Teaching Robotics: Description Model for Synergetic Combination of Robotics Learning Content

Abstract

The continuing growth in robotics achieves its goal to support humans in monotonous and physically demanding tasks sustainably. However, a robot colleague must, of course, be further developed, programmed, and maintained. Thus, a significant trend towards training in the field of robotics is emerging for a broad target group of teachers and learners. Unfortunately, there is no uniform description model for the classification of the growing robotics learning content available, making it impossible to compare existing contents and combine them for a suitable curriculum adapted to individual needs. This paper proposes, therefore, such a model for the classification of learning content in the field of robotics for sustainable human-robot work. The classification is based on three pillars (human, robot, and environment) and combines/extends existing classifications and keyword concepts. Not only the learner’s knowledge level and the subject area in robotics are thereby classified, but also the environment used or recommended for this purpose. Finally, three different state-of-the-art robotics learning contents have been classified to outline the broad and general applicability, but also the limitations of the proposed classification. It will be shown that the associated and proposed keywords make it easier for learners to find suitable content in the field of robotics via all kinds of channels. Based on these results, the authors suggest applying this description model within Learning Factories, online learning platforms, and offline robotics courses.