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"Here is a great Google Doc tip that helps me a lot with my studies in university. As a graduate student, most of my reading assignments and hand-outs come in the form of PDFs and some of these documents are only scanned versions of the original documents. Often times, these PDFs are low-quality as they are poorly scanned which makes reading them a real pain in the butt. Also, scanned PDFs do not allow you to do much on them: You can not annotate or edit text on them. However, there is a workaround to this using Google Docs OCR(Optical Character Recognition). Optical Character Recognition(OCR) lets you convert scanned PDFs or any image that include text in it into text documents using automated computer algorithms in Google Docs. Once converted, you can then edit and annotate the text as you like. Here is how to activate OCR on your Drive."

"While not every student might want to write their own software, understanding the big ideas of coding is a skill that all students would benefit from, even the very young ones. Understanding the key ideas of computational thinking - identifying patterns, thinking algorithmically, manipulating data, solving real problems, etc - is an important step in helping our students build mastery over their world. This presentation aims to take you on a guided tour through some of the resources available to your students to help them learn the principles of creating code. It starts by looking at a range of desktop and mobile apps suitable for teaching very young students to program, right through to tools and websites that can help your older students learn to hack code, and much more."

"Here's one way to get kids excited about programming: a "robot garden" with dozens of fast-changing LED lights and more than 100 origami robots that can crawl, swim and blossom like flowers. A team from MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and the Department of Mechanical Engineering has developed a tablet-operated system that illustrates their cutting-edge research on distributed algorithms via robotic sheep, origami flowers that can open and change colors and robotic ducks that fold into shape by being heated in an oven."

"We all have them, some good and some bad. We pick them up from friends, family, and even strangers. But we may not recall who we picked them up from or when they began. Because we've practiced them over and over, these seemingly thoughtless repeated habits or behaviors, the pathways in our brain have become so broad, fast, and efficient in carrying them out that we do them automatically without even thinking. Yet these unconscious habits and behaviors add structure and order to our lives and help us to make sense of the world we live in. Our classrooms are full of them. We teachers are pros when it comes to employing and modeling good habits and routines that enable us to manage and carry out the many tasks and demands of teaching. And when it comes to teaching mathematics, we model and teach our students how to carry out procedures and algorithms flawlessly. But why is it that these same students often struggle when confronted with a problem to which the immediate answer is unknown?"

"omputational thinking is one of the core objectives that runs through the computing program of study in England from Key Stage 1 to Key Stage 4. Before computers can be used to solve a problem, computational thinking refers to understanding the problem itself and the ways in which it could be resolved. Software engineers and computer scientists for example, routinely engage in computational thinking. As a higher order thinking skill, computational thinking has applications both across and beyond the school curriculum. There are four key techniques to computational thinking: Abstraction - focusing on the important information only, ignoring irrelevant details Algorithms - developing a step-by-step solution to the problem Decomposition - breaking down the problem into smaller, more manageable parts Logic - looking for similarities among and within problems Learning to program is one of the best ways to develop computational thinking, as it uses each one of these techniques. My intention here is to show an example of a lesson in which computational thinking is taught at Key Stage 1 (5 to 7 years) through programming. I took the lesson plan (attached above) from The Barefoot Computing Project and I taught it to my 1st grade class last week.  It required the children to work in pairs to create step-by-step instructions through pictures.  The pairs then swapped each other's instructions, which they used to draw the 'crazy character' that the other child had in mind."

"Today's students will enter a workforce that is powerfully shaped by computing. To be successful in a changing economy, students must learn to think algorithmically and computationally, to solve problems with varying levels of abstraction. These computational thinking skills have become so integrated into social function as to represent fundamental literacies. However, computer science has not been widely taught in K-12 schools. Efforts to create computer science standards and frameworks have yet to make their way into mandated course requirements. Despite a plethora of research on digital literacies, research on the role of computational thinking in the literature is sparse. This conceptual paper proposes a three dimensional framework for exploring the relationship between computational thinking and literacy through: 1) situating computational thinking in the literature as a literacy; 2) outlining mechanisms by which students' existing literacy skills can be leveraged to foster computational thinking; and 3) elaborating ways in which computational thinking skills facilitate literacy development."

