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Record W4310455523 · doi:10.52041/serj.v21i3.29

PSYCHOMETRIC EVALUATION OF THE STUDENTS’ ATTITUDES TOWARD STATISTICS AND TECHNOLOGY SCALE (SASTSc)

2022· article· en· W4310455523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStatistics Education Research Journal · 2022
Typearticle
Languageen
FieldMathematics
TopicStatistics Education and Methodologies
Canadian institutionsWestern UniversityToronto Metropolitan University
Fundersnot available
KeywordsReplicateScale (ratio)PsychologyReliability (semiconductor)StatisticsTest (biology)Test validityMathematics educationScripting languageInternal consistencyItem response theoryPsychometricsComputer scienceMathematics

Abstract

fetched live from OpenAlex

The current study sought to evaluate the SASTSc in two samples of students taking a statistics course that incorporates statistical software. The SASTSc was given at two time points, once at the beginning of the semester and then again at the end of the semester. Our evaluation included examining competing factor analytic models, examining convergent validity, test-retest reliability, and assessing internal consistency. Our results in both samples replicate the scale’s proposed factor structure; however, not all items were useful and we propose some changes to the wording of items to improve the scale. Data, analysis scripts, and results are publicly available at https://osf.io/rv64m/?view_only=6dfbf883f0d841b69c238773cee6e62e.

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.

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)0.013
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.402
GPT teacher head0.592
Teacher spread0.190 · 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