Index

Recently there is an increasing importance of artificial intelligence (AI) and robotics in organizations and everyday life, but existing barriers prevent the widespread adoption of AI. Human-robot interaction (HRI) is widely used in industrial applications, e.g., picking and placing in production lines. So far, the market for personal domestic and service robots, or social robots, is comparably small. During the Covid-19 pandemic, quarantine measures, contact restrictions, and home office have led to increased social isolation. Social isolation is a risk factor for loneliness and impairing mental health. Thus, domestic and social robots will likely become increasingly prevalent and penetrate our everyday lives. Engaging with social robots can potentially prevent or at least minimize these negative consequences.  

In this thesis/project, you will investigate the impact of a perspective switching intervention with an embodied social robot on the technology acceptance and perceptions of people. The candidate may use an existing research model and study design that has already been developed in a previous study. Certainly, ideas for adaptions to either the research model or experimental design are welcome. Key constructs of interest will be incorporated from the Technology Acceptance Model by Davis, but also other related dependent variables, such as anxiety, perceived enjoyment, and perceived sociability. Having investigated technology acceptance at the example of the virtual social robot GateBox before, we now strive to build on our promising results and study the effects of taking the perspective with a physical embodied social robot.   

By measuring the constructs before and after the exercise, the student is expected to determine what impact perspective switching has on the technology acceptance of state-of-the-art social robots. The results can inspire the design and implementation of future HRI systems. 

The ideal candidate is interested in Artificial Intelligence and HRI and eager to learn more about social robots. The student will be responsible for the data collection and data analysis. Thus, basic skills in descriptive and inferential statistics are expected. Besides, candidates with enthusiasm for interdisciplinary research at the intersection of psychology and technology are preferred. We would like to highlight that this thesis is an excellent opportunity to gain visibility in the HRI research community. Also, there is the option to coauthor scientific papers with the chair, as have done students in the past. This project does not require any programming skills or expertise in software engineering. 

Game-Designer haben es perfektioniert Nutzer digitaler Spiele bereits ab dem ersten Klick zu begeistern. Dieses Wissen kann auch außerhalb von Spielen die Annahme digitaler Services unterstützen und optimieren. Im Rahmen des Serious-Game „INFLAMMANIA“ möchten wir verschiedene Onboarding-Ansätze erproben und Design-Wissen für die Gestaltung von effektiveren Lern-Spielen erarbeiten. Inflammania ist ein Lernspiel, in dem Entzündungen bei chronischen Erkrankungen bekämpft werden.

Ziel dieser Arbeit
– Entwicklung und empirische Untersuchung verschiedener „Onboarding-Ansätze“ für das Spiel Inflammania
– Statistisches testen von Hypothesen
– Untersuchung der Wirksamkeit von Design-Interventionen auf Nutzerverhalten, Wissensaufbau und Lernerfahrung
– Auswertung der Ergebnisse und Ableitung von theoretischen und praktischen Handlungsempfehlungen für die Gestaltung von „Onboarding-Ansätzen“ für Gamification und Serious-Game-Ansätze

This bachelor thesis presents an overview on the use of gamification in proprietary innovation of the automotive industry based on a structured literature review in the database Espacenet of the European patent
office. As part of this review 83 relevant patents were screened and classified by using an own framework. The screening revealed novel insights and provide researchers anchor points for future research.

Using qualitative interviews with N=14 participants, this thesis examines who creates content in the metaverse and what reasons and motives drive content creators.

In collaboration with the STABILO International GmbH, we developed a text-based adventure for the STABILO DigiPen and empirically evaluated whether personalized gamification experience produce better outcomes in gamified crowdsourcing compared to one-size-fits-all approaches.

