ANALYZING FACTORS INFLUENCING STUDENT ACADEMICPERFORMANCE IN SECONDARY EDUCATION: AN EDUCATIONAL DATA MINING APPROACH
Keywords:
Student Academic Performance, Educational Data Mining, Secondary Education, Student AchievementFactors, Predictive AnalysisAbstract
The relationship between academic, behavioraland socio-educational factors in shaping student academic performancedefines learning outcomes in secondary school. The proposed research set out to determine the variables that affect studentperformance in schools by applying educational data mining technique. It was analyzed on the basis of the StudentPerformance dataset where demographic, social, and academic information of the secondary school students wererecorded. The major variables that be considered in the research are study time, the lack ofattendance, the education ofparents, the previous academic failures, and the family support. The descriptive statistical analysis and predictivemodeling methods were used to determine the correlation between these variables and final grades of students.Thefindings reveal that the study time and attendance are important predictors of the academic success since those studentsthat spend more of their time studying and those students who attend school regularly tend to achieve better academicresults. On the contrary, absenteeism on a regular basis and poor performance in school were linked with poor academicperformance. It is also found out that parental education and family support also lead to better student achievementthrough the creation of a good learning environment. The paper shows that educational data mining methods give usefulinformation about the intricate correlation among student behavior, socio-educational and academic achievement. Theseare the insights that can help the educators and policymakers to come up with data-driven strategies which help themimprove student learning and improve the level of education in secondary education.
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