Abstract:

Computational thinking lies at the heart of engineering and technology learning beyond computer science. This capacity has been heralded as a foundational capability for the 21st Century, because of its main benefits in developing problem- solving and creative thinking skills, as well as, in improving autonomy and confidence.

The need to foster students' computational thinking in engineering subjects is a matter of urgency; to adapt the way students learn, and to prepare them to overcome professional challenges in the workplace.

At the same time, Artificial Intelligence (AI) has heavily irrupted in society, bringing new applications and possibilities in all aspects, including education. Literature recognizes AI as a tool in the cognitive ecosystem where immersive humans-with-technology environments strengthen the potential of computational thinking over subjects such as mathematics, computing, physics, writing, etc.

University students tend to believe that mathematics consists of mastering formal procedures that are completely divorced from real life and engage them in meaningful learning activities as to develop useful thinking skills and digital competences represent a real challenge. One aspect of this difficulty relies in identifying from many applied math problems, the subjects by discipline in correspondence with the four dimensions of computational thinking: Decomposition, Pattern Recognition, Abstraction, and Algorithm Design.

The above refers to having a dataset of multiple applied problems from textbooks and a classification system, which could group and organize them by similarity and by discipline, which is of fundamental help to students in making decisions about the solution process.

We are oriented to design a proposal for the application of AI technologies that considers the dimension of Pattern Recognition applied to fundamental mathematics for engineering careers. The objective is to improve in students the acquisition and development of the skill of pattern recognition, fundamental in the modeling of applied mathematical problems, which at the same time is presented in computational thinking.

The design of a supervised classification system is developed for the solution of mathematical problems from various textbooks, which are distinguished by containing the dimension of pattern recognition and which enter into the classifier that assigns them in the disciplines of Algebra, Analytical Geometry, Calculus, Linear Algebra, Differential Equations, Vectorial Calculus, and Numerical Methods.

The scope of this proposal is that the student demonstrates that he/she identifies or does not the solution process of an assigned problem.

Keywords:

Computational Thinking, Supervised classification, pattern recognition, applied math problems, math skills.