Conference Agenda

This paper analyses a Global Shared Learning Classroom (GSL) experience developed between undergraduate students from the Dominican Republic and Puebla, Mexico, focused on collaborative research into the relevance of different vitamins for human health. The study was implemented as a pilot quasi-experimental design, integrating international collaborative learning, digital tools, and regulated artificial intelligence support as part of a structured pedagogical architecture. The intervention was articulated through the Dynamic Table for Research and Dissemination (TABDIM), used to organize, systematize, and synthesize the scientific information generated by binational teams. Students analyzed various vitamins considering physicochemical properties, biochemical functions, health implications, food sources, and practical applications. To support the research process, the specialized chatbot Albiomim was integrated as a cognitive scaffolding tool for consultation and conceptual clarification. The outcomes of the collaborative work were presented through a dynamic digital poster within an immersive virtual environment accessible via avatars, complemented by a reflective phase supported by the Padlet platform. Quantitative analysis of the results revealed a significant increase in conceptual learning, with mean scores rising from 65.68 to 78.18, along with a strong positive correlation between pre- and post-intervention results (r = 0.8006). Overall, the findings suggest that the intentional and structured integration of international collaboration, experiential learning, digital tools, and artificial intelligence contributes positively to conceptual learning, student engagement, and the overall learning experience in science courses for engineering education, providing relevant evidence for the design of innovative learning environments in higher education.

Communication barriers between deaf, nonverbal individuals and hearing people remain significant across various aspects of daily life. This article introduces an application for translating individual hand signs from the alphabet, based on the Puerto Rican Sign Language, into written text, as well as converting spoken language into text through speech recognition technologies. By integrating both gesture-based and voice-based input, the system promotes inclusive communication, especially in educational settings. Its main objective is to reduce communication barriers by offering an intuitive, real-time platform accessible through a standard webcam and microphone. The sign recognition process is based on the use of Artificial Intelligence techniques. The selected architecture combined the strengths of Multi-Layer Perceptron (MLP) and Multi-Layer Perceptron (MLP), allowing the system to learn both spatial patterns from individual frames and temporal dependencies across gesture sequences. To provide users with an accessible and real-time translation experience, a web application was developed using Django, a Python web framework. The system achieved an accuracy exceeding 84%, demonstrating its capacity to recognize both static and dynamic hand gestures with high reliability.

This document outlines the need for virtual physical therapy as a complement to, and even a substitute for, in-person therapy, which faces limitations related to cost and other access barriers. A literature review, conducted using the PRISMA guidelines, establishes a starting point for the design of an intelligent virtual agent that enables patients to undergo autonomous and safe rehabilitation. The results showed exponential growth in interest in virtual therapy. Bibliometric networks revealed two approaches: a technical one for patient and scheduling management, and an evaluative one focused on clinical effectiveness. The literature review highlights the integration of the Internet of Things and artificial intelligence for structuring virtual therapists that guide physical and mental rehabilitation, the use of RGB cameras and MediaPipe as tools for evaluating movement accuracy remotely, and the use of Lifelong Learning (LLL) and serious games to personalize therapies and provide real-time feedback. In conclusion, intelligent virtual therapy expands access, reduces dependence on hospital infrastructure, allows for interaction with a degree of independence, and enables objective monitoring.

This study analyzes the influence of artificial intelligence (AI) on the academic motivation of Peruvian university students, in a context of educational transformation aimed at strengthening retention and academic success. The research was conducted using a quantitative approach and a quasi-experimental design. A non-probabilistic, intentional sample of 180 students was used. Validated instruments (α=0.92) were employed, and an intervention based on the use of generative and analytical AI tools such as ChatGPT, Gemini, and GeoGebra was implemented to promote autonomous learning and self-regulation. The results revealed a significant increase in motivation in the experimental group (76.1%) compared to the control group (13.3%), confirmed by Student's t-test (p< 0.001) and Wilcoxon's t-test (Z=-6.45; p<0.001). These findings demonstrate the potential of AI as an innovative pedagogical resource for fostering intrinsic motivation and student retention, providing useful evidence for strengthening institutional strategies and national programs aimed at improving quality, equity, and innovation in higher education.