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A Transformative Investigation of an Inclusive and Positive IEP Framework

2024· article· en· W4404251702 on OpenAlexaff
Shendah M. Benoit

Bibliographic record

VenueInternational Journal for Cross-Disciplinary Subjects in Education · 2024
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsTransformative learningPsychologyPedagogySociologyMathematics education

Abstract

fetched live from OpenAlex

In British Columbia, inspired and guided by Shelley Moore and her inclusionary and consultative efforts, a working group of school districts piloted a competencybased Individual Education Plan (IEP).This new IEP is to support the inclusion of students into a positive learning experience.Five years after this implementation phase and the acceptance of this IEP within the BC provincial system, a mixed-method study can investigate what changes are noticed when a competency-based IEP is implemented, who notices these changes, and do these changes extend beyond the IEP design phase.The transformative approach will best investigate these phenomena as the IEP is to support students from kindergarten to grade twelve who require additional support through special targeted funding.Student's voice is central to the competencybased IEP and can be central to this investigation.Care, therefore, for the student participants and centralizing their voice is essential within the study.Awareness on the part of the researcher will be critical to creating the space for student voice.The transformative approach can investigate whether a competency-based IEP promotes a more inclusive learning environment and/or a more positive learning experience.Findings indicating a more inclusive and positive learning experience deserve comprehensive knowledge mobilization so that more students within the kindergarten to grade twelve sectors may flourish.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.009
GPT teacher head0.340
Teacher spread0.331 · 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 designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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