Projects

Projects in progress

Metacognition in human-AI interaction

More and more often, people collaborate on complex cognitive tasks with systems based on artificial intelligence (AI). Augmented decision-making places high metacognitive demands on human decision-makers who must monitor, interpret, evaluate, and refine the AI’s results. In this project, funded by the Forum for Interdisciplinary Research, we combine methodological and theoretical approaches from psychology and information systems to investigate the role of metacognition in augmented decision-making.

Funded by the Forum for Interdisciplinary Research

Project collaborators

Prof. Dr. Monika Undorf – Principle investigator

Prof. Dr. Ekaterina Jussupow – Principle investigator

Franziska Ingendahl - PhD student

Finished projects

Metamemory and processing fluency

Humans possess the striking reflexive capacity to monitor and control their own learning and retrieval (metamemory). In the scientific literature on metamemory, the impact of the ease of processing stimuli during learning (processing fluency) on metamemory has been a topic of much debate. This project combines experimental, statistical, and model-based approaches to investigate to what extent and under what conditions processing fluency contributes to people’s predictions of their future memory performance. Addressing this issue will enhance the scientific knowledge about metamemory and produce practical recommendations on how to improve metacognitive monitoring.

Project collaborators

Prof. Dr. Monika Undorf – Principle investigator

Dr. Malte Zimdahl – Previous PhD student

Funded by the German Research Foundation (DFG, UN 345/1-1; UN345/1-3)

Selected publications

Undorf, M., Navarro-Báez, S., & Zimdahl, M. F. (2022). Metacognitive Illusions. In R. F. Pohl (Ed.), Cognitive Illusions: Intriguing Phenomena in Thinking, Judgment and Memory. Routledge.

Tatz, J. R., Undorf, M., & Peynircioğlu, Z. F. (2021). Effect of impoverished information on multisensory integration in judgments of learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 47(3), 481–497. https://doi.org/10.1037/xlm0000953

Undorf, M. (2020). Fluency illusions in metamemory. In A. M. Cleary & B. L. Schwartz (Eds.), Memory quirks: The study of odd phenomena in memory (pp. 150–174). New York, NY: Routledge.

Undorf, M., Amaefule, C. O., & Kamp, S.-M. (2020). The neurocognitive basis of metamemory: Using the N400 to study the contribution of fluency to judgments of learning. Neurobiology of Learning and Memory, 169, 107176. https://doi.org/10.1016/j.nlm.2020.107176

Undorf, M., & Zimdahl, M. F. (2019). Metamemory and memory for a wide range of font sizes: What is the contribution of perceptual fluency? Journal of Experimental Psychology. Learning, Memory, and Cognition, 45(1), 97–109. https://doi.org/10.1037/xlm0000571

Undorf, M., & Zander, T. (2017). Intuition and metacognition: The effect of semantic coherence on judgments of learning. Psychonomic Bulletin & Review, 24(4), 1217–1224. https://doi.org/10.3758/s13423–016-1189–0

Undorf, M., Zimdahl, M. F., & Bernstein, D. M. (2017). Perceptual fluency contributes to effects of stimulus size on judgments of learning. Journal of Memory and Language, 92, 293–304. https://doi.org/10.1016/j.jml.2016.07.003

Undorf, M., Böhm, S., & Cüpper, L. (2016). Do judgments of learning predict automatic influences of memory? Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(6), 882–896. https://doi.org/10.1037/xlm0000207

Undorf, M., & Erdfelder, E. (2015). The relatedness effect on judgments of learning: A closer look at the contribution of processing fluency. Memory & Cognition, 43(4), 647–658. https://doi.org/10.3758/s13421–014-0479-x

Spontaneous monitoring of learning – Situational determinants, individual differences, and consequences

Funded by the Israel Science Foundation, International Cooperation Grant (Individual Research Grant No. 1082/21)

PI: Prof. Dr. Vered Halamish, Bar-Ilan University, Ramat-Gan, Israel)

Metacognition viewed through the judgment lens

Metacognition, the ability to monitor and control one’s own cognitive processes, guides effective regulation of behavior. To assess this ability, researchers often obtain metacognitive judgments. In this project, we analyze metacognitive judgments with tools and methods of judgment and decision making research. This research extends the scope of metacognition research, contributes to the development of better measures for metacognitive accuracy, and provides the foundation for a theoretical framework that integrates metacognition with first-order cognition.

Project collaborators

Prof. Dr. Monika Undorf – Principle investigator

Prof. Dr. Arndt Bröder, Universität Mannheim – Principle investigator

Sofia Navarro-Báez, M.Sc. - PhD student

Funded by the German Research Foundation (DFG, UNI 345/2-1 and BR 2130/14-1)

Selected publications

Undorf, M., Navarro-Báez, S., & Bröder, A. (2022). “You don’t know what this means to me” – Uncovering idiosyncratic influences on metamemory judgments. Cognition, 222, 105011. https://doi.org/10.1016/j.cognition.2021.105011

Undorf, M., & Bröder, A. (2021). Metamemory for pictures of naturalistic scenes: Assessment of accuracy and cue utilization. Memory & Cognition, 49(7), 1405–1422. https://doi.org/10.3758/s13421–021-01170–5

Undorf, M., & Bröder, A. (2020). Cue integration in metamemory judgements is strategic. Quarterly Journal of Experimental Psychology, 73(4), 629–642. https://doi.org/10.1177/1747021819882308

Bröder, A., & Undorf, M. (2019). Metamemory viewed through the judgment lens. Acta Psychologica, 197, 153–165. https://doi.org/10.1016/j.actpsy.2019.04.011

Undorf, M., Söllner, A., & Bröder, A. (2018). Simultaneous utilization of multiple cues in judgments of learning. Memory & Cognition, 46(4), 507–519. https://doi.org/10.3758/s13421–017-0780–6

The diminishing criterion model as a comprehensive model of metacognitive regulation of effort

Funded by the Israel Science Foundation, International Cooperation Grant (Individual Research Grant No. 234/18)

PI: Prof. Dr. Rakefet Ackerman, Technion – Israel Institute of Technology, Haifa, Israel