Open Access

Applications helping us to maintain the focus on work are called “Zenware” (from concentration and Zen). While form factors, use cases and functionality vary, all these applications have a common goal: creating uninterrupted, focused attention on the task at hand. The rise of such tools exemplifies the users’ desire to control their attention within the context of omnipresent distraction. In expert interviews we investigate approaches in the context of attention-management at the workplace of knowledge workers. To gain a broad understanding, we use judgement sampling in interviews with experts from several disciplines. We especially explore how focus and flow can be stimulated. Our contribution has four components: a brief overview on the state of the art (1), a presentation of the results (2), strategies for coping with digital distractions and design guidelines for future Zenware (3) and an outlook on the overall potential in digital work environments (4).

While human emotions have been researched for decades, designing authentic emotional behavior for non-human characters has received less attention. However, virtual behavior not only affects game design, but also allows creating authentic avatars or robotic companions. After a discussion of methods to model and recognize emotions, we present three characters with a decreasing level of human features and describe how established design techniques can be adapted for such characters. In a study, 220 participants assess these characters' emotional behavior, focusing on the emotion "anger". We want to determine how reliable users can recognize emotional behavior, if characters increasingly do not look and behave like humans. A secondary aim is determining if gender has an impact on the competence in emotion recognition. The findings indicate that there is an area of insecure attribution of virtual affective behavior not distant but close to human behavior. We also found that at least for anger, men and women assess emotional behavior equally well.

Gamification, die spielerische Anreicherung von Tätigkeiten, erfreut sich zunehmender Beliebtheit. Insbesondere in den Bereichen Gesundheit (Exergames) oder Lernen (Serious Games, Edutainment) gibt es eine Vielzahl erfolgreicher Anwendungen. Weniger verbreitet ist Gamification dagegen bislang bei Arbeitsprozessen. Zwar gibt es erfolgreiche Ansätze im Bereich Dienstleistung und Service (z. B. bei Callcentern), der Bereich der industriellen Produktion wurde jedoch bis vor wenigen Jahren nicht adressiert. Dieses Kapitel gibt einen Überblick der Entwicklung von Gamification und zeigt den Stand der Technik. Wir leiten allgemeine Anforderungen für Gamification im Produktionsumfeld ab und stellen zwei neue Ansätze aus der aktuellen Forschung vor. Diese werden in einer Studie mit Trainern aus der Automobilbranche auf Akzeptanz untersucht. Die Ergebnisse zeigen eine insgesamt positive Haltung zur Gamifizierung der Produktion und eine sehr hohe Akzeptanz insbesondere des Pyramiden-Designs.

We present the design outline of a context-aware interactive system for smart learning in the STEM curriculum (science, technology, engineering, and mathematics). It is based on a gameful design approach and enables "playful coached learning" (PCL): a learning process enriched by gamification but also close to the learner's activities and emotional setting. After a brief introduction on related work, we describe the technological setup, the integration of projected visual feedback and the use of object and motion recognition to interpret the learner's actions. We explain how this combination enables rapid feedback and why this is particularly important for correct habit formation in practical skills training. In a second step, we discuss gamification methods and analyze which are best suited for the PCL system. Finally, emotion recognition, a major element of the final PCL design not yet implemented, is briefly outlined.