About this paper

Appears in:
Pages: 3404-3411
Publication year: 2016
ISBN: 978-84-608-5617-7
ISSN: 2340-1079
doi: 10.21125/inted.2016.1802

Conference name: 10th International Technology, Education and Development Conference
Dates: 7-9 March, 2016
Location: Valencia, Spain

A MODULE FOR SENTIMENT ANALYSIS IN MOODLE

D. Maia, F. Belau, S.J. Rigo, I. Alves, J.L. Barbosa, A. Hentges

Universidade do Vale dos Sinos (BRAZIL)
This work describes a proposal of a module in order to provide a sentiment analysis in virtual learning environment Moodle. One goal of this module is to generate subsidies for teacher performance in the form of distance education through the organization of results that may indicate students' feelings, expressed in textual form tools virtual learning environment. The article describes the proposal and its theoretical basis, as well as interaction with work in the field of linguistics which support for the analysis of subjectivity in textual messages.

The general objective of this work consists in the implementation of a module for moodle environment that enable the application of the automatic mining of opinions and sentiment analysis in virtual learning communities, in order to assist the teacher to better evaluate the teaching method. Evaluate the opinions and feelings of the students in courses being taught via distance learning helps the teacher to evaluate their current methods and identify perhaps positive and negative points, which may be enhanced or modified in order to achieve better attention and performance of students in their classes.

To achieve this goal some steps described below were adopted. The first step consists in defining the technical and data mining task to be used in the application. This step was developed in parallel with the analysis and research in the area of recognition of emotions in virtual learning environments, aiming at integration with the Moodle environment. The final steps consist in the implementation of a prototype that performs reviews and analysis of mining feelings based on linguistic information used and makes testing in a controlled environment. These tests were performed with texts extracted from private tuition in EAD, in moodle, based on a prior analysis.

The results are presented in a format divided into levels of student satisfaction regarding the class given. The main contributions of this work are related to the analysis and identification of requirements for the implementation of a module of the Virtual learning environment MOODLE, which allows performing the mining of opinions and sentiment analysis in this environment, tools such as chat or forums.

Moreover, it is necessary to emphasize the implementation and evaluation of joint work with a team of professionals in the field of Linguistics, which provided information about the classification of words. In this way, it was possible to perform the comparison between the results of the analysis with these resources, in contrast to the analysis without this type of resource.
@InProceedings{MAIA2016AMO,
author = {Maia, D. and Belau, F. and Rigo, S.J. and Alves, I. and Barbosa, J.L. and Hentges, A.},
title = {A MODULE FOR SENTIMENT ANALYSIS IN MOODLE},
series = {10th International Technology, Education and Development Conference},
booktitle = {INTED2016 Proceedings},
isbn = {978-84-608-5617-7},
issn = {2340-1079},
doi = {10.21125/inted.2016.1802},
url = {http://dx.doi.org/10.21125/inted.2016.1802},
publisher = {IATED},
location = {Valencia, Spain},
month = {7-9 March, 2016},
year = {2016},
pages = {3404-3411}}
TY - CONF
AU - D. Maia AU - F. Belau AU - S.J. Rigo AU - I. Alves AU - J.L. Barbosa AU - A. Hentges
TI - A MODULE FOR SENTIMENT ANALYSIS IN MOODLE
SN - 978-84-608-5617-7/2340-1079
DO - 10.21125/inted.2016.1802
PY - 2016
Y1 - 7-9 March, 2016
CI - Valencia, Spain
JO - 10th International Technology, Education and Development Conference
JA - INTED2016 Proceedings
SP - 3404
EP - 3411
ER -
D. Maia, F. Belau, S.J. Rigo, I. Alves, J.L. Barbosa, A. Hentges (2016) A MODULE FOR SENTIMENT ANALYSIS IN MOODLE, INTED2016 Proceedings, pp. 3404-3411.
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