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http://repositorio.grial.eu/handle/grial/1095
Title: | Analyzing Content Structure and Moodle Milestone to Classify Student Learning Behavior in a Basic Desktop Tools Course |
Authors: | Ros, S. Lázaro, J. C. Robles-Gómez, A. Caminero, A. C. Tobarra, L. Pastor, R. |
Keywords: | Learning Analytics (LA) Indicators Principal Component Analysis (PCA) Moodle Ex-ploratory Data Analysis (EDA) |
Issue Date: | 18-Oct-2017 |
Publisher: | ACM |
Citation: | Ros, 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:10.1145/3144826.3145392 |
Abstract: | This 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. |
URI: | http://repositorio.grial.eu/handle/grial/1095 |
ISBN: | 978-1-4503-5386-1 |
Appears in Collections: | Publications |
Files in This Item:
File | Description | Size | Format | |
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a42-ros-preprint.pdf | Article | 252,15 kB | Adobe PDF | View/Open |
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