An overview of data warehousing and OLAP technology
ACM SIGMOD Record
A Theory of Fun for Game Design
A Theory of Fun for Game Design
Practical guide to controlled experiments on the web: listen to your customers not to the hippo
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Investigating the core group effect in usage of resources with analytics
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
| Hi-index | 0.00 |
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.