Abstract

MENDOZA JURADO, Helmer Fellman. Models of artificial neural networks, as an evaluative support to virtual Pedagogical Growth in Higher Education. Edu. Sup. Rev. Cient. Cepies [online]. 2020, vol.7, n.2, pp.25-36. ISSN 2518-8283.

Abstract The present research aims to implement a technological model based on an Artificial Neural Network and a Natural Language Processing algorithm, which provides an automatic process to support critical reviews in virtual assessments to undergraduate students (7th and 8th semester respectively, in the subject of Programming II and Computer Security I). Thus it seeks to support the educational process that was implemented as a contingency because of the global pandemic COVID-19. The above assessments were taken through Moodle which is currently a fundamental resource for the teaching and learning process at the Domingo Savio Private University in all the departments. This platform makes possible a way of study and evaluation that, due to its innovative nature, better supports the currently instituted distance education process. An additional function of this neural network is to evaluate students by identifying individuals with an appropriate psychological profile to reach a specialization in subjects of high academic level.

Keywords : Artificial Neural Network; Natural Language Processing; Virtual Education; Motivation.

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