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Group Projects

1.  Consider complicated research questions; those that if answerable, would solve large, overarching problems in American society. Then make a list of the types of data necessary to solve these questions. How long would it take a researcher (or team of researchers) to collect all this data on their own? Now, identify if any of this data already exists, consulting the large secondary sources presented in this chapter as well as on the broader Internet. How much does the use of secondary data analysis cut down the estimated time researchers would spend solving the world’s problems? What are the problems with this approach with respect to your specific research question?
    
2. Break students into groups of 2 or 3. Each group will be assigned an article that they will present to the class (either mixed, quantitative, and qualitative). Have them discuss the methodology used in their article. What type of research design was used? What advantages did this design have? Finally, critique the methods used by the authors.
    
3. Break students into groups of 4 or 6. As a group, have them choose a research question they want to address. Make sure they specify their target population, the scope of their study, and any other broad logistics. Have them then divide themselves up into qualitative and quantitative teams. Each subgroup will write a research proposal on how they would answer their research question using only the methods of their ‘team’. Have this proposal include a substantial ‘limitations section’ where they identify how their analysis falls short. Bring the two teams back together; demonstrate how they can greatly limit their overall limitations by incorporating both types of analysis.
    
4. In groups of 2 or 3, have students review and critique a mixed methods research study from the lens of a methodological purists, methodological pragmatists, and a methodological pluralist. Have them present their critiques to the class.
    
5. Mixed methods research is often considered a lesser type of research, for no other reason than because of the academic feud present between pure quantitative and pure qualitative scholars. That being said, when acting in the real world, mixed methods provide researchers and social workers with much more complete and understandable information. In groups, brainstorm reasons why individual researchers might oppose or be in favor of mixed methods. Then write an impassioned speech (either against or in favor) to an envisioned national academic conference.
    

Mini Projects

1. Designing a Mixed Methods Study

1. You will read two articles which represent data sources and analyses using only one method. In this brief conceptual paper, you should:
2.  Suggest a few research questions raised but not answered by the analyses presented in each paper.
3. Propose additional data sources and analytic methods that you might employ to address those questions for each paper.
4. You should provide details for each suggested source and method (e.g., if proposing a semi-structured interview, then provide the interview prompts and a method for analyzing those data; if proposing an experimental intervention, then discuss the intervention design, outcome measures, and analytic methods for examining growth as a result of the intervention).
5. Discuss how these proposed methods would work in tandem with the methods already employed in the published study.
    

2. Big Data, Baby

1. Students should identify a software or analytic package that can process large amounts of data. Options include R, Weka, and Stata.
2. Students should acquire a huge data set, such as those found on city data portals or from the Census.
3. Students should import this data into their software/analytics package and play around with visualizations.
4. Students should keep a list of potentially interesting relationships between different variables in their data set.
5. Students should write up their results; noting how their preliminary (exploratory) research with this data set could be used to help identify avenues for further research and research proposals. Students should also note how they would complement their use of big data with narrower, specific data sets or personally collected data.
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3. Integrating Quantitative Data into a Qualitative Study

1. You start with qualitative data, design and conduct a focused study, and then design a quantitative study to address questions unaddressed or suggested by the quantitative data to which you have access.
2. For example, you may conduct intensive interviews around depression in the college setting.
3. Based  on your qualitative, thematic results, you will design an accompanying quantitative study that details:
   
   1. (a) the frequency of these occurrences
   2. (b) the the number of individuals who feel similar symptoms
   3. (c) a plan for integrating the findings with the qualitative data you have already collected and analyzed.

4. The objective of this project is to consider how the quantitative study should be designed to complement — not merely supplement — the qualitative study you have conducted.