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Zihan Song, Sang-Ha Sung, Do-Myung Park and Byung-Kwon Park
The core of dropout prediction lies in the selection of predictive models and feature tables. Machine learning models have been shown to predict student dropouts accurately. Because students may drop out of school in any semester, the student history dat...
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Georgios Psathas, Theano K. Chatzidaki and Stavros N. Demetriadis
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Choong Hee Cho, Yang Woo Yu and Hyeon Gyu Kim
Student dropout is a serious issue in that it not only affects the individual students who drop out but also has negative impacts on the former university, family, and society together. To resolve this, various attempts have been made to predict student ...
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José Manuel Porras, Juan Alfonso Lara, Cristóbal Romero and Sebastián Ventura
Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own data. However, that approach is ...
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Andres Gonzalez-Nucamendi, Julieta Noguez, Luis Neri, Víctor Robledo-Rella, Rosa María Guadalupe García-Castelán and David Escobar-Castillejos
With the recent advancements of learning analytics techniques, it is possible to build predictive models of student academic performance at an early stage of a course, using student?s self-regulation learning and affective strategies (SRLAS), and their m...
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Muhammad Hammad Musaddiq, Muhammad Shahzad Sarfraz, Numan Shafi, Rabia Maqsood, Awais Azam and Muhammad Ahmad
Quality education is necessary as it provides the basis for equality in society. It is also significantly important that educational institutes be focused on tracking and improving the academic performance of each student. Thus, it is important to identi...
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Spyridon Garmpis, Manolis Maragoudakis and Aristogiannis Garmpis
The plethora of changes that have taken place in policy formulations on higher education in recent years in Greece has led to unification, the abolition of departments or technological educational institutions (TEI) and mergers at universities. As a resu...
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María Erika Narvaez Ferrin,Maria Angélica Cervantes Muñoz
Pág. 81 - 92
This article unveils key variables identified by MIC MAC method (Matrix of Crossed Impacts Multiplication Applied to Classification) related to student dropout from the business administration program of the National Open and Distance University-UNAD Uni...
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Catarina Félix de Oliveira, Sónia Rolland Sobral, Maria João Ferreira and Fernando Moreira
Retention and dropout of higher education students is a subject that must be analysed carefully. Learning analytics can be used to help prevent failure cases. The purpose of this paper is to analyse the scientific production in this area in higher educat...
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William Villegas-Ch, Joselin García-Ortiz, Karen Mullo-Ca, Santiago Sánchez-Viteri and Milton Roman-Cañizares
Currently, private universities, as a result of the pandemic that the world is facing, are going through very delicate moments in several areas, both academic and financial. Academically, there are learning problems and these are directly related to the ...
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