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Record W7095907830

AND ANTECEDENT DEVELOPMENTS

2008· article· en· W7095907830 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAntecedent (behavioral psychology)Orientation (vector space)Work (physics)Period (music)
DOInot available

Abstract

fetched live from OpenAlex

marked its fiftieth year of operation. During the middle period of these years, beginning at about 1968, the Faculty became well known for Its innovative work in the use of computer assisted Instruction (CAl). This paper identifies the antecedents of this work as the research orientation of those who brought the Faculty into existence. This orientation provided the Impetus for the development of a research laboratory which grew to eventually encompass numerical computing as well as computer assisted instruction. Some of the factors contributing to the decline of computer assisted instruction at the University of Alberta are also identified. Résumé: 1992 marque le cinquantieme anniversaire de Ia faculté d'´Education de I ' Université d 'Alberta. Dés 1968. Ia Faculté étaif reconnue pour le travail innovateur qu'on y accomplissait dons le domaine de l'enseignement assisté par ordinateur (Computer Assisted instruction [CAl]). Le présent exposé retrace l'historique de 'orientation prise par ceux qui ont contribué mettre cette Faculté au monde. C 'est cette orientation qui a favorise' l'etabilssement du laboratoire de recherche qui s'est par Ia suite orlenté vers i'informatique numérique et vers l'enseignement assisté par ordinateur. Les facteurs qui ont contribué au declin de l'enseignement assisté par ordinateur å l'Unlversite ' de l'Aiberta sont aussi identifiés.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.447
Threshold uncertainty score0.157

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.196
Teacher spread0.174 · 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 designNot applicable
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".

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Citations0
Published2008
Admission routes1
Has abstractyes

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Same topicHistory of Computing TechnologiesFrench-language works237,207