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A convergent model of the fluency heuristic for inference and recognition judgments

English title A convergent model of the fluency heuristic for inference and recognition judgments
Applicant Marewski Julian
Number 159822
Funding scheme Project funding
Research institution Département de comportement organisationnel Faculté des HEC Université de Lausanne
Institution of higher education University of Lausanne - LA
Main discipline Psychology
Start/End 01.04.2016 - 31.03.2018
Approved amount 125'564.00
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Keywords (3)

recognition memory; probabilistic inference; fluency heuristic

Lay Summary (German)

Lead
Das Ziel dieses Forschungsprojektes ist es eine integrative Theorie darüher aufzustellen, wie die Geschwindigkeit, mit der wir Informationen aus dem Gedächtnis abrufen können, unser Entscheidungsverhalten beeinflusst. Dazu bringen wir zwei verschiedene Forschungszweige zusammen-- sowohl auf der theoretischen Ebene (wir entwickeln und vergleichen verschiedene quantitative Modelle von „fluency“-basierten Entscheidungen) und auf der methodischen Ebene (in einer Reihe von Experimenten).
Lay summary

Wenn wir Personen treffen, erinnern wir uns an Informationen, die wir mit diesen Personen verbinden, wie zum Beispiel deren Namen. Wie lange es dauert diese Informationen aus dem Gedächtnis abzurufen, hängt davon ab, wie gut wir die jeweilige Person kennen. Uns sehr vertraute Personen, wie Mitglieder unserer Familie, erkennen wir oft unmittelbar. Doch wir alle wissen, was für ein Gefühl in uns aufkeimt, wenn es länger dauert bis uns der Name einer nur "losen" Bekanntschaft einfällt. Die Geschwindigkeit, mit der Informationen aus dem Langzeitgedächtnis abgerufen werden, wird als "Flüssigkeit des Abrufens" (engl. „retrieval fluency“) bezeichnet. Im täglichen Leben spielt dieses Nebenprodukt des Gedächtnisabrufes bei vielen Entscheidungen eine wichtige Rolle. In der wissenschaftlichen Literatur haben sich verschiedene Forschungsfelder zur „retrieval fluency“ entwickelt. Ein wichtiger Zweig der Forschung konzentriert sich z.B. auf den Einfluss von Vertrautheit auf sogenannte probabilistische Inferenzurteile (d.h. Urteile bei denen bekannte Attribute eines Objekts, wie zum Beispiel dessen Abrufgeschwindigkeit, benutzt werden, um ein unbekanntes Kriterium, wie zum Beispiel die Wichtigkeit einer Person, zu erschließen). Ein anderer Forschungszweig exploriert, wie die Erfahrung eines Stimulus im unmittelbaren Kontext die Abrufgeschwindigkeit und damit das Wiedererkennungsgedächtnis beeinflusst. Trotz vieler Parallelen zwischen diesen und anderen Forschungsfeldern haben sich selbige leider weitgehend unabhängig voneinander entwickelt. Das Ziel des vorliegenden Forschungsprojektes ist der Versuch eine vereinheitlichende Theorie zum Phänomen „fluency“ aufzustellen. 

Direct link to Lay Summary Last update: 09.07.2015

Responsible applicant and co-applicants

Employees

Publications

Publication
Broadening the scope of recognition memory
Olds Justin, Marewski Julian (2017), Broadening the scope of recognition memory, in Proceedings of the 39th Annual Conference of the Cognitive Science Society , London, England.
Unpacking decision domains: Commentary on “Domain-specific preferences for intuition and deliberation in decision making”
Olds Justin, Link Daniela (2016), Unpacking decision domains: Commentary on “Domain-specific preferences for intuition and deliberation in decision making”, in Journal of Applied Research in Memory and Cognition, 5(3), 325-328.

