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Record W2996801413 · doi:10.31436/ijohs.v1i2.74

Preliminary Study: Validation of Measure for Psychology Students Employability Skills

2019· article· en· W2996801413 on OpenAlexaboutno aff
Fadillah Suwarno, Amy Mardhatillah

Bibliographic record

VenueIIUM JOURNAL OF HUMAN SCIENCES · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsEmployabilityMeasure (data warehouse)PsychologyApplied psychologyMathematics educationPedagogyComputer scienceData mining

Abstract

fetched live from OpenAlex

The purpose of this study is to validate the measurement of Psychology students Employability Skills. This research used quantitative method by conducting two studies, exploratory and confirmatory studies. The sample used in this study was 206 Psychology students. The references in developing this measurement are SCANS (1992), The Conference Board of Canada (1992), Cotton (1993), Robinson (2000), Rosenberg (2012), Hamid (2014) which produced 87 questionnaire items with six aspects. The result of the Exploratory Factor Analysis (EFA) showed 27 items that are grouped together into five factors namely thinking skills, basic academic, interpersonal skills, technology skills, and personal qualities. The Confirmatory Factor Analysis (CFA) yields 16 items (CR = 0.81) with three factors namely Basic Academic (CR = 0.74), Thinking Skills (CR = 0.70), Sociability (CR = 0.64). The model of measurement is fit for the first-order (Chi-Square = 105.95, df = 93, p-value = 0.12, RMSEA = 0.029) and for second-order (Chi-Square = 101.21, df = 83, p-value = 0.066, RMSEA = 0.034). This measurement is able to provide an evaluation for Psychology students employability skills. Implication of this evaluation can be used to design intervention in enhancing employability skills among Psychology students.

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)0.010
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 score0.016
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.076
GPT teacher head0.480
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

Citations0
Published2019
Admission routes1
Has abstractyes

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