Orientação acadêmica apoiada por learning analytics e visualização de dados
Academic guidance is a regimental activity to be performed by the professor in higher education institutions. Through this activity, the professor can guide, accompany and advise the student in his academic life and in the paths to be taken during the course and in internship, research and extens...
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| Formato: | Dissertação |
| Idioma: | pt_BR |
| Publicado em: |
Brasil
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/28591 |
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| Resumo: | Academic guidance is a regimental activity to be performed by the professor in higher education
institutions. Through this activity, the professor can guide, accompany and advise the student
in his academic life and in the paths to be taken during the course and in internship, research
and extension activities. The Integrated System for the Management of Academic Activities
(SIGAA), developed by the Federal University of Rio Grande do Norte (UFRN), which
computerizes the procedures of the academic area and allows the supervisor to view some
information of the student, such as school transcripts, exchange of messages and authorize
enrollment in disciplines requested by him. However, there is no display of student grades and
absences over time. Nor does it present information in a simplified form of the student's
performance during the discipline, which can provide observation, possible interventions and
continuous counseling. However, the counseling becomes more effective in the role of advisor
if he has technological resources that provide him with better conditions for monitoring and
making academic decisions for him. With this, they will be able to carry out individualized
analyzes for each student, based on the analysis of data of their profile and characteristics,
notifying in communication channels. Given this perspective, the present work presents an
approach for academic guidance, supported by the analysis of the academic and socioeconomic
data of students using Learning Analytics and Data Visualization. The goal is to provide
monitoring of student performance through information geared to the professor. The work was
divided into the following steps: in the first, an online questionnaire was applied with UFRN
professors. Then, a qualitative analysis of the research responses was made, where it was
possible to identify requirements for the development of the proposal. Then we performed the
extraction, transformation and application of student data from some UFRN courses in data
analysis tools, generating graphical visualizations designed to assist the professor in his
academic guidance activities in a future implementation. Finally, a search was made for works
related to the purpose of identifying similarities and differences to research, helping to
characterize and master the research problem. |
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