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Record W2793793943 · doi:10.5539/jel.v7n3p125

The Effect of Self-Directedness in Learing on Employment Readiness of Undergraduates in South Korea

2018· article· en· W2793793943 on OpenAlexvenueno aff
Hee Yeong Kim, Gi Un Kim

Bibliographic record

VenueJournal of Education and Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySet (abstract data type)Graduate studentsTask (project management)Social psychologyGoal orientationMathematics educationPedagogyManagement

Abstract

fetched live from OpenAlex

The purpose of this study is to analyze whether self-directedness in learning has positive effects on employment readiness of undergraduates. The subject of this study has little precedent research and we generated a research model. This study shows the following results: First, intrinsic motivation factor of self-directedness in learning has a positive effect on employment readiness directly. Task-solving abilities in self-directedness in learning indirectly have positive effects on employment readiness through the mediating effect of intrinsic motivation. Second, the higher the achievment orientation undergraduates have, the more negatively affected the employment readiness of undergraduates is. It means that higher achievement orientation may encourage them to explore new career paths such as graduate school or youth startup not normal employment of companies. Third, this study has the following significance: We set up and proved the relationship between subordinate variables in self-directedness in learning of undergraduates and subordinate varibles in employment readiness. We proved that the intrinsic motivation of self-directedness in learning is the most important factor to have a positive effect on the employment readiness of undergraduates.

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)0.003
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 score0.064
Threshold uncertainty score0.138

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0000.000
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 head0.017
GPT teacher head0.348
Teacher spread0.330 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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