Browsing by Author "Rahnev, Dobromir"

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    Consensus goals for the field of visual metacognition
    (2021) Rahnev, Dobromir; Balsdon, Tarryn; Charles, Lucie; De Gardelle, Vincent; Denison, Rachel; Desender, Kobe; Faivre, Nathan; Filevich, Elisa; Fleming, Stephen; Jehee, Janneke; Lau, Hakwan; Lee, Alan; Locke, Shannon; Mamassian, Pascal; Odegaard, Brian; Peters, Megan; Reyes, Gabriel; Rouault, Marion; Sackur, Jérôme; Samaha, Jason; Sergent, Claire; Sherman, Maxine Tamara; Siedlecka, Marta; Soto, David; Vlassova, Alexandra; Zylberberg, Ariel
    Despite the tangible progress in psychological and cognitive sciences over the last several years, these disciplines still trail other more mature sciences in identifying the most important questions that need to be solved. Reaching such consensus could lead to greater synergy across different laboratories, faster progress, and increased focus on solving important problems rather than pursuing isolated, niche efforts. Here, 26 researchers from the field of visual metacognition reached consensus on four long-term and two medium-term common goals. We describe the process that we followed, the goals themselves, and our plans for accomplishing these goals. If this effort proves successful within the next few years, such consensus-building around common goals could be adopted more widely in psychological science.
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    The Confidence Database
    (2020) Rahnev, Dobromir; Desender, Kobe; Lee, Alan L. F.; Adler, William T.; Aguilar-Lleyda, David; Akdoğan, Başak; Arbuzova, Polina; Atlas, Lauren Y.; Balcı, Fuat; Bègue, Indrit; Birney, Damian P.; Brady, Timothy F.; Calder-Travis, Joshua; Chetverikov, Andrey; Clark, Torin K.; Davranche, Karen; Denison, Rachel N.; Double, Kit S.; Bang, Won Ji; Duyan, Yalçın A.; Faivre, Nathan; Fallow, Kaitlyn; Filevich, Elisa; Gajdos, Thibault; Gallagher, Regan M.; Gardelle, Vincent de; Gherman, Sabina; Haddara, Nadia; Hainguerlot, Marine; Hsu, Tzu-Yu; Hu, Xiao; Iturrate, Iñaki; Jaquiery, Matt; Kantner, Justin; Koculak, Marcin; Konishi, Mahiko; Koß, Christina; Kvam, Peter D.; Kwok, Sze Chai; Lebreton, Maël; Reyes, Gabriel
    Understanding how people rate their confidence is critical for characterizing a wide range of perceptual, memory, motor, and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations, and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analyzed in multiple software packages. Each dataset is further accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (available at osf.io/s46pr) contained 145 datasets with data from over 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. We show the usefulness of this large collection of datasets in four different analyses that provide precise estimation for several foundational confidence-related effects.

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