Ruipérez-Valiente, José A.Muñoz Merino, Pedro JoséLeony Arreaga, Derick AntonioDelgado Kloos, Carlos2021-01-132021-01-132015-06-01Ruipérez-Valiente, J. A., Muñoz-Merino, P. J., Leony, D., & Delgado Kloos, C. (2015). ALAS-KA: A learning analytics extension for better understanding the learning process in the khan academy platform. Computers in Human Behavior, 47, 139-1480747-5632https://hdl.handle.net/10016/31699The Khan Academy platform enables powerful on-line courses in which students can watch videos, solve exercises, or earn badges. This platform provides an advanced learning analytics module with useful visualizations. Nevertheless, it can be improved. In this paper, we describe ALAS-MA, which provides an extension of the learning analytics support for the Khan Academy platform. We herein present an overview of the architecture of ALAS-KA. In addition, we report the different types of visualizations and information provided by ALAS-MA, which have not been available previously in the Khan Academy platform. ALAS-MA includes new visualizations for the entire class and also for individual students. Individual visualizations can be used to check on the learning styles of students based on all the indicators available. ALAS-MA visualizations help teachers and students to make decisions in the learning process. The paper presents some guidelines and examples to help teachers make these decisions based on data from undergraduate courses, where ALAS-MA was installed. These courses (physics, chemistry, and mathematics) for freshmen were developed at Universidad Carlos HI de Madrid (UC3M) and were taken by more than 300 studentseng© 2014Atribución-NoComercial-SinDerivadas 3.0 EspañaLearning analyticsArchitecturesDecision makingVisualizationsData processingresearch articleTelecomunicacioneshttps://doi.org/10.1016/j.chb.2014.07.002open access139148Computers in Human Behavior47AR/0000015541