About this paper

Appears in:
Pages: 6374-6381
Publication year: 2017
ISBN: 978-84-697-6957-7
ISSN: 2340-1095
doi: 10.21125/iceri.2017.1648

Conference name: 10th annual International Conference of Education, Research and Innovation
Dates: 16-18 November, 2017
Location: Seville, Spain

APPLICATION OF A DATA MINING METHOD IN TO LMS FOR THE IMPROVEMENT OF ENGINEERING COURSES IN NETWORKS

W. Villegas-Ch1, S. Luján-Mora2, D. Buenaño-Fernández1

1Universidad de Las Américas (ECUADOR)
2Universidad de Alicante (SPAIN)
Learning management systems (LMS) provide education with tools that help manage resources and log activities as well as evaluation in the development and fulfillment of tasks by students. The tools that contribute to LMS have become a subject of analysis by the areas of learning management that are part of educational institutions. The analysis starts from a large amount of data generated in the LMS, these data arouse the interest of institutions to look for patterns that help teachers to customize resources and improve education. Several of the proprietary or free LMS platforms have created modules or plugins with the ability to generate reports based on the available data of the activities performed. These modules have, to a certain extent, covered learning assessment needs. However, to make decisions for the improvement of e-learning, a broader analysis of the data is necessary with the use of tools that suitably fit the different LMS platforms. The answer to this process is given by data mining, its characteristics allows to apply several methods and algorithms to the data where individuals share patterns or even draw projections of behavior.

Once the appropriate model-driven development (MDD) tool has been established, the process will be analyzed in a case study focused on the Moodle platform. The case study was done to a group of students from a University of Ecuador, specifically in a computer course. In this analysis we can find patterns in students' performance, applying a search algorithm. With these results the student can be offered a personalized education or create methods to improve e-learning.

In this paper, section II presents several concepts necessary to approach the problem from previous work; section III details the pre-processing step required for the analysis of the data using the main techniques of data mining; section IV performs an analysis of the results obtained; finally section V presents the conclusions and makes recommendations for future investigations.
@InProceedings{VILLEGASCH2017APP,
author = {Villegas-Ch, W. and Luj{\'{a}}n-Mora, S. and Buena{\~n}o-Fern{\'{a}}ndez, D.},
title = {APPLICATION OF A DATA MINING METHOD IN TO LMS FOR THE IMPROVEMENT OF ENGINEERING COURSES IN NETWORKS},
series = {10th annual International Conference of Education, Research and Innovation},
booktitle = {ICERI2017 Proceedings},
isbn = {978-84-697-6957-7},
issn = {2340-1095},
doi = {10.21125/iceri.2017.1648},
url = {http://dx.doi.org/10.21125/iceri.2017.1648},
publisher = {IATED},
location = {Seville, Spain},
month = {16-18 November, 2017},
year = {2017},
pages = {6374-6381}}
TY - CONF
AU - W. Villegas-Ch AU - S. Luján-Mora AU - D. Buenaño-Fernández
TI - APPLICATION OF A DATA MINING METHOD IN TO LMS FOR THE IMPROVEMENT OF ENGINEERING COURSES IN NETWORKS
SN - 978-84-697-6957-7/2340-1095
DO - 10.21125/iceri.2017.1648
PY - 2017
Y1 - 16-18 November, 2017
CI - Seville, Spain
JO - 10th annual International Conference of Education, Research and Innovation
JA - ICERI2017 Proceedings
SP - 6374
EP - 6381
ER -
W. Villegas-Ch, S. Luján-Mora, D. Buenaño-Fernández (2017) APPLICATION OF A DATA MINING METHOD IN TO LMS FOR THE IMPROVEMENT OF ENGINEERING COURSES IN NETWORKS, ICERI2017 Proceedings, pp. 6374-6381.
User:
Pass: