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dc.contributor.advisorRigo, Sandro José
dc.contributor.authorAndrade, Tiago Luís de
dc.date.accessioned2023-11-08T13:23:09Z
dc.date.accessioned2024-02-28T18:58:08Z
dc.date.available2023-11-08T13:23:09Z
dc.date.available2024-02-28T18:58:08Z
dc.date.issued2023-08-24
dc.identifier.urihttps://hdl.handle.net/20.500.12032/126604
dc.description.abstractDistance Education enabled educational practices based on digital platforms. Despite the widespread adoption of this teaching modality, the high dropout rates are a matter of concern for teachers and institutional managers. There are initiatives to mitigate this situation, such as the application of Educational Data Mining (EDM) and Learning Analytics (LA) techniques and the use of Recommender Systems (RS). Despite being effective in identifying students prone to dropping out and recommending complementary learning materials, they lack mechanisms for student motivation and teachers' pedagogical intervention, as they do not present methodological proposals to encourage the learning of those identified as at risk of dropout, mitigating this possibility. Given this, this work aims to develop an RS model that presents as a differential integration of the pedagogical strategy of Active Methodologies, Problem-Based Learning (PBL), with the EDM and LA techniques, capable of identifying students at risk of disapproval and dropout and enhance their permanence, in a collaborative and interactive process for solving problems. In the studies carried out in the literature, no evidence of this integration was found, with the development of the model being the main scientific contribution of this work, since recent studies point to the importance of improving the ways of teaching. In this sense, a prototype was developed, called Éforo-SR, and a Case Study was carried out with 3 evaluations: (i) verification of the functionalities and interfaces with the use by a teacher; (ii) the evaluation of 13 professors from different areas of knowledge based on acceptance and perceived usefulness, according to the TAM Model - Technology Acceptance Model; (iii) the evaluation of the practical application in a discipline offered in the Distance Education, by 1 teacher to 89 students. Data were collected through questionnaires and submitted for quantitative and qualitative analysis. The results indicated that teachers and students attested to the correct functioning of Éforo-SR, and, according to the TAM Model, more than 87% of teachers and 90% of students agreed with its ease of use. Furthermore, 77% of teachers and more than 88% of students agreed that RS could be helpful in the teaching and learning process. Such results are confirmed when more than 84% of the teachers and 87% of the students answered that they would recommend the prototype of the RS model developed since, in the subject studied, there was an increase in the class average and effective participation of students in an interactive and collaborative process, considered positive and, at the same time, promising given the scientific contribution of the integration of Active Methodologies with the recommendation of materials, EDM and LA for Distance Education. Thus, the results of the evaluations suggested that the model can contribute to improving teaching practices since it helps the teacher recommend complementary materials, encourages collaborative learning, and favors the monitoring of this process and the activities developed by the students.en
dc.description.sponsorshipNenhumapt_BR
dc.languagept_BRpt_BR
dc.publisherUniversidade do Vale do Rio dos Sinospt_BR
dc.rightsopenAccesspt_BR
dc.subjectEducação a distânciapt_BR
dc.subjectLearning Analyticsen
dc.titleMetodologias ativas integradas a um sistema de recomendação com suporte à mineração de dados educacionais e learning analytics para a mitigação de evasão da educação a distânciapt_BR
dc.typeTesept_BR


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