Educational Resource Recommender Systems Using Python and Moodle
This paper presents the implementation in Phyton of an algorithm for recommending educational resources based on the user’s needs, where these resources will be obtained through the use of the YouTube API that suggests videos of educational materials focused on the student’s level of knowledge to cu...
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Published in | Computational Science and Its Applications - ICCSA 2022 Workshops Vol. 13380; pp. 15 - 30 |
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Main Authors | , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2022
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | This paper presents the implementation in Phyton of an algorithm for recommending educational resources based on the user’s needs, where these resources will be obtained through the use of the YouTube API that suggests videos of educational materials focused on the student’s level of knowledge to customize the recommendations, taking into consideration data obtained from a knowledge survey and the academic grades obtained from different resources made from the Moodle learning platform. The emphasis is on building an RS with the capacity to assist in educational settings. The RSs applied in education allow students to find materials that fit their needs and preferences, and the recommended materials are adapted to the pedagogical objectives of the teachers. It should be noted that the implementation of the project was carried out in a controlled environment, with the interaction of a group of students of a particular subject and semester. |
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ISBN: | 9783031105418 3031105419 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-031-10542-5_2 |