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Record W4407032225 · doi:10.61838/kman.psynexus.1.2.2

The Impact of Peer Attachment on Academic Motivation: A Quantitative Analysis

2023· article· en· W4407032225 on OpenAlexaff
Sara Moradi, Farzaneh Mardani

Bibliographic record

VenueKMAN Counseling and Psychology Nexus · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySocial psychology

Abstract

fetched live from OpenAlex

This study aimed to explore the predictive relationship between peer attachment and academic motivation among adolescents, understanding how emotional bonds with peers influence educational engagement and performance. Utilizing a cross-sectional design, data were collected from 300 high school students through standardized questionnaires measuring peer attachment and academic motivation. Linear regression analysis was conducted using SPSS-27 to examine the predictive capacity of peer attachment on academic motivation. Results indicated that peer attachment significantly predicts academic motivation, accounting for 23% of the variance in motivation levels among participants. A positive correlation was found between the quality of peer relationships and the degree of academic motivation, suggesting that stronger peer attachments are associated with higher motivation. The study underscores the importance of peer relationships in shaping academic motivation, suggesting that interventions aimed at enhancing peer connections could positively impact students' educational outcomes. These findings contribute to the broader discourse on the role of social relationships in educational settings, highlighting the need for supportive peer networks to foster academic success.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.092
GPT teacher head0.460
Teacher spread0.368 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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