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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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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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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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.
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Psychometric properties of the strategy inventory for language learning in Peruvian university students
(2025-05-13)
Nataly Susan Saez-Zevallos
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Danitza Elfi Montalvo-Apolín
Background In contemporary academia, proficiency in a second language, particularly English, is of significant importance for university students. The objective of this research is to determine the validity and reliability properties of the Strategy Inventory for Language Learning (SILL) among Peruvian university students. Methods Six hundred ten Peruvian university students, aged between 18 and 50 years ( M = 22.8; SD = 5.90), participated in the study. Statistical techniques for latent variables were employed, and recommendations for determining the psychometric properties of educational and psychological tests were followed. Results The results show that the SILL exhibits an internal structure organized into six first-order factors and one second-order factor, consistent with the theoretical proposal. This structure was confirmed through CFA with excellent goodness-of-fit indices (χ 2 = 222.254, df = 129, p = 0.000, RMSEA = 0.034, SRMR = 0.037, CFI = 0.971, TLI = 0.966). The inventory also demonstrates adequate internal consistency for its six factors, as well as for the complete inventory ( α / ω /H &gt; 0.7), and is invariant according with gender (male and female), geographical location (coast, mountains and jungle) age (late adolescence and early adulthood), and English educational level (A and B). Concussion It’s concluded that the SILL is a measurement instrument that demonstrates validity, factorial invariance, and high reliability in its scores. Consequently, it can be utilized in future academic research.
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Academic engagement and academic self-efficacy as predictors of academic procrastination in Peruvian adolescents
(2025-05-05)
Tito Cutipa-Flores
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Lizvell Fabian-Osorio
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Marco Antonio Navarro-Cárdenas
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Introduction Academic procrastination is a maladaptive learning behavior that can impair student performance. The research aims to determine whether academic engagement and self-efficacy predict academic procrastination in Peruvian adolescents. Method This is a cross-sectional predictive design, with a sample of 450 high school students of all grades, selected by convenience. The students were mostly female (60.9%), were in the first year of high school (28.9%) and were from private institutions (85.1%). The averages, variability and distribution of the data obtained were calculated. A correlation analysis was performed between the variables, as well as a multiple correlation analysis and, finally, a multiple linear regression analysis. Results The results showed that self-efficacy was inversely related to academic procrastination ( r = −0.250; p &lt; 0.001) and this, in turn, to commitment ( r = −0.263; p &lt; 0.005). Self-efficacy was directly related to engagement ( r = 0.112; p &lt; 0.005). Self-efficacy ( β = −0.223; p &lt; 0.001) and engagement ( β = −0.238; p &lt; 0.001) inversely influenced procrastination, explaining 11.8% of its variability ( R = 0.344, R 2 = 0.118, F = 30.0, p &lt; 0.001). Discussion The results showed the importance of academic engagement and self-efficacy in mitigating the propensity for academic procrastination among Peruvian adolescents. Consequently, educational institutions and schools should prioritize the implementation of teaching methodologies and interventions that improve students’ motivation and engagement, as well as foster confidence in their abilities to achieve academic success, in order to counteract the detrimental effects of procrastination on their academic development.
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Relationship between English self-efficacy and language learning strategies among Peruvian university students: the mediating role of academic self-efficacy
(2025-10-15)
Nataly Susan Saez-Zevallos
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Danitza Elfi Montalvo-Apolín
Introduction This study investigates the mediating role of academic self-efficacy in the relationship between English self-efficacy and language learning strategies among Peruvian university students. Method An explanatory cross-sectional design was employed, utilizing a convenience sample of 610 participants. The instruments used included the Strategy Inventory for Language Learning (SILL), the English Self-Efficacy Scale (EAI), and the Perceived Academic Situational Self-Efficacy Scale (EAPESA). The reliability and internal structure of each scale were verified, and the SILL was validated. Descriptive and correlation analyses between variables were conducted, followed by path and mediation analyses. Results The proposed model showed adequate fit indices (χ 2 = 178, df = 33, p &lt; 0.001, CFI = 0.964, TLI = 0.951, RMSEA = 0.085 [CI 90%: 0.073; 0.097]). The indirect effect of English self-efficacy on language learning strategies through academic self-efficacy was significant (β = 0.202, p &lt; 0.001, 95% CI [0.144, 0.261]), indicating that 31.61% of the total effect (direct plus indirect) of English self-efficacy on language learning strategies is explained by this indirect effect. Conclusion The results highlight the importance of academic self-efficacy as a mechanism through which English self-efficacy enhances the use of language learning strategies.
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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.

Abanto Ramirez, Carlos Daniel

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