TY - JOUR
KW - Academic Analytics
KW - Automatic Course Classification
KW - Learning Management Systems
KW - Rule-based System
KW - Expert System
AU - Luisa M. Regueras
AU - María Jesús Verdú
AU - Juan-Pablo de Castro
AB - In recent years and accelerated by the arrival of the COVID-19 pandemic, Learning Management Systems (LMS) are increasingly used as a complement to university teaching. LMS provide an important number of resources and activities that teachers can freely select to complement their teaching, which means courses with different usage patterns difficult to characterize. This study proposes an expert system to automatically classify courses and certify teachers’ LMS competence from LMS logs. The proposed system uses clustering to stablish the classification scheme. From the output of this algorithm, it defines the rules used to classify courses. Data registered from a university virtual campus with 3,303 courses and two million interactive events have been used to obtain the classification scheme and rules. The system has been validated against a group of experts. Results show that it performs successfully. Therefore, it can be concluded that the system can automatically and satisfactorily evaluate and certify the teachers’ LMS competence evidenced in their courses.
IS - Regular Issue
M1 - 7
N2 - In recent years and accelerated by the arrival of the COVID-19 pandemic, Learning Management Systems (LMS) are increasingly used as a complement to university teaching. LMS provide an important number of resources and activities that teachers can freely select to complement their teaching, which means courses with different usage patterns difficult to characterize. This study proposes an expert system to automatically classify courses and certify teachers’ LMS competence from LMS logs. The proposed system uses clustering to stablish the classification scheme. From the output of this algorithm, it defines the rules used to classify courses. Data registered from a university virtual campus with 3,303 courses and two million interactive events have been used to obtain the classification scheme and rules. The system has been validated against a group of experts. Results show that it performs successfully. Therefore, it can be concluded that the system can automatically and satisfactorily evaluate and certify the teachers’ LMS competence evidenced in their courses.
PY - 2022
SP - 75
EP - 81
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - A Rule-Based Expert System for Teachers’ Certification in the Use of Learning Management Systems
UR - https://www.ijimai.org/journal/sites/default/files/2022-11/ijimai7_7_8.pdf
VL - 7
SN - 1989-1660
ER -