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Perception towards Development of Employability Skills by Students: A Module Analysis

2017· article· en· W2779755639 on OpenAlexaboutno aff
Sivajothi Paramasivam, John Tan, Kanesan Muthusamy

Bibliographic record

VenueInternational Journal of Engineering and Technology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
FundersNorthumbria University
KeywordsEmployabilityPerceptionPsychologyMathematics educationComputer sciencePedagogyNeuroscience

Abstract

fetched live from OpenAlex

For some time, engineering education literature has suggested that the employability capability of engineering graduates does not meet the expectations of many local modern industries.The need to enhance their employability skills is critical because employability has been a challenging national concern and agenda.Thus, gauging student's satisfactory level is a central concern especially in ensuring engineering graduates are able to bridge between their acquired skills and the elementary demands of the labour market.The study entails a review of established research to understand the views and perceptions of engineering undergraduate students in harnessing their employability skills through Barrie's teaching content approach in the Engineering Product Development module.The study described in this paper used 55 responses from engineering students to a standardized student feedback questionnaire over 3 years, to gauge their overall satisfaction with the module as well as to explore perception associated with students' learning experiences, including a two-fold study on collaborative learning experience and satisfactory development of ten important attributes that are closely aligned towards adapting to work environment.The findings indicate that 67.3% of the students are satisfied with the module in terms of nurturing them with crucial employability skills desirable for the workforce.Besides, the result provides a significant impact of adoption of teaching content mode in the effort of enhancing the teaching and learning process towards producing graduates with broader employability skills.Keyword -engineering education,

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.011
GPT teacher head0.348
Teacher spread0.337 · 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
Published2017
Admission routes1
Has abstractyes

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