Design de experiência aplicado a times

Abstract

Despite recent advances, current Gamification methodologies still face challenges in effectively personalizing learning experiences and accurately assessing the development of specific competencies. This thesis presents the Marcta Autonomy Framework (MAF), an innovative framework that aims to overcome these limitations by increasing team members’ motivation and participation while promoting personal development and skills through a personalized experience.The MAF, consisting of six phases (Planning, Reception, Advancement, Feedback, Process Evaluation, and Lessons and Adjustments), guides the development of activities with both intrinsic and extrinsic rewards. The research was applied in two academic case studies: a Software Factory and an Introduction to Programming course for students of the Bachelor’s degree in Artificial Intelligence. Using a qualitative approach, including interviews and observations, the results demonstrate that the MAF significantly enhances the development of personal skills. The analysis suggests that the framework can be applied both within a course and in a specific discipline. The main contribution of the MAF lies in its ability to provide a structured roadmap for planning and evaluating pedagogical actions focused on Personal Skills Development.Furthermore, the framework leverages easily capturable data through observation, context, and evaluations. It is concluded that the MAF stands as a personalized and affective Gamification solution for Experience Design in Learning, promoting Personal Skills Development in both academic and corporate contexts.