Conference Agenda

The integration of Artificial Intelligence (AI) in language education is transforming traditional teaching methodologies. This quasi-experimental study examines the impact of ChatGPT on the motivation, engagement, and proficiency of undergraduate students learning English at the A1 level. A total of 290 students from Law and Business Administration programs at Universidad Privada del Norte participated in a 12-week AI-enhanced curriculum. Pre-test and post-test results were analysed alongside student perceptions collected through surveys. Findings indicate that while students reported increased motivation and engagement, statistical analysis showed no significant improvement in test scores. ChatGPT was particularly valued for its feedback and vocabulary-building capabilities but was less effective in enhancing pronunciation. These results suggest that AI tools like ChatGPT can serve as valuable supplements to language instruction, especially when combined with specialized resources for speaking and pronunciation, such as THINKLING. The study highlights the need for continued exploration of AI-driven learning methodologies to optimize their impact on language acquisition.

This study conducts a systematic review on the application of Artificial Intelligence (AI) in academic research for higher education, focusing on the period 2014-2024, in the context of the remarkable increase in scientific production and current technological trends. The main objective of the review is to analyze the use of AI in this field; in addition to identifying trends, challenges and opportunities that contribute to the improvement of educational quality and institutional management. For this purpose, the PRISMA methodology was used, using databases such as Scopus, Scielo and Google Scholar, with inclusion and exclusion criteria that allowed the selection of 14 studies out of a total of 113 analyzed. The results obtained reveal that AI is used in areas such as personalization of learning, automation of administrative tasks, research and library services, virtual assistants and development of future skills. Therefore, although with great potential to transform higher education, the integration of AI must be managed with caution to maximize its benefits and mitigate the associated risks, being crucial the training of students and professionals in skills linked to AI for an adequate adaptation.

The objective of this study was to evaluate the influence of the use of virtual reality in improving university education in engineering students. A quasi-experimental design was used with comparative groups, applying a pre-test and a post-test to measure the impact of virtual reality on the learning process. The sample included 40 students, divided into an experimental group that used virtual reality and a control group that maintained traditional teaching methods. The results showed that after the intervention the experimental group presented significant improvements in the levels of efficiency in immersive, observational and experiential learning, pointing out that virtual reality encourages greater interaction with content, autonomy in learning and decision making in simulated environments. In conclusion, virtual reality demonstrated its ability to improve academic performance and the development of critical competencies for vocational training, which, despite technological challenges, the adoption of this technology in Peruvian higher education has the potential to transform teaching, providing students with more dynamic and personalized educational experiences in line with the demands of the labor market.

In recent years, the need to promote the development of technological and cognitive skills from the earliest levels of schooling has become increasingly evident, driven by the growing impact of Information and Communication Technologies (ICT). The objective of this study is to assess the development of Computational Thinking (CT) through the implementation of learning activities supported by programming challenges using Educational Robotics (ER) among early childhood education students. A quasi-experimental design was employed, with pretest/posttest measures and a non-equivalent control group, involving a sample of 77 students aged between 3 and 6 years, divided into an experimental group and a control group. The intervention consisted of six sessions using the Blue-Bot robot, integrating STEM approaches and the Play-Work methodology. Three CT dimensions were evaluated using a validated instrument adapted to the curriculum. The statistical analyses confirmed significant improvements in the experimental group compared to the control, demonstrating the positive impact of ER on the development of CT at an early age and providing a foundation for strengthening innovative pedagogical practices in early childhood education.

Electrodermal Activity (EDA) has emerged as a valuable physiological measure in educational research, providing insights into emotional and cognitive engagement. This study investigates the variation in students’ EDA responses under traditional lecture-based and active learning conditions. Data were collected from eight university students using electrodermal resistance sensors during instruction on the Single Minute Exchange of Die (SMED) methodology. Each participant engaged in both instructional modalities within a controlled environment. The EDA signals were analyzed using statistical techniques including paired t-tests and Mann-Whitney tests. Results indicated that most students exhibited significantly higher EDA levels during active learning sessions, suggesting increased arousal and engagement. However, individual differences, including potential non-responsiveness and gender-based variability, were also observed. These findings underscore the potential of EDA as a real-time, non-invasive tool for assessing instructional effectiveness and student engagement, offering implications for the design of adaptive and student-centered learning environments.

Abstract– Technological advances applied to present and future industrial processes demand an update in the teaching processes in the training of industrial engineers, integrating technologies such as robotics and automation. This article addresses how to make use of technological equipment in academic training through practical exercises that allow students to develop key content and skills to face the challenges of the sector.
Three exercises applied to the training of industrial engineers are presented; the first, focused on improving productivity, allows students to analyze and optimize processes through process automation; the second, focused on quality control, uses automated inspection tools to evaluate quality in production; and the third, related to statistics, uses data analysis techniques for evidence-based decision making.
These exercises not only reinforce the theoretical content of the degree, but also develop practical skills in the use of advanced technology, preparing future professionals to design, operate and improve production systems in increasingly technological industrial environments. It is concluded that the teaching of industrial engineering must evolve in sync with technological advances, adopting methodologies that promote practical learning. The implementation of exercises with robotics and automation strengthens the analytical and decision-making capacity of students, ensuring their adaptation to modern industry.

This work describes the findings from the creation of a virtual reality driving experience simulator, where the validation of the experience with a group of individuals was considered. From this process, various physiological effects caused by the characteristics of the simulator and the parameters associated with it were discovered. The simulator created with the Unity platform, for the FORMULA SAE competition, has been described and presented in previous works and the experience has been described by its participants. This document presents the variables discovered in the simulator, which influence said physiological effects in the participants of the vehicle journey on the F1-type track. The results obtained and analyzed showed the influence of various variables on the physiological conditions of the participants, as well as the effects caused in the users that resemble the real driving conditions for the Formula type vehicle. This information was validated with a new group of engineering students and participants of the FORMULA SAE project, where the results will allow the content of the simulator to grow, as well as taking the necessary precautions when using it.