Moodle Predicta: A Data Mining Tool for Student Follow Up

被引：7
|
作者：
Felix, Igor Moreira [1 ]
Ambrosio, Ana Paula [1 ]
Neves, Priscila Silva [1 ]
Siqueira, Joyce [1 ]
Brancher, Jacques Duilio [2 ]
机构：
[1] Univ Fed Goias, Inst Informat, Goiania, Go, Brazil
[2] Univ Estadual Londrina, Dept Comp, Londrina, Parana, Brazil
来源：
PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED EDUCATION (CSEDU), VOL 1 | 2017年
关键词：
Educational Data Mining; Moodle; Prediction; Tool; Virtual Learning Environment;
D O I：
10.5220/0006318403390346
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Educational data mining (EDM) aims to find useful patterns in large volumes of data from teaching/learning environments, increasing academic results. However, EDM requires previous and deep knowledge of data mining methods and techniques, involving several computing paradigms, preprocessing and results' interpretation. In this paper, Moodle Predicta, an educational data mining desktop tool is presented. This software is developed in Java and enables non-expert data mining users to enjoy benefits from EDM, within the Moodle system. Divided in two modules, Moodle Predicta allows: (i) visualization of Moodle courses data; and (ii) predict students' performance.
引用
收藏
页码：339 / 346
页数：8
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