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Record W4399880298 · doi:10.55016/ojs/ajer.v49i1.54957

Gender Differences in Mathematics Anxiety Among Preservice Teachers and Perceptions of Their Elementary and Secondary School Experience with Mathematics

2003· article· en· W4399880298 on OpenAlexfundvenueno aff
Alan D. Bowd, Patrick Brady

Bibliographic record

VenueAlberta Journal of Educational Research · 2003
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
FundersLakehead University
KeywordsMathematics educationPerceptionPsychologyElementary mathematicsPedagogy

Abstract

fetched live from OpenAlex

This study investigated experiential antecedents of mathematics anxiety and associations with gender among preservice student teachers. Participants were 357 students enrolled in the final year of a teacher education program. They responded to the Mathematics Anxiety Rating Scale (Richardson & Suinn, 1972) and a questionnaire to assess experience with mathematics in the elementary and secondary school together with attitudes toward mathematics and beliefs about the subject. Male and female participants did not differ informal mathematics achievement or the time elapsed since taking a mathematics course. Several gender differences were found in perceptions of school mathematics experience, and both men and women reported greater enjoyment of mathematics in elementary school compared with high school. Women expressed less positive beliefs about their use of, and intrinsic interest in, mathematics. Associations between mathematics anxiety and both perceptions of school experience and beliefs about mathematics were higher for women. Negative experience with mathematics in high school was an important precursor of mathematics anxiety, especially among women. Some implications for teacher education programs were reviewed; these emphasize the importance of both teachers' and peers' behavior, especially in the high school environment.

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)0.001
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 score0.097
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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 head0.395
Teacher spread0.325 · 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

Citations13
Published2003
Admission routes2
Has abstractyes

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