Industry 4.0 and International Collaborative Online Learning in a Higher Education Course on Machine Learning

Abstract

The need for more efficient online learning strategies surged due to the global pandemic, providing opportunities to use global classrooms such as the COIL (Collaborative Online International Learning) model. COIL facilitates faculty members' interactions at two different universities in different countries and creates virtual learning communities. Additionally, besides the pandemic, the advent of Industry 4.0 confronts graduates with the need to develop competencies in Machine Learning (ML), which are applied to resolve many industrial problems requiring prediction and classification and the availability and management of large amounts of data. This paper describes a global classroom in ML designed and implemented by professors at Tecnologico de Monterrey (Tec) in Mexico and the University of Applied Sciences Würzburg-Schweinfurt (FHWS) in Germany <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> The collaboration was funded by the German Academic Exchange Service (DAAD). The global classroom's goal was to implement a joint international experience to develop machine learning competencies among students working in teams to resolve real problems with data-driven methods using an online digital platform called Remote Virtual Lab 4.0 (vLab).