About this paper

Appears in:
Pages: 1166-1172
Publication year: 2017
ISBN: 978-84-697-3777-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2017.1241

Conference name: 9th International Conference on Education and New Learning Technologies
Dates: 3-5 July, 2017
Location: Barcelona, Spain

LEARNING ANALYTICS TO CLASSIFY STUDENTS ACCORDING TO THEIR ACTIVITY IN MOODLE

In the last years, the use of Learning Analytics (LA) tools has been increasing to process the available information about students. In this study, we have analyzed the interactions in the educational scenario collected through Moodle in order to provide a classification of students by using clustering techniques, to improve the learning process. Students online activities generate large quantities of data that before were wasted since no LA tools were available to process them. With the irruption of the big data techniques in the educational sector, a lot of information can be easily treated to extract behaviors of the students and classify them according to their profiles. These analyses define models of action that help both the in-service teacher and the new teacher who joins the department. In addition, detailed analysis of this information may help us in the study of a possible relationship between different indicators of use of these platforms and the performance of students, both generated throughout the learning process as those coming from summative evaluation.

In this study, we provide the construction of a data analysis model facilitated by the Moodle platform, from the different interactions between the teacher, the student and the developed subject; so that this information can be transformed into knowledge and their understanding can help to the improvement of teaching practice. In particular, it addresses the application of these models to the improvement of the students' learning strategies according to their typology.
@InProceedings{VELAPEREZ2017LEA,
author = {Vela-P{\'{e}}rez, M. and Hern{\'{a}}ndez-Estrada, A. and Tirado Dom{\'{i}}nguez, G. and Mart{\'{i}}nez Rodr{\'{i}}guez, M.E. and Pe{\~n}aloza Figueroa, J.L.},
title = {LEARNING ANALYTICS TO CLASSIFY STUDENTS ACCORDING TO THEIR ACTIVITY IN MOODLE},
series = {9th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN17 Proceedings},
isbn = {978-84-697-3777-4},
issn = {2340-1117},
doi = {10.21125/edulearn.2017.1241},
url = {http://dx.doi.org/10.21125/edulearn.2017.1241},
publisher = {IATED},
location = {Barcelona, Spain},
month = {3-5 July, 2017},
year = {2017},
pages = {1166-1172}}
TY - CONF
AU - M. Vela-Pérez AU - A. Hernández-Estrada AU - G. Tirado Domínguez AU - M.E. Martínez Rodríguez AU - J.L. Peñaloza Figueroa
TI - LEARNING ANALYTICS TO CLASSIFY STUDENTS ACCORDING TO THEIR ACTIVITY IN MOODLE
SN - 978-84-697-3777-4/2340-1117
DO - 10.21125/edulearn.2017.1241
PY - 2017
Y1 - 3-5 July, 2017
CI - Barcelona, Spain
JO - 9th International Conference on Education and New Learning Technologies
JA - EDULEARN17 Proceedings
SP - 1166
EP - 1172
ER -
M. Vela-Pérez, A. Hernández-Estrada, G. Tirado Domínguez, M.E. Martínez Rodríguez, J.L. Peñaloza Figueroa (2017) LEARNING ANALYTICS TO CLASSIFY STUDENTS ACCORDING TO THEIR ACTIVITY IN MOODLE, EDULEARN17 Proceedings, pp. 1166-1172.
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