"Computational thinking isn't new. Three decades ago, Seymour Papert introduced computational thinking when he developed the concept of bricolage, which is the construction of something new from many sources. He rightly understood the significance of computers, and with computational thinking, he surmised that they would not only be an integral part of our educational process, but we would need to acquire new ways for learning when using computers. In essence, the bricoleur builds knowledge by engaging in a process of building precise steps that encourage the construction of knowledge. Papert recognized that over time, the learner's theory may change as the result of refining his or her responses in any of the four stages of computational thinking. Even before Papert's work, however, educational visionaries insisted that the way to solve problems in any field was by adopting sequential problem-solving methods, which became algorithmic or computational thinking. In short, we use computational thinking (CT) to solve problems."

"Math has been a traditionally thorny subject in many American schools. Lots of children dislike math and many more adults stopped taking mathematics as soon as they are able, even when they were successful in their classes. At the same time, mathematical thinking is a crucial part of many of the most exciting and growing careers in science, technology, engineering and math, not to mention important for a general understanding of the mathematical world around us. So, what can U.S. math educators do to shift this dynamic? Stanford Mathematics Education Professor Jo Boaler is championing a dramatic shift in how many math teachers approach instruction. Rather than focusing on the algorithms and procedures that make mathematics feel like a lock-step process -- with one right way of solving problems -- Boaler encourages teachers to embrace the visual aspects of math. She encourages teachers to ask students to grapple with open-ended problems, to share ideas and to see math as a creative endeavor. She works with students every summer and says that when students are in a math environment that doesn't focus on performance, speed, procedures, and right and wrong answers they thrive. They even begin to change their perceptions of whether they can or can't do math."

"All it takes is a single selfie. From that static image, an algorithm can quickly create a moving, lifelike avatar: a video not recorded, but fabricated from whole cloth by software. With more time, Pinscreen, the Los Angeles start-up behind the technology, believes its renderings will become so accurate they will defy reality. "You won't be able to tell," said Hao Li, a leading researcher on computer-generated video at USC who founded Pinscreen in 2015. "With further deep-learning advancements, especially on mobile devices, we'll be able to produce completely photoreal avatars in real time.""

"Business adoption of artificial intelligence is accelerating, fueled by an explosion of data, the rapid growth in cloud computing and the emergence of advanced algorithms.1 In a survey of IT decision-makers that my company, CCS Insight, conducted in July 2017, 58 percent of respondents said they are using, testing or researching the use of artificial intelligence (AI) in their organizations.  Respondents also estimated that as much as 30 percent of their business applications would be enhanced with machine learning within the next 24 months - a bullish view, considering the technology's well-documented problems with trust, cost and the lack of skills needed to train machine learning systems."

"Computer science education is not a new field. Much of what we know about the pedagogy and content for elementary students comes from Seymour Papert's research on teaching elementary students to code back in the 1970's and 80's. But, as we shift from labs and one-off classrooms to a broad expansion for all students in every classroom K-12, we are seeing changes to how computer science is taught. This means we are working in a rapidly evolving field (insert metaphor of building a plane while flying it). Over time, we have gone from a focus on coding (often in isolation) to a more broad idea of computer science as a whole, and now to the refined idea of computational thinking as a foundational understanding for all students. Pause. You may be asking, "But wait, what's computational thinking again?" In her book Coding as a Playground, Marina Umaschi Bers explained: "The notion of computational thinking encompasses a broad set of analytic and problem-solving skills, dispositions, habits, and approaches most often used in computer science, but that can serve everyone." More simply, you can think of computational thinking as the thought processes involved in using algorithms to solve problems. Sheena Vaidyanathan writes some good articles explaining the differences between computer science, coding, and computational thinking here and here."

"Coding is the ability to write step by step instructions (programs) for a computer to understand to complete a task. The Hour of Code website has tons of ready to go online activities that get students to write code that results in a number of cool outcomes, such as making a monster dance, creating avatars, remixing music or making a game. When students complete these easy tutorials they learn these important skills- logic, problem solving, fitting puzzle pieces together, selection, instructional writing, editing, revision, and creation. Below are some great websites to find engaging coding projects that take an hour or less. Most require no registration! Just provide students with a quick introduction to the task on the projector and the link for them to get started. I would highly recommend doing the activity first. In the next post I will introduce you to unplugged activities, which get students to focus on specific coding skills you will notice in these activities, which include working with puzzles, providing good instructions, problem solving and algorithms."

