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Record W1617217730 · doi:10.1002/pits.21836

THE POWER OF SOCIAL AND MOTIVATIONAL RELATIONSHIPS FOR TEST‐ANXIOUS ADOLESCENTS’ ACADEMIC SELF‐REGULATION

2015· article· en· W1617217730 on OpenAlexaff
Diana Raufelder, Frances Hoferichter, David Schneeweiss, Megan A. Wood

Bibliographic record

VenuePsychology in the Schools · 2015
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsConcordia University
FundersVolkswagen Foundation
KeywordsPsychologyTest anxietyStructural equation modelingTest (biology)Association (psychology)AnxietySocial cognitive theoryDevelopmental psychologySocial anxietySelf-determination theorySocial psychologyClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Based on cognitive evaluation theory (CET) and organismic integration theory (OIT) – both sub‐theories of self‐determination theory (SDT) – the present study examined whether the academic self‐regulation of youth with test anxiety can be strengthened through social and motivational relationships with peers and teachers. This study employed a large sample (N = 1088; MAge = 13.7) of early adolescents from secondary schools in Brandenburg, Germany. Structural equation modeling (SEM) was used to test the proposed associations. The results revealed a negative association between test anxiety and intrinsic motivation as well as test anxiety and identified regulation, which was fully mediated by teachers as positive motivators. Furthermore, both teachers as positive motivators as well as the teacher‐student relationship were found to be strong predictors of the self‐determined aspects of academic self‐regulation. Additionally, both peers as positive motivators and the student‐student relationship are essential for external self‐regulation.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
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 head0.078
GPT teacher head0.369
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations15
Published2015
Admission routes1
Has abstractyes

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