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Record W2470210741 · doi:10.1002/pits.21937

THE INTERPLAY BETWEEN ADOLESCENTS’ PERCEPTIONS OF TEACHER-STUDENT RELATIONSHIPS AND THEIR ACADEMIC SELF-REGULATION: DOES LIKING A SPECIFIC TEACHER MATTER?

2016· article· en· W2470210741 on OpenAlexaff
Diana Raufelder, Sandra Scherber, Megan A. Wood

Bibliographic record

VenuePsychology in the Schools · 2016
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsConcordia University
Fundersnot available
KeywordsPsychologyPerceptionIntrinsic motivationSelf-determination theoryAssociation (psychology)Mathematics educationDevelopmental psychologySocial psychologyAutonomy

Abstract

fetched live from OpenAlex

Although positive teacher-student relationships are known to aid students’ academic self-regulation, the emotional aspects of teacher liking are often neglected within research. The present study used a large sample of seventh- and eighth-grade students (N = 1,088; MAge = 13.7) in secondary schools in Germany to investigate whether the motivation students gain from specific well-liked teachers (i.e., that students identify) can moderate the relation between their perception of teacher-student relationships overall and academic self-regulation (intrinsic motivation, identified, introjected, and external regulation). By means of latent moderated structural equations, students’ motivation based on liking one specific teacher was found to moderate the association between teacher-student relationships and intrinsic motivation. The present study makes a contribution to the existing research on teacher-student relationships and academic self-regulation by investigating the role of students’ motivation related to the liking of a specific teacher. Results indicate that when early adolescent students can identify a well-liked teacher, they tend to have higher levels of academic motivation. Hence, students’ motivation based on liking a single teacher compensates for generally low-quality teacher-student relationships and their respective impact on students’ intrinsic motivation.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.354
Teacher spread0.319 · 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

Citations36
Published2016
Admission routes1
Has abstractyes

Explore more

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