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Record W3013656633 · doi:10.5430/wjel.v10n1p29

Most Prevalent Study Skills among Taiwanese High School Students with Reference to Gender

2020· article· en· W3013656633 on OpenAlexvenueno aff
Abolfazl Shirban Sasi, Toshinari Haga

Bibliographic record

VenueWorld Journal of English Language · 2020
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsViewpointsProcrastinationRubricPsychologySignificant differenceTest (biology)Developmental psychologyMathematics educationMedical educationSocial psychologyMedicineMathematicsStatistics

Abstract

fetched live from OpenAlex

This study investigated Taiwanese high school students’ study skills with reference to gender differences. 612 students (358 girls, and 254 boys) from six random high schools in Taiwan participated in this study. A 24-item questionnaire originally developed by University of Houston Clear Lake, Texas was adopted, abridged, and administered. The main focus of the questionnaire was on three study habits/skills constructs of “time management & procrastination”, “study aids & note-taking”, and “organizing & processing information” (eight items each). A Pearson Chi-square test (α ≤.05) was used for each of the 24 items of the questionnaire. The results showed that Taiwanese high school boys and girls have very similar, an even sometimes identical, viewpoints towards study skills. The only significant difference observed in the data analysis in this study were items 1, 5, and 8, suggesting that compared with girls, boys typically care more about time management. Moreover, and based on the rubrics devised by the original instrument developer, it was calculated that the highest difference between boys and girls was .61 “arriving at classes and other meetings on time”, whereas the lowest difference was 0 for “maintaining a critical attitude during study - thinking before accepting or rejecting”. Also, both girls and boys equally seemed to be strongest in “arriving at classes and other meetings on time” (item 1), and weakest in “having a system for marking textbooks” (item 14).

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)0.002
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 score0.212
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 science0.0010.000
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 head0.029
GPT teacher head0.363
Teacher spread0.334 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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