This thesis examines the intrinsic motivations of content creators related to word of mouth (WOM) and the intention to continue creating content on and for the Metaverse platform Roblox. The results are compared to the findings of previous studies of content creators of Web 2.0 platforms. Data for this study was collected using an online survey of 50 content creators of Roblox and was analyzed using structural equation modeling in SmartPLS. Based on the uses and gratifications theory (U&G), the study provides first insights of a quantitative approach exploring the intrinsic motivations of people creating for the Metaverse Roblox, trying to build the most renowned virtual 3D worlds and games, meet people or to hang out.

Recently there is an increasing importance of AI and Robotics in organizations and everyday life, but existing barriers prevent the widespread adoption of AI. Human-Robot-Interaction is widely used in industrial applications, e.g., picking and placing in production lines. So far, the market for personal domestic and service robots, or social robots, is comparably small. Still, mainly domestic and social robots will likely become increasingly prevalent and penetrate our everyday lives. During the Covid-19 pandemic, quarantine measures, contact restrictions, and home office have led to increased social isolation. Social isolation is a risk factor for loneliness and impairing mental health. The use of social robots can potentially prevent or at least minimize these negative consequences. In this master thesis, we investigate the impact of an audio-visual perspective switching exercise on the technology acceptance of a social robot measured by the Technology Acceptance Model by Davis. We also incorporate other related constructs, such as anxiety, perceived enjoyment, and perceived sociability. As a social robot for the experiment, we chose the so-called Gatebox, which is developed and manufactured by the Japanese tech company Vinclu. Gatebox is a virtual home robot that accompanies its owner in everyday life. Azuma Hikari represents an AI assistant; she not only communicates with her voice but is a holographically depicted anime girl who inhabits the Gatebox. In times of a global pandemic and increasing social isolation, the Gatebox is not only a home assistant that is supposed to make everyday life easier but also a social robot companion with which the user lives together. By measuring the constructs before and after the exercise, we would like to determine what impact Perspective Switching has on technology acceptance. The results can inspire the design and implementation of future HRI/HAI systems.

Benedikt Morschheuser

Artificial Intelligence (AI) is considered as one of the most important enablers of industry 4.0. Thanks to increasing computing power and the availability of large amounts of valuable data, AI can be used on a large scale in the manufacturing industry. AI can be perceived in different forms. It can have a physical representation. One example are AI-powered robots on the shop floor that are responsible for assembly tasks. But it can also be invisible and embedded in software, such as predictive maintenance software. However, there is still a long way to go before AI is implemented from pilot projects into practice, because there are several obstacles to the introduction of AI-based systems. One main obstacle is people’s lack of trust in AI. This may be due to cognitive barriers. Powerful AI uses complex algorithms. Ordinary users, however, often perceive AI as a “black box” because it is difficult to comprehend an AI’s decision making. In addition, emotional barriers exist. These barriers include, for instance, the fear of being replaced by a robot. To overcome this impediment, a concept from recent research in game design seems very promising, namely perspective switching. Game developers implement elements of perspective switching between human players and Non-Player-Characters (NPC) to improve cooperation and trust. In this way, the NPC can be viewed as a team member rather than a mere tool. Implementing perspective switching as a design pattern is also powerful to elicit feelings towards NPCs as it can help human players to identify and sympathize more easily with the NPC. We will apply this concept to human-AI-interaction in the manufacturing industry to assess if it is possible to achieve the same effect as in the game industry. To carry out this study, a game prototype will first be developed in Roblox, in which the player and a cooperative robot work together to complete tasks on the shopfloor of a manufacturing facility. The unique feature of the game is the player’s ability to switch perspective with the robot. Our research model is based on the Technology Acceptance Model by Davis. To test our hypotheses and investigate the impact of perspective switching on employees’ attitudes toward AI, experiments will be conducted with a few voluntary participants. Pre- and post-game survey data will be collected and analyzed using statistical software. The insights of this work can inspire the design of future human-AI-cooperation scenarios in a manufacturing environment.

Benedikt Morschheuser

Dr Velvet Spors

Benedikt Morschheuser

Benedikt Morschheuser