Peeking into the black box: visualising learning activities
| Autor: | Raquel M. Crespo Garcia, Martin Wolpers, Maren Scheffel, Carlos Delgado Kloos, Abelardo Pardo, Katja Niemann |
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| Přispěvatelé: | Publica, García, Raquel M Crespo, Pardo, Abelardo, Kloos, Carlos Delgado, Niemann, Katja, Scheffel, Maren, Wolpers, Martin |
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
Experimental datasets
Computer science Process (engineering) Learning analytics Educational datasets Observation computer.software_genre Education Visualisation Student monitoring Data visualization Time management Set (psychology) Telecomunicaciones business.industry Data science Learning activity Virtual machine Computer Science Applications Visualization Scatter plot Learning activity visualisation Datatel Attention metadata Technology-enhanced learning business computer Data visualisation |
| Zdroj: | e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid instname |
| Popis: | Learning analytics has emerged as the discipline that fosters the learning process based on monitored data. As learning is a complex process that is not limited to a single environment, it benefits from a holistic approach where events in different contexts and settings are observed and combined. This work proposes an approach to increase this coverage. Detailed information is obtained by combining logs from a LMS and events recorded with a virtual machine given to the students. A set of visualisations is then derived from the collected events showing previously hidden aspects of an experience that can be shown to the teaching staff for their consideration. The visualisations presented focus on different learning outcomes, such as self learning, use of industrial tools, time management, information retrieval, collaboration, etc. Depending on the information to convey, different types of visualisations are considered, ranging from graphs to starbusts and from scatter plots to heatmaps. Work partially funded by the projects: Adaptation of learning scenarios in the .LRN platform based on Contextualized Attention Metadata (CAM) (DE2009-0051), Learn3 (\Plan Nacional de I+D+I" TIN2008-05163/TSI), EEE (\Plan Nacional de I+D+I" TIN 2011-28308-C03-01), and Emadrid: Investigación y desarrollo de tecnologías para el e-learning en la Comunidad de Madrid (S2009/TIC-1650). Publicado |
| Databáze: | OpenAIRE |
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