Una Solución para la Administración del Ciclo de Vida de Learning Analytics en un LMS: AnalyTIC
Date
2019Abstract
Learning Analytics (LA) has a significant impact in
learning and teaching processes. These processes can be improved
using the available data retrieved from students’ activity inside
the virtual classrooms of a learning management system (LMS).
This process requires the development of a tool that allows one to
handle the retrieved information properly. This paper presents
a solution to this need, in the form of a development model and
actual implementation of an LA tool. Four phases (Explanation,
Diagnosis, Prediction and Prescription) are implemented in the
tool, allowing a teacher to track students’ activity in a virtual
classroom via the Sakai LMS. It also allows for the identification
of users who face challenges in their academic process and the
initiation of personalised mentoring by the teacher or tutor. The
use of the tool was tested on groups of students in an algorithms
course in the periods 2017-1, 2017-2, 2018-1 and 2018-2, with
a total of 90 students – in parallel with the control groups in
the same periods that totalled 95 students – obtaining superior
averages in the test groups versus the control groups, which
evidenced the functionality and utility of the software.