Jonathan Ruiz-Castro
Biographic Data
| ID | 10096831 |
|---|---|
| NAME | Jonathan Ruiz-Castro |
| GIVEN NAMES | Jonathan |
| FAMILY NAME | Ruiz-Castro |
| SIGNATURE | RUIZ-CASTRO J |
| AFFILIATIONS | Universidad Continental |
| ORCID | 0000-0003-1800-2533 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Predicting a few or many friends in schoolchildren
Machine learning algorithms were used to determine whether Peruvian 8–12-year-olds (N = 730) believe they have many or few friends based on sociodemographic and psychological variables. Theoretical variables were depression (PHQ-8), subjective well-being (SWB-3), sorrow, bullying, and birthplace. With stratified 10-fold cross-validation, the easyML R package examined six algorithms: Random Forest, XGBoost, Support Vector Machine, Neural Network, …
Cultural adaptation and psychometric validation of the academic progress goals scale for Peruvian university students
Introduction Academic goal progress is a key motivational construct linked to students' planning, self-regulation, and academic success, yet there is a dearth of culturally adapted, validated instruments for assessing this construct in Peruvian higher-education contexts. Grounded in Social Cognitive Career Theory, this study addresses this gap by adapting and validating the Academic Progress Goals Scale (AGPS) for Peruvian university students. Me…
No prominent works on this page.
Cultural adaptation and psychometric validation of the academic progress goals scale for Peruvian university students
Introduction Academic goal progress is a key motivational construct linked to students' planning, self-regulation, and academic success, yet there is a dearth of culturally adapted, validated instruments for assessing this construct in Peruvian higher-education contexts. Grounded in Social Cognitive Career Theory, this study addresses this gap by adapting and validating the Academic Progress Goals Scale (AGPS) for Peruvian university students. Me…
Predicting a few or many friends in schoolchildren
Machine learning algorithms were used to determine whether Peruvian 8–12-year-olds (N = 730) believe they have many or few friends based on sociodemographic and psychological variables. Theoretical variables were depression (PHQ-8), subjective well-being (SWB-3), sorrow, bullying, and birthplace. With stratified 10-fold cross-validation, the easyML R package examined six algorithms: Random Forest, XGBoost, Support Vector Machine, Neural Network, …
Artificial neural network (1 work) · Attachment and Relationship Dynamics (1 work) · Bullying, Victimization, and Aggression (1 work) · Child and Adolescent Psychosocial and Emotional Development (1 work) · Class (philosophy) (1 work) · Confirmatory factor analysis (1 work) · Construct validity (1 work) · Convergent validity (1 work) · Education, Achievement, and Giftedness (1 work) · Educational Outcomes and Influences (1 work)