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Acquiring competence from both extrinsic and intrinsic rewards

2024· article· en· W4398208957 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLearning and Instruction · 2024
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCompetence (human resources)PsychologyIntrinsic motivationCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

Structured abstract Background The distinction between extrinsic and intrinsic rewards and their related motivations has been a major concern in educational psychology for decades. Although both types of rewards are related to the dopamine-fueled activation of the reward circuitry, neuroscientific studies now support the view that their processing also involves independent brain mechanisms. Aims We show that these mechanisms also are already present in birds and nonhuman mammals, as they track cues and extrinsic rewards in their environment (such as food and shelter), and we discuss a number of intrinsically rewarded activities (such as information seeking and play). The two categories of motivated behaviors evolved to perform distinct functions and are both crucial for the species survival. Conclusion We assume that a human-animal comparison is appropriate, and suggest that both extrinsic and intrinsic rewards in humans are necessary to acquire competence, and optimally manage real-life settings, including school environments. More specifically, we argue that intrinsic and extrinsic motivations are additive rather than conflicting processes, and that intrinsic motivation is characterized by exploratory behavior and is associated with benefits for an individual; it is a step to apprehend and exploit the knowledge acquired by means of extrinsic sources of reward.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.401

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.309
Teacher spread0.294 · 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