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Quantitative design
In order to examine such topic as equity in academic marker, a research can apply several strategies. The choice depends on the type of objective that the study has to achieve. For instance, if the key goal is to test a certain hypothesis, quantitative research methods will be more appropriate.
They help to identify the relationships between several variables such as impacts of gender or race on the compensation, paid to the educators, promotion opportunities, workload and so forth. Similar studies have already been conducted. For example, one can refer to the study by Paul Umbach (2006) who examined statistical data about the salaries of teachers and determined to what extent they are determined by gender.
If a researcher is interested in the affects on gender (independent variable) on equity in academic labor marker (dependent variable), he/she can choose statistical survey or structured interview as a method of data collection (Aanerud et al, 2007). It will be necessary to determine the sample size of the population. Furthermore, the sample has to be divided into two groups: male educators and female educators.
Each of the respondents will be asked the same questions about the number of working hours, monthly wages, and promotion opportunities. The researcher should also establish several control variables which remain unchanged during the study. They will be work experience, degree, and academic discipline (Umbach, 2006, p 187).
The researcher must maintain control over these variables because their essential for the validity of the findings. The respondents of the participants should be codified and later these data will be analyzed with the help of T-test and ANNOVA.
In this way, one can determine whether the relationship between the variables is statistically significant. Again, we need to say that quantitative design is more suitable in those cases, when a researcher need to test an assumption or a hypothesis.
Qualitative design
It is also possible to choose qualitative research methods in order to examine equity in academic market. Qualitative design is more appropriate in those cases, when a scholar intends to describe a certain social phenomenon in order to form assumption about a specific topic (Creswell, 2003, p 15).
Such approach has also been adopted by researchers. We can mention the study by Kennelly et al (1999) who attempted to identify the sources of inequality in academic labor market. The relied mostly on interviews and group discussions rather then statistical methods.
Under such circumstances, unstructured interview can be the most suitable a respondents will be asked a set of questions that would prompt them to express their views about the problem of inequality in academic labor market. It will be necessary to use open-ended question since they enable an interviewer to explain and expand his/her ideas.
They will need to describe those challenges which they face on a daily basis. Additionally, the respondents will need to describe the factors that affect equity. The major advantage of unstructured interview is that it enables the interviewer to clarify both questions and respondents of the participants. However, it has some limitations, especially the so-called interviewer effect.
This means that the subject can behave or respond differently in the presence of interviewer. While analyzing the responses of interviewees, the researcher has to single out the most common themes or issues. On the basis of these findings, a scholar will be able to form a hypothesis about the factors that impact equity in academic labor market. Later these assumptions should be verified with the help of quantitative research methods.
Mixed method design
The third framework is mixed method design which relies on the combined use of quantitative and qualitative research methods. This model is most suitable in those cases when a scholar has certain assumption about the problem of inequality in academic labor market. Under such circumstance he/she can use both unstructured interview and statistical survey.
The first tool will be based on open-ended questions, whereas the second will rely on Likert scale items. As in quantitative research it is necessary to single out a set of variables, for instance, the gender (independent variable) on the one hand and compensation, workload, organizational support, on the other. Quantitative methods will help to determine if there is statistically significant relationship between the variables.
In turn, qualitative techniques will enable him/her to better understand the opinions and concerns of those people who may suffer from inequality in the workplace. They will be asked about the influence of gender on the compensation received by a teacher, his/her workload, and promotion opportunities.
It is necessary to determine the sample size and divide it into two groups. Each of the subjects will need to respond to the same question during interview and a survey. The researcher has to ensure that unstructured interview and survey are consistent with another.
This consistency will become crucial when he/she will analyze the findings. The analysis of quantitative data has to identify the most widespread patterns in the opinions of the respondents, whereas the purpose of statistical analysis is to understand to what extent two variables are related with one another.
Reference List
Aanerud, R., Morrison, E., Homer, L., Rudd, E., Nerad, M., & Cerny, J. (2007). Widening the lens on gender and tenure: Looking beyond the academic labor market Johns Hopkins University Press. Web.
Creswell. J. (2003). Research design: qualitative, quantitative, and mixed method approaches. London: SAGE.
Glazer-Raymo. J. (2001). Shattering the Myths: Women in Academe. JHU Press.
Kennely I., Misra J., & Karides M. (1999). The Historical Context Of Gender, Race, & Class In The Academic Labor Market. Race Gender and Class, 6 (3), p 125-140.
Umbach. P. (2006). Gender Equity in the Academic Labor Market: An Analysis of Academic Disciplines. Research in Higher Education, 48, (2), pp 169-192.
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