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Record W2750215992 · doi:10.1177/0734282917724904

Exploring Cross-Cultural and Gender Differences in Test Anxiety Among U.S. and Canadian College Students

2017· article· en· W2750215992 on OpenAlexaboutno aff
Patricia A. Lowe

Bibliographic record

VenueJournal of Psychoeducational Assessment · 2017
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisMeasurement invarianceTest anxietyAnxietyTest (biology)Construct validityConstruct (python library)Clinical psychologyPopulationDevelopmental psychologySocial psychologyPsychometricsStructural equation modelingDemographyStatistics

Abstract

fetched live from OpenAlex

Existing measures of test anxiety used with the college student population are old with old norms and old items, and they do not capture the multiple dimensions of the test anxiety construct or assess facilitating anxiety. In the present study, the validity of the scores of a new, multidimensional measure of test anxiety with a facilitating component, the Test Anxiety Measure for College Students (TAM-C) was examined in a sample of 1,344 Canadian and U.S. college students. Tests of measurement invariance were performed across culture and gender on the TAM-C and cultural and gender differences were explored. The results of multigroup confirmatory factor analyses across culture and gender supported strong invariance on the TAM-C. Latent mean analyses were also conducted and cultural and gender differences were found on the TAM-C. Although additional research is needed, the TAM-C appears to be a promising new measure for use with Canadian and U.S. college students.

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 score0.009
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.221
GPT teacher head0.472
Teacher spread0.251 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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