Industrial production is still widely sustained by human operators. However, the design of human–machine interaction often does not foster the motivation to learn more about their machine or system. This may decrease operators’ ability to flexibly adjust their decision making and problem-solving skills to the current production context. Motivation to learn could be attained by a motivating socio-technical design of assistance systems, but suitable and context-specific design strategies are lacking. In the present study, a systematic literature review of motivation theories in education, at the workplace, and in system design was carried out. The resulting 16 theories were integrated into a conceptual model of motivating assistance system design in industrial production. In this model, learning motivation results from the satisfaction of the needs for autonomy, competence, and relatedness, which in turn is mediated through the design of the system (including interface, task, and behavior). Moreover, this process is subject to moderating influences from job characteristics, personal variables, and factors concerning the respective work domain. Strategies for motivational design are derived from the model, and an example from the discrete processing industry is used to illustrate how the model could be applied to design assistance systems in this domain. Finally, the procedures for theory selection and model development are discussed, theoretical and practical implications are derived, and alternative strategies of instilling motivation are considered.