Perception and Action

Perception and Action

Duration 09/2024 - open

Multimodal large language models (LLMs) generate texts based on image inputs. This makes them attractive for a wide range of applications where a large amount of image data needs to be processed. One of these applications is the cataloguing of archival images. ArchiveGPT thus focuses on applying a multimodal LLM to archaeological photo material provided by the Leibniz-Zentrum für Archäologie (LEIZA) in Mainz. We investigate the following questions: How does a multimodal LLM perform when confronted with – for the model, often unfamiliar – archaeological objects and terms? How do archive experts (compared to non-experts) perceive the quality of the model’s image descriptions? Can they at all tell the difference between these AI-generated descriptions and descriptions generated by archive experts? How good are they at estimating their ability to distinguish them beforehand? How important is trust in AI in regard to its use? For the first study on these questions, we generated the experimental material in close collaboration with the LEIZA. Provided with photocards from the image archive, a meta-data template usable in an archival cataloging process was generated for each photocard by the multimodal LLM and LEIZA archivists.

Perception and Action

Duration 08/2024 - open

In a systematic literature analysis, psychological research conducted since the end of the Cold War on people’s responses to the threat of nuclear weapons is examined. The aim is to provide an evidence-based overview of how perception, emotion, and behavior in the face of nuclear risks have been studied—offering insights relevant to education, media, and political communication in times of growing global uncertainty. More than three decades after the last comprehensive reviews of psychological responses to nuclear threats, there is a renewed need to assess the current state of research. The analysis investigates which topics and questions have been addressed, which methods have been applied, and to what extent a coherent research community has developed. The literature review is based on a systematic search in Web of Science and SCOPUS. Out of more than 18,000 identified publications, 256 met the criteria for detailed evaluation. These studies were analyzed with regard to publication trends, author networks, sampling strategies, and measurement instruments. The findings indicate a re-emerging but still weakly connected field of research. A coherent research community has not yet fully formed, and many studies remain isolated efforts with limited generalizability. At the same time, increasing methodological diversity and growing scholarly interest in the societal relevance of nuclear threats can be observed. Overall, the results provide a foundation for future research on global threat perception and its communication in educational and public contexts.

Perception and Action

Duration 01/2024 - open

This secondary analysis of four large, nationally representative datasets examines how political ideology relates to metacognitive confidence in detecting political misinformation. The study investigates whether individuals with more extreme political views—regardless of ideological direction—display higher confidence in their judgments than politically moderate individuals. A symmetric relationship is expected, with metacognitive overconfidence being more pronounced at ideological extremes, while showing no systematic differences between conservatives and liberals. The analyses combine frequentist and Bayesian models to precisely quantify effects of ideological direction and extremity. The findings will provide new evidence on the role of metacognition in political judgment and belief formation.

Perception and Action

Duration 07/2023 - open

Generative Artificial Intelligence is capable of generating texts or images based on verbal prompts. With its universal range of application fields and the human-like output quality the interaction with generative AI becomes increasingly similar to the interaction with other humans. How does interaction with generative AI impact human behavior, understanding, and trust, and how can these insights be used to optimize human-machine collaboration?

Perception and Action

Duration 05/2023 - open

How should we communicate politiczed science such as climate change or COVID-19? We explore how metacognition, the insight that citizens have into the reliability and fallibility of their own knowledge, interacts with science communication to shape behavior and beliefs, and how metacognition is shaped back by science communication.

Perception and Action

Duration 03/2023 - open

While historically, the aim of propaganda was to convince citizens of a certain agenda, novel forms of disinformation come with a different goal in mind: To confuse, rather than convince. Or, as former president Trump’s advisor Steve Bannon put it: “The Democrats don’t matter. The real opposition is the media. And the way to deal with them is to flood the zone with shit”. Although this zone-flooding strategy poses a serious threat to democratic functioning, it currently lacks empirical investigation that maps out its effects on citizens. We conduct a rigorous, pre-registered investigation into the effects of zone-flooding that harnesses state of the art-methods from Signal Detection Theory and metacognition to illuminate pressing questions: Does zone-flooding affect citizens’ ability to distinguish truth from falsehood? Does it affect their insight into the accuracy of this distinction? Does it render citizens more skeptical or more gullible? And are these effects politically symmetrical?

Perception and Action

Duration 09/2022 - open

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.

Perception and Action

Duration 04/2022 - open

How do citizens form beliefs about politicized topics science such as climate change, COVID-19 or vaccinations? In this project, we illuminate the role of metacognition, the insight that citizens have into the reliability and fallibility of their own knowledge and reasoning.

Perception and Action

Duration 02/2022 - open

The comprehension of different types of narratives, such as text, pictures, or comics, is important for societal participation. This dissertation project investigates how narrative comprehension changes with age and which factors contribute positively or negatively to narrative comprehension. These findings are essential for the development of interventions for different age groups and thus for greater societal participation.

Perception and Action

Duration 10/2020 - open

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.

