Estudo da Trajetória Navegacional do Médico com interesse em Diagnóstico por Imagem em Ambiente Virtual de Aprendizagem no Contexto da Educação Continuada - Albanez, Maria De Fatima Bazoni [UNIFESP] (2020)
This study describes the medical student's navigational trajectory by mining secondary data recorded in the virtual learning environment. The research, on whose data he relies, had an exploratory, descriptive character, with a quantitative approach and involved the understanding of the student's navigation in a set of virtual learning objects, which made it possible to interpret the quantitative data collected through the analysis of the data log records generated by the educational technological system. This research was carried out on Cetrus Diagnósticos, Ltda, using the information stored in the database of students enrolled in self-instructional distance learning courses, on the topic Diagnostic Imaging and who used the virtual learning environment AVA to carry out their studies. The study included all students who accessed the virtual learning environment; and those who did not have access were excluded. Data collection was performed in the AVA - Moodle, based on the records that generated access report data, which allowed to view each of the course activities and the number of times that this activity was accessed. The data analysis process took place by mining the selected data from the fields of interest and generating the infographics, using the statistical package SPSS - Statistical Package and the spreadsheet software MS-OFFICE Excell®. With support in the planned records, it was possible to obtain statistics from the student's navigational data that allowed to map the choices that the student made during his studies. By knowing how this process occurred, through the analysis of students' navigational behavior, it was possible to unveil a scenario that contributed to the pedagogical designs of the courses, favoring learning and communication, and, in alignment with the interest and motivation of the student. Student, also compete to guide decisions about investments in the production of teaching materials, identify risks and characteristics that indicate the possibility of dropping out, failing or dropping out and to understand digital learning, which is characteristic of contemporary times.