Análise da influência das variáveis ambientais e da percepção ambiental no desempenho de estudantes em ambientes de ensino superior

• Autor(a) principal: Lucas, Ruan Eduardo Carneiro
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
• Texto Completo: https://repositorio.ufpb.br/jspui/handle/123456789/20842
• topic: Variáveis ambientais; Percepção ambiental; Desempenho; Estudantes universitários; Environmental variables; Environmental perception; Performance; College students; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO

The needs of the current world increasingly result in the use of closed environments, causing people to be subjected to environmental conditions controlled by mechanical devices. Teaching environments are examples of this and the existing environmental conditions are incompatible with the needs of students, compromising well-being and impacting performance. As a result of this scenario, this dissertation analyzes the influence of environmental variables and environmental perception on the performance of students in air-conditioned teaching environments in different Brazilian regions. To operationalize this objective, an experimental method was applied in seven higher education environments. The experiment was carried out on three consecutive days, in which a type of thermal condition was proposed for each day by manipulating and fixing the air temperature of the air conditioning units. In the three days the environmental parameters were measured and a questionnaire was applied about the perception in relation to the thermal, acoustic, lighting and air quality variables. Subsequently, students were subjected to a battery of tests, in order to identify cognitive performance. With this information, statistical analysis was developed. Initially, generalized linear models were applied to investigate the influence of environmental variables on performance. Subsequently, factor analysis was applied to generate perceptual dimensions. Then, he related the perceptual dimensions with the performance based on structural equations. Finally, Bayesian networks were applied to understand how the perceptual dimensions were related and to estimate probabilistic scenarios for the relationships found. From this, it was identified that the thermal perception influenced the perception of the other variables. In addition, it was found that the luminous and thermal perceptions were related to the number of correct answers and the response time, respectively. Regarding the environmental variables, it was found that the air temperature was the one with the most significant relationship with performance.