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Nano-Scale Phase Separation of Block...
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This document, created by Pennsylvania State University and hosted by the Nanotechnology Applications and Career Knowledge Network, serves as a guide for a laboratory activity where students "cast thin films of the block copolymer formed by the sequential polymerization of styrene and methyl methacrylate." The lab guide includes objectives, required prerequisite knowledge, an introduction to the topic of block copolymer films, step-by-step directions to the three procedures that make up the lab activity, and a grading rubric that includes post-lab questions to test student comprehension. In order to access and download this material, users must complete a free registration.
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How Humans Speak, Sing, Squeak and...
The National Center for Voice and Speech developed this series of mini-courses and tutorials to assist people with difficult concepts in voice production....
High School Biology Resources
The Concord Consortium is a non-profit educational technology group that has been designing teacher-ready tools, from lesson plans to activities, for over two...
Biotechnology Teachers Resources...
Educators assembling lessons on biotechnology will find much to appreciate in this list of teacher resources from the North Carolina Biotechnology Center. Here...
Space Science Institute
The Space Science Institute has built a website geared toward the constructivist learning approach, which posits that learning entails an active and fluid...
Mathematics Illuminated
Everything (mathematics) is illuminated in this excellent thirteen-part series created by Annenberg Media for adult learners and high school teachers. As their...



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AMSER is a portal of educational resources and services built specifically for use by those in Community and Technical Colleges but free for anyone to use.

AMSER is funded by the National Science Foundation as part of the National Science Digital Library, and is being created by a team of project partners led by Internet Scout.
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Reverend Thomas Bayes (1702-1761) was the mathematician who first used probability inductively and established a mathematical basis for probability inference, a means of calculating, from the number of times an event has not occurred, the probability that it will occur in future trials.


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