IBotAcademy, a Learning Environment to Learn Skills and Competences in Mobile and Manipulator Robotics Using a Problem-Based Learning Methodology in the Industry 4.0 Education

Smart industries base their development, maintenance, and operation on technologies compatible with what is known as Industry 4.0. In this context, the education sector needs the implementation of new learning schemes and environments for conceptual and practical learning, thereby supporting students’ training to help in the industrial digital transformation. The main contributions of this work are a learning environment for robotics that integrates software applications that quantitatively measure the student’s learning process; a competence framework focused on learning robotics, ROS background, and developing pickup/delivery tasks very common in the Industry 4.0 context; and a learning path implemented in step-by-step guided documentation that considers the competence framework proposed and progressively teaches ROS concepts. This work also describes the development of the learning environment and the software tools that support the student’s learning process. Two pilot tests were performed on iBotAcademy considering twenty students of the Universidad del Valle. The iBotAcademy mobile robotics and the manipulator robotics learning paths achieved an average of 82% positive answers, and 99% positive answers, respectively. The average coefficients of variation of these tests were 16.4% and 8.3%, showing high data consistency. Then, the iBotAcademy learning environment helps to train students for the industrial digital transformation.