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Record W4281253478 · doi:10.5430/jct.v11n4p184

Development of Core Competencies for University Students during the Pandemic, Crisis of Public Health

2022· article· en· W4281253478 on OpenAlexvenueno aff
Ju-Kyoung Kim

Bibliographic record

VenueJournal of Curriculum and Teaching · 2022
Typearticle
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCore competencyCreativityScale (ratio)Medical educationGlobalizationPsychologyCore KnowledgeMedicineKnowledge managementManagementComputer sciencePolitical scienceSocial psychologyGeography

Abstract

fetched live from OpenAlex

Future competency is a necessary condition for securing the competency of college students who lead the changed era. Therefore, this study was conducted to derive core competencies reflecting future competencies and to develop diagnostic tools. To this end, the reliability and validity of the draft questionnaire prepared after reviewing previous studies and receiving reviews from experts were secured. The survey was conducted for 983 college students from April 12 to 16, 2021, and the final 75 questionnaires were confirmed through statistical verification. Through the collected data, potential profiles with heterogeneous characteristics based on core competencies were classified into three, and the characteristics of each potential group profile were confirmed. The main analysis results are as follows. First, the five core competencies (humanities competency, communication competency, globalization competency, creativity competency, professionalism competency) consists of 15 sub-competencies and 75 questionnaires. Second, the improved K-University core competency scale has secured validity after verifying the improvement plan through the expert meetings and surveys. Third, based on the improved K-University Core Competency Diagnosis scale, the overall average of core competencies was 3.85, communication competencies 3.99, creativity competency 3.96, humanities competencies 3.85, professionalism competencies 3.85, and globalization competencies 3.58. Furthermore, a total of three analyzing the latent profile through the core competency diagnosis result, a total of three latent profiles (upper group, middle group, and lower group) were identified. Through the analysis results, a new core competency diagnostic scale was developed by reflecting the educational goals, vision, and future capabilities of the university. Through the results of this study, other higher education institutions will also be able to raise their interest in the future competencies of university students and provide competency-based curriculum to enhance the quality and effectiveness of 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.360
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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