See how one 5th grade teacher is working on Genius Hour with his students, with a little help from Trello.
Trello is a very useful tool. I'm using it to track the learning interventions we carry out currently. This article is a clear outline of how to use it with a classroom of students for planning and tracking an inquiry project.
Trello allows you to archive cards so if a student decided to reverse a decision and reinstate part of their project, the work would still be accessible.
Links to documents can be imbedded in the cards allowing for quick reference access.
I currently use only the free version of Trello and it has been great. They do offer a 'free month of premium" at some stage once you've been using it for a while.
In C. M. Rubin's interview, Howard Rheingold states: "When I decided to write a book about the essential literacies necessary today—with the aim of using the book as a text for a Stanford course—I decided that the essential literacies are attention, crap detection, participation, collaboration, and network awareness."
"Google Classroom is quietly becoming the most powerful tool in education technology.
"It may lack the visual appeal of iPads, or the student credibility of a BYOD program. It may not be as forward-thinking as we’d like here at TeachThought, but Google Classroom excels in providing solutions for a broad swath of teachers who have a variety of expertise and comfort level with education technology. It also uses Google’s familiar template that many teachers have used for years. As such, it scratches the itch for many teachers in many classrooms right here, right now.
"So below are (at least) 60 thing you can do with Google Classroom. We’ll be updating this list as new ideas come in, the platform changes, and we learn more about its subtleties on our own."
Two great trends are evident in the evolution of life on Earth: towards increasing diversification and towards increasing integration. Diversification has spread living processes across the planet, progressively increasing the range of environments and free energy sources exploited by life. Integration has proceeded through a stepwise process in which living entities at one level are integrated into cooperative groups that become larger-scale entities at the next level, and so on, producing cooperative organizations of increasing scale (for example, cooperative groups of simple cells gave rise to the more complex eukaryote cells, groups of these gave rise to multi-cellular organisms, and cooperative groups of these organisms produced animal societies). The trend towards increasing integration has continued during human evolution with the progressive increase in the scale of human groups and societies. The trends towards increasing diversification and integration are both driven by selection. An understanding of the trajectory and causal drivers of the trends suggests that they are likely to culminate in the emergence of a global entity. This entity would emerge from the integration of the living processes, matter, energy and technology of the planet into a global cooperative organization. Such an integration of the results of previous diversifications would enable the global entity to exploit the widest possible range of resources across the varied circumstances of the planet. This paper demonstrates that it's case for directionality meets the tests and criticisms that have proven fatal to previous claims for directionality in evolution.
The direction of evolution: The rise of cooperative organization John E. Stewart
Chinese search giant Baidu says it has invented a powerful supercomputer that brings new muscle to an artificial-intelligence technique giving software more power to understand speech, images, and written language.
The new computer, called Minwa and located in Beijing, has 72 powerful processors and 144 graphics processors, known as GPUs. Late Monday, Baidu released a paper claiming that the computer had been used to train machine-learning software that set a new record for recognizing images, beating a previous mark set by Google.
“Our company is now leading the race in computer intelligence,” said Ren Wu, a Baidu scientist working on the project, speaking at the Embedded Vision Summit on Tuesday. Minwa’s computational power would probably put it among the 300 most powerful computers in the world if it weren’t specialized for deep learning, said Wu. “I think this is the fastest supercomputer dedicated to deep learning,” he said. “We have great power in our hands—much greater than our competitors.”
Computing power matters in the world of deep learning, which has produced breakthroughs in speech, image, and face recognition and improved the image-search and speech-recognition services offered by Google and Baidu.
The technique is a souped-up version of an approach first established decades ago, in which data is processed by a network of artificial neurons that manage information in ways loosely inspired by biological brains. Deep learning involves using larger neural networks than before, arranged in hierarchical layers, and training them with significantly larger collections of data, such as photos, text documents, or recorded speech.
So far, bigger data sets and networks appear to always be better for this technology, said Wu. That’s one way it differs from previous machine-learning techniques, which had begun to produce diminishing returns with larger data sets. “Once you scaled your data beyond a certain point, you couldn’t see any improvement,” said Wu. “With deep learning, it just keeps going up.” Baidu says that Minwa makes it practical to create an artificial neural network with hundreds of billions of connections—hundreds of times more than any network built before.
A paper released Monday is intended to provide a taste of what Minwa’s extra oomph can do. It describes how the supercomputer was used to train a neural network that set a new record on a standard benchmark for image-recognition software. The ImageNet Classification Challenge, as it is called, involves training software on a collection of 1.5 million labeled images in 1,000 different categories, and then asking that software to use what it learned to label 100,000 images it has not seen before.
Software is compared on the basis of how often its top five guesses for a given image miss the correct answer. The system trained on Baidu’s new computer was wrong only 4.58 percent of the time. The previous best was 4.82 percent,reported by Google in March. One month before that, Microsoft had reportedachieving 4.94 percent, becoming the first to better average human performance of 5.1 percent.
"While technology is an important part of the education equation, it doesn’t tell the whole story. Teachers play a bigger role than ever in developing an engaging well-rounded curriculum, though integrating technology into the mix presents its own unique set of challenges. Many teachers have been reluctant to replace their print materials due to cost and dissatisfaction with the available digital options. According to the MDR 2014 State of the K–12 Market Report, there’s a growing demand for solutions that improve teaching and personalized learning and educators are willing to consider new instructional models.
"So, how do we build an engaging curriculum based on the components of critical thinking, while incorporating technology into the mix – without sacrificing the basics? Here are a few simple tips to integrate technology into almost any lesson."
Love the blog all about it suggestion to get kids thinking, collating and collaborating at all stages. Also from a UDL perspective the idea of making learning as visual as possible in more situations is great for our students with specific learning needs.
With all the "sky is falling" cries about American students reading less, I often wonder why we don't track how much reading and writing students do daily on social media. Bring social media into your lessons is crucial to helping students develop critical thinking about the media many of them consume and create in large amounts every day.
In this article from Edutopia, Dave Guymon suggests that pairing visual or non-linguistic ideas with text-based ones can help students recall or interpret...
Visual connectors, UDL and accessible learning through social media strategies.
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