An Open Repository and analysis tools for fine-grained, longitudinal learner data.

Abstract

We introduce an open data repository and set of associated visualization and analysis tools. The Pittsburgh Science of Learning Center’s “DataShop” has data from thousands of students deriving from interactions with on-line course materials and intelligent tutoring systems. The data is finegrained, with student actions recorded roughly every 20 seconds, and it is longitudinal, spanning semester or yearlong courses. Currently over 110 datasets are stored including nearly 18 million student actions. Most student actions are “coded” meaning they are not only graded as correct or incorrect, but are categorized in terms of the hypothesized competencies or knowledge components neede to perform that action. Researchers have analyzed these data to better understand student cognitive and affective states and the results have been used to redesign instruction and demonstrably improve student learning.