This study explores qualitative feedback provided by professors and ChatGPT 40 version when evaluating conclusions of laboratory reports. The experiment involves validating the final moisture content of shredded carrot through material balance calculations and thermogravimetric analysis. While reports are team-based, conclusions are individually written, resulting in 60 unique submissions focused on the argumentation of variations between estimated and measured moisture content. Thirdsemester students in the Bioengineering and Chemical Processes pathway at Tecnologico de Monterrey participated in this lab, part of the course “Application of the Principles of Conservation of Matter in Chemical and Biological Processes” (IQ1001B). Four professors established feedback guidelines, which were also provided to the AI. Advanced natural language processing (NLP) techniques were used to evaluate feedback, employing the Sentence-Transformer model ('all-MiniLM-L6-v2') to generate semantic embeddings and calculate cosine similarity. Statistical methods, including Shapiro-Wilk, paired t-tests, Wilcoxon signedrank, and Friedman tests, analyzed semantic alignment and significant differences. The study evaluates whether AI can provide feedback that aligns semantically with human input, focusing on the model's ability to identify meaning and context, emphasizing scalability and efficiency in large-scale STEM education, contributing to student-centered learning in 21st-century education.

The urgent challenge of climate change demands innovative educational strategies that not only disseminate scientific knowledge but also foster critical thinking and active engagement, particularly on large groups that need to be taught online. This paper presents the redesign and implementation of the online course Causes, Consequences, and Solutions to Climate Change, delivered to 137 students across diverse regions of Mexico. Leveraging advanced technological tools such as generative AI and immersive metaverse experiences, the course aimed to enhance student engagement, learning outcomes, and environmental awareness. The curriculum was structured around core components of the climate system, including the atmosphere, biosphere, hydrosphere, and the anthropogenic drivers of climate change. Guided by principles of active learning and project-based education, the redesign emphasized interactive, technologyenhanced learning experiences. One of the highlights was a metaverse-based group project, where students collaborated to propose solutions for mitigating climate change impacts in their local regions. This activity encouraged teamwork, creativity, and the practical application of scientific knowledge to real-world environmental challenges. To evaluate the impact of this course, pre- and post-course assessments were conducted to measure prior knowledge of the students about climate change and their familiarity with the innovative technological tools. Initial results revealed a lack of understanding in both areas. However, postcourse evaluations showed a 20% improvement in knowledge of climate science and technological platforms. These findings highlight the effectiveness of integrating advanced digital tools into environmental education.

Air quality is not typically covered in undergraduate studies, particularly in Chemical Engineering programs, despite its critical importance in addressing environmental challenges. This project provided two undergraduate students with the opportunity to engage in multidisciplinary research, helping them develop a broader understanding of air pollution and its impacts. Air pollution is a pressing issue that negatively affects human health, especially in urban areas where exposure to high concentrations of particulate matter (PM) in ambient air is a serious concern.$\mathbf{P M}_{\mathbf{2}. 5}$(particles with a diameter of$\mathbf{2. 5}$micrometers or less) and$\text{PM}_{1}$are particularly hazardous, as they can penetrate deep into the lungs and even enter the bloodstream, leading to significant health risks such as respiratory and cardiovascular diseases. Traditionally, air quality has been monitored using automatic stations, which, while effective, are costly and cover only limited areas. Recently, the use of low-cost sensors has gained attention as a more flexible and affordable alternative, allowing for the identification of localized areas with high pollution, or “microenvironments.” This six-month study, conducted by two Chemical Engineering students, involved the installation of 14 low-cost PM monitors on the roofs of vehicles to analyze PM concentrations throughout the Guadalajara Metropolitan Area, Mexico, in 2022. The students gained valuable skills in data analysis, environmental monitoring, programming, and scientific writing. Moreover, they wrote code in Python, using ChatGPT as a generative AI tool, with the aim of producing high-quality graphs to analyze the big data sets collected. The study found that PM concentrations were highest in the city center, where the daily average reached$79 \mu ~\mathrm{g} / \mathrm{m}^{3}$, likely due to heavy vehicular traffic. In the southern part of the city, PM concentrations peaked at$94.5 \mu ~\mathrm{g} / \mathrm{m}^{3}$, potentially linked to traditional brick manufacturing. These findings highlight the importance of identifying specific pollution sources to improve air quality in urban settings.

Teaching engineering, and chemical engineering in particular, heavily relies on laboratory work and it is not uncommon that students may have limited access to and use of big and robust equipment needed to experience and confirm the theoretical contents exposed in classrooms. Today, the advances in artificial intelligence, and the new student perceptions about business and entrepreneurship require students to translate their engineering ideas and to connect them to current requirements of technologies along with other subjects such as programming, control, and business. Academic institutions may not have access to large equipment due to their high costs. This situation limits the experience of students implementing in practice what they learn in classrooms. The availability of low-cost sensors and the use of the Internet of Things (IoT) allows the readily fabrication of testing equipment The objective of this research work was to evaluate the potential of a learning strategy model based on the design, fabrication and use of smart technologies by chemical engineering students, and to orient their learning as an early stage on entrepreneurship. Students designed, constructed, and instrumented three different apparatus: a reactor, a set of pipes, and a set of 4 packed bed columns. After 12 months, students expressed a better understanding of the theoretical principles and developed their entrepreneurship skills by learning how to instrument and control some experimental variables, as well as exploring the marketing potential of the apparatus as entrepreneurs. A cost analysis showed that the investment in this equipment could be between 10 % and 25 % of the cost that is currently on the market.

As the global community grapples with environmental challenges, there is a pressing need to transition from the linear ‘take-make-dispose’ model to a more regenerative and sustainable approach. Circular Economy (CE) principles offer a promising framework to achieve this shift by emphasizing resource efficiency, waste reduction, and the promotion of closed-loop systems. While CE has been successfully applied in various projects, there is still the need to involve University students from various academic backgrounds in this multidisciplinary subject. This paper describe a CE course imparted to students from various academic backgrounds and shows the results that explore the intricate relationship between materials, sustainable manufacturing processes, and the principles of circularity. By linking theoretical concepts taught in the course whit an industry real case study. This paper aims to provide students and practitioners with practical insights and actionable strategies to integrate CE principles to the academic formation of diverse professional profiles effectively. For the assessment, the results of the pre and post questionnaires showed that questions with an increase generally refer to the characteristics, objectives, and scopes of CE. The findings of the sentimental analysis highlight not only the measurable increase in knowledge but also the positive sentiments and perceptions associated with integrating CE principles into diverse academic disciplines.