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As schools reopen, officials reflect on first months of coronavirus device lending programs

School districts across the United States had varying experiences with trying to get devices to every child at the onset of the COVID-19 pandemic.

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Every teacher and administrator was faced with an unprecedented problem when schools across the country were shut for the year in March to help states deal with the COVID-19 pandemic. Most schools were given barely a few weeks to suddenly prepare students, parents, and themselves for remote learning, which is only possible with some kind of device. While hundreds of districts were lucky enough to already have 1:1 device lending programs in place for all their students, others scrambled to order and deliver millions of iPads and Chromebooks just in time for the end of spring break.

SEE: Coronavirus: Critical IT policies and tools every business needs (TechRepublic Premium)

“A lot of districts are building the plane while they’re flying it. Some districts were better prepared for this online transition than others but it’s all over the map,” said Susan Bearden, chief innovation officer with the Consortium for School Networking. 

“Districts that were better prepared for this before it happened are probably handling it well. Other districts just were not at a point where they were thinking about distributing laptops for student use. It’s not something most people have on their radar. I’m a former district K-12 technology director myself and, I’ll be honest, I’m grateful that I’m not in the field right now because I would not want to have to be dealing with these challenges,” Bearden added.

Schools have already reported shortages of devices for the fall semester, with Lenovo, HP, and Dell reportedly telling school districts that they have a shortage of nearly 5 million laptops. 

After a haphazard Spring term, schools spent the summer trying their best to acquire enough devices to teach the nation’s 55 million students in the fall. But shipping issues and supply shortages have left thousands of schools in the exact same place they were in the March when schools closed. 

Foreign policy feuds between the US and Chinese government have also exacerbated device shortages, leaving many schools with almost no options, and device makers themselves are still recovering from being shut down for months due to the pandemic. 

1:1 programs or lack thereof

Each state and school district had come up with its own device lending policies, but for the vast majority, size is what matters. Smaller school districts have long given school-owned devices out to students while larger ones, particularly those in big cities, have never even considered it before being forced to in March. 

Steve Smith, chief information officer for Cambridge Public Schools in Massachusetts and the founder of the Student Data Privacy Consortium, said districts faced a variety of problems that ranged from device preferences to a district’s flexibility on specification requirements. 

Due to overwhelming demand and sourcing constraints, some districts settled for different devices for different grades, both Smith and Bearden explained. Much of it depended on a school’s relationship with resellers, especially for those schools ordering by the thousands. 

Cindy Costanza, technology manager at Denville Township Schools in New Jersey, said their 1:1 device lending program began last year while Mike Daugherty, director of Technology & Innovation at Chagrin Falls Exempted Village Schools in Ohio said the district’s 1:1 program began in 2015. 

SEE: Online education toolbox: Tips and resources for distance learning (free PDF) (TechRepublic)

Chantell Manahan, director of technology at the Metropolitan School District of Steuben County, IN, said the district’s lending program began in 2015 and while Drew Lane, executive director of information and communication technologies for Shawnee Mission School District in Kansas, told TechRepublic its device lending program goes back to 2013.  

But cities like New York City have never had a 1:1 device lending program at all due to the sheer size of its student population. With more than a million students attending New York City public schools, the city had to rush to deliver 300,000 tablets as well as 175,000 devices in just a few weeks. Parents had to go online and fill out forms to get devices while thousands of others were forced to use their own tools.

New York City Mayor Bill de Blasio reportedly had to personally ask Apple CEO Tim Cook for help in procuring the thousands of devices needed to fill the gap. 

While devices were eventually procured, the program in New York City has faced criticism from some students and families who said it took weeks to get working laptops or devices. The students, many of them being already disadvantaged, lost valuable education time that they can never get back. 

“Districts with 1:1 programs where kids could take devices home were better prepared but in many cases, districts were forced to have students use their own devices or disassemble laptop carts and send those devices home. What that looks like is very different across the country,” Bearden said. 

SEE: Inside UPS: The logistics company’s never-ending digital transformation (free PDF) (TechRepublic)

“Even if districts have devices available at school which had not been sent home, they may not have been configured for off-campus use. That can include everything from web filtering to device updates remotely. If districts had 1:1 programs, they probably had those issues addressed.”

Bearden said the Consortium for School Networking has been a resource for school administrators nationwide as they grapple with a range of issues related to device lending, like security, returns, damage, cost, repairs, and more. 

