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Record W3132217111 · doi:10.1080/14703297.2021.1886970

Social context and transferable skill development in experiential learning

2021· article· en· W3132217111 on OpenAlexaffabout
Rebecca Collins‐Nelsen, Frank Koziarz, Beth Levinson, Erin Elizabeth Allard, Stephanie Verkoeyen, Sandeep Raha

Bibliographic record

VenueInnovations in Education and Teaching International · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsExperiential learningPsychologyContext (archaeology)Experiential educationTransfer of trainingMathematics educationContext effectPedagogyCognitive psychology

Abstract

fetched live from OpenAlex

Increasingly, employers are seeking candidates with transferable skills in addition to technical and educational requirements. Thus, university students seek opportunities to develop transferrable skills, often through extra and co-curricular programs. With this in mind, our research explores student assessments of their own development of transferable skills after participation in a co-curricular, experiential volunteer program (McMaster Children and Youth University) in Canada. Using pre/post-survey methods, we find statistically significant increases in participants' self-assessments of leadership, problem solving, knowledge translation, and knowledge mobilization. Adaptability emerges as an unexpected skill several participants report developing as a result of working with young people. We conclude that co-curricular programs play an important role in transferable skill development. Further, we argue that social contexts of experiential learning opportunities play a significant role in shaping transferrable skill development.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.394
Teacher spread0.364 · 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 designNot applicable
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

Citations17
Published2021
Admission routes2
Has abstractyes

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