Work

Contributions from Data Mining to Study Academic Performance of Students of a Tertiary Institute

Year: 2014

Type: article

Abstract: Education-oriented data mining allows to predict determined type of factor or characteristic of a case, phenomenon or situation. In this article the mining models used are described and the main results are discussed. Mining models of clustering, classification and association are considered especially. In all cases seeks to determine patterns of academic success and failure for students, thus predicting the likelihood of dropping them or having poor academic performance, with the advantage of being able to do it early, allowing addressing action to reverse this situation. This work was done in 2013 with information on the years 2009 to 2013, students of the subject Operating Systems tertiary career Superior Technical Analyst (TSAP) Higher Institute of Curuzú Cuatiá (ISCC), Corrientes, Argentina.

Source: American Journal of Educational Research

DOI: 10.12691/education-2-9-3

Authors: David L. la Red Martínez, Carlos E. Podestá Gómez

Institution: National University of the Northeast

Language: English

Topic: Online Learning and Analytics

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: diamond

OpenAlex ID: W2109910107

FWCI: 1.059

Cites: 52

Cited by: 12

Related to: 9