About this paper

Appears in:
Pages: 5946-5955
Publication year: 2017
ISBN: 978-84-697-3777-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2017.2343

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

TOWARD A COLLECTIVE INTELLIGENCE RECOMMENDER SYSTEM FOR EDUCATION

J. Meza1, L. Vaca2, E. Simó1, J.M. Monguet1

1Universitat Politécnica de Catalunya (SPAIN)
2Escuela Superior Politécnica de Chimborazo (ECUADOR)
The development of Information and Communication Technology (ICT), have revolutionized the world and have moved us into the information age, however the access and handling of this large amount of information is causing valuable time losses. Teachers in Higher Education especially use the Internet as a tool to consult materials and content for the development of the subjects. The internet has very broad services, and sometimes it is difficult for users to find the contents in an easy and fast way. This problem is increasing at the time, causing that students spend a lot of time in search information rather than in synthesis, analysis and construction of new knowledge. In this context, several questions have emerged: Is it possible to design learning activities that allow us to value the information search and to encourage collective participation?. What are the conditions that an ICT tool that supports a process of information search has to have to optimize the student's time and learning?

This article presents the use and application of a Recommender System (RS) designed on paradigms of Collective Intelligence (CI). The RS designed encourages the collective learning and the authentic participation of the students.

The research combines the literature study with the analysis of the ICT tools that have emerged in the field of the CI and RS. Also, Design-Based Research (DBR) was used to compile and summarize collective intelligence approaches and filtering techniques reported in the literature in Higher Education as well as to incrementally improving the tool.

Several are the benefits that have been evidenced as a result of the exploratory study carried out. Among them the following stand out:
• It improves student motivation, as it helps you discover new content of interest in an easy way.
• It saves time in the search and classification of teaching material of interest.
• It fosters specialized reading, inspires competence as a means of learning.
• It gives the teacher the ability to generate reports of trends and behaviors of their students, real-time assessment of the quality of learning material.

The authors consider that the use of ICT tools that combine the paradigms of the CI and RS presented in this work, are a tool that improves the construction of student knowledge and motivates their collective development in cyberspace, in addition, the model of Filltering Contents used supports the design of models and strategies of collective intelligence in Higher Education.
@InProceedings{MEZA2017TOW,
author = {Meza, J. and Vaca, L. and Sim{\'{o}}, E. and Monguet, J.M.},
title = {TOWARD A COLLECTIVE INTELLIGENCE RECOMMENDER SYSTEM FOR EDUCATION},
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.2017.2343},
url = {http://dx.doi.org/10.21125/edulearn.2017.2343},
publisher = {IATED},
location = {Barcelona, Spain},
month = {3-5 July, 2017},
year = {2017},
pages = {5946-5955}}
TY - CONF
AU - J. Meza AU - L. Vaca AU - E. Simó AU - J.M. Monguet
TI - TOWARD A COLLECTIVE INTELLIGENCE RECOMMENDER SYSTEM FOR EDUCATION
SN - 978-84-697-3777-4/2340-1117
DO - 10.21125/edulearn.2017.2343
PY - 2017
Y1 - 3-5 July, 2017
CI - Barcelona, Spain
JO - 9th International Conference on Education and New Learning Technologies
JA - EDULEARN17 Proceedings
SP - 5946
EP - 5955
ER -
J. Meza, L. Vaca, E. Simó, J.M. Monguet (2017) TOWARD A COLLECTIVE INTELLIGENCE RECOMMENDER SYSTEM FOR EDUCATION, EDULEARN17 Proceedings, pp. 5946-5955.
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