Research on Application of Data Mining Based on Improved APRIORI Algorithm in Enrollment Management in Colleges and Universities

Wu, Hequn; Enhe, Mende; Wang, Jinyu

doi:10.1007/978-981-13-3648-5_136

Cited by 1 publication

(1 citation statement)

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“…Association rules as a data mining technique are used to investigate the correlation between different enrollment factors. Some studies investigated the Apriori algorithm on enrollment to extract the behavior of low-and high-income students [35], the quality of talent training and enhance the overall competitiveness of colleges and universities [36], student performance for a certain outcome (Pass or Fail) [37]. This paper gets benefits from previous studies to determine the different factors influencing the enrollment decision.…”

Section: Related Workmentioning

confidence: 99%

Factors Influencing Students Decisions to Enrollment in Sudanese Higher Education Institutions

Sedahmed¹,

Noureldien²

2019

IIM

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There is a growing body of literature that recognizes the importance of data mining in educational systems. This recognition makes educational data mining a new growing research community. One way to achieve the highest level of quality in a higher education system is by discovering knowledge from educational data such as students' enrollment data. Many mining tools that aim to discover exciting correlations, frequent patterns, associations, or casual structures among sets of items in educational data sets have been proposed. One of the widely used tools is association rules. In this paper, the Apriori algorithm is used to generate association rules to discover the importance and correlation between factors that influence student's decision to enroll in higher education institutions in Sudan. The algorithm is applied using a student's enrollment data set that was created using a questionnaire and 800 students enrolled in governmental and private sector universities as a sample. This paper classifies factors that influence enrollment into: student's demographic factors and four categories of enrollment related factors (Student and Society, Educational Institution, Admission, and Employment related factors), and determines the most influential factors in determining student's decision to enroll in Sudanese universities. The analysis result shows that the Educational Institution related factors (50%) and Admission related factors (40%) are strongly influencing students' enrollment decision, while the Employment related factors (10%) and Student and Society related factors (0%) have weak influence. The factors out of the 14 Educational Institution related factors that have a high impact are: reputation, diversity of study, quality of education, education facilities, and feasibility.

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Section: Related Workmentioning

confidence: 99%