightforward. For one thing academic journals tend to be organised around disciplines and may favour particular types of research. Moreover different types of data analyses may sit awkwardly together on the published page and may require rather a lot of space to justify their validity and credibility. Some researchers using mixed methods may for such reasons report their qualitative and quantitative results separately. Researchers presenting evidence based on both qualitative and quantitative methods but drawing upon one set of evidence and under reporting the other may risk criticism for not fully exploiting the possibilities for the analysis of both data sets.

15. Competition and Cooperation Among Working Women in the Context of Structural Adjustment: The Case of Street Vendors in la Paz-El Alto, Bolivia Victor Agadjanian Journal of Developing Societies 2002 18: 259 Abstract This case study of women street vendors in La Paz-El Alto, Bolivia, examines the dynamics of competition and cooperation among this group of poor working women in the context of economic structural adjustment and political pluralization. It is argued that the economic and political reforms not only increase street vendors’ insecurities, but may also undermine the potential for their broad-based solidarity and collective actions. Extreme competition in the overcrowded street commerce, diminishing returns, and disillusionment with traditional forms of workers’ organization hinder cooperation among street vendors and fragment the social body of the street marketplace, often by further reinforcing its gender, class, ethnoracial, and religious fault lines. http://jds.sagepub.com/content/18/2-3/259.full.pdf