Collaboration

Group / person Country
Types of collaboration
State University of New York United States of America (North America)
- Publication
University of Lausanne Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
Syracuse University New York United States of America (North America)
- Publication
Max Planck Institute for Human Development, Center for Adaptive Rationality Germany (Europe)
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
39th Annual Meeting of the Cognitive Science Society Talk given at a conference Broadening the scope of recognition memory 26.07.2017 London, Great Britain and Northern Ireland Olds Justin;
7th Annual Thurgau Experimental Economics Meeting Talk given at a conference Modeling memory-based decision making: Incorporating the role of immediate context. 10.04.2017 Kreuzlingen, Switzerland Olds Justin;
38th Annual Conference of the Cognitive Science Society Poster Memory-based decision making: Examining the relative influence experimental and pre-experimental exposure 10.08.2016 Philadelphia, PA, United States of America Olds Justin;


Abstract

Title of Research ProjectA Convergent Model of the Fluency Heuristic for Inference and Recognition JudgmentsLeadWith this research project, we strive to build an integrative theory of how the speed of retrieving information from memory influences decision making. In order to do so, we integrate two disparate lines of research theoretically (by developing and comparing different quantitative models of fluency-based decision making) and methodologically (with a series of experiments).BackgroundWhenever we encounter people, we recall information associated with them, such as their names. However, how long it takes to retrieve this information varies depending on the specific person we meet. Indeed, we tend to recognize and retrieve information instantly for people we are highly familiar with, such as our loved ones. Yet, we have all experienced the nagging feeling that occurs while trying to remember a loose acquaintance’s name. The speed with which information is retrieved from long-term memory is called retrieval fluency, and this readily available byproduct of mnemonic processing is used as a cue for many judgments, such as recognition, truth, the fame of politicians, and the size of cities, to name but a few. Because retrieval fluency is an ongoing mnemonic experience associated with all stimuli we encounter, it has monumental implications for our daily decisions.Within the literature, research on retrieval fluency during decision-making has proceeded on separate tracks. One track has focused on natural familiarity (i.e., produced by exposure to a stimulus during a person’s prior learning history outside the laboratory) as a determinant of retrieval speed and how it influences probabilistic inference judgments (i.e., using known attributes of a stimulus, such as processing speed, as cues to make inferences about an unknown or future criterion such as the fame of politicians or the population of cities; e.g., Hertwig et al., 2008; Marewski & Schooler, 2011; Schooler & Hertwig, 2005). Another track has focused on immediate context (e.g., recent exposure of a stimulus during an experiment or quality of stimulus presentation during testing) as a determinant of retrieval speed and how it influences recognition memory judgments (i.e., using episodic knowledge to judge if stimuli were presented during an experiment; e.g., Jacoby & Whitehouse, 1989; Unkelbach, 2006; Westerman, 2008). Despite many similarities, unfortunately, these two bodies of research have remained largely independent. In this research project, we strive to build a more unified theory of fluency by integrating these research paradigms methodologically (across a series of experiments) and by integrating these paradigms theoretically (by formalizing and testing disparate models of fluency-based decision making). Because theory integration is often a thorny process, we rely on a quantitative cognitive modeling tool as a vehicle for making our hypotheses explicit and readily comparable. That tool is the ACT-R cognitive architecture (e.g., Anderson & Lebiere, 1998)-a theory that provides, arguably, the most detailed quantitative account of cognition developed until today. It is our hope that, by focusing on formal model building and methodological integration, this project will delineate the meaningful parallels between both research fields and create a favorable avenue for future research on memory-based decision making. ReferencesAnderson, J. R. & Lebiere, C. (1998). The Atomic Components of Thought. Mahwah, NJ: Lawrence Erlbaum Associates.Hertwig, R., Herzog, S. M., Schooler, L. J., & Reimer, T. (2008). Fluency heuristic: A model of how the mind exploits a by-product of information retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 1191-1206.Jacoby, L. L., & Whitehouse, K. (1989). An illusion of memory: False recognition influenced by unconscious perception. Journal of Experimental Psychology: General, 118, 126-135.Marewski, J. N., & Schooler, L. J. (2011). Cognitive niches: An ecological model of strategy selection. Psychological Review, 118, 393-437.Schooler L. J. & Hertwig R. (2005). How forgetting aids heuristic inference. Psychological. Review, 112, 610-28. Westerman, D. L. (2008). Relative fluency and illusions of recognition memory. Psychonomic Bulletin & Review, 15, 1196-1200.Unkelbach, C. (2006). The learned interpretation of cognitive fluency. Psychological Science, 17, 339-345.
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