Abanto Ramirez, Carlos Daniel

Preferred name

Main Affiliation

carlosabanto@upeu.edu.pe

ORCID

0000-0002-6471-696X

Scopus Author ID

58979494900

Mostrando 1 - 10 de 15

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HIV & Hepatitis in the Americas 28–30 April 2016, Mexico City, Mexico
(2016-04-28)
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Kenneth Mayer
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Omar Sued
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Néstor Sosa
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Ricardo Sobhie Diaz
and creative negotiations. Eradication is possible. It is up to us to make it so.
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Relationship between academic procrastination and internet addiction in Peruvian university students: the mediating role of academic self-efficacy
(2025-01-23)
Dana Rocio Chavez-Yacolca
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Ruth Beatriz Castro-Champión
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Nely Marlene Cisneros-Gonzales
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Introduction This study evaluated the mediating role of academic self-efficacy in the relationship between internet addiction and academic procrastination among Peruvian university students. Method A cross-sectional explanatory design was employed with a convenience sample of 334 participants. Instruments used included the Specific Perceived Self-Efficacy Scale of Academic Situations (EAPESA), the Lima Internet Addiction Scale (EAIL), and the Academic Procrastination Scale (APS). The reliability and internal structure of each scale were verified, and the EAIL was validated. Descriptive analysis and correlation between variables were conducted, followed by path and mediation analyses. Results Internet addiction significantly negatively affected academic self-efficacy ( β = −0.381, t = −4.52, p &lt; 0.001). Academic self-efficacy negatively impacted academic procrastination ( β = −0.522, t = −7.04, p &lt; 0.001). Internet addiction positively affected academic procrastination ( β = 0.642, t = 5.72, p &lt; 0.001). The total effect of internet addiction on academic procrastination and academic self-efficacy was significant ( β = 0.841, t = 7.17, p &lt; 0.001). Academic self-efficacy partially mediates the relationship between internet addiction and academic procrastination, suggesting universities should implement strategies to enhance academic self-efficacy in students.
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Academic Co-Creation and Attitudes Towards Research as Predictors of Environmental Action in Peruvian Environmental Engineering Students
(2026-04-21)
Liz Katerin Echevarría Rodríguez
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Lesly Noemí Santisteban Salvador
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This study aims to ascertain whether academic co-creation and attitudes towards research serve as predictors of environmental action among a sample of Peruvian environmental engineering students. The study sample comprised 460 environmental engineering students enrolled in Peruvian universities. For the analysis, the Environmental Action Scale, the Attitudes Towards Research Scale, and the Academic Co-Creation Scale were utilized. Additionally, the data collected were analyzed using correlation coefficients and multiple linear regression models. The findings reveal positive and significant correlations between academic co-creation, attitudes towards research, and environmental action within the studied sample. Linear regression analyses indicated a satisfactory model fit (test F = 70.1, p < 0.001), with attitudes towards research (β = 0.431, p < 0.001) and academic co-creation (β = 0.108, p < 0.05) emerging as significant predictors of environmental action in the participating students (adjusted R2 = 0.231). Consequently, the results suggest that, in this group of Peruvian environmental engineering students, attitudes towards research and academic co-creation are relevant predictors of environmental action. These results may inform directors and educators working with similar student populations in the promotion of pedagogical strategies and institutional policies that integrate academic co-creation as a transversal axis in the training process, while also fostering positive attitudes towards research, without implying generalization to other academic disciplines or broader populations.
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Disposition to critical thinking, anxiety due to COVID-19 and academic self-efficacy in university students
(2024-03-27)
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Abel Apaza
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Introduction The present study aims to determine whether anxiety due to COVID-19 (AC) and disposition to critical thinking (DCT) predict academic self-efficacy (AS). Method The study is non-experimental, predictive, and cross-sectional. The sample was made up of 218 university students from northern Peru. The instruments used were the CAS, CTDS, and the EAPESA. Results The results showed that the AS was negatively and positively related to AC and DCT, respectively. AS in university students was significantly predicted by DCT ( p &lt; 0.01), while AC was not a significant predictor ( p &gt; 0.05). Conclusion DCT is a significant predictor of AS, while AC ins not. Strategies must be sought to improve and support this important aspect in each student to improve their disposition to critical thinking and academic self-efficacy. It is recommended for future studies to continue investigating variables associated with academic factors, such as those in this study, that lead to taking action for the effective development of university students.
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Scale of Teachers' Coping Strategies Towards the Evaluation of Performance
(2024-01-01)
Jocabeth Nohemi Chambilla-Apaza
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Ailyn Yicela Merchan-Fuentes
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A hybrid AI approach for predicting academic performance in RBE students
(2025-10-21)
Willy Gonzales
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Zindel Cordero
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Edgar Tito Susanibar Ramírez
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Hasnain Iftikhar
Machine learning has advanced significantly in recent years and is being used in higher education to perform various types of data analysis. While the literature demonstrates the application of machine learning algorithms to predict performance in university education, no such applications are found in EBR, let alone in private institutions of a denominational nature, which presents an opportunity to study prediction in these institutions. To address this gap, this research aims to propose a predictive approach as a decision-support tool for regular basic education, using machine learning techniques. Among the techniques utilized, three machine learning models (Logistic Regression, Support Vector Machine, and Random Forest), along with deep learning models (AlexNet, Gated Recurrent Unit, and Bidirectional Gated Recurrent Unit), were analyzed, as well as ensemble models. Nonetheless, the Ensemble model, which combines deep learning and machine learning techniques, is preferred due to its superior accuracy, precision, and sensitivity performance metrics.
