SIERA: The use of classification and knowledge modeling to identify students at risk of evasion and with the need to reinforce learning
Author: Cicero Silva Jr Summary: A web application that incorporates education data mining and student knowledge tracing techniques Source: https://github.com/cicerosilvajunior/siera.git
What is SIERA?
This tool aims to demonstrate the feasibility of using data mining techniques and performance analysis to support the identification of students at risk of evasion or with the need to reinforce learning.
SIERA uses some classification algorithms implemented at Weka machine learning workbench to classify students at risk of evasion and BKT Brute Force algorithm from Baker, Corbett, and Aleven (2008) to identify the need to reinforce learning for a specific student.
System requirements
To be defined.
Configure
To be defined.
Running
To be defined.
Access the application
The application will be running at the following URL: http://localhost:8080/edmtool-webapp/.
Run the SIERA in Eclipse or JBoss Developer Studio
To be defined.
Debug the Application
To be defined.