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Record W4235174533 · doi:10.31234/osf.io/wxtky

Feeling-of-knowing experiences breed curiosity

2020· preprint· en· W4235174533 on OpenAlexaff
Greg Brooks, Haopei Yang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicPsychological and Educational Research Studies
Canadian institutionsBaycrest HospitalWestern University
Fundersnot available
KeywordsCuriosityPsychologyMetacognitionEpisodic memoryMetamemoryFeelingSet (abstract data type)Context (archaeology)Cognitive psychologyFace (sociological concept)Social psychologyTest (biology)WorryDevelopmental psychologyCognitionNeuroscienceComputer science

Abstract

fetched live from OpenAlex

A central tenet in theoretical work on metacognition is that retrieval experiences during memory search can exert control over behaviour. States of curiosity, which reflect motivational tendencies to seek out information, may play a critical role in this control function. We conducted two experiments to address this idea, focusing on links between feeling-of knowing (FOK) experiences, memory-search duration, and subsequent information-seeking behaviour. We administered an episodic FOK paradigm that probed memory for previously studied face-name pairs and subsequently provided an opportunity to select limited pairs for restudy. This set-up allowed us to test whether current search duration and subsequent restudy choices are biased towards information with high FOK ratings. Results revealed a positive relationship between FOK ratings and the response times of these judgements. We observed a similar positive relationship between FOK ratings and subsequent item selection for restudy. Moreover, experimental manipulations of FOK ratings based on familiarity of the face cues also had parallel effects. Our findings suggest that metacognitive experiences during unsuccessful retrieval from episodic memory can induce states of curiosity that shape behaviour beyond the immediate retrieval context. Curiosity may act as a bond to ensure that memory gaps identified through unsuccessful retrieval adaptively guide future learning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.246
GPT teacher head0.472
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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