MétaCan
Menu
Back to cohort
Record W4220856220 · doi:10.31234/osf.io/fgw8t

Developing and Validating a Growth Mindset Scale for Young Children (GM-C)

2022· preprint· en· W4220856220 on OpenAlexfundno aff
Melis Muradoglu, Tenelle Porter, Kali H. Trzesniewski, Andrei Cimpian

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicGrit, Self-Efficacy, and Motivation
Canadian institutionsnot available
FundersYork University
KeywordsMindsetPsychologyScale (ratio)Developmental psychologyMalleabilityInternal consistencyTest (biology)Measurement invariancePsychometricsStructural equation modelingConfirmatory factor analysisMathematics

Abstract

fetched live from OpenAlex

Beliefs about the malleability of intellectual ability—mindsets—shape achievement. Recent evidence suggests that even young children hold such mindsets; yet, no reliable and valid instruments exist for measuring individual differences in young children’s mindsets. Here, we developed and made freely available an instrument for this purpose—the Growth Mindset Scale for Children (GM-C), suitable for children as young as 4. Among other psychometric properties, we assessed this instrument’s (a) measurement invariance, (b) internal consistency, (c) temporal stability (or test-retest reliability), (d) predictive validity, and (e) cross-cultural robustness in samples of US children (Study 1; N = 220; ages 4 through 6; 50% girls; 39% White) and South African children (Study 2; predominantly grades 4 and 5; N = 331; 54% girls; 100% non-White). The GM-C scale demonstrated invariance across age, as well as strong internal consistency and test-retest reliability. Further, the scale is valid: Four- to six-year-old children with higher GM-C scores oriented toward learning goals (Study 1). Similarly, second- to fifth-grade children with higher GM-C scores oriented toward learning goals, were more likely to take on challenges, and had better grades in math and English (Study 2). These findings suggest that the GM-C is a promising tool for measuring mindsets in young children. We offer practical recommendations on how the scale can be used in future research and discuss theoretical implications of the results.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.335
Teacher spread0.288 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicGrit, Self-Efficacy, and MotivationFrench-language works237,207