This paper describes the first regional nanosatellite competition, “Tampico CanSat Competition 2023.” This competition is an initiative of the School of Engineering and Sciences of the Tecnológico de Monterrey Campus Tampico, focused on bachelor students from 14 to 19 years old, combining scientific and technological education with the motivation to integrate the STEAM methodology in the teaching-learning process. In this competition, participants are tasked with designing, building, programming, and launching a device known as CanSat, which resembles a soda can in size and shape. The research is intended to study the motivation, engagement, communication, and critical thinking of the students developing multidisciplinary tasks.

Maintaining student motivation during physics and mathematics classes can be quite challenging for teachers. To achieve this, an interactive technological platform, Nearpod, was integrated into the class sessions, since it allows the incorporation of gamified learning activities and follow-up on the performance of the group. This study evaluates the impact of Nearpod on the attention levels of first-semester engineering students. The interventions took place within structured five-week learning modules focused on physics and mathematics content. Robust data collection instruments, encompassing the validated survey Instructional Materials Motivation Survey, Nearpod-generated reports, and opinion surveys directed to teachers and students, were deployed. The study involved a group of 87 first-semester engineering students. According to the study, classes that used Nearpod had an average student attention rate of 76% during the 38 analyzed class sessions. Additionally, student participation in interactive activities reached an average of 86%, which is higher than the participation rates reported by teachers in traditional courses. Student feedback underscored a positive perception of Nearpod's impact, emphasizing its role in maintaining focus and enhancing the learning process. In essence, this research underscores the transformative potential of Nearpod when coupled with gamification strategies in the context of university engineering education.

The development of critical and scientific thinking skills represents a major role in the education of engineering students, enabling them to suggest practical solutions to the diverse challenges confronting contemporary society. This paper describes the use of research-based learning as a pedagogical approach with the assistance of the Simscape platform in the Simulink environment to encourage the development of these competencies among second-semester engineering students at Tecnologico de Monterrey. For the course denominated “Analysis of Electrical Systems in Engineering”, they were asked to analyze the charging and discharging process of a supercapacitor through an equivalent electrical circuit model. The study included 42 students enrolled in the course, divided into the control group and the experimental group. As a result, the study demonstrates that this approach significantly improves student learning outcomes in both cohorts. The average scores in the post-test showed an increase of 3% among the experimental group over the control group. Furthermore, the students in the experimental group were administered a survey to ascertain their perspectives on the enhancement of scientific and critical thinking abilities as a result of engaging in research-based activities. The survey results indicate a consensus among students, with over 70% stating that this pedagogical approach enhanced this kind of skills and emphasizing the positive impact of these strategies in education.

This study introduces a transformative educational model that merges behavioral economics and ethics within the engineering ethics curriculum. This integration aims to address the ethical complexities arising from rapid technological advancements. Our primary finding reveals that embedding an ethics curriculum within the broader educational framework significantly boosts ethical decision-making competencies among engineering students. By promoting diversity and inclusivity, the study demonstrates that incorporating varied perspectives leads to improved ethical decision outcomes, essential for the global impact of engineering practices. The research validates the effectiveness of challenge-based learning in instilling ethical competencies and examines the role of e-learning environments in upholding ethical standards. Significantly, the paper re-evaluates assessment methodologies, emphasizing behavioral measures to capture the practical application of ethical principles in realistic scenarios. Ultimately, the paper argues for a shift in engineering education towards active engagement in ethical reasoning, highlighting the complex interplay of psychological influences on behavior. This approach is posited to cultivate a generation of engineers capable of navigating the moral dimensions of their profession with acumen and integrity.

We present a new speech rate classifier (SRC) which is directly based on the dynamic coefficients of the feature vectors and it is suitable to be used in real time. We also report the study that has been carried out to determine what parameters of speech are the best regarding the speech rate classification problem. In this study we analyse the correlation between several speech parameters and the average speech rate of the utterance. Finally, we report a compensation technique, which is used together with the SRC. This technique provides with a word error rate (WER) reduction of a 64.1% for slow speech rate and a 32% reduction of the average WER.

In this paper we report our development work in Spanish spontaneous speech conversational systems. We describe the automatic telephone operator service (ATOS) and present the improvements introduced into it to deal with spontaneous speech, which are: (a) a task independent dialogue manager, that can be adapted to a new semantic domain by changing a configuration file. It also generates a prediction about the user's expected utterance to constrain the language model used by the speech recognizer; (b) a language modeling strategy, which allows to adapt the statistical language model to a new task with just few hundreds of sentences. This strategy reduces a 27% the word error rate. We also report the results, conclusions and the speech database collected in the evaluation of the ATOS system, which has been tested by 30 real users.

Statistical language models provide a powerful tool for modelling natural spoken language. Nevertheless a large set of training sentences is required to estimate reliably the model parameters. The authors present a method for estimating n-gram probabilities from sparse data. The proposed language modeling strategy allows one to adapt a generic language model (LM) to a new semantic domain with just a few hundred sentences. This reduced set of sentences is automatically tagged with eighty different pseudo-morphological labels, and then a word-bigram LM is derived from them. Finally, this target domain word-bigram LM is interpolated with a generic back-off word-bigram LM, which was estimated using a large text database. This strategy reduces by 27% the word error rate of the SPATIS (SPanish ATIS) task.