Some schools without 1:1 programs, she noted, had to just tear Chromebooks off of carts and hand them out to students, with thousands of schools not having any time to think through the logistics of managing or counting devices that went out. 

According to Bearden, one of the biggest challenges is getting the devices back safely, if at all, during the summer and preparing for the fall, which may present its own issues. 

Collection and repair

Once the school year ended and summer began, administrators focused on the next phase of problems related to their device lending programs, namely the collection-and-repair processes. 

How do you collect millions of devices from students safely during a pandemic? How do you  cover the costs for repairs? Should students be able to keep devices over the summer for learning? 

Costanza from Denville, NJ, said the school district put measures in place when bringing devices back from the more than 1,600 students who attend Township Schools. They now repair the devices in house instead of shipping them out, saving time and money that can be better spent elsewhere. All of the devices brought back were not touched until the summer and eventually were sprayed down, disinfected and only touched with gloves before they were put back into circulation for the fall term.

Costanza added that the school district plans every year in its budget to replace and purchase devices for the incoming class and include a 20% overage so that if devices break they can be replaced. 

At Chagrin Falls in Ohio, Daugherty said the school district purchased about 25 more Chromebooks to add to its current fleet, and the district has been doing weekly swap outs with students who have issues with their devices so they can be repaired. 

“Our transportation department drops off a replacement device and collects the broken one.   We fix it, clean it, and it can be sent out to another student,” Daugherty said. 

For Indiana’s Steuben County, Manahan said the district has been swapping damaged and malfunctioning devices twice per week while the buildings have been closed, running tiered help desk support through all layers of school staff, and attempting to accommodate students who may not have internet access at home as well. 

“We collected devices in June and redistributed in August,” she said adding that one of the biggest challenges has been setting up safe protocols for exchanging broken or malfunctioning devices for loaners. 

“I am very proud of our program. We are fortunate to have an established 1:1 program and experience with e-learning days for inclement weather and for teacher professional development,” she added. 

Anthony Smith, director of technology at Brockport Central School District in New York said overall, the district’s device lending program has gone over very well. It put structures in place for a remote help desk and device repairs, with two phone lines for the community to call tickets in and then put a process in place for students and staff to be able to drop off broken devices for repair and to pick up when done. The district’s transportation department pitched in as well to deliver devices to those who were unable to pick up the device at the district.

Prepping for the fall

Even as the summer approached, administrators were very worried about how things would play out in the fall. Bearden said most school districts planned for three different scenarios including full in-person instruction, which some schools across the country have returned to due to low coronavirus infection numbers. 

The next scenario has become the most common route schools have taken since last month and involves a partial return with a mix of in-school learning and remote schooling done on a rotating basis. A few schools around the nation have continued a version of the spring, when every child learned from home. 

There are still concerns about whether an increase in coronavirus infections due to a partial return to in-school learning will force schools to shut again, Bearden added. 

SEE: Zoom vs. Microsoft Teams, Google Meet, Cisco WebEx and Skype: Choosing the right video-conferencing apps for you (TechRepublic)

A number of schools reopened but were forced to close because of infections of teachers and students. 

“This was a disaster scenario that no one could have predicted,” Bearden said.

One of the biggest concerns every district has had this fall are budget cuts, which most state governments have hinted at due to the decreased tax revenues resulting from quarantines. Bearden said multiple district administrators have been told to expect cuts as high as 20%, which is particularly difficult considering the increased money required for digital learning.  

“How are they going to acquire more devices? Even if you have the funding to acquire devices, because of the supply line cuts with China, there are shortages of computer hardware, like Chromebooks and hotspots that are available for sale. Districts may want to place orders for devices but they may not be in stock,” Bearden said. “A lot of resellers had big inventories so they were able to absorb immediate demand. But are there devices for purchase now?”

A recent report from the Association of School Business Officials International found that on average, districts will have to spend an extra $490 per student to cover the cost of hand sanitizer, extra cleaning and beefed up nursing teams for the fall. 

A district with an average student population of about 4,000 kids will have to spend about $1.8 million just to pay for the health-related costs. This figure does not include the cost for devices and repairs. Administrators are now looking to the federal government for more than $175 billion to help with the costs of teaching the nation’s 55 million children.

But despite the concerns, many school district leaders said they felt their experience this spring would help prepare them for what is coming. 

“If we can turn toward that 21st century learning and embrace it more fully, then all the lessons we’ve learned through this, even those that have been painful, we can come out the other side of this much much stronger,” said Lane of Kansas’ Shawnee Mission School District. 

“We