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Record W7134477412

Multiple intelligence and the Five Minds in home economics curriculum

2018· other· en· W7134477412 on OpenAlexaff
Katherine Budgell

Bibliographic record

VenuecIRcle (University of British Columbia) · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCurriculumMandateTheory of multiple intelligencesCurriculum mappingCurriculum theoryEmergent curriculum
DOInot available

Abstract

fetched live from OpenAlex

This project is inspired by my pedagogic goal of meeting the learning needs of my students on an individual level. This project connects Gardner's Theory of Multiple Intelligences (MI) and the Five Minds for the future (the Five Minds) with BC's New Home Economics (HE) curriculum, with the goal of formulating a teacher handbook to assist teachers in customizing the curriculum to individual students’ learning preference, needs and intelligences. This project includes analysis of curriculum documents and literature, as well as the creation of a handbook. The design of the handbook allows it to be taken from this project and distributed to HE teachers interested in facilitating MI and the Five Minds in their curriculum delivery and classroom community. This project begins with a literature review to synthesize the literature on MI and Five Minds, then uses the information gained to pair with the new curriculum competencies and content of the new Home Economic curriculum in British Columbia in order to help meet the Ministry of Education’s mandate of personalized learning.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.172
Teacher spread0.165 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

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