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Record W2738149500 · doi:10.5539/hes.v7n3p55

Enhancing Students’ Confidence in Employability Skills through the Practice of “Recall, Adapt and Apply”

2017· article· en· W2738149500 on OpenAlexvenueno aff
Alison J. Sinclair

Bibliographic record

VenueHigher Education Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityAdaptation (eye)RecallSet (abstract data type)Computer scienceMathematics educationPsychologyPedagogyCognitive psychology

Abstract

fetched live from OpenAlex

The ability to apply prior knowledge to new challenges is a skill that is highly valued by employers, but the confidence to achieve this does not come naturally to all students. An essential step to becoming an independent researcher requires a transition between simply following a fail-safe set of instructions to being able to adapt a known approach to solve a new problem. Practical laboratory classes provide an ideal environment for active learning, as the primary learning objective of these teaching sessions is to gain skills. However, laboratory handbooks can be presented as a series of fail-safe recipes. This aids the smooth running of practical classes but misses the opportunity to promote engagement with the underlying theory and so develop confidence in recalling approaches and adapting them to a new problem. To aid the development of employability skills, a practical laboratory series was developed for Bioscience teaching that requires on-the-spot decision-making, the recall of skills and their adaptation to new challenges. After using this approach, the proportion of student’s expressing a high level of confidence with each of eight key employability skills rose by between 9 and 35% following the practical sessions, showing that the approach of recalling, adapting then applying prior knowledge and skills can increase the confidence that students have in their employability related skills. The approach was developed for use within biological sciences practical laboratories but the principles can be adapted to any discipline involving project work.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.068
GPT teacher head0.472
Teacher spread0.404 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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