The comprehension of different types of narratives (NC), e.g., text or comics, is important for societal participation. This dissertation project investigates which factors influence NC. These findings are essential for developing interventions to improve NC in different age groups and thus also to enable greater societal participation, especially in a constantly changing world (e.g. digitalization or internet use).
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.
In various research areas and topics such as climate change or testimonies it has already been demonstrated that mental representations are influenced by true and false information. Problematically, it becomes increasingly difficult to identify false information in our daily lives. Furthermore, new technologies simplify the creation of realistic-looking false messages in media. This dissertation project, therefore, addresses the question of how discriminability of information influences mental representations.
How do people perceive dynamic media such as educational videos, movies, or soccer broadcasts? Human information processing is specialized in processing dynamic information. It distinguishes relevant, and thus informative, information from irrelevant information. This project follows two research lines, bridging the gap between cognitive psychological theories of event cognition and typical situations of media reception. On the one hand, we investigate the perceptual and psychological foundations of dynamic event perception by specifying, for example, the processes of encoding and the properties of mental representations of natural action sequences. On the other hand, we use cinematic stylistic devices (e.g., different camera perspectives, film editing) and new cinematographic film techniques (e.g., 3D films) to explain basic psychological processes, such as the experience of spatial presence or the experience of suspense.
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?
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.
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.
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.
Do people know about their own knowledge? And how does this relate to their experience and behavior? In this project, we investigate how insight into ones’ own cognition relates to information selection and processing, as well as opinion and judgment formation.
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.