In an increasingly complex and competitive global environment, developing scientific thinking and research skills in university students has become a crucial component of higher education. This article highlights the importance of fostering these skills to train future innovators and problem solvers who can address scientific and societal challenges. We present a case study describing the implementation of a research stay experience designed for university students from various disciplines, offering them hands-on research experience in real-world scientific projects. At the initiative's core is an educational platform de-signed to cultivate complex thinking through the lens of scientific entrepreneurship. This platform integrates SDG-based learning modules and project-based activities to encourage students to de-velop original ideas, test hypotheses, and apply scientific methods in a dynamic learning environment. By linking theoretical knowl-edge with practical research experience, students are encouraged to conduct critical inquiry, collaborate with peers and mentors, and hone their problem-solving skills. In addition, the platform emphasizes scientific entrepreneurship, allowing students to apply their research to real-world challenges and explore the potential commercialization of their ideas. Preliminary data from the program's evaluations indicate that students who participate in this experience show a marked improvement in their ability to think critically, approach problems from multiple perspectives, and design innovative solutions. In addition, many students report being more confident about pursuing graduate studies or careers in research-intensive fields. This article contributes to the growing literature that underscores the need for early and ongoing exposure to scientific research in higher education. It offers valuable insights to educators, academic institutions, and policymakers who wish to implement or improve research-based learning programs in their curricula.

In today's rapidly evolving technological landscape, marked by the proliferation of artificial intelligence and robotics, the role of engineering education stands as a cornerstone of sustainable progress. Recognizing this imperative, engineering curricula are increasingly incorporating a competency-based approach that reflects the complexities of the real world, for lifelong learning, using enabling and disruptive technologies such as humanoid robotics. We present a case study from the Tecnologico de Monterrey, Mexico City Campus, where NAO robots are used in social projects with immediate impact in the fields of health and education, addressing sustainable development objectives. This research shows projects that have had a significant social impact in different communities in Mexico, in the areas of education and health with innovative solutions that motivate and engage the attention of the audience. A group of students from different engineering careers design, develop and implement application scenarios for the accompaniment and social appropriation of challenges such as: the incorporation of girls in STEM areas, support for groups with intellectual disabilities, dissemination and knowledge of sign language and dissemination of the cultural heritage of Xochimilco as a cultural heritage of humanity. Preliminary results indicate that this pedagogical approach not only inculcates students with essential skills such as problem solving, critical thinking and teamwork, but also makes them more aware of the social implications of their engineering studies. Evidence and results of the involvement of undergraduate students in social scenarios are shown, showing that, by integrating these elements, engineering programs aspire to train professionals capable of harnessing their technical knowledge for the general good of society as well as the perception of the participants and audiences reached.

This paper contributes to the realization of learner-centered learning scenarios. It is developing an IoT learning platform for different educational levels. On the other hand, the use of “Pocket Labs” is proposed as an effective tool in the meaningful learning of emerging technologies. The fact that these tools can guide the student towards the realization of projects using a set of technologies that are on the rise generate as advantages: an increase in personnel familiar with the IoT, which has an economic impact on the industry, or that the learning is long term, as students develop and improve their understanding. Furthermore, the intention is to develop Information and Communication Tools (ICT) disciplinary competencies, which aligns with the spirit of the Tecnologico de Monterrey’s educational model. Both strategies are a relatively new teaching concept that supports students’ creativity and initiative, allowing them to wear and experiment with actual equipment at any time and place of their choice. Both experiences result in significant long-term learning in fundamental technologies for Education 4.0 and Industry 4.0. These include IoT, RFID (Radio Frequency Identification), NFC (Near Field Communications), Cloud Services, Etc.

Maze navigation is a recurring challenge in robotics competitions, where the aim is to design a strategy for one or several entities to traverse the optimal path in a fast and efficient way. To do so, numerous alternatives exist, relying on different sensing systems. Recently, camera-based approaches are becoming increasingly popular to address this scenario due to their reliability and given the possibility of migrating the resulting technologies to other application areas, mostly related to human-robot interaction. The aim of this paper is to present a pipeline methodology towards enabling a robot solving maze autonomously, by means of computer vision and path planning. Afterwards, the robot is capable of communicating the learned experience to a second robot, which then will solve the same challenge considering its own mechanical characteristics which may differ from the first robot. The pipeline is divided into four steps: (1) camera calibration (2) maze mapping (3) path planning and (4) communication. Experimental validation shows the efficiency of each step towards building this pipeline.

The system presented in this paper aims to serve as a low cost tool for the detection and characterization of different neurodegenerative diseases by measuring the skeletal muscle movement in the patients' fingers. Conditions like Parkinson's, Multiple Sclerosis, psychiatric diseases, alcoholism and drug abuse have specific movement frequencies which could be graphed. The system looks to make possible the identification of the disease mapped according to the characteristic graph, reducing the number of tests needed for this matter. Research focused, it aims to measure the disease's intensity and progress as well as the effect of medicine treatment and therapy.