MétaCan
Menu
Back to cohort
Record W7100045786

Improvement; Teacher Qualifications IDENTIFIERS *QUALM Teacher Education Program; *University of

2016· article· en· W7100045786 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval and Classical Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsPracticumTeacher educationCompetence (human resources)Conceptual frameworkIdentifierFocus groupSchema (genetic algorithms)Program evaluation
DOInot available

Abstract

fetched live from OpenAlex

This paper describes an ongoing comprehensive model of program evaluation which has as its major goal the improvement of teacher education. This project, developed at the University of Lethbridge (Alberta, Canada), is presented in four parts: (1) the process--how and why the project developed or is developing as it Is; (2) the conceptual framework--the model within which the evaluation occurs; (3) implementation--specific eviluation projects within the conceptual framework; and (4) the administrative framework for facilitating utilisation of the evaluation results. The evaluation model provides a focus for research discussions, a framework for designing collaborative projects, a basis for collecting and sharing common data, and an opportunity for sharing research findings. Flexible enough to accommodate any teacher education program, it promotes longitudinal research; allows for individual, group and collaborative research; and can be fitted into an administrative schema for decision-making. Five evaluation projects utilising the framework are briefly described: (1) selection and development of teacher education candidates; (2) teachers ' perceptions of their educational programs; (3) the evaluation of the preservice competence of Alberta teachers; (4) becoming a teaC.,er; and (5) alternative practicum experiences for education students. (PM)

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score0.984

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)0.0170.000

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 head0.039
GPT teacher head0.262
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicMedieval and Classical PhilosophyFrench-language works237,207