Perception and Action

Duration 10/2020 - open

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.

Perception and Action

Duration 01/2020 - open

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.

Perception and Action

Duration 01/2020 - open

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 informal education settings. This project therefore addresses the question how we comprehend and process visual narratives like comics.

Perception and Action

Duration 01/2012 - open

It is generally believed that humans prefer information that confirms their attitudes and avoid information that represents opposing views. Striving for confirmation and congeniality are also held responsible for a number of toxic phenomena on the Internet, such as the emergence of echo chambers and filter bubbles, the polarization of society, or the dissemination of misinformation. The present project investigates how people deal with opposing opinions – are they really ignored?

Perception and Action

Duration 04/2025 - 03/2028

This dissertation-project examines how climate-change-denial can be effectively countered in video content. The focus is on the question of how proactive strategies (building resilience) and reactive strategies (corrections) can be combined synergistically. The aim is to develop a deeper understanding of the psychological mechanisms that influence the acceptance of corrections. Furthermore, this dissertation project aims to develop evidence-based recommendations for science communication and internet platforms. The dissemination of misinformation about climate change, particularly through online videos, contributes to public skepticism and hinders necessary climate action. To counter these psychological barriers, research has so far mostly pursued two separate paths: proactive strategies that build resilience against misinformation and reactive strategies that correct misinformation after exposure. This project aims to combine both approaches in an integrated model. A central challenge is the so-called “Continued Influence Effect” - the tendency for information that has already been refuted to continue to influence thinking and beliefs. Experimental studies are therefore investigating how video-based misinformation in particular can be optimally corrected. Design principles from the cognitive theory of multimedia learning (CTML) will be applied. The project tests the central assumption that a combination of a proactive message (e.g. about the scientific consensus) and a subsequent reactive correction has a synergistic, i.e. mutually reinforcing, effect. The results should provide a deeper understanding of concrete psychological mechanisms while providing practical, evidence-based guidance for policy makers, video platform operators and science communicators.

Perception and Action

Duration 04/2024 - 03/2027

How can we protect biodiversity and the climate while ensuring a stable and resilient food supply? This central question lies at the heart of a research project that seeks innovative answers to this complex challenge. It aims to develop solutions that respect and sustainably use the planet’s limited resources. By bringing together experts from diverse disciplines, the project strives to identify and address knowledge gaps at the intersections of biodiversity, climate, agriculture, and nutrition. Its interdisciplinary approach fosters a holistic understanding of the complex interconnections among these areas. A key focus of the project is linking scientific research with public discourse. It prioritizes the integration of knowledge and the development of transformative solutions that can be applied at local, regional, and international levels. The overarching goal is to support societal shifts toward comprehensive sustainability through the promotion of innovation and evidence-based decision-making. Another essential component is the development of effective strategies for communicating scientific information to the public. This includes actively addressing misinformation related to sustainability. The project reviews and synthesizes various science communication methods, creates educational materials tailored to different audiences, and designs training programs that treat biodiversity, climate, agriculture, and nutrition as interconnected fields. It also explores new ways of transferring knowledge and technology, aiming to make complex information more accessible and engaging. These tools are intended to support both classroom teaching and self-directed learning. To test and refine its approaches, the project will implement activities at five pilot sites located in both developed and developing countries. These sites will help ensure the applicability and effectiveness of its solutions in real-world contexts.

Perception and Action

Duration 04/2024 - 03/2027

The Leibniz Lab is dedicated to enhancing pandemic preparedness by harnessing the interdisciplinary expertise of 41 Leibniz institutions. Its work spans four central domains: exploring how interactions among the environment, animals, and humans contribute to the emergence and spread of pathogens; mitigating the physical and psychological health impacts of pandemics; optimizing pandemic response strategies; and strengthening the resilience of educational systems in crisis contexts. By integrating diverse perspectives, the Lab functions as a dynamic think tank that complements clinical and infection-control efforts, and provides policymakers and civil society with evidence-based guidance. Recognizing the threat posed by emerging respiratory pathogens, the Lab investigates factors such as alternative livestock farming practices to curb zoonotic transmission, population-level immunity, and the biological mechanisms behind severe disease outcomes. These insights inform strategies to reinforce urban infrastructure and healthcare systems, as well as to enhance educational support for students and teachers during pandemic conditions. In addition, the Lab advances frameworks for robust international collaboration on pandemic preparedness and response. At the IWM, researchers contribute to this effort by examining science communication in pandemic contexts—particularly how individuals navigate and make sense of scientific information in environments saturated with conflicting, ambiguous, or misleading messages.

