Use of the collaborative wall to improve the teaching-learning conditions in the bachelor of visual arts

Abstract

This mixed research analyzes the use of the Collaborative Wall to improve the teaching-learning conditions in the Bachelor of Visual Arts considering data science and machine learning (linear regression). The sample is made up of 46 students who took the Geometric Representation Systems course at the National Autonomous University of Mexico (UNAM) during the 2019 school year. The Collaborative Wall is a web application that facilitates the organization and dissemination of ideas through the use of images and text. In the classroom, the students formed teams and used mobile devices to access this web application. The results of machine learning indicate that the organization of ideas in the Collaborative Wall positively influences the participation of students, motivation and learning process. Data science identifies 3 predictive models about the use of this web application in the educational field. Also, the Collaborative Wall facilitates the learning process in the classroom through the comparison and discussion of information. Finally, technological advances allow organizing creative activities that favor the active role of students.