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Understanding Educational Research PDF

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Understanding Educational Research and Assessment
Review of a quantitative article
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Review of a quantitative article
Balkis, M., Arslan, G., & Duru, E. (2016). The School Absenteeism among High School
Students: Contributing Factors.Educational Sciences: Theory and Practice,16(6),
Summary of the article
Purpose of study
The article aims to evaluate and examine the relationship between the absenteeism
registered in high schools and the related factors contributing to these incidences. The author
illustrates that these factors are classified into personal and family factors. The examples of the
individual factors include student attitudes towards the schools and teachers, motivation, and
academic self-perception among others whereas the family factors include the income and the
level of education among the parents (Balkis, Arslan, and Duru, 2016, pp.1819-1831).
Sampling and selection of respondents
The sample of the participants was selected from two schools in an urban town in
Turkey where the target students were from grades 9 to 12. Concisely, 423 students were
sampled out where 58.4 percent were boys while 41.6% were boys ranging between 15 and 18
years of age. However, the sample had students from the entire similar ethnic group although
they had different social and economic backgrounds. The participation was on a voluntary basis
as required by the code of ethics in any research and lasted 25 minutes approximately (Harriss,
MacSween, and Atknison, 2017, pp.1126-1131).
Data collection
The use of demographic information sheet was used to gather data. These were
administered using the School Assessment Survey-Revised (SAAS-R) to collect the students’
information such as their age, parent’s income, their academic qualification, and current
absenteeism among other aspects as acknowledged by (Suldoet al., 2014, pp.3-14).
Research design and Statistical analysis
The study utilized the use of the Statistical Package for Social Sciences technique to
perform the correlations among the variables from the data obtained by the SAAS-R tool. The
SPSS was also used to draw the relationships among the variances using a one-way ANOVA to
examine whether there could be the change in the dependent variable with alterations in the
independent variable. Additionally, the SPSS AMOS was used in the estimation of the likelihood
of the parameters alongside the Chi-square and other error approximations in the SPSS software
(Jatnika, 2015, pp.818).
The correlation between the variables established using the Pearson product-moment
of correlation analysis indicated that the personal factors and the level of education of the parents
were statistically associated negatively to the current and previous absenteeism among the
students. The results of the correlations analysis are displayed in the table below.
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