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Record W4293658472 · doi:10.5539/hes.v12n4p9

Exploration of Test Anxiety Profiles in U.S. Undergraduate Students

2022· article· en· W4293658472 on OpenAlexvenueno aff
Patricia A. Lowe

Bibliographic record

VenueHigher Education Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPerfectionism (psychology)Test anxietyPsychologyAnxietyHomogeneousLatent class modelTest (biology)Clinical psychologyPsychiatryStatistics

Abstract

fetched live from OpenAlex

The present study was conducted using latent profile analysis to determine whether homogeneous test anxiety groups could be identified among 625 undergraduates and to determine whether gender, self-critical perfectionism, and rigid perfectionism were significant predictors of class membership in the identified test anxiety groups. The students completed two multidimensional instruments, measures of test anxiety and perfectionism, online. Results of the latent profile analysis identified a test anxiety profile with three homogeneous groups as the best model. The three homogeneous groups were labeled low, medium, and high. Moreover, gender, self-critical perfectionism, and rigid perfectionism were found to predict class membership differentially in the three homogeneous groups. Implications of the results are discussed in relation to prevention and intervention in the fields of perfectionism and test anxiety.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.406
Teacher spread0.336 · 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
Published2022
Admission routes1
Has abstractyes

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