This project develops a new computational and educational resource, the Distributome, for exploring, discovering and interacting with varieties of probability distributions. The Distributome project leverages the results of successful NSF projects that have been sustained over decades of work in developing interactive learning materials, forging technological advances, and building and sustaining digital libraries; all integrated with an effective dissemination and professional development infrastructure to ensure on-going use. There are several novel features of this project. This resource builds the infrastructure for community based development, expands and validates the distributions' meta-data that is stored, processed, searched, traversed and updated by experts, learners, and educators. The Distributome provides a graphical user interface for interactive exploration of diverse distribution resources, as well as a web-service for query, discovery and computational utilization of these distribution resources by other software programs and tools.
Specifically, this project provides an open (development and utilization), platform-agnostic, extensible and broad framework for navigation, discovery and usage of probability distributions in diverse applications. The entire framework is built using XML/JAVA/HTML/Wiki/MathML/LaTeX and is freely made available to the entire community via www.Distributome.org. The user-base of the Distributome infrastructure includes both educators (integrating these graphical tools and instructional materials in their course curricula and participating in a unique virtual community led by a cadre of activists) and most importantly learners (exploring, validating and understanding the use of probability distributions and models for practical problem solving). Probability modeling is at the root of solving driving biological, engineering, health, physical science, and social problems fundamental to the modern STEM curriculum. The Distributome infrastructure enables representation, demonstration, computation and visualization of a large number of probability distributions, their interrelations and their applications integrated with associated class and out-of-class activities to advance learning.
The Distributome project developed resources for instructors and learners in the field of probability. The project created an open computational infrastructure that can be used as a building block for other projects. It created learning materials such as reference tools, challenge problems, games, and a variety of other materials that help students learn about probability modeling and its value in addressing real-world problems. Finally, the project implemented many professional development opportunities for probability instructors and created a vast array of instructional resources for their use. The project’s hub can be found at the www.distributome.org website and a summary of project outcomes is given below. The impact of the Distributome project is enhanced by the recent growth in probability education nationwide and the burgeoning understanding of the stochastic (not just deterministic) nature of nearly every scientific endeavor. Major accomplishments Infrastructure: Deployed the Distributome server www.Distributome.org Introduced the Distributome Blog www.Distributome.org/blog Introduced the Distributome Game www.distributome.org/V3/DistributomeGame.html Developed open-source Java, HTML and JavaScript library for Navigating the Distributome and exploring distribution properties and inter-distribution relations Developed an HTML Distributome Carousel www.distributome.org/tools.html Introduced Distributome Preferences distributome.org/V3/data/Distributome.xml.Book.pref Computational Tools Developed a large collection of Java and JavaScript probability distribution calculators Designed Simulators and Experiments for different probability distributions Developed the Distributome Navigator www.distributome.org/V3 Instructional Modules Introduced 31 new instructional modules demonstrating the classroom use of the Distributome resources for a wide spectrum of applications Developed 70+ examples of problems and corresponding probability distribution models www.distributome.org/V3/data/DistributomeGame_ProblemExamples.csv Training & Dissemination Validated the Distributome infrastructure in 21 courses at UMich, UAH, OSU, UCLA Trained 17 undergraduate and 5 graduate students at UMich, UAH, OSU, UCLA Organized 8 Distributome Continuing Education Workshops and dissemination events Published 6 peer-reviewed scientific publications reporting on our theoretical, educational and applied R&D efforts
