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"Bloom's Revised Taxonomy breaks each learning stage (remember, understand, apply, analyze, evaluate and create) into four separate levels of knowledge. These levels include the factual, conceptual, procedural, and metacognitive. Together the levels of knowledge are making incremental movements from a factual understanding, to the personal command and realization of the learning process. The revised taxonomy also lists two cognitive processes within the applying stage: executing and implementing.1 These two processes illustrate the range of thinking skills possible within a stage. Executing requires the application of factual knowledge and refers to the ability to carry out learned procedures such as solving a long division problem. On the other hand, implementing reaches up into the metacognitive level and demands that students be able to apply learned skills to a task that initially appears to be an unrelated to prior learning experiences. "

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"Many teachers are starting to code in math classrooms.  I have integrated coding in math initially to start a coding club.  I soon realized that coding is best suited as an option in learning.  There are many benefits to coding that I have found.  The benefits are too extensive for one blog post.  So I am starting a series of blogs to emphasize the advantages. For my first post, I would like to highlight that coding is an excellent application of math skills.  All math can be applied to daily life.  As teachers, we have to apply learning so that our students see relevance.  Coding applies so beautifully to math.  It emphasizes these skills so naturally."

"The shift toward applying more executive function (EF) within learning and assessment will cause some discomfort in teachers and students. The transition will not eliminate the need for memorization, as automatic use of foundational knowledge is the toolkit for the executive functions. Memorization, however, will not be adequate as meaningful learning becomes more about applying, communicating and supporting what one knows. "

" want to quickly share with you this awesome little graphic I came across in iLearn different. The graphic outlines the different steps teachers and educators can follow to apply SAMR model to iPad apps used in the classroom. " This graphic is not intended to be an exhaustive list but it will give you an idea of how you can integrate the SAMR Model into your teaching and learning. ""

"This isn't just for people with traditional careers and family lives. It applies to all families regardless of how busy your schedule or important your job, In her book "The Obamas," author Jodi Kanter highlights the President's commitment to having dinner with his family five times a week. Unfortunately in the hustle and bustle of today's digital world, the art of the family dinner has been drained out of many homes with device interaction replacing face-to-face connection. During a panel discussion hosted by Common Sense Media that focused on raising caring kids in a digital world, Howard Gardner of the Harvard Graduate School of Education shared that many families are not even sure what to do at dinner time if all are free of digital devices. If this applies to your family, don't despair. Below are ideas for dinner time activities for each day of the week. These suggestions should serve as a helpful way to ensure dinner time is a valuable experience for families."

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How can your learning network help you? By helping you to sift through all the data to identify the information that will be most useful to you. By helping you to identify learning resources and opportunities. By coaching you and answering your questions as you try to apply your learning to your work. By sharing their wisdom with you through dialogue. Building a personal learning network is requires that you not only seek to learn from others, but also that you also help others in the network learn. Even when you are a novice in a field of learning, you can still make contributions. Did you read an article that might be of interest to others? Then distribute it to other in your network with a short note that you thought they might find it interesting. Did you hear of a conference on the subject? Let others know about the program and speakers and, if you attend, circulate your notes and papers you collect to other network members. A personal learning network can be your most powerful learning tool no matter what the subject.

The greatest challenge is moving beyond the glitz and pizzazz of the flashy technology to teach true literacy in this new milieu. Using the same skills used for centuries-analysis, synthesis, and evaluation-we must look at digital literacy as another realm within which to apply elements of critical thinking... Literacy includes the ability to read and interpret media (text, sound, images), to reproduce data and images through digital manipulation, and to evaluate and apply new knowledge gained from digital environments. According to Gilster,5 the most critical of these is the ability to make educated judgments about what we find online.

"That said, the handy infographic below takes a look at 4 ways technology is changing how people learn. The things that I find striking - and important- about this particular graphic is how simple the concept is. These four general concepts can be applied across the board: to learners of all ages, in all subjects, in any area of the world or for any type of learner. Take a look and see what you think: are there any other very general principles of how technology is changing learning that can be widely applied? Weigh in by leaving a comment below, mentioning @Edudemic on Twitter or leaving your thoughts on our Facebook page."

"True Project Based Learning (PBL) challenges students to acquire deeper knowledge of a concept by establishing connections outside their classroom. According to the research on PBL, the main tenets are to create real world connections, develop critical thinking skills, foster structured collaboration, motivate student driven work, and enable a multifaceted approach. Similarly, coding applies all of these core tenets as programs require logical thinking, team work, a variety of tools, and - most importantly - perseverance on the part of the student. Consider the potential of applying the challenges of coding to the proven successful tenets of PBL."

