Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Factors Associated to High School Students Dropout in Malakand District Pakistan

Version 1 : Received: 22 May 2021 / Approved: 25 May 2021 / Online: 25 May 2021 (13:22:59 CEST)

How to cite: Asif, M.; Hayat, M.; Khan, S. Factors Associated to High School Students Dropout in Malakand District Pakistan. Preprints 2021, 2021050611 (doi: 10.20944/preprints202105.0611.v1). Asif, M.; Hayat, M.; Khan, S. Factors Associated to High School Students Dropout in Malakand District Pakistan. Preprints 2021, 2021050611 (doi: 10.20944/preprints202105.0611.v1).

Abstract

Academic failure, low attendance, financial difficulties, and mental illness are some of the major reasons most students drop out of high schools. We investigated how high school dropout risk is affected by socioeconomic, demographic, and institutional characteristics. Therefore, research design is composed of a literature review, Questionnaire surveys by interviewing each student. Besides, the analysis and statistical modelling, the Logistic Regression method was used. The results show that academic performance, job, lack of interest and low learning ability were the significant individual characteristics that affect the high school dropout. Moreover, parental characteristics, including financial condition, lack of awareness, and education, are significant factors associated with high school dropout rates. Some other related factors, such as adaptability and influence of the peer groups, abandoning school by siblings, and extra responsibility at home and a joint family system, are also some notable factors that significantly affect the dropout rate in schools Malakand District of KP province. This research study delivered the results that contribute to the literature in education to identify different factors like student's own, parental, institutional, and household characteristics, which affect a student being a dropout from high school in Malakand district Pakistan.

Subject Areas

Statistical Modelling; Education; Public Sector

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