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Record W4410977293 · doi:10.53103/cjess.v5i3.342

Integration of Trades-Based STEM Education in Canadian K-12 Schools

2025· article· en· W4410977293 on OpenAlexaffabout

Bibliographic record

VenueCanadian Journal of Educational and Social Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsLethbridge College
FundersStrong
KeywordsMathematics educationPsychology

Abstract

fetched live from OpenAlex

Demand for skilled trades occupations in Alberta has steadily increased, coinciding with a decade-high youth unemployment rate. Addressing this challenge, this study evaluates the effectiveness of trades-based STEM kits in enhancing Canadian K-12 students’ retention of STEM knowledge and fostering interest in skilled trades careers. By addressing a gap in practical, hands-on learning opportunities, the research explores whether participation in STEM kit activities improves students' understanding of STEM concepts and influences their career aspirations. Surveys were administered to students from kindergarten to grade six, in two formats: Group or Individual. Results indicating significant STEM concept retention and a majority of students expressing enjoyment and willingness to engage in similar activities in the future. The initiative was also found to be statistically significant in affecting career aspirations. Thematic analysis of feedback highlighted the benefits of interactive, practical learning while also identifying logistical challenges. These findings suggest that trades-based STEM kits are a valuable educational tool that not only support STEM learning outcomes but also encourage youth to consider careers in the skilled trades.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.052
GPT teacher head0.380
Teacher spread0.328 · 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 designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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