Despite this being a 'thinking' conference, despite us all being advocates for structured and scaffolded models of thinking, not one group had applied any thinking routines, utilised a collaborative planning protocol or talked about applying an inquiry model or design thinking cycle. It wasn't that we didn't know about them. It wasn't that we don't know how to use them. It wasn't that we don't value them. We had all the knowledge we could desire on the how to and the why of a broad set of thinking tools and anyone of these would have enhanced the process, but we did not use any of them. Why was this the case and what does this reveal about our teaching of these methods to our students?

"The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers - harnessed to algorithms refined over the past decade - are driving an explosion of applications in everything from medical physics to materials, as Marric Stephens discovers When your bank calls to ask about a suspiciously large purchase made on your credit card at a strange time, it's unlikely that a kindly member of staff has personally been combing through your account. Instead, it's more likely that a machine has learned what sort of behaviours to associate with criminal activity - and that it's spotted something unexpected on your statement. Silently and efficiently, the bank's computer has been using algorithms to watch over your account for signs of theft. Monitoring credit cards in this way is an example of "machine learning" - the process by which a computer system, trained on a given set of examples, develops the ability to perform a task flexibly and autonomously. As a subset of the more general field of artificial intelligence (AI), machine-learning techniques can be applied wherever there are large and complex data sets that can be mined for associations between inputs and outputs. In the case of your bank, the algorithm will have analysed a vast pool of both legitimate and illegitimate transactions to produce an output ("suspected fraud") from a given input ("high-value order placed at 3 a.m."). But machine learning isn't just used in finance. It's being applied in many other fields too, from healthcare and transport to the criminal-justice system. Indeed, Ge Wang - a biomedical engineer from the Rensselaer Polytechnic Institute in the US who is one of those pioneering its use in medical imaging - believes that when it comes to machine learning, we're on the cusp of a revolution."

"At the end of 2016, I found myself mentally exhausted and barely able to string together a coherent thought or formulate an original idea. As I swiped through my social media feeds for inspiration-or maybe procrastination-a nagging feeling hit. I needed a break from screen time. Pediatricians, psychologists, and neuroscientists warn of potential negative consequences associated with constant mental stimulation as a result of interacting with our devices. Without a screen-free space for my brain to relax, stop firing, and just think, I felt incapable of significant mental processing. I could blame the technology for thwarting my attempts at creative thought, or I could blame myself for taking the easy route and using my devices to constantly stimulate my brain. Though I chose to blame myself, I am finding a lot of support for the idea of blaming technology when discussing the idea of screen time. Get the best of Edutopia in your inbox each week. Mobile devices have the potential to provide amazing learning opportunities as well as great distractions. They can further social interactions to help us build stronger connections in our communities, or allow us to destroy relationships by hiding behind a screen. In the book The Triple Focus: A New Approach to Education, authors Daniel Goleman and Peter Senge describe three essential skills for surviving in a society increasingly dominated by internet-enabled devices: focusing on ourselves, tuning in to others, and understanding the larger world. While the authors apply these concepts to the broader field of social and emotional learning, these same foci also apply as we address the issue of screen time with our students and children."

"From autonomous vehicles, predictive analytics applications, facial recognition, to chatbots, virtual assistants, cognitive automation, and fraud detection, the use cases for AI are many. However, regardless of the application of AI, there is commonality to all these applications. Those who have implemented hundreds or even thousands of AI projects realize that despite all this diversity in application, AI use cases fall into one or more of seven common patterns.  The seven patterns are: hyperpersonalization, autonomous systems, predictive analytics and decision support, conversational/human interactions, patterns and anomalies, recognition systems, and goal-driven systems. Any customized approach to AI is going to require its own programming and pattern, but no matter what combination these trends are used in, they all follow their own pretty standard set of rules. These seven patterns are then applied individually or in various combinations depending on the specific solution to which AI Is being applied."

"Anyone who says you can't apply computational thinking and digital learning strategies to strengthen students' writing skills is wrong. To the contrary, this innovative learning style helps students hone critical-thinking skills across every discipline. In my classroom, I teach students computational thinking through free materials from Ignite My Future in School, a partnership between Tata Consultancy Services and Discovery Education. I especially enjoy using their Curriculum Connectors, online resources for teachers across disciplines to help their students apply computational thinking techniques. The core tenets of computational thinking are the building blocks that help my students become better learners and problem-solvers across every area of their work-from all areas of reading and language arts. Here's how five core computational thinking approaches help my students build stronger critical thinking and writing skills:"