The raw data was classified or categorised manually using a codebook. Data was coded appropriately as per the responses to different sections and questions in the questionnaire. The data that was collected was both qualitative and quantitative. The qualitative data was thematically analysed following the objectives. Quantitative data was coded in variable view window of SPSS with 26 variables. The data was entered in the data view window of SPSS. Every questionnaire formed one row, and there were 451 rows. Each column in the
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data view window represented a variable making 26 variables. The computer programme used in data analysis was SPSS version 17
Statistical Test Analysis
Five null (statistical) hypotheses were tested as follows:
H01-There is no significant relationship between school type and students’ self-esteem.
This hypothesis was analysed using chi-square statistics. Chi-square is a non- parametric test that is used in analysis to establish relationships between two variables that are categorical (nominal measurement) in nature. Self-esteem and school type variables are in nominal levels of measurement. School type was measured in four categories of Sub-county school-coded 1, County school- coded 2, Extra-county school-coded 3 and National school - coded 4. Self- esteem of students was measured using Rosenberg Self-esteem Scale (RSES) and was categorised as low, normal and high self-esteem.
H02- There is no significant relationship between school type and students’ academic achievement.
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This was analysed using one way Analysis of Variance (ANOVA) that
compared differences in students’ academic achievement among the four levels or groups of schools (types)
ANOVA assumes that the dependent variable should be measured at the interval or ratio level (continuous variable). Academic achievement which is the KCPE results and mock class means scores is the dependent variable. This is continuous variable which is at the interval level of measurement. The independent variable is the school type which is categorical with four unrelated school type. Therefore ANOVA determined whether there are significant academic achievement differences between the means of these school types.
H03- There is no significant relationship between school type and students’ career aspirations.
This was analysed using one way Analysis of Variance (ANOVA)
Students’ career mean levels were established and ranked into three continuous levels with high-level careers assigned highest mean of 3, middle-level careers with a mean of 2, and low-level careers with a mean of 1. The school types being the independent variable had 4 independent groups (sub-county, county, extra-county and national schools). ANOVA analysed how the career mean levels of students varied across the school types.
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In addition, the Chi- square (ᵡ2) test statistics was used for analysis basically for triangulation purposes to enhance validity and reliability of data. In this case data was categorical considering school types as the independent variable and dependent variable (career aspirations) were given as various professions selected by the students.
H04- There is no significant gender differences in students’ self-esteem. This was analysed by use of independent sample t-test in determining
individual students’ gender -self-esteem mean differences. This answered the question, if there are differences in self-esteem between boys and girls. HO5: There is no significant difference in boys’ self-esteem by school type. HO6: There is no significant difference in girls’ self-esteem by school type. One way ANOVA test analysis was done for both null hypotheses 5 and 6. Self-esteem means of boys and that of girls was compared separately among the four independent school types. The continuous self-esteem students’ scores were used in the analysis. Scores range between 0-15 is considered low, 16-25 is normal and 26-30 is high self-esteem. School types were boys’ national, boys’ extra-county, boys’ county and boys’ sub-county, and similarly the same for girls schools.
H07: There is no significant gender difference in students’ career aspirations. ANOVA test statistics was used to determine whether there were gender differences in students’ career aspirations. Chi-square statistics also analysed
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this hypothesis on relationship between career aspirations and gender of the students.
HO8: There is no significant difference in boys’ career aspirations by school type.
HO9: There is no significant difference in girls’ career aspirations by school type
For the two null hypotheses 8 and 9, the main question was that, are boys or girls career aspirations similar irrespective of their school type?
One way ANOVA was computed for analysis. Career aspirations were continuously ranked into three career levels. High-level careers given a mean of 3, middle-level careers given a mean of 2 and low-level careers given a mean of 1. School type was in four independent groups from national to sub- county schools for boys’ (HO8) and girls’ (HO9) schools.
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CHAPTER FOUR
PRESENTATION OF FINDINGS, INTERPRETATIONS AND DISCUSSIONS
4.1 Introduction
This chapter presents findings, interpretations and discussions according to the research objectives and hypotheses. The discussions also refer (cross reference) to the reviewed related literature and theoretical linkages between variables. The chapter is organized into four major sections. That is, introduction, general and demographic information, findings for each objectives, and hypotheses, interpretations and discussions. Descriptive statistics and inferential statistics have been used in the interpretations. Data presentation was done using frequency distribution tables and percentages. One-way ANOVA, t-test and Chi-square statistics were used in statistical hypotheses testing. Presentation of findings, interpretations and discussions were related to the following objectives and hypotheses.
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i. To find out if there was any relationship between school type and students’ self-esteem, the HO1: There is no significant relationship between school type and students’ self-esteem was tested using Chi- square.
ii. To establish if school type was a factor influencing students’ academic achievement, the HO2: There is no significant relationship between school type and students’ academic achievement- was tested using One Way ANOVA.
iii. To investigate out if school type was a factor influencing students’ career aspirations, the HO3: There is no significant relationship between school type and students’ career aspirations- was tested using One Way ANOVA and Chi- square statistics.
iv. To find out if there were gender differences in self-esteem among students, the HO4: There is no significant gender difference and students’ self-esteem was tested using t-tests for independent samples.
v. To find out if there were differences in boys’ self-esteem by school type, the HO5: There are no significant differences in boys’ self- esteem by school type, was tested by one way ANOVA.
vi. To find out if there were differences in girls’ self-esteem by school type, the HO6: There are no significant differences in girls’ self- esteem by school type, was tested by one way ANOVA.
vii. To find out if there were gender differences in students’ career aspirations, HO7: There is no significant gender differences and
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students career aspirations was tested using chi-square and one way ANOVA.
viii. To find out if there were differences in boys’ career aspirations by school type, the HO8: There are no significant differences in boys’ career aspirations by school type, was tested by one way ANOVA. ix. To find out if there were differences in girls’ career aspirations by
school type, the HO9: There are no significant differences in girls’ career aspirations by school type, was tested by one way ANOVA. x. The objective on teachers’ perception towards students’ self-esteem
and career aspirations was qualitatively analyzed and this enhanced triangulation of results.