"Math matters for computer science because it teaches students how to use abstract language, work with algorithms, self-analyze their computational thinking, and accurately modeling real-world solutions."

"An artificial intelligence algorithm has outperformed humans in a reading comprehension test for the first time"

"Benefits of Coding At the heart of computational thinking - and mathematics - is abstraction. When children write code, they come to… understand in a tangible way the abstractions that lie at the heart of  mathematics, dynamically model mathematics concepts and relationships, gain confidence in their own ability and agency as mathematics learners. Computer coding is creating a buzz in education. Prime Minister Justin Trudeau recently said, "We need to do a lot better job of getting young people to understand what coding is and how it's important, how to program, how to problem solve, how to create the most elegant algorithm possible."1 BC recently announced that computer coding will be added to all grades of the K-12 curriculum, and Nova Scotia has made a similar announcement. The trend of adding some form of computer coding to curriculum is an international phenomenon; in 2014, England mandated a coding curriculum for all K-12 students."

The Bebras cards are designed to enable pupils to develop their computational thinking skills, whilst at the same time providing an introduction to more advanced computing concepts. Computational Thinking Each card is aligned to one of the following computational thinking concepts, which are indicated in the top right-hand corner of each card.  Patterns  Algorithms  Logic  Abstraction Task Difficulty The difficulty of the task on each card is indicated by the icon in the bottom right-hand corner.  = Easy  = Medium  = Hard Answers and Other Materials Answers to tasks, ideas for teaching and national curriculum links can be found at: www.bebras.uk Tip: pupils will need an exercise book or a piece of paper in order to record their answers to each activity

"In this half-hour presentation at Education Week's Leaders To Learn From event in Washington, Aileen Owens, director of technology and innovation for Pennsylvania's South Fayette school district, describes her efforts around cultivating students' "computational thinking." At the event, Owens was recognized as an exceptional school district leader for her leadership in innovation in curriculum. Since being hired at South Fayette in 2010, Owens' passion has been on cultivating students' "computational thinking." That includes coding. But the real emphasis is on helping students learn to problem-solve; to think algorithmically, in step-by-step sequences; to debug and revise; and to work with abstract concepts."

"In an era of breakneck change and tech innovation, evaluating dyslexia in young students looks much the same today as it has in the past: A struggling reader's parents and teachers might sit down, gather information and assess the child on their strengths and weaknesses to determine a diagnosis and appropriate interventions. Often this is done via paper tests-despite the growing usage of predictive analytics in schools, where there are seemingly as many data dashboards as students in a classroom. All that's to say, it seems like an industry almost too tempting for deep-pocketed tech investors and an ambitious startup with an eye on using machine learning to trim the fat. "Today's methods are quite cumbersome," explains Frederik Wetterhall, the CEO and co-founder of Lexplore, a company that has devised a dyslexia screening tool that pairs eye tracking cameras with AI and algorithms. "With paper- and pen-based tests, it's quite hard to read the results and takes a lot of time. [Educators] ask, 'Who are the kids we think have difficulties?' and they miss a lot of kids.""

"At Excel Public Charter School, we place a strong focus on integrating computational thinking within our curriculum across all disciplines. To us, computational thinking means solving hard problems of all kinds using ideas from computer science. These include algorithmic thinking, decomposition, pattern recognition and abstraction, as well as confidence in the face of ambiguity and tenacity to persist through challenges requiring iteration and experimentation. Our computational thinking curriculum is freely provided here for you to incorporate within your own classrooms. You'll find lessons divided into disciplines along the top of this and every other page. With these lessons and projects, we hope you will encourage your students to grow and flourish as computational thinkers, ready to face the real-world challenges of their generation!"

The Bebras cards are designed to enable pupils to develop their computational thinking skills, whilst at the same time providing an introduction to more advanced computing concepts. Computational Thinking Each card is aligned to one of the following computational thinking concepts, which are indicated in the top right-hand corner of each card.  Patterns  Algorithms  Logic  Abstraction Task Difficulty The difficulty of the task on each card is indicated by the icon in the bottom right-hand corner.  = Easy  = Medium  = Hard Answers and Other Materials Answers to tasks, ideas for teaching and national curriculum links can be found at: www.bebras.uk Tip: pupils will need an exercise book or a piece of paper in order to record their answers to each activity