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Record W3162214270 · doi:10.1177/07342829211016933

Cross-National Comparisons between Canadian and US Higher Education Students on a New, Brief, Multidimensional Measure of Test Anxiety

2021· article· en· W3162214270 on OpenAlexaboutno aff
Patricia A. Lowe

Bibliographic record

VenueJournal of Psychoeducational Assessment · 2021
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMultivariate analysis of variancePsychologyTest (biology)Equivalence (formal languages)Test anxietyMeasurement invarianceAnxietyClinical psychologyRepeated measures designSample (material)Developmental psychologySocial psychologyStructural equation modelingConfirmatory factor analysisStatisticsMathematicsPsychiatry

Abstract

fetched live from OpenAlex

Cross-cultural equivalence, country and gender differences, and external relations with other measures were examined on a new, brief measure of test anxiety, the Test Anxiety Measure for College Students-Short Form (TAMC-SF), in a sample of Canadian and US higher education students. The sample of 1204 students completed the TAMC-SF and other measures online. The results of tests of invariance found support for partial scalar invariance across country and gender on the TAMC-SF. In addition, results of a multivariate analysis of variance (MANOVA) and analysis of variances (ANOVAs) found country and gender differences on the TAMC-SF scales. Furthermore, validity evidence for the TAMC-SF scores with the scores of external measures was found. Overall, the findings support the use of the same test score interpretation for Canadian and US higher education students on the TAMC-SF and the use of the TAMC-SF in Canadian higher education 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.224
Threshold uncertainty score0.451

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.048
GPT teacher head0.431
Teacher spread0.382 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2021
Admission routes1
Has abstractyes

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Same venueJournal of Psychoeducational AssessmentSame topicPerfectionism, Procrastination, Anxiety StudiesFrench-language works237,207