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BEEweb Serious Games: Free Tutors For Every Student on the Planet

Professor Jordan B. Pollack directs a research lab called DEMO-Dynamical & Evolutionary Machine Organization, at the Computer Science Department of Brandeis University.

BEEweb is his biggest vision ever - free tutors for every student on the planet! Thousands of students who drive each other's learning.

BEEweb is a serious games project based which is focused on k-8 multiplayer educational gaming using a new kind of motivational structure. It turns kids into each other teachers and can scale P2P to millions for free. They have 4 games so far, won 3 "Bessies" and have more on the way. They plan to launch Melobee in the spring (music appreciation/composition/listening) and Historbee by summer.

GeograBEE is a really fun way to learn geography of the United States where two players challenge each other with questions like "Where is the state of Texas?" You can even call up a friend and play GeograBEE with them! 

PatternBEE is a fun game where two players challenge each other with geometric puzzles using a rare version of Tangrams. It is fun and challenging, and build skills in geometry, spatial rotation, problem-solving and creativity. You can even call up a friend and play PatternBEE with them! 

MoneyBEE is a fun game from the creators of SpellBEE where two players challenge each other to solve coin problems, like "Which two coins add up to 30 cents?" It helps develop arithmetic, algebraic and scientific skills, and, besides, its really fun! You can even call up a friend and play MoneyBEE with them!

BEEweb educational multi-player communities harness the Internet to provide every learner with a human tutor who can deliver individual challenges using real-time assessment.

Supported by scientific discoveries made while studying dynamics of complex adaptive systems, BEEweb has developed a new kind of educational technology based on a non-competitive incentive that effectively turns peers into teachers.

DEMO attacks problems in agent cognition using complex machine organizations that are created from simple components with minimal human design effort. They study recurrent neural networks, evolutionary computation, and dynamical systems as substrates.