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Preparing new teachers for inclusive schools and classrooms

2006· article· en· W2148066245 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

VenueSupport for Learning · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsQueen's University
Fundersnot available
KeywordsMainstreamInclusion (mineral)LegislationSpecial educational needsPedagogyMainstreamingWork (physics)Teacher preparationPsychologyPolitical scienceMedical educationPerceptionSpecial educationMathematics educationTeacher educationPublic relationsMedicineEngineeringSocial psychology

Abstract

fetched live from OpenAlex

The policy of including pupils with special educational needs (SEN) in mainstream schools and classes is now firmly established in many jurisdictions worldwide. Successful implementation of such policy depends largely on teachers having the knowledge, skills and competencies necessary to make it work. This poses a considerable challenge for both teachers and those responsible for Initial Teacher Education (ITE). This article presents the results of a study investigating current Northern Ireland practitioners' perceptions of their initial ITE relative to SEN. The major question under investigation was whether they felt that their ITE prepared them to be effective teachers in inclusive settings. Findings confirm research in other jurisdictions that teachers feel unprepared for inclusion. Emerging from this are the participants' recommendations for the content and delivery of SEN courses in ITE. Their recommended model of SEN delivery is a combination of ‘permeation’ plus a ‘stand alone’ course with the focus on student characteristics, behaviour management, assessment and evaluation, and SEN legislation.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.013
GPT teacher head0.328
Teacher spread0.316 · 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