Ros, S.Lázaro, J. C.Robles-Gómez, A.Caminero, A. C.Tobarra, L.Pastor, R.2017-12-262017-12-262017-10-18Ros, S., Lázaro, J. C., Robles-Gómez, A., Caminero, A. C., Tobarra, L., & Pastor, R. (2017). Analyzing Content Structure and Moodle Milestone to Classify Student Learning Behavior in a Basic Desktop Tools Course. In J. M. Dodero, M. S. Ibarra Sáiz, & I. Ruiz Rube (Eds.), Fifth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM’17) (Cádiz, Spain, October 18-20, 2017) (pp. Article 42). New York, NY, USA: ACM. doi:10.1145/3144826.3145392978-1-4503-5386-1http://repositorio.grial.eu/handle/grial/1095This paper analyzes the content structure and Moodle milestone to classify the students’ learning behavior for a basic desktop-tools on-line virtual course. The data collection phase is completed for a Learning Analytics (LA) process as a first step; by using the gen-erated interactions among students, and with learning resources, assessments, and so on. A first exploratory data analysis study is also done with the extracted indicators (or features) of all interac-tions to classify them in five traits. A multidimensional parameter reduction has been implemented based on Principal Component Analysis (PCA), an example of it is also given.enLearning Analytics (LA)IndicatorsPrincipal Component Analysis (PCA)MoodleEx-ploratory Data Analysis (EDA)Article