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.

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. A Quick Review Quantitative research Qualitative 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

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)
Approach
Type
Purpose
Limitations
Resolutions
QUAL + quant
Simultaneous
Enrich description of sample
Qualitative sample
Utilize normative data for comparison of results
QUAL >>> quant
Sequential
Test emerging H, determine distribution of phenomenon in population
Draw adequate random sample from same population
QUANT + qual
To describe part of phenomena that cannot be quantified
Quantitative sample
Select appropriate theoretical sample from random sample
QUANT>>>qual
To examine unexpected results
Which model did we use?
Which model did we use?

11. Concurrent Mixed Methods Designs
Parsimonious Designs (Creswell & Plano Clark, 2007)
Concurrent Mixed Methods Designs
Triangulation Design
QUAN Data & Results
Interpretation
QUAL Data & Results
Embedded Design
QUAN Pre-test Data & Results
QUAN Post-test Data & Results
Intervention
qual Process
Interpretation

12. Before-intervention qual After-intervention qual
Sequential Designs Mixed Methods Designs
Explanatory Design
QUAN Data & Results
Interpretation
qual Data & Results
Following up
Exploratory Design
QUAL Data & Results
quan Data & Results
Interpretation
Building to
Sequential Embedded Design
Before-intervention qual
QUAN Intervention
Trial
After-intervention qual
Interpretation

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 : 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.