MétaCan
Menu
Back to cohort

The Attribute Hierarchy Method for Cognitive Assessment: A Variation on Tatsuoka's Rule‐Space Approach

2004· article· en· W2108611097 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

VenueJournal of Educational Measurement · 2004
Typearticle
Languageen
FieldComputer Science
TopicCognitive Science and Mapping
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCognitionSpace (punctuation)HierarchyTask (project management)PsychologySyllogismDomain (mathematical analysis)Variation (astronomy)Cognitive psychologyComputer scienceArtificial intelligenceMathematicsEpistemology

Abstract

fetched live from OpenAlex

A cognitive item response theory model called the attribute hierarchy method (AHM) is introduced and illustrated. This method represents a variation of Tatsuoka's rule‐space approach. The AHM is designed explicitly to link cognitive theory and psychometric practice to facilitate the development and analyses of educational and psychological tests. The following are described: cognitive properties of the AHM; psychometric properties of the AHM, as well as a demonstration of how the AHM differs from Tatsuoka's rule‐space approach; and application of the AHM to the domain of syllogistic reasoning to illustrate how this approach can be used to evaluate the cognitive competencies required in a higher‐level thinking task. Future directions for research are also outlined.

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)0.005
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.654
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.071
GPT teacher head0.360
Teacher spread0.289 · 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