Application of A Teaching Plan for Algorithm Subjects Using Active Methodologies: An Experimental Report

Abstract

Computer programming subjects have high failure rates, their contents are of great importance for the formation of undergraduate students, however their learning is considered challenging. In this sense, the use of approaches that promote active learning on the part of students in algorithmic subjects stand out in the specialized literature, in order to increase their engagement and awaken their interest in the contents covered, making them protagonists of their learning. However, the proposals do not always fully disclose the instruments used, such as the detailing of the teaching plan, which is extremely important material for the good conduct of a subject, since in it the professor is able to articulate his strategies of intervention, the tools used, as well as the learning objectives that must be achieved. Thus, the objective of this work is to discuss and analyze the results of an experiment that consisted in the application of a teaching plan that makes use of multiple active methodologies (Virtual Learning Environments, Coding Dojo, Gamification, Problem Based Learning, Flipped Classroom and Serious Games) in an algorithms subject. We sought to evaluate the learning gains of the proposed approach compared to teaching using the traditional teaching method. A statistical analysis was performed using the Student-t two-tailed approach for independent samples, which showed significant statistical gains when using the proposed approach.