MétaCan
Menu
Back to cohort
Record W4220939936 · doi:10.1177/00332941221077026

The Mediating Effects of Psychological Capital and Academic Self-Efficacy on Learning Outcomes of College Freshmen

2022· article· en· W4220939936 on OpenAlexaff
Po-Lin Chen, Ching-Hui Lin, I-Hui Lin, C. Owen Lo

Bibliographic record

VenuePsychological Reports · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyStructural equation modelingSelf-efficacyBootstrapping (finance)Academic achievementExperiential learningSocial psychologyApplied psychologyMathematics educationDevelopmental psychology

Abstract

fetched live from OpenAlex

This study was an investigation of the relationship between past and present learning experiences of first-year college students and of how the psychological capital and academic self-efficacy they had accrued from past learning experiences were correlated with their current learning engagement. Longitudinal data were collected to examine how students' learning experiences in high school impacted their learning in college. Structural equation modeling (SEM) and bootstrapping techniques were employed in data analysis. Results indicated that psychological capital and academic self-efficacy functioned as mediators between students' past learning experience and present learning engagement. Overall, the findings highlight the importance of these two psychological constructs and suggest that postsecondary institutions should provide learning environments that support these factors to ensure student success.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.041
GPT teacher head0.449
Teacher spread0.408 · 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 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

Citations41
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePsychological ReportsSame topicHigher Education Research StudiesFrench-language works237,207