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- Institut Mensch - Computer - Medien (50) (remove)
Sonstige beteiligte Institutionen
Over the past years, scholars have explored eudaimonic video game experiences—profound entertainment responses that include meaningfulness, reflection, and others. In a comparatively short time, a plethora of explanations for the formation of such eudaimonic gaming experiences has been developed across multiple disciplines, making it difficult to keep track of the state of theory development. Hence, we present a theoretical overview of these explanations. We first provide a working definition of eudaimonic gaming experiences (i.e., experiences that reflect human virtues and encourage players to develop their potential as human beings fully) and outline four layers of video games—agency, narrative, sociality, and aesthetics—that form the basis for theorizing. Subsequently, we provide an overview of the theoretical approaches, categorizing them based on which of the four game layers their explanation mainly rests upon. Finally, we suggest the contingency of the different theoretical approaches for explaining eudaimonic experiences by describing how their usefulness varies as a function of interactivity. As different types of games offer players various levels of interactivity, our overview suggests which theories and which game layers should be considered when examining eudaimonic experiences for specific game types.
A substantial number of people refused to get vaccinated against COVID-19, which prompts the question as to why. We focus on the role of individual worldviews about the nature and generation of knowledge (epistemic beliefs). We propose a model that includes epistemic beliefs, their relationship to the Dark Factor of Personality (D), and their mutual effect on the probability of having been vaccinated against COVID-19. Based on a US nationally representative sample (N = 1268), we show that stronger endorsement of post-truth epistemic beliefs was associated with a lower probability of having been vaccinated against COVID-19. D was also linked to a lower probability of having been vaccinated against COVID-19, which can be explained by post-truth epistemic beliefs. Our results indicate that the more individuals deliberately refrain from adhering to the better argument, the less likely they are vaccinated. More generally, post-truth epistemic beliefs pose a challenge for rational communication.
Learning about informal fallacies and the detection of fake news: an experimental intervention
(2023)
The philosophical concept of informal fallacies–arguments that fail to provide sufficient support for a claim–is introduced and connected to the topic of fake news detection. We assumed that the ability to identify informal fallacies can be trained and that this ability enables individuals to better distinguish between fake news and real news. We tested these assumptions in a two-group between-participants experiment (N = 116). The two groups participated in a 30-minute-long text-based learning intervention: either about informal fallacies or about fake news. Learning about informal fallacies enhanced participants’ ability to identify fallacious arguments one week later. Furthermore, the ability to identify fallacious arguments was associated with a better discernment between real news and fake news. Participants in the informal fallacy intervention group and the fake news intervention group performed equally well on the news discernment task. The contribution of (identifying) informal fallacies for research and practice is discussed.
Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.
In the context of medical device training, e-Learning can address problems like unstandardized content and different learning paces. However, staff and students value hands-on activities during medical device training. In a blended learning approach, we examined whether using a syringe pump while conducting an e-Learning program improves the procedural skills needed to operate the pump compared to using the e-Learning program only. In two experiments, the e-Learning only group learned using only the e-Learning program. The e-Learning + hands-on group was instructed to use a syringe pump during the e-Learning to repeat the presented content (section “Experiment 1”) or to alternate between learning on the e-Learning program and applying the learned content using the pump (section “Experiment 2”). We conducted a skills test, a knowledge test, and assessed confidence in using the pump immediately after learning and two weeks later. Simply repeating the content (section “Experiment 1”) did not improve performance of e-Learning + hands-on compared with e-Learning only. The instructed learning process (section “Experiment 1”) resulted in significantly better skills test performance for e-Learning + hands-on compared to the e-Learning only. Only a structured learning process based on multi-media learning principles and memory research improved procedural skills in relation to operating a medical device.
When interacting with sophisticated digital technologies, people often fall back on the same interaction scripts they apply to the communication with other humans—especially if the technology in question provides strong anthropomorphic cues (e.g., a human-like embodiment). Accordingly, research indicates that observers tend to interpret the body language of social robots in the same way as they would with another human being. Backed by initial evidence, we assumed that a humanoid robot will be considered as more dominant and competent, but also as more eerie and threatening once it strikes a so-called power pose. Moreover, we pursued the research question whether these effects might be accentuated by the robot’s body size. To this end, the current study presented 204 participants with pictures of the robot NAO in different poses (expansive vs. constrictive), while also manipulating its height (child-sized vs. adult-sized). Our results show that NAO’s posture indeed exerted strong effects on perceptions of dominance and competence. Conversely, participants’ threat and eeriness ratings remained statistically independent of the robot’s depicted body language. Further, we found that the machine’s size did not affect any of the measured interpersonal perceptions in a notable way. The study findings are discussed considering limitations and future research directions.
The relevance of user experience in safety–critical domains has been questioned and lacks empirical investigation. Based on previous studies examining user experience in consumer technology, we conducted an online survey on positive experiences with interactive technology in acute care. The participants of the study consisted of anaesthesiologists, nurses, and paramedics (N = 55) from three German cities. We report qualitative and quantitative data examining (1) the relevance and notion of user experience, (2) motivational orientations and psychological need satisfaction, and (3) potential correlates of hedonic, eudaimonic, and extrinsic motivations such as affect or meaning. Our findings reveal that eudaimonia was the most salient aspect in these experiences and that the relevance of psychological needs is differently ranked than in experiences with interactive consumer technology. We conclude that user experience should be considered in safety–critical domains, but research needs to develop further tools and methods to address the domain-specific requirements.
The current condition of (Western) academic psychology can be criticized for various reasons. In the past years, many debates have been centered around the so-called “replication crisis” and the “WEIRD people problem”. However, one aspect which has received relatively little attention is the fact that psychological research is typically limited to currently living individuals, while the psychology of the past remains unexplored. We find that more research in the field of historical psychology is required to capture both the similarities and differences between psychological mechanisms both then and now. We begin by outlining the potential benefits of understanding psychology also as a historical science and explore these benefits using the example of stress. Finally, we consider methodological, ideological, and practical pitfalls, which could endanger the attempt to direct more attention toward cross-temporal variation. Nevertheless, we suggest that historical psychology would contribute to making academic psychology a truly universal endeavor that explores the psychology of all humans.
With the increasing adaptability and complexity of advisory artificial intelligence (AI)-based agents, the topics of explainable AI and human-centered AI are moving close together. Variations in the explanation itself have been widely studied, with some contradictory results. These could be due to users’ individual differences, which have rarely been systematically studied regarding their inhibiting or enabling effect on the fulfillment of explanation objectives (such as trust, understanding, or workload). This paper aims to shed light on the significance of human dimensions (gender, age, trust disposition, need for cognition, affinity for technology, self-efficacy, attitudes, and mind attribution) as well as their interplay with different explanation modes (no, simple, or complex explanation). Participants played the game Deal or No Deal while interacting with an AI-based agent. The agent gave advice to the participants on whether they should accept or reject the deals offered to them. As expected, giving an explanation had a positive influence on the explanation objectives. However, the users’ individual characteristics particularly reinforced the fulfillment of the objectives. The strongest predictor of objective fulfillment was the degree of attribution of human characteristics. The more human characteristics were attributed, the more trust was placed in the agent, advice was more likely to be accepted and understood, and important needs were satisfied during the interaction. Thus, the current work contributes to a better understanding of the design of explanations of an AI-based agent system that takes into account individual characteristics and meets the demand for both explainable and human-centered agent systems.