Seamless Learning in the Production

Abstract

Production SMEs in the automotive value chain/network are increasingly confronted with a serious number of specific requirements and regulations. Compared to large enterprises especially blue-collar workers have to deal with shared responsibilities at the shop floor in order to fulfill the different tasks they have to perform. There is a great need of an overall on-the-job knowledge, available in the right time at the right place. In this case workers need seamless learning in real-life situations (“in-situ”, pervasive learning), a field which is still emerging, especially in settings of production SMEs. This industrial challenge gives rise to the following research questions: How need such learning services to be designed in order to achieve a high acceptance rate by learners and/or trainers? What are multimodal input and output interactions as well as interfaces suitable for HCI concepts for learning? How can contextual data be applied for high efficiency and efficacy of context-aware pervasive learning? Therefore we examine a context-of-use scenario in a metal forming SME for the purpose of developing a mobile pervasive learning system.