MétaCan
Menu
Back to cohort
Record W3133329885 · doi:10.5430/ijhe.v10n3p259

Social Skills of Students from Educational Sciences: Validity, Reliability, and Percentiles for Evaluation

2021· article· en· W3133329885 on OpenAlexvenueno aff
Emilio Rodriguez-Macaya, Rubén Vidal-Espinoza, Rossana Gómez‐Campos, Marco Cossio‐Bolaños

Bibliographic record

VenueInternational Journal of Higher Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Skills and Education
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaChecklistReliability (semiconductor)PsychologyPercentileTest (biology)Medical educationMathematics educationClinical psychologyMathematicsMedicineStatisticsPsychometrics

Abstract

fetched live from OpenAlex

The development of social skills (SS) at various stages of life provides the basis for social and academic success throughout life. This cross-sectional study validates and verifies the reliability of the SS checklist proposed by Goldstein et al 1983. The checklist was administered, which is composed of 6 dimensions and 50 SS questions. 671 students between 18 and 25 years of age, belonging to eight professional programs in the area of Educational Sciences, participated. The results showed that five factors explained 41.4% of the variance of the instrument. The Kaiser-Meyer-Olkin KMO measure of 0.906 and Bartlett's test of sphericity were highly significant (X2= 11020.251, gl= 1225). The factor loadings of the 6 dimensions and the 50 questions ranged between 0.42 and 0.72. The reliability achieved by Cronbach's alpha was r=0.92. The proposal of percentiles will allow classifying low, moderate and high levels of SS, providing information that can be used not only by students, but also for professionals working in higher education. Consequently, it highlights the importance of developing SS not only at home, but also at school and university, since they need to be stimulated at every stage of life to achieve the proposed objectives.

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)0.001
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 score0.070
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0010.000

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 head0.063
GPT teacher head0.487
Teacher spread0.425 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Higher EducationSame topicSocial Skills and EducationFrench-language works237,207