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"We live in a stressful world, and the stress is heightened for students and educators when it's time to prepare for high-stakes tests. When test scores are tied to school funding, teacher evaluations, and students' future placement, the consequences of these stressors can be far-reaching. From a neurological perspective, high stress disrupts the brain's learning circuits and diminishes memory construction, storage, and retrieval. Neuroimaging research shows us that, when stresses are high, brains do not work optimally, resulting in decreased understanding and memory. In addition, stress reduces efficient retrieval of knowledge from the memory storage networks, so when under pressure students find it harder to access information previously studied and learned. Get the best of Edutopia in your inbox each week. Students (and their parents) often interpret suboptimal standardized test scores as a measure of the students' limitations in intelligence and potential. The consequence is a loss of confidence, further activating their brains' stress response, making it more difficult for them to employ their cognitive resources and knowledge during the tests themselves."

"Released in 2013, the NGSS was created to align science education with how scientists actually work and think. It encourages students to learn science content and concepts deeply by using critical thinking and primary investigation skills. Adopted by 18 states (with as many as 40 interested and in the process), the standards define science education through core concepts (such as wave properties), practices (like analyzing and interpreting data ) and crosscutting concepts (like cause-and-effect). Some of the NGSS guidelines directly overlap with the practices listed in the K-12 Computer Science framework and the new CSTA Computer Science standards. Here's a doodle that illustrates how the two subjects overlap. "

Understanding how mobile, global and virtual social networks influence our interpretation of socio-cultural theories of learning might allow us to better understand the interplay of settings and contexts within which learning occurs and in doing so better understand how learning may be facilitated.

"Regardless of whether you think every infant needs an iPad, I think we can all agree that technology has changed education for the better. Today's learners now enjoy easier, more efficient access to information; opportunities for extended and mobile learning; the ability to give and receive immediate feedback; and greater motivation to learn and engage. We now have programs and platforms that can transform learners into globally active citizens, opening up countless avenues for communication and impact. Thousands of educational apps have been designed to enhance interest and participation. Course management systems and learning analytics have streamlined the education process and allowed for quality online delivery. But if we had to pick the top ten, most influential ways technology has transformed education, what would the list look like? The following things have been identified by educational researchers and teachers alike as the most powerful uses of technology for learning. Take a look. 1. Critical Thinking In Meaningful Learning With Technology, David H. Jonassen and his co-authors argue that students do not learn from teachers or from technologies. Rather, students learn from thinking-thinking about what they are doing or what they did, thinking about what they believe, thinking about what others have done and believe, thinking about the thinking processes they use-just thinking and reasoning. Thinking mediates learning. Learning results from thinking. So what kinds of thinking are fostered when learning with technologies? Analogical If you distill cognitive psychology into a single principle, it would be to use analogies to convey and understand new ideas. That is, understanding a new idea is best accomplished by comparing and contrasting it to an idea that is already understood. In an analogy, the properties or attributes of one idea (the analogue) are mapped or transferred to another (the source or target). Single analogies are also known as sy

"In 2006 there was a term that started to grow in the United States-- STEM education (Science, Technology, Engineering and Math). The basis of the STEM movement was the growing concern that our students were not prepared for the high-tech jobs of the future. Just a year later a well-know researcher, Georgette Yakman, announced the need to include the arts in STEM programs; thus STEM became STEAM. Georgette took the inclusion of the arts and expanded on how it relates to the other STEM subjects. Her well-know quote is "Science and technology, interpreted through engineering and the arts, all based in elements of mathematics." This is a rich beginning to our dive into the 21st century job market... but! We have lost sight of one very important aspect of our education and all jobs, be they high-tech, low-tech, or no-tech. What about the importance of reading? Without the ability to read and write, there is not a job to be found for which STEM or STEAM education is going to be enough preparation. ELA, or English Language Arts, is a critical component of the core standards. There are also standards that help reference reading and writing for science and the technical subjects. The notion seems to be that reading is still a critical element in any student's success. Why not give it its proper place... STEM to STEAM to STREAM, standing for Science, Technology, Reading, Engineering, Arts and Math. "

"Recently, I've also been fascinated by the way the human mind interprets visual symbols. From doodling to reading and writing text, the brain is wired with a proclivity for visual sensory ability. In order to help students harness this power, we have been trying our hand at visual notes and sketchnoting in class. Then I decided to try some lessons with infographics."

"In the latest issue of Nature Human Behavior, Przybylski and coauthor Amy Orben use a novel statistical method to show why scientists studying these colossal data sets have been getting such different results and why most of the associations researchers have found, positive and negative, are very small-and probably not worth freaking out about."

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