Gender and Educational Leadership: Hypothesis Testing Research Paper

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Updated: Apr 9th, 2024

Data Analysis Plan

A standard model of research requires developing, deducing, and testing a hypothesis or several hypotheses (Vogt, Gardner, & Haeffele, 2012). In this paper, the process of testing hypotheses will be explained and described. In the current project, there are two pairs of hypotheses that should be tested. One pair touches upon the qualities of a good leader in an educational process. Another pair discusses the importance of gender roles in leadership. As soon as null and alternative hypotheses are defined for research questions, it is time to test all of them (Greene & D’Oliveira, 2005).

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The first stage is the identification of the level of significance within the frames of which it is possible to identify if the null hypothesis is true (Mitchell & Jolley, 2012). The T-test can be used. This test allows the research to answer the questions created for research. It is necessary to gather sample data (students) and observe how the chosen group of people (in this case) achieves various scores.

It is also possible to rely on the method of qualitative data analysis called SPSS. Research is qualitative as all information is taken from the interviews and questionnaires based on the LPI scoring instrument offered by Kouzes and Posner (2003). With the help of this method, it is possible not only to test the hypothesis but also to create a powerful research journal to understand the facts gathered (Field, 2013). Both pairs of hypotheses are analyzed and tested according to the following stages:

  1. Identification of variables;
  2. Extraction of themes;
  3. Enumeration of the questions and calculation of the answers;
  4. Highlighting similarities and differences;
  5. Creation of the diagrams on the basis of the answers got.

Justification

T-tests help to clarify if the groups chosen for analysis can be statistically different from each other or not. This analysis helps to compare the achievements of different groups. In the current research, there are two research questions and two hypotheses per each question. Both questions are of the same nature; the only difference is the dependent variables: RQ1 – qualities, RQ2 – genders.

The level of measurement identifies the relationship between the values of leadership as a crucial part of team work (Northouse, 2010). With the help of the answers and the observations made on the groups, it is possible to clarify if male or female leaders are more successful and understand what kind of qualities are inherent to good leaders (3C’s or necessity to control, give orders, and make people listen). The results can be introduced in tables as it is promoted by the SPSS method.

Mock Data Set

The research study separates two variables in the educational process. To evaluate the impact of gender differences and leadership qualities in the educational process, the study proposed the chi-square analysis on 20-sample populations. By implication, the researcher structured two research questions to facilitate the evaluation process.

Research questions

  1. What are the main qualities of a good leader in an educational process?
  2. Do the differences between male and female leaders play an important role in the sphere of education?

However, the research analysis will accept or reject the test hypothesis based on the statistical method.

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Research design

Twenty participants were randomly selected to evaluate the quantitative study. The questionnaires were distributed based on gender allocation and individual consent.

However, the appropriateness of the statistical methods depends on observed values and variables. The statistical method examined the differential index of two variables. By implication, we accessed the differences between male and female populations in the educational process. The research study will use the nominal levels of measurement. Thus, the nominal level of measurement will test the gender distribution of the study.

Table 1: Mock Data.

S/NOTeaching influenceTeaching programLeadership qualitiesAgeGenderLeadership CurriculumTeacher behavior
1PositivePositiveIndifferent21-25MaleNegativePositive
2PositivePositivePositive16-20FemalePositiveIndifferent
3IndifferentPositivePositive16-20MaleMonthlyPositive
4PositivePositivePositive21-25MaleIndifferentIndifferent
5IndifferentPositivePositive16-20FemalePositiveIndifferent
6IndifferentPositivePositive21-25MaleIndifferentIndifferent
7IndifferentUndecidedIndifferent21-25FemalePositivePositive
8IndifferentUndecidedNegative26-30FemalePositivePositive
9IndifferentUndecidedNegative21-25MalePositivePositive
10IndifferentUndecidedNegative26-30MalePositivePositive
11IndifferentUndecidedNegative21-25MalePositivePositive
12IndifferentUndecidedNegative16-20FemalePositivePositive
13IndifferentUndecidedNegative21-25FemalePositivePositive
14IndifferentUndecidedNegative21-25FemalePositivePositive
15IndifferentUndecidedNegative16-20MalePositivePositive
16IndifferentUndecidedNegative21-25FemalePositivePositive
17IndifferentUndecidedNegative21-25FemalePositivePositive
18IndifferentUndecidedNegative21-25FemalePositivePositive
19PositivePositivePositive16-20FemalePositivePositive
20PositivePositivePositive16-20MalePositivePositive

Table 2: Result analysis.

Gender
MaleFemale
CountColumn N %CountColumn N %
Teaching influencePositive333.3%218.2%
Negative00.0%00.0%
Indifferent666.7%981.8%
Teaching programPositive555.6%327.3%
Negative00.0%00.0%
Indifferent444.4%872.7%
Leadership qualitiesPositive444.4%327.3%
Negative444.4%763.6%
Indifferent111.1%19.1%
Leadership CurriculumPositive666.7%11100.0%
Negative111.1%00.0%
Indifferent222.2%00.0%
Teacher behaviorPositive777.8%981.8%
Negative00.0%00.0%
Indifferent222.2%218.2%

The analysis revealed that 55% of respondents are female, while 45 are male. Consequently, the results showed no significant difference between male and female respondents. As a result, we will reject the hypothesized gender difference in the educational process. Thus, gender differences do not affect leadership roles in the educational process.

References

Greene, J. & D’Oliveira, M. (2005). Learning to use statistical tests in psychology. New York, NY: McGraw-Hill Education.

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Thousand Oaks, CA: SAGE.

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Kouzes, J. & Posner, B. (2003). Leadership practices inventory (“LPI”) Self-Scoring Instrument. Hoboken, NJ: Wiley.

Mitchell, M. & Jolley, J. (2012). Research design explained. Belmont, CA: Cengage Learning.

Northouse, P. (2010). Leadership: Theory and practice. Thousand Oaks, CA: SAGE Publications.

Vogt, W.P., Gardner, D.C., & Haeffele, L.M. (2012). When to use what research design. New York, NY: Guilford Press.

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IvyPanda. (2024) 'Gender and Educational Leadership: Hypothesis Testing'. 9 April.

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IvyPanda. 2024. "Gender and Educational Leadership: Hypothesis Testing." April 9, 2024. https://ivypanda.com/essays/gender-and-educational-leadership-hypothesis-testing/.

1. IvyPanda. "Gender and Educational Leadership: Hypothesis Testing." April 9, 2024. https://ivypanda.com/essays/gender-and-educational-leadership-hypothesis-testing/.


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IvyPanda. "Gender and Educational Leadership: Hypothesis Testing." April 9, 2024. https://ivypanda.com/essays/gender-and-educational-leadership-hypothesis-testing/.

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