Conference Agenda

Recent literature has consolidated the study of academic performance as a key interdisciplinary field for understanding both learning and student well-being in higher education. In Latin America, approaches have evolved from cognitive models toward integrative perspectives that combine psychological, pedagogical, technological, and socioeconomic factors. Through a scoping review of twelve articles indexed in Scopus and Web of Science between 2015 and 2025, four predominant paradigms were identified: predictive, psychoeducational, socioeconomic-contextual, and collaborative pedagogical. The results reveal a growing trend toward the use of mixed methodologies, artificial intelligence models, and learning analytics, along with humanistic theories that prioritize motivation, self-regulation, and educational equity. It is concluded that academic performance is a multidimensional and dynamic phenomenon, whose study requires integrating empirical evidence with a broader understanding of the human and social context of university learning.

The present study analyzed the impact of training on quality management at SGS Pisco using a quantitative, basic, explanatory approach with a non-experimental design applied to a sample of 20 workers from the fuel handling area. The research problem focuses on compliance gaps with standards such as ISO 29001 and the need for a specialized workforce to mitigate risks in high-complexity operations. Linear regression results demonstrated that training explains 65.65% of quality management performance (R² = 0.6565). The development of technical competencies emerged as the most influential factor (72.50%), followed by content relevance (56.17%) and training frequency (41.55%). In conclusion, personnel training strengthens operational safety and process standardization, confirming that the enhancement of technical skills constitutes a critical support mechanism for reducing errors and ensuring efficient processes. Therefore, prioritizing specialized technical training programs is recommended to enhance institutional sustainability.

Resumen— In the textile sector, productive efficiency is a key factor for the competitiveness and sustainability of companies. In this context, the present study was carried out in a Peruvian textile company dedicated to garment manufacturing, where a low level of productive efficiency was identified, reaching 31.52%, compared to the sector’s average of 50.3%, which reveals a technical gap of 18.78%. This problem arises mainly from the lack of process standardization, the high variability of production times, and long changeover times between product references. To address this situation, an intelligent manufacturing model is proposed that integrates the tools Standard Work, TPM and SMED, complemented with IoT technologies within the framework of Industry 4.0, with the purpose of optimizing the efficiency of the garment manufacturing process. Based on the application of these methodologies, it is expected to achieve a reduction of more than 40% in non-productive times, a reduction of at least 35% in set-up times, and an increase in the overall efficiency of the process above 50%, reaching industry benchmarks. These results will help close the identified technical gap, improve productivity and process traceability, and contribute to the digital transformation of the Peruvian textile industry.

Scientific productivity during doctoral education in engineering has become a key indicator of academic quality and institutional positioning; however, its development faces limitations associated with individual, institutional, and technological factors. In this context, the objective of this study was to evaluate knowledge management as a methodology for strengthening scientific productivity among engineering doctoral students, considering human, structural, and relational capitals, as well as technological skills. The research adopted a mixed-methods approach, with a longitudinal, descriptive, correlational, and predictive design, covering the period from 2018 to 2024. The population consisted of 188 doctoral students, complemented by 773 valid survey records. The analysis included descriptive statistics, Spearman’s rho correlation, and machine learning models such as random forest, multilayer perceptron, and metaheuristic additive regression. The results reveal positive and statistically significant associations between knowledge management capitals and scientific productivity, with human capital and technological skills showing the strongest relationships. Moreover, non-linear predictive models demonstrated superior performance, suggesting that the relationship between knowledge management and scientific publication is complex and non-additive. It is concluded that knowledge management constitutes an operational and predictive methodology for strengthening doctoral scientific productivity in engineering education.

The classroom environment can contribute to the development of professional and personal competencies essential in a global and competitive context. The primary objective of this study was to analyze the relationship between the classroom environment and academic self-efficacy among engineering students. A quantitative approach, correlational scope, and cross-sectional non-experimental design were followed. A total of 156 university students participated anonymously and voluntarily, aged between 18 and 42 years old, including 97 males and 59 females. The results showed a positive and significant correlation between the classroom environment and academic self-efficacy (r = 0.511, p < 0.001, z = 0.565), as well as with the specific dimensions of self-efficacy. Male students scored higher in academic self-efficacy and input-related activities; furthermore, older students (31–42 years old) obtained higher scores in all cases. Systems engineering students scored higher in their perception of the classroom environment, and those studying in virtual mode obtained higher scores in all analyses except for the academic interaction activities dimension. Finally, a trend was observed for intermediate-semester students to present lower scores across all analyses compared to their peers in initial and final semesters. These findings allow for an analysis of the current context in university engineering education.

Abstract– Purpose: Professionalization of academic management in engineering faculties constitutes a strategic factor for educational quality; however, scientific evidence remains scattered with scarce Latin American representation. This research aimed to systematically analyze the literature on professionalization of academic management in engineering faculties, identifying roles, competencies, management models, and evidence of institutional impact. A systematic review was conducted following the PRISMA 2020 protocol, consulting Scopus, Web of Science, ERIC, and ScienceDirect databases, identifying 915 initial records. After applying inclusion and exclusion criteria, 60 studies were included in the qualitative synthesis. Results identify three predominant approaches: competency-based (n=24), professional development (n=19), and institutional-organizational (n=17). The best-documented impacts correspond to improvements in organizational climate (n=18) and accreditation processes (n=15). A persistent tension between academic legitimacy and managerial competencies is evidenced. Latin American representation reaches only 12% of studies. Findings support institutional decisions to strengthen university governance in engineering programs, contributing to SDG 4, SDG 9, and SDG 16.