Research Planning Uop Res728

Funding for domestic violence shelters in Sebastian County, Arkansas has decreased with the decline of the state’s economy beginning in 2010, when most manufacturing jobs were outsourced to foreign countries. Funding now primarily comes from private and non-profit sponsors and donors. This change in funding has brought about the need to be responsive to the wants and needs of not only the victims but also of the donors that provide the funding for the shelters.

The expectations of the donors with regard to the role of paid employees referred to as advocates and the volunteers has also changed. The donors expect the advocates and volunteers to be on call 24 hours a day 7 days a week and the shelters’ executives have had to establish in written form the boundaries established for the role of employees and volunteers. The focus of this study will be the actual role of the employees and volunteers versus the perceived role of the employees and volunteers by the private and non-profit sponsors and donors.

This study will require data to be gathered from all persons involved with the domestic violence shelters, which will include donors, executives, employees, and volunteers. The data that will be collected during this study will be relevant to the perceptions of the domestic violence shelters’ executives, employees, and volunteers’ role versus what the donors to the shelters perceive to be the roles of the people that work on either a paid or volunteer basis. The data collection methods will include participant observations, informal interviews, and open-ended questionnaires. Data Collection and Sampling Strategies

The data will be collected during the annual fundraiser by observing the interactions of the donors with the executives, employees, and volunteers that are participating in the fund raiser. Observations of the way each cohort interacts with one another, whether there is respect shown toward the employees, volunteers, executives, and donors. According to Kawulich (2005), observations allow the researcher to see the nonverbal expressions, determine who interacts with whom, determine the manner in which communication takes place and to ascertain how much time is spent on the various interactions.

Kawulich also posits that observation allows for the checking of definitions of certain terms used within the environment by the participants while also allowing the observation of the mannerisms of the participants that indicate their resolve not to be impolite, politically incorrect, or insensitive. The informal interviews according to Turner (2010), work well for the spontaneous generation of questions within the natural interaction that occurs with informal conversation. The informal interview will not have a predetermined number of or structure of questions.

It is the feeling of Turner and this researcher that this would interfere with the flexibility and naturalness of the interviews. The main disadvantage to this method of data collection is the potential to stray from the research topic. The last method of data collection will be the use of open-ended questionnaires, which will have five questions for the participants to answer after receiving instruction about the data collection tool. According to Sapsford and Jupp (2006), the chief advantage of the questionnaire is that it can be administered to a group of people at the same time.

Sapsford and Jupp posit that the main disadvantage to questionnaires is that some people will not return the questionnaire to the researcher. Data Management and Analysis According to Merriam (2009), the preferred method of data analysis is to perform the analysis during the data collection. Merriam posits that without ongoing analysis prevents confusion, inability to focus, and may allow the sheer volume of the data to become overwhelming for the researcher. Bogdan and Biklen (1998) as cited by Merriam (2009, p. 171) offer ten suggestions for analyzing data as it is collected.

Those suggestions include:

1. Make decisions to narrow the study
2.  Make decision about the type of study you want to accomplish
3. Develop analytic questions
4.  Plan data collection sessions according to what was previously experienced
5.  Record as many observer’s notes as possible as you go
6.  Write memos to yourself about what you are learning
7. Try out ideas and themes on participants 8
8. Begin exploring the literature while in the field
9. Play with metaphors, analogies, and concepts
10. Use visual devices.

Data collection and analysis could possibly go on forever but once the researcher has reached saturation or in other words, information starts repeating itself then the researcher knows it is time to stop the collection of data. Managing the data during the collection process requires that coding or the assignment of some sort of shorthand designation that will allow the researcher to find the information quickly and with ease (Merriam, 2009). Data analysis can be performed by hand by developing categories or themes for the data collected.

Coding is the assignment of notations next to data as you read over the data. It is like marking in the side margin what you the researcher believes is potentially relevant to your research (Merriam, 2009). Assigning codes to the pieces of data is the way the researcher begins categorizing the data. This process is used for each set of data to be analyzed. Data analysis can also be performed with the use of modern technology such as the computer and software programs developed especially for qualitative data analysis such as CAQDAS (computer assisted qualitative data analysis software), MAXQDA, ATLAS. i, HyperRESEARCH and NVivo. Bazeley asserts that the use of technology for data analysis further than is possible when performing analysis by hand (2006). According to Leech and Onwuegbuzie (2007), CAQDAS programs provide an excellent tool for recording, storing, indexing, and sorting the voluminous data that are the hallmark of many qualitative research studies. Bazeley also posits that another advantage to using CAQDAS programs is that the programs can record all of the major analytic decisions that the researcher makes, which then leaves an audit trail.

However, it is noted by Leech et al. , that even though programs can help the researcher analyze the data the program cannot analyze the data for the researcher. Denzin and Lincoln (2005) make the point that the researcher is still the main tool for analysis and the flexibility, creativity, insight, and intuition of the researcher should never be replaced by mechanical analysis of data. Conclusion The use of multiple data collection and analysis methods allows the researcher to use the strength of all chosen methods in order to get a better picture of what they are focusing on in the study.

Using multiple qualitative data analysis tools can help researchers to address what Denzin and Lincoln (2005) refer to as the crisis of representation, namely, the difficulty in capturing lived experiences via text. Denzin and Lincoln posit that using multiple types of data collection and analysis makes the process of qualitative research more rigorous, which may make qualitative research even more popular than it has become.

References

1. Bazeley, P. (2006). The contribution of computer software to integrating qualitative and quantitative data and analyses. Research in the Schools,, 13(1), 64-74.
2. Bogdan, R. C. , & Biklen, S. K. (1998). Qualitative research for education: An introduction to theory and methods.
3. Bosston, MA: Allyn & Bacon. Denzin, N. K. a. L. , Y S. (2005). Introduction: The discipline and practice of qualitative research. In N. K. D. Y. S. Lincoln (Ed. ), The sage handbook of qualitative research (2nd ed. ).
4. Thousand Oaks, CA: Sage Publications. Kawulich, B. B. (2005). Participant observation as a data collection method. Forum: Qualitative Social Research: Sozialforschung, 6(2).
5. Leech, N. L. & Onwuegbuzie, A. J. (2005). Qualitative data analysis: Ways to improve accountability in qualitative research. Paper presented at the annual meeting of the American Educational Research Association, Montreal, Canada.
6. Merriam, S. B. (2009). Qualitative research: A guide to design and implementation. San Francisco, CA: Jossey-Bass. Sapsford, R. J. , V. (2006). Data Collection and Analysis (2nd ed. ).
7. Thousand Oaks, CA: Sage Publications. Turner, D. W. , III. (2010). Qualitative interview design: A practical guide for novice investigators. The Qualitative Report, 15(3), 754-760.