The Data Analytics and Visualization Efficiency Framework for xAPI and the Total Learning Architecture
If the objective is to analyze, interpret, and visualize micro-level behavior-driven learning, we need a framework for analysis and visualization which aligns with xAPI, xAPI Profiles, and the Total Learning Architecture (TLA).
Enter Project DAVE — a framework featuring
Project DAVE is funded by the Advanced Distributed Learning Initiative at the U.S. Department of Defense.
We're looking for learning and data professionals as well as the executives and business users of learning data to help us create an open source framework that meets the needs of real users in industry, government, and academia.
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By increasing consistency of the way data is represented and visualized through the TLA, Project DAVE will increase value of xAPI as a data asset for implementers and end users of distributed learning.
DAVE will bring structure to analytics and visualization within and across the Total Learning Architecture.
Commonly-used data visualization approaches often do not align with the types of data available in an xAPI statement and therefore xAPI-specific data visualizations are often necessary.
As an open source framework, DAVE provides developers and analytics with models, prototypes, and specifications for analyzing, interpreting, and visualizing xAPI data.
As a framework serving the needs of the xAPI community, DAVE is all about helping to turn learning data into business intelligence.
Now is the best time to contribute your thoughts. Throughout 2018, we'll be asking key decision makers what they need from the data produced in distributed learning environments.