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Record W2337232082 · doi:10.14288/1.0054614

Analysis of item characteristics of the Slosson Intelligence Test for British Columbia school children

2010· article· en· W2337232082 on OpenAlexaboutno aff
Barbara Kathleen Gard

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)Psychology

Abstract

fetched live from OpenAlex

This study investigated item characteristics which may affect the validity of the Slosson Intelligence Test (SIT) when used with school children in British Columbia. The SIT was developed as a quick, easily administered individual measure of intelligence to correlate highly with the Stanford-Binet Intelligence Scale as an anchor test. Use of the SIT has become widespread, but little technical information is available to support this. To examine the internal psychometric properties of the SIT for British Columbia schoolchildren, SIT responses were collected from 319 children (163 males, 156 females) in three age groups (7 1/2, 9 1/2, and 11 1/2 years). These data were subjected to a variety of item analysis procedures. Indices were produced for: item difficulty, item discrimination (item-total test score correlations), rank correlation between empirically determined item difficulties and item order given in the test, test homgeneity, and item-pair homogeneity. Results of the item analyses suggest that the SIT does not function appropriately when used with British Columbia school children. Two-thirds of the item difficulty indices were found to be outside the desired range: one-third of the items did not discriminate effectively; and many items are not in correct order of difficulty in administration of the SIT. The thesis discusses effects of these findings on the test's internal consistency, criterion validity, and technical utilization. Factors which may underlie the shift in item difficulties are also discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.218
Teacher spread0.207 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicTeacher Professional Development and MotivationFrench-language works237,207