Exploring the Challenges and Applications of Generative AI on Engineering Education in Mexico

Introduction

With the arrival of 21st-century skills and the Next Generation Science Standards, the relevance of broader learning skills and competences such as cognitive processing, critical thinking, and cooperation has been stressed. As a result, contemporary educational environments and philosophies aim to include authentic practices that entail solving serious challenges together. To prosper in this changing environment, both students and teachers demand better and more customized support.

To generate students with 21st-century abilities, the interaction between STEM education and Industry 4.0 should be strengthened. Collaboration, communication, critical thinking, and creativity are examples of these abilities. It is commonly understood that the technologies of the Fourth Industrial Revolution will have deep and rapid effects on society and the earth. While the exact impact is unknown, higher education must respond immediately. The potential for these technologies to create either catastrophic environmental devastation or great societal consequences is upon us. Furthermore, there is rising concern about the potential loss of control over networks of strong AI agents with increasing autonomy, especially in the financial and urban infrastructure sectors (Roll et al., 2016).

The technique known as generative artificial intelligence (AI) has gained significant traction and has the capacity to transform numerous academic fields. This technology provides new chances to improve teaching and learning approaches in the field of education. Engineering education in Mexico, in particular, can benefit substantially from the use of generative AI.

A prominent use-case for computer-based learning in the past featured a student working with a computer in a math or science classroom to answer step-by-step tasks focusing on domain-specific knowledge, with a human tutor serving as the gold standard. This use-case, however, fails to take into account current changes in educational practices and theories (Pillay et al., 2018).

Furthermore, the function of the teacher in the classroom has changed. From being the wise man on stage, they have become the sidekick. Teachers are no longer expected to know everything and simply pass it on to students. Instead, their job is to help students search, find, and integrate information, allowing them to become independent and collaborative thinkers.

Technology and education are connected in a complex and varied area with political, economic, social, and pedagogical repercussions. In today's “technological societies,” the use of technology to facilitate teaching and learning tasks has become critical. Understanding and incorporating technology into the curriculum has also developed as a critical part of education. As a result, the creation of technology and programs that firmly support instructional activities has become critical, supporting overall advancements in the educational landscape (Zhao et al., 2019).

The use of computer applications to supplement teaching and learning has become widespread in many nations, notably in the global North. These apps facilitate a wide range of educational activities, from subject-specific learning, such as “Logic” or “Algorithms”, to engaging in practice exercises and drills in subjects such as “Arithmetic” or “Geometry.” They are also used in formative and summative evaluations. This ubiquity extends across all educational levels, from primary to postgraduate, and includes a wide range of courses that go beyond the sciences and into the realms of the arts and humanities. Notably, many of these programs can be defined as artificial intelligence in essence, sticking to the broad definition of serving as instrumental tools that aid students in their understanding of various topics, such as mathematics (Sanchez-Pi et al., 2021).

AI-powered systems have enormous potential to change the educational landscape. These applications can provide personalized and adaptive learning experiences by employing AI algorithms and methodologies, adapting educational content and exercises to the specific needs of individual learners. AI-based tools, with their ability to analyze large volumes of data and discover trends, provide insights into student performance and fast feedback, increasing the learning process.