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Conrado
Print version ISSN 2519-7320On-line version ISSN 1990-8644
Abstract
QUIROZ MARTINEZ, Miguel Ángel; PALACIOS BRAVO, Johnny Giuseppe; GOMEZ RIOS, Mónica Daniela and LEYVA VAZQUEZ, Maikel Yelandi. Model of recommendation based on knowledge for the development of the thought of the work with objects of apprenticeship. Conrado [online]. 2020, vol.16, n.75, pp.111-116. Epub Aug 02, 2020. ISSN 2519-7320.
Information and communication technologies favor universal access to education, equality in the exercise of teaching, quality learning and professional development of people, and among them are introductory courses in computer science, These are valuable resources for students from various disciplines, while students' end products are often looked at to judge their proficiency and there is no analysis of how learning occurs, which is the programming process, due to the Difficult it is to track the development of a student's programming skills. This paper proposes a knowledge-based recommendation system for the development of thinking about learning objects, in order to improve programmers' problem-solving skills. The recommendation systems arise in response to the need for a content personalization tool, using historical information from the user to recommend elements that they like.
Keywords : Recommendation system based on knowledge; information; semantic web; learning objects.