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Perception and Action

In the Perception and Action lab, we study human perception and action processes in digital environments. The lab follows a perceptual approach to digital media usage and investigates the effects on human action. In doing so, we address a broad spectrum of media usage formats. The research focus Multicodal Perception addresses the question of how media-mediated content (e.g., texts, images, comics, videos) is perceived and mentally organized. The research focus Perception and Interaction in Social Networks deals with the interplay of attitudes, knowledge, and metacognition in the reception of information and interaction with others (e.g., in online forums). The research focus on Perception and Action with Digital Agents deals with information exchange between humans and artificial intelligence technologies (e.g., algorithms, voice assistants, robots). This spectrum of investigated forms of interaction is flanked by the research focus on risk perception of artificial intelligence, in which opportunities and risks of emergent digital technologies are addressed. 

In all projects, we focus on how information is selected, how the mind organizes these different pieces of information and integrates them with existing knowledge. Important influencing factors that we consider in our work are education, age, and culture. We collaborate with cognitive scientists, computer scientists, and educational scientists. Our research approach is experimental - we collect data in laboratory and field studies and use a variety of empirical (e.g., reaction time measurement, eye-tracking, augmented reality) and statistical methods (including signal detection theory).



How do we read comics? – Investigating comprehension processes in visual narratives

Narratives communicate information in many ways, for example in books, audio dramas, films, or visual narrations like comics. While there is extensive research on text or film comprehension, relatively little is known about comic comprehension. Visual narratives, however, offer many possibilities in formal and information education settings. This project therefore addresses the question how we comprehend and process visual narratives like comics.


Artificial agents are a topic in the digital world that can no longer be ignored. One concern of many people is that these agents no longer make comprehensible decisions. This hinders collaborative work, which is supposed to be facilitated by automation. Humans are able to know what other humans know and can adapt their actions accordingly. Whether this ability also works for artificial agents is an open question.

Polarization and conflict-laden communication on the internet

The polarization of attitudes and opinions about political, societal, or scientific issues on the Internet is generally held to be a challenge for a functioning democracy. Research on this topic is dominated by the view that polarization is caused by a preference for reading attitudinally congenial information and a preference for interacting with like-minded others in echo chambers. Is attitudinal unison the only factor that leads to polarization?

Prosocial behavior towards artificial agents

As the world becomes increasingly technology forward, the presence of artificial agents in day-to-day life also becomes more apparent. Studying the interaction between humans and artificial agents, such as robots or virtual assistants, has long been in the research spotlight. While research in this field is traditionally focused on how artificial agents can improve our lives, this PhD project aims at flipping the focus on humans helping artificial agents. 

Psychological Determinants of Risk Perception about Artificial Intelligence

In societal discourse, Artificial Intelligence (AI) is strongly tied with both opportunities and risks. In this project, it is investigated how humans perceive the risks of AI and how their risk assessments are associated with psychological factors like prior knowledge and judgmental confidence. The behavioral consequences of risk perception are investigated, as well as intervention methods aimed at raising an awareness of AI risks.

Risk perception and codality in a cross-cultural context

People receive daily warnings of risks through images and texts and are supposed to decide if a certain situation is dangerous. Interestingly, people behave differently toward the same risk situation (like wearing a mask during a pandemic), which raises the question, if risk perception is culturally universal. This project takes a closer look at how culture and language shape the processes underlying the risk perception.

Traces in video portals: The potential of user generated data for the design of effective educational videos

In nearly all educational settings (schools, universities, further education), videos play an increasingly large role. On video portals learners can deepen and broaden their acquired knowledge and while watching they leave traces like pauses or skips. This cooperation project investigates how such usage data in conjunction with videos automatically prepared under pedagogical and psychological considerations can be harnessed to make video learning adaptive and effective.

Utilizing software agents to depolarize attitudes

When navigating the Internet, people are confronted both with attitudinally congenial and uncongenial information. Typically, congenial information is read and processed more superficially. The long-term goal of this project is to develop a software agent that uses reading time information to infer whether someone is reading congenial or uncongenial information. The agent can then adapt the presentation of content in a way that pro and con arguments are read with the same depth.

Former Projects