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Record W2100963076 · doi:10.5539/ies.v8n10p193

Investigation of Academic Procrastination Prevalence and Its Relationship with Academic Self-Regulation and Achievement Motivation among High-School Students in Tehran City

2015· article· en· W2100963076 on OpenAlexvenueno aff
Setareh Ebadi, Reza Shakoorzadeh

Bibliographic record

VenueInternational Education Studies · 2015
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsnot available
Fundersnot available
KeywordsProcrastinationPsychologyAcademic achievementStatisticDescriptive statisticsMathematics educationCluster samplingScale (ratio)Test (biology)Developmental psychologySocial psychologyDemographyStatisticsPopulationMathematics

Abstract

fetched live from OpenAlex

The present study was carried out with the aim of Investigation of academic procrastination prevalence and its relationship with academic self-regulation and achievement motivation among high-school students in Tehran city. The sample included 624 high school students (312 Boys & 312 Girls) from different areas and regions that selected using random cluster-multistage sampling method. Procrastination Assessment Scale-Student (Solomon & Rothblum, 1984), Self-Regulated Learning Strategies questionnaire (Zimmerman & Pons, 1982) and Achievement motivation test (Hermans, 1970) were used in this study. Data were analyzed in two parts, descriptive and inferential statistics. The results of academic procrastination prevalence using descriptive statistic showed that over half of students nearly always or always procrastinate. Also, results showed that boys and girls procrastinate with the same rate, in general. And boys more than girls procrastinate only on preparing academic tasks. The result of regression analysis also showed that academic self-regulation and achievement motivation predict academic procrastination significantly.

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)0.003
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 score0.009
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.089
GPT teacher head0.389
Teacher spread0.300 · 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

Citations34
Published2015
Admission routes1
Has abstractyes

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