Perception and Action

Duration 10/2023 - 09/2026

Event perception and cognition theories assume dynamic events are segmented into meaningful chunks of sub-actions with partonomic relationships. This allows viewers to process streaming information in units and predict future states of action based on their expectations and event knowledge. Event models store relevant information for events and guide perception using schemas (or scripts). While event models hold immediately accessible representations stored in long-term memory, working event models process perceptual representations of unfolding activity throughout the event. The studies of this project will shed light on whether event processing in working event models and long-term event schemas are modality-dependent. Considering that the grain of action leads to different levels of processing – with fine-grained events being aggregated into coarse-grained events – understanding modal and amodal representations of fine and coarse context will be important to the perceptual and conceptual organization of event comprehension. Furthermore, this project will explore the role of confidence and metacognitive sensitivity in event cognition. Since sensory information is continuously processed at working event models to predict what will happen next, it is important to know if one’s cognition relies on the perception of event boundaries. Results obtained from metacognitive sensitivity measures will provide further evidence for the event models and their interactions with event schemata. Lastly, this project will address whether event schemata influence the processing of events in general and whether repeated exposure to new events changes their cognition. However, the testing of these questions will be applied using visual and verbal events to observe modality-specific effects of different context grains (fine and coarse).<br>

Perception and Action

Duration 08/2024 - 04/2026

Our interdisciplinary longitudinal study investigates the evolving dynamics of human-AI interaction over six waves spanning one year. By examining individual, behavioral, and task-related variables, the project aims to uncover how users' trust in, perceptions of, self-efficacy, and willingness to engage with AI systems develop and interrelate over time. The insights gained from this research are essential for better understanding human-machine interaction, a critical foundation for fostering effective collaboration between users and AI systems. This knowledge will inform user-centered AI design and guide the ethical integration of these technologies into various aspects of everyday life.

Perception and Action

Duration 01/2023 - 12/2025

This PhD project explores the role of video structure in influencing learning outcomes as well as popularity. By studying structural elements of videos through cognitive psychology, event segmentation theory, and basic shapes of narratives, the project examines how these impact measures of learning and video popularity. The research combines traditional psychological methods with big data and machine learning techniques to gain comprehensive insights into video impact. Online video content consumption, including educational, entertaining, and social media videos, holds significant relevance in today's society. As such, this PhD project delves into how video structure can influence video impact. The research is subdivided into two primary areas. The first part investigates how structural elements in educational videos affect learning outcomes. It utilizes event segmentation theory which posits that people break down events into units to comprehend them. This theory is employed to get an understanding of video structure. It combines this information with the learning outcome analysis to gain valuable insights into the impact of video structure on learning success. The project's second aspect addresses the impact of narrative video structure on the popularity and reach of TikTok short videos. It employs an approach derived from narrative theory and Kurt Vonnegut's six basic shapes of narratives to categorize video content into emotional narrative arcs. In order to obtain these narrative arcs, machine learning techniques are employed. In conjunction, this project seeks not only to deepen the understanding of video structure's influence on video impact but also to show how machine learning and big data can enhance psychological research.

Perception and Action

Duration 01/2023 - 12/2025

Video-SRS is an interdisciplinary project that focuses on supporting video learning in mathematics by exploring and improving self-regulation. It combines insights from cognitive and educational psychology, mathematics education, and computer science to develop innovative approaches to this type of learning. The use of responsible machine learning algorithms plays a significant role in this process. Specifically, the collaborative project aims to identify and address self-regulation problems in video learning by automatically recognizing when such problems occur and providing appropriate and automated assistance. Similarly, the project aims to recognize suboptimal characteristics of instructional videos that could assist learners in selection and creators in the production of better videos. On the educational side, the project focuses on the study of learning for derivation, as there is a great need for learning in this area among German students. Methodologically, the project not only utilizes machine learning techniques, but also analyzes video materials, log file data from video platforms, and multimodal sensor data from individual video learners, such as eye movement data. Where possible, these analyses are triangulated to make the best possible statements about self-regulation problems and their solutions. The goal of the project is both to deepen theoretical insights into the role of self-regulation in video learning and to obtain practical approaches for optimizing learning.

Perception and Action

Duration 12/2021 - 11/2025

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.

Perception and Action

Duration 02/2021 - 01/2025

As the world becomes increasingly technologically 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, has long been in the research spotlight. While research in this field is traditionally focused on how robots can improve our lives, this PhD project aims at flipping the focus on humans helping robots.

Perception and Action

Duration 07/2020 - 06/2024

The human environment is populated by other agents. Other humans make up an important part of this, but animals and increasingly autonomously acting machines, i.e., artificial agents, also act without explicit prompting. As a result, their actions are sometimes incomprehensible. This hinders joint work, which is meant to be facilitated by automation. An important aspect of any interaction with other agents is understanding the other. This includes assessing the capabilities of the other person. In a cooperative situation, it is important to be able to assess how much you can rely on your partner. In a competitive situation, you need to assess in which aspects you are superior.

Perception and Action

Duration 07/2023 - 10/2023

Belief in climate change misinformation such as denying its anthropogenicity has been shown to confuse the electorate, and stall political action. While the extent of the public’s incorrect beliefs is comparatively well-understood, its causes are subject to an ongoing debate. One of the most prominent questions centers around the role of social media: Does social media use drive widespread belief in science-related misinformation?