Conference Agenda

This review examines the impact of Artificial Intelligence and Natural Language Processing on the academic performance of undergraduate engineering students. Data were collected from Scopus and Web of Science, analyzed following PRISMA guidelines, and processed using the Bibliometrix package. The review encompasses 100 peer-reviewed articles published between 2000 and 2024. The findings reveal a marked surge in publications after 2020, underscoring the growing integration of AI tools such as machine learning models and ChatGPT into engineering education. Key contributors and influential journals were identified, with significant research outputs originating from China, the United States, Spain and Peru. The thematic analysis indicates a clear shift from traditional educational methods toward data-driven learning strategies, positioning AI, machine learning, and engineering education as central themes in current research. This study offers valuable insights into the evolving role of AI in education, providing an important foundation for future research aimed at enhancing academic performance through technological innovations.

The objective of this study was to analyze the implementation of Design Thinking (DT) in higher education between 2013 and 2024. To understand its application and its coherence with the changing needs of higher education, 26 research articles were examined. The methodology included a systematic literature search in Scopus, followed by data selection and extraction according to the PRISMA-ScR methodology. The results revealed that DT has been widely adopted in higher education contexts, as it encourages creativity, problem solving and interdisciplinary collaboration. However, challenges were identified, such as the need for training for educators and resistance to change. In conclusion, DT has been effectively implemented in higher education, as it enriches pedagogy and promotes innovation, but attention must be paid to the challenges and sustainable implementation in this context must be guaranteed.

This study analyzes the impact of Flipped Learning on the active learning of engineering students. A systematic literature review was carried out using indexed databases such as Scopus and ScienceDirect, selecting relevant studies under quality and relevance criteria. The results show that Flipped Learning improves knowledge retention and academic performance, although it faces challenges such as resistance to change and the digital divide. Highlights the key role of digital technologies in its optimization. It is concluded that this methodology enhances student autonomy and interaction in the classroom, recommending its implementation with technological strategies adapted to various educational contexts

This study analyzed the shear strength of Cajamarca clays through Undrained Consolidated (CU) and Undrained Unconsolidated (UU) triaxial tests, complemented with numerical simulations in ABAQUS using the Finite Element Method (FEM). Key parameters such as cohesion, shear stress, and confining pressure were compared. The results showed that the effective cohesion in the CU was 3.26 kg/cm², while in the UU it reached 5.1 kg/cm², reflecting the effect of consolidation. The internal friction angle in the CU was 22.47°, confirming the soil strength under confined loading. In the FEM simulation, the shear stress values ​​showed a deviation less than 3% in CU and below 1.5% in UU, validating the accuracy of the numerical model. The difference in deviatoric stress between the tests and the simulation ranged between 0.96% and 1.41%, ensuring a high correlation. These results highlight the reliability of numerical modeling to predict the mechanical behavior of soil. The integration of triaxial tests with ABAQUS allows the optimization of foundation design and slope stability, reducing uncertainties and costs in geotechnical projects.

The study evaluates the mechanical behavior of the Baños del Inca soil, Cajamarca, through drained consolidated triaxial (CD) tests and numerical simulations in ABAQUS using constitutive failure models. The results obtained in the laboratory were compared with the Mohr-Coulomb, Drucker-Prager and Modified Cam-Clay models, analyzing the relationship between shear and normal stress, pore pressure and volumetric change. The results show that ABAQUS predicts values ​​slightly higher than the experimental ones, with differences of 2-5%. In terms of shear strength, the triaxial test reported cohesion values ​​of 30.5 kPa and a friction angle of 22.5°, while in ABAQUS the values ​​were 32.1 kPa and 23.8°, respectively. Drucker-Prager overestimated the shear strength by 8-10%, while Modified Cam-Clay better represented the secondary consolidation, with a difference of 1.5-3% with respect to the experimental values. Regarding the pore pressure, the maximum values ​​recorded were 40.5 kPa in the laboratory and 42.1 kPa in ABAQUS, while the maximum volumetric reduction was -23.6 cm³ in the laboratory and -24.2 cm³ in ABAQUS. The research validates the use of numerical models to estimate soil strength and highlights the importance of a correct calibration of the geotechnical parameters for their application in infrastructure projects.

The research was established to determine the relationship between academic engagement and academic satisfaction of university students studying a career in administration. The methodology used was applied, quantitative approach, with a non-experimental, cross-sectional and correlational design. This study was carried out in the city of Arequipa, whose sample was made up of students from 6 private universities and 1 public university with a total number of 423 university students in the city of Arequipa. The following instruments were applied: Utrecht Work Engagement Scale - 17 (UWES-17) and Academic Satisfaction Scale (ESA), which have the respective validity and reliability. According to the statistical analysis, a significant relationship was found between both variables; however, the dimensions of absorption and dedication have a higher positive index, while the dimension of vigor has a lower positive incidence with academic satisfaction. The analysis of the results suggests that universities should implement updated psychological evaluation methods and apply them periodically to optimize their performance, fostering commitment and effectiveness, to maintain student productivity, universities should reformulate academic methods that preserve their potential and energy in the face of daily changes, thus increasing the perceived reward. In summary, knowing these results and the above mentioned, it can be concluded that, in order to achieve optimal and beneficial behavior and performance, it is essential to work on the psychological well-being of students, actively participating in the learning and adaptation process.