Ensino de Engenharia via e-learning: relação entre uso de simuladores, ambiente virtual e design instrucional do conteúdo

• Ano de defesa: 2017
• Autor(a) principal: Araújo, Régia Talina Silva
• Orientador(a): Medeiros, Fátima Nelsizeuma Sombra de
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Teleinformática; Engenharia - Estudo e ensino; Ensino à distância; Software educacional; Engineering education; Statistical analysis; Instructional content design
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/48095

The main objective of this research is to statistically assess the learning effectiveness in e-learning engineering courses. Given this context, the following research question was outlined: Do educational resources available in on-line engineering courses, such as Virtual Learning Environment (VLE), Design of Content and simulations, impact on learning effectiveness? To fulfill this objective, we have observed these learning resources in two classes of distance learning courses: a pilot team electrical-engineering course offered by a Federal institute of technological education, part of the Brazilian Open-Tech-School Network E-TEC Brazil, in the discipline of Electric Power Systems; and an extension course on Image Processing and Pattern Recognition using Python / NumPy – PIRP. As a procedure, the use of an interactive simulator was observed in the respective discipline of the Electrotechnical course, as well as the AVA analysis and instructional content design. The development of the simulator was based on virtual reality techniques and cognitive-learning-basis theories, in order to provide training courses in power distribution theme. In PIRP, AVA and instructional content design were also analyzed, and programming simulations available in Adessowiki environments were observed. An evaluation instrument was also applied to the students of both courses. In order to test the effectiveness learning of these resources, we have used the following statistical methods: descriptive and multivariate statistics, namely the principal component analysis (PCA), as well as reliability analysis and canonical correlation analysis (CCA). The results of the statistical analysis confirmed the importance of the three investigated educational resources for learning effectiveness. In this research, we introduced descriptive statistical analysis in terms of a representative index for each question of the educational resource under test. Thus, it possible to observe relevant characteristics to be considered in online engineering courses. Another important contribution of the descriptive statistical analysis is that it enabled identifying opportunities to increase student satisfaction by illustrating institutional strengths and weaknesses. The multivariate analysis by canonical correlation over PIRP course data confirmed the positive contribution of the tested resources through AVA Functionality, Design of Content and Simulations in the effectiveness learning.