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Evolving a learning analytics platform
Author(s) -
Ari Bader-Natal,
Thomas Lotze
Publication year - 2011
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2090116.2090146
Subject(s) - computer science , flexibility (engineering) , variety (cybernetics) , learning analytics , data science , scalability , analytics , task (project management) , data analysis , world wide web , human–computer interaction , artificial intelligence , data mining , database , statistics , mathematics , management , economics
Web-based learning systems offer researchers the ability to collect and analyze fine-grained educational data on the performance and activity of students, as a basis for better understanding and supporting learning among those students. The availability of this data enables stakeholders to pose a variety of interesting questions, often specifically focused on some subset of students. As a system matures, the number of stakeholders, the number of interesting questions, and the number of relevant sub-populations of students also grow, adding complexity to the data analysis task. In this work, we describe an internal analytics system designed and developed to address this challenge, adding flexibility and scalability. Here we present several examples of typical examples of analysis, discuss a few uncommon but powerful use-cases, and share lessons learned from the first two years of iteratively developing the platform.

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