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Record W2952352533 · doi:10.82308/35632

Implicit beliefs, achievement goals and affect: a cross-cultural comparison

2010· article· en· W2952352533 on OpenAlexfundno aff
Lavanya Sampasivam

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAffect (linguistics)PsychologySet (abstract data type)Social psychologyCognition

Abstract

fetched live from OpenAlex

Research suggests that the implicit theories students hold about learning predict the types of goals they set for learning and the consequences these belief-goal structures have on student cognition, affect, and behaviour. Although previous studies have indicated that individuals with incremental and entity theories of intelligence set mastery and performance goals for learning, respectively, there is a lack of studies testing the validity of this relationship across cultures. Caucasian (n = 58) and Asian (n = 38) students completed measures of their implicit beliefs about intelligence, their achievement goals, and affect. After learning a novel way to solve multiplication problems, participants were randomly assigned to a negative, positive, or no feedback condition. Participants' beliefs, goals and affect were reassessed following feedback. Results show that Asians did not endorse incremental theories of intelligence significantly more than Caucasians, that Asian students' endorsements of mastery and performance goals were highly correlated and that both Caucasian students and Asian students were significantly affected by negative performance feedback. These results are consistent with a growing body of research suggesting that current conceptualizations of achievement goal theory are not cross-culturally valid.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.032
GPT teacher head0.353
Teacher spread0.322 · 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 designObservational
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

Citations2
Published2010
Admission routes1
Has abstractyes

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