WIP: Use of a Self-Executing Notebook Based on Matlab's Live Editor for the Development of Autonomous Learning Competency in an Analog Communications Course

This innovative practice WIP paper describes how autonomous learning competency is developed in a course called “Communications Theory 1” that covers analog communications topics within the Telecommunications Engineering Program. To this end, all course material has been redesigned as a self-executing notebook using Matlab Live Editor¹¹https://www.mathworks.com/products/matlab/live-editor.htm1 and is delivered chapter by chapter throughout the semester. This allows students to read the course content and interact with the simulations, modifying them freely to explore the session theory in greater depth and, finally, recognize relevant limits and characteristics. Within the course platform, based on Moodle, the contents have been accompanied by exercises in the Matlab Grader model, which allow feedback to the student when answering the questions provided, validating the developed code. This work helps to strengthen their knowledge in parallel to the activities carried out in the classroom. Since the self-executing notebook provides the information necessary to understand the behavior of the different analog communication techniques seen in the course, in the final chapter, all the knowledge is integrated into an activity that combines the flipped classroom and the puzzle technique, allowing students through teamwork, fully develop the final chapter of the course with a high level of autonomy. This work will be evaluated with the support of rubrics that will allow us to know its progression in the different learning outcomes related to the specific competencies developed in the course and the advancement of generic competencies, including autonomous learning. As a work in progress, initial measurements in applying the self-executing notebook indicate high student satisfaction with the notebook's content and the associated activities. Additional assessments are then planned to refine the teaching-learning cycle and improve course outcomes. Finally, new activities are proposed to complement the training by applying AI technologies and using new laboratory resources.