Study and analysis of data mining technology in college courses students failed

Zhang, Zhiyu

doi:10.1109/iciss.2010.5657100

Cited by 3 publications

(1 citation statement)

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“…Com o avanço da tecnologia e custos cada vez menores para a compra de dispositivos de armazenamento de dados, é comum para empresas e instituições possuírem grandes quantidades de dados acumuladas ao longo dos anos [21]. Esses dados comumente são usados apenas para geração de relatórios e estatísticas [21], [22].…”

Section: Introductionunclassified

Mineração de Dados Educacionais Visando a Identificação da Evasão no Ensino Superior

Carminati¹,

Augusto²,

Dallabrida³

et al. 2020

Anais Do XI Computer on the Beach - COTB '20

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This paper tackles the problem of dropout of undergraduate studentsin a private university, by using Educational Data Mining(EDM) techniques. The EDM is an emerging area, concerned withdeveloping methods for exploring the increasingly large-scale datathat come from educational settings and using those methods tobetter understand students and the settings which they learn in. Inthis work, EDM is used to identify profiles of students who withdrawfrom their engineering courses. The considered dataset iscomposed of 53 attributes, involving financial and academic aspectsof 2,925 engineering students. Preliminary results have identifiedsome attributes that are related to the dropout in engineering courses,such as: the semester of the year (students are more prone todropout in the first half of the year), attendance, grades (in thiscase median is more important than the mean value) and numberof credits in the previous semester, and the current semester thestudent is enrolled (students bellow the 5th semester have a highertendency to dropout).

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Section: Introductionunclassified

Mineração de Dados Educacionais Visando a Identificação da Evasão no Ensino Superior

Carminati¹,

Augusto²,

Dallabrida³

et al. 2020

Anais Do XI Computer on the Beach - COTB '20

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Data Mining in Higher Education

AlHammadi¹,

Aksoy²

2013

PEN

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Students’ comprehensive evaluation system based on data mining method

He¹,

Bian²

2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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the paper researched comprehensive quality evaluation system of college student, and introduces data mining method to solve mess students data. Firstly, the paper construct students' data warehouse, then construct comprehensive multi-dimensions OLAP (Online Analysis Process) model, and through classification deterministic method, we can get useful message from the system to guide college manage students, and some Employers can find their satisfied employees.

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Study and analysis of data mining technology in college courses students failed

Cited by 3 publications

References 0 publications

Mineração de Dados Educacionais Visando a Identificação da Evasão no Ensino Superior

Mineração de Dados Educacionais Visando a Identificação da Evasão no Ensino Superior

Data Mining in Higher Education

Students’ comprehensive evaluation system based on data mining method

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