Hypothetical Designs:. Strategies & Methods

Quantitative Design

This research paper reviews the numerous strategies, which are essential for a broader assessment and basic understanding of the topic under discussion. When making a decision on which technique to use, the choice depends on the type of objective that the study has as the main intention. For instance, if the key goal is to test a certain hypothesis, quantitative research methods will be more appropriate since quantitative technique helps to indentify 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.

Numerous studies have already been conducted on this particular topic. For instance, by referring to the study by Umbach (2006) who examined statistical data about the salaries of teachers and determined to what extent they are determined by gender. When effects of gender (independent variable) on equity in academic labor marker (dependent variable) becomes the interest of a researcher, he/she can choose statistical survey or structured interview as a method of data collection (Aanerud et al., 2007); this will be necessary to determine the sample size of the population.

In Umbach’s (2006) the sample under research is usually divided into two groups: male educators and female educators. Each of the respondents is questioned on the same topic or question, about the number of working hours, monthly wages, and promotion opportunities among others. A researcher should also make a point of establishing several control variables, which remain unchanged during the study. Umbach (2006) list that, these category can include work experience, degree, and academic discipline. Additionally, a researcher must maintain control over these variables because their essential for the validity of the findings. In fact, Glazer (2001) elaborates that, the respondents of the participants will be codified and then later the collected data can be analyzed with the help of T-test and ANNOVA. Through such ways, one can determine whether the relationship between the variables is statistically significant. Alternatively, we need to say that quantitative design is more suitable in those cases, which a researcher needs to test an assumption or a hypothesis.

Qualitative Design

Creswell (2003) argues that, while assessing the topic of equity in academic market, a researcher can be able to use the qualitative method since this technique is more reliable and appropriate in such cases. In fact, the technique is specifically appropriate when an investigator intends to describe a certain social phenomenon in order to form assumption about a specific topic (Creswell, 2003, p 15). Besides, researchers in numerous areas have also adopted qualitative design. In deed, such instance can be observed from a research conducted by Kennelly who attempted to identify the sources of inequality in academic labor market whose research relied mostly on interviews and group discussions rather than statistical methods (Kennelly et al., 1999).

Unstructured interview can be the most suitable in a qualitative research where the 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 is also necessary to use open-ended question since they enable an interviewer to explain and expand his/her ideas. Examiners at all times 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.

Kennel et al. (1999) basis on the fact that, unstructured interview has more that one advantage. One merit is that, it enables the interviewer to clarify both questions and respondents of the participants. However, Kennelly et al. (1999) argues that 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. Based on these findings, a scholar will be able to form a hypothesis about the factors that affect equity in academic labor market. Later these assumptions should be verified with the help of quantitative research methods.

Mixed Method Design

Aanerud et al. (2007) specifies that, mixed design is the third framework that is also common and it mainly relies on the combined use of quantitative and qualitative research methods. This model is most suitable in those cases which a research 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 in order to acquire resalable data. The first tool is based on open-ended questions, whereas the second mainly focuses on Likert scale items. Just like 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.

A quantitative method is really helpful and can be used to determine if there is statistically significant relationship between the variables. On the other hand, qualitative technique enables a researcher to better understand the opinions and concerns of those people who are suffering from inequality in the workplace. According to Glazer (2001) the interviewees are questioned about the influence of gender on the compensation received by a teacher, his/her workload, and promotion opportunities. Most importantly, 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. Unstructured interview and survey are consistent with another and the researcher has to ensure that such consistency will become crucial when he/she is making final report. The data analysis using the quantitative methods 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.


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. Baltimore: 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. Baltimore: Johns Hopkins University Press.

Kennely I., Misra J., & Karides M. (1999). The Historical Context of Gender, Race, and Class in The Academic Labor Market. Race Gender and Class, 6(3), 125-140. Web.

Umbach. P. (2006). Gender Equity in the Academic Labor Market: An Analysis of Academic Disciplines. Journal of Research in Higher Education, 48(2), 169-192. Web.

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