Conference Agenda

The increasing technological mediation in educational environments has substantially transformed teaching and learning processes, generating scenarios in which information processing occurs in a distributed manner among individuals, digital tools, and sociocultural contexts. Within this framework, this article aims to analyze Distributed Cognition as a relevant theoretical approach for understanding the organization and processing of information in hybrid and virtual educational environments.

Based on a structured theoretical review and a critical analysis of the main conceptual developments of Distributed Cognition, this study examines its historical evolution, philosophical foundations, and core concepts, as well as its articulation with learning theories, metacognition, self-regulation, and multimedia learning. The analysis highlights how cognition is configured as a dynamic system that integrates human agents, technological artifacts, and social structures, promoting collaborative knowledge construction processes.

The findings suggest that Distributed Cognition provides a solid interpretative framework for understanding technology-mediated learning and for guiding the design of educational environments that optimize information processing. Finally, the pedagogical implications, limitations, and future research directions of this approach are discussed, emphasizing its potential contribution to the development of educational strategies aligned with the demands of 21st-century education.

Keywords-- Distributed Cognition, Information Processing, Hybrid Learning, Educational Technology, Collaborative Learning.

Educational robotics has emerged as a key pedagogical tool in engineering education between 2020 and 2025. This research aimed to examine the academic literature on the use of educational robots in undergraduate and graduate engineering programs. The methodology of this study applies a PRISMA systematic review to analyze 30 relevant studies, identified through searches in seven academic databases. The results show sustained growth in publications, with a moderate positive effect on learning. The most common uses are educational kits (LEGO, mBot), mobile robots, and low-cost systems, primarily at the undergraduate level. Improvements in computational thinking, programming, design, collaborative work, and motivation are reported, supported by pedagogical approaches such as constructivism and project-based learning. Educational robotics is found to be effective for developing technical and soft engineering skills, but limitations exist, such as the lack of longitudinal and graduate studies. It is recommended to incorporate frameworks such as CDIO and explore new platforms associated with Industry 4.0.

The persistence of low participation levels and high failure rates in online engineering courses has motivated the search for pedagogical strategies that increase engagement and academic achievement without reducing disciplinary rigor. This study analyzes the effect of a gamified intervention integrated into the Learning Management System (LMS) on participation and academic performance in an online engineering course, using a quasi-experimental design with a non-equivalent comparison group. A comparative analysis was performed with two groups corresponding to two cohorts: one with the course where the content was delivered in a traditional manner (control group, n=102) and one with the course where gamification was applied (experimental group, n=108), which included experience points, badges, levels, weekly challenges, leaderboards, and immediate feedback, while maintaining the same content and assessments. The data collected consisted of objective indicators of participation and performance, and were analyzed using chi-square tests, ANCOVA, and regression models. The findings indicate that the experimental group achieved significant improvements in participation (days of activity, income, activities, and interaction in forums) and increased the pass rate from 62.7% to 78.7%. Additionally, in the experimental group, participation and interaction with game elements were positively correlated with the final grade, which explains a significant distribution of its variance. It is concluded that when gamification is implemented in alignment with the course objectives and integrated schematically into the Learning Management System (LMS), it can become an effective methodology for increasing both participation and academic performance in online engineering courses, while also providing a framework for replication in future studies.

Interactive technologies in neuromotor and cognitive rehabilitation training can strengthen applied learning, especially when embedded in a blended passive–active approach that links guided conceptual preparation with simulation-based practice and immediate feedback. This study evaluated the effectiveness of a technology-enhanced educational innovation that enables undergraduate students to practice patient assessment, intervention, and progress monitoring through digital exercises and real-time data analysis. A descriptive post-intervention design was applied. The total sample comprised 27 cases, all of whom completed the evaluation instruments. Measures included the Simulation-Based Teaching Evaluation Scale for Technical Skills Training (ESIMHAT), a Cognitive Load Scale, a three-item Academic Goal Progress questionnaire, and open-ended questions to capture perceptions and suggestions. Results showed a very good overall appraisal of the simulation experience (M = 49.9, SD = 2.47), with high levels of favorable responses in the Preparation dimension (90–100%), suggesting appropriate instructional conditions and a positive working climate. Cognitive load results were largely positive: extraneous load reached 82.4% favorable responses, indicating that the instructional design minimized unnecessary barriers, and germane load reached 94.1% favorable responses, suggesting productive mental effort directed toward learning. In contrast, intrinsic load showed lower favorability (47.1%), consistent with the inherent complexity of the content and tasks addressed. In open-ended responses, students reported strong formative value and proposed improvements related to greater resource availability, infrastructure adjustments (connectivity/space), and accessibility conditions to optimize curricular integration. Overall, the findings support the perceived effectiveness of the innovation for enhancing applied learning in neuromotor and cognitive rehabilitation for routine curricular use at scale.

Artificial intelligence (AI) has become an essential component of higher education, especially due to the advancement of generative AI, which has transformed pedagogical practices and teaching-learning methods. The objective of this systematic literature review (SLR) is to analyze the impact of AI on students and teachers compared to those who continue to use traditional learning meth ods. To this end, the PRISMA 2020 protocol and the PICO method were applied through an exhaustive search of the Scopus database, yielding a total of 33 documents that met the established inclusion and exclusion criteria. The results show a sustained increase in publications by 2025 and a multidisciplinary character, with contributions from the social sciences, computer science, and engineering. Among the benefits highlighted are personalized learning, improved feedback, support for teaching, and increased student motivation. However, limitations also emerge, such as technological dependence, insufficient teacher training, institutional resistance, a decline in critical thinking, and the absence o f robust ethical frameworks. Overall, the RSL indicates that AI has a mostly positive effect on higher education, facilitating time management, comprehension of complex content, and enabling more adaptive learning experiences. Nevertheless, challenges persist related to the reliability of AI-generated information, the lack of institutional regulations, and technological gaps stemming from internet access or the cos t of advanced tools.

Currently, the integration of digital platforms in higher education represents a key strategy to strengthen the understanding of complex subjects, particularly in the areas of engineering. Digital logic, being a fundamental subject in the training of future engineers, requires pedagogical tools that facilitate both conceptual understanding and the development of practical skills. Faced with this need, the design of an interactive and intuitive web platform, developed in Python, is proposed, which aims to support both teachers and students in the teaching and learning process of digital logic courses. The platform incorporates structured modules of theoretical content, interactive practices, visual simulations of digital circuits and academic monitoring panels customized according to the user profile (student, teacher, or administrator). In addition, it integrates an embedded visual simulator, an automated assessment system, and an academic management dashboard that allows teachers to manage courses, assign activities, and track student progress in real time. The design of this tool seeks to bridge the gap between theoretical knowledge and practice through accessible and adaptive resources that adjust to various levels of mastery, from beginners to advanced students progressively. Likewise, the requirements, the architecture of the system and the curricular mapping of the digital logic course are defined, establishing the bases for its future implementation and experimental validation.