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Factors influencing student retention university students: an analysis of institutional reputation, social responsibility and loyalty
(2025-03-19)
Roger Hiroshi Albornoz-Toyohama
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Ruth Mendigure-Hachircana
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Sady Haro-Casildo
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Introduction This study investigates the impact of institutional reputation (IR), social responsibility (SR) and student loyalty (LY) on student retention (RT) in university students. Methods Using a quantitative, non-experimental, cross-sectional design, 409 students of private universities, both domestic and foreign, were surveyed. Results Analysis using Partial Least Square Structural Equation Modeling (PLS-SEM) revealed that SR positively influences LY ( β = 0.218, p &lt; 0.001) and RT ( β = 0.123, p = 0.006). LY showed a strong impact on RT ( β = 0.765, p &lt; 0.001), whereas IR significantly influenced LY ( β = 0.556, p &lt; 0.001). Contrary to expectations, no direct relationship was found between institutional reputation and retention. In addition, it was shown that SR had a positive effect on IR ( β = 0.531, p &lt; 0.001). Conclusion Based on the results obtained, it is concluded that SR positively predicts LY, RT and IR, Ly positively predicts RT and IR LY, with significant implications for university management and research at this educational level.
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Relationship Between Procrastination and Perceived Academic Achievement: The Mediating Role of Internet Addiction
(2026-01-10)
Maria Edita Huanambal-Pérez
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Elias Javier Calixtro-Ruiz
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Academic achievement serves as a crucial indicator of quality within higher education. In this context, internet addiction and procrastination emerge as significant factors influencing student performance. However, existing literature has predominantly focused on objective and comparative metrics, such as grades, thereby limiting the exploration of the subjective dimension from the student’s perspective. This research aims to investigate the mediating role of internet addiction (IA) in the relationship between academic procrastination (AP) and self-perceived academic achievement (AA) among Peruvian university students. Employing an explanatory and cross-sectional design, data were collected from 525 university students aged 18 to 40 years, utilizing validated instruments such as the Internet Addiction Questionnaire, the University Academic Performance Scale, and the Academic Procrastination Scale. The findings revealed a negative influence of AP on AA (b = −0.385, p < 0.001, 95% CI [−1.457, −0.991]), a positive influence of AP on IA (b = 0.205, p < 0.001, 95% CI [0.341, 0.886]), and a positive influence of IA on AA (b = 0.326, p < 0.001, 95% CI [0.239, 0.441]). IA partially and competitively mediates 12.5% of the relationship between AP and AA.
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Development and Psychometric Properties of a Scale of Teachers’ Coping Strategies Towards the Evaluation of Performance in Public Schools
(2024-12-02)
Jocabeth Nohemi Chambilla-Apaza
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Ailyn Yicela Merchan-Fuentes
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Teaching evaluation performance is an important policy adopted by the governing body of education in Peru to promote the growth of educational quality, professional development, and continuous training of teachers, as well as to ensure educational quality standards, especially in Peruvian elementary education. Therefore, this research aims to develop and evaluate the psychometric properties of a scale that measures the coping strategies adopted by elementary education teachers when evaluating their performance. A study was conducted with 317 teachers between 20 and 70 years old (M = 43.6, SD = 11.8) in public education, from preschool (10.4%) to secondary (24.9%) educational levels, including special and alternative education, and with employment status of contracted (46.1%) and appointed (53.9%). An exploratory factor analysis was performed, from which four factors emerged. These factors were then corroborated by confirmatory factor analysis (χ2 = 162, df = 13, CFI = 0.968, TLI = 0.961, RMSEA = 0.061, and SRMR = 0.056) and were named as follows: maladaptive coping, adaptive individual coping, religious coping, and instrumental support coping. Internal reliability was high for the full scale and dimensions (α and ω > 0.8), indicating that it was free of random error, yielding the same results across multiple applications for the same sample. It is concluded that the scale of teachers’ coping strategies towards the evaluation of performance (STCEP) is a valid and reliable instrument to measure coping strategies adopted by elementary education teachers in response to performance evaluation.
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Factors influencing student retention university students: an analysis of institutional reputation, social responsibility and loyalty
(2026-04-28)
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Roger Hiroshi Albornoz-Toyohama
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Ruth Mendigure-Hachircana
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Sady Haro-Casildo
This dataset supports the article “Factors Influencing University Student Retention: An Analysis of Institutional Reputation, Social Responsibility, and Loyalty” and contains the empirical data used to examine determinants of student retention in higher education institutions. The data were collected through a quantitative research design using a structured questionnaire administered to university students. The dataset includes variables measuring institutional reputation, university social responsibility, student loyalty, and intention to remain enrolled, along with selected sociodemographic characteristics employed as control variables. Measurement items were adapted from previously validated scales in the academic literature to ensure reliability and construct validity. All responses were collected anonymously, and no personally identifiable information is included, in accordance with ethical research standards and data protection principles. The dataset has been cleaned and organized to facilitate replication, secondary analysis, and reuse. This resource is intended for researchers, educators, and policymakers interested in higher education management, student experience, retention strategies, educational marketing, and institutional social responsibility. It may be used for comparative studies across institutions or countries, methodological validation, or as a reference dataset for teaching quantitative analysis techniques. Users of this dataset are encouraged to cite the associated article when using the data for academic or professional purposes.

Abanto Ramirez, Carlos Daniel

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