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Record W3177452992 · doi:10.24908/pceea.vi0.14917

TRANSFORMATION OF EMPLOYABILITY SKILLS THROUGH CO-OP EXPERIENCES

2021· article· en· W3177452992 on OpenAlexafffundvenue
Haaniyah Ali, Jeffrey Harris

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsYork University
FundersYork University
KeywordsEmployabilityTransformative learningPsychologyReflection (computer programming)PedagogyMathematics educationConceptual frameworkSociologyComputer science

Abstract

fetched live from OpenAlex

The structure of co-operative programs gives students the opportunity to transform employability skills. Using a proposed conceptual framework and inspirationfrom Mezirow’s Transformative Learning Theory, this paper analyzes four engineering students in varying disciplines across the three contexts that a co-op experience provides: pre co-op school setting, co-op work placement and the post co-op school setting. Using reflection and by adapting to their settings, these students transformed their communication, organization/ time management and initiative/ responsibility skills. Analyzing these skills and experiences against the framework, we can see how the details and specifics of the transformation varies for each student; however, each student needs to experience each stage for successful transformation. Each of the stages then feeds into and helps further the skills as it changes.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.264
Teacher spread0.257 · 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 designQualitative
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
Published2021
Admission routes3
Has abstractyes

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