PBL in Computational Mathematics course, TUG

Course overview

This course introduces the study and design of mathematical models for the numerical solution of scientific problems. It focuses on numerical methods for the solution of linear and nonlinear systems, basic data fitting problems, and ordinary differential equations. Robustness, accuracy, and speed of convergence of algorithms is investigated including the basics of computer arithmetic and round-off errors

Participants in piloting 

The course enrolled 20 students in the 3rd year of undergraduate studies, following a degree course in Industrial Management. The course is elective in the formal curriculum of the Department of Mathematics of the Technical University of Gabrovo.

Use of ALIEN services and tools

During the course, students were exposed to active and problem-based learning in the contexts of a team project where they were organized in teams so as to study Probability Theory and Mathematical Statistics by applying computational mathematics systems (Мaple, MathCad, Excel and Mathematica). The teams got familiar with the resources provided by the teacher. Each team selected a problem from the problem system in probability theory and mathematical statistics given by the teacher and discussed problem solutions with each of the computational mathematics systems – Мaple, MathCad, Excel and Mathematica. Then the team chose the most appropriate CMS and applied it to solve the problem. Finally, the teams analyzed their results and answered some questions related to the topic.

The active learning activities allowed students to incorporate IT in their calculations so that they can be prepared for their future work life as engineers. In addition, they were able to improve their analytical and critical thinking, and communication skills and built a team spirit. Problem-solving played a key role.