A student-oriented tool to support course selection in academic counseling sessions

Abstract:

Course selection and recommendation are important aspects of any academic counseling system. The Learning Analytics community has long supported these activities via automatic, data-based tools for recommendation and prediction. We contribute to this body of research with a tool that allows students to select multiple courses and predict their academic performance based on historical academic data. The tool is intended to be used prior to counseling sessions in which students plan their upcoming semester at the Ecuadorian university ESPOL. This paper presents the tool’s design and implementation and discusses its potential to improve the student-counselor discourse.

Año de publicación:

2020

Keywords:

• learning analytics
• Educational Data Mining
• Academic performance pbkp_rediction

Fuente:

scopus