Inovação na experiência de aprendizagem em ciência dos dados : implementação a partir da teoria da aprendizagem significativa

Abstract

This is an Applied Technical Project whose aim is to investigate theoretical and methodological assumptions for the construction of online courses to be taught in the continuing education of professionals in the logistics sector. The new innovation cycles of society 4.0 includes the intensive use of digital technologies such as artificial intelligence, robotics, the internet of things, autonomous vehicles, bio and nanotechnology, 3-D printing, material science, quantum computing and energy storage, requiring new approaches to professional learning. The research begins with a diagnosis of the problem and a conceptual exploration suitable for analyzing the data in the report which involved companies in the logistics and cargo segment in the state of Paraiba. The study of Significant Learning Theory was applied to the restructuring of courses involving people development, especially in the area of Data Science. This theoretical approach enabled the design of a framework for planning a meaningful learning experience. The conceptual model was based on the assumptions of meaningful learning and pedagogical usability heuristics for designing materials and evaluating problem-based learning. By structuring the framework, it was possible to design a prototype for proposing a learning experience in two courses: Data Intelligence for Management and Data Analysis with Power BI. The two courses were rewritten using a graphic editing tool called Figma, which made it possible to apply TAS assumptions, usability heuristics, hyperlinked navigation, ease of use and feedback collection. The design of the framework made it possible to innovate in the planning of learning experiences aimed at creating materials to develop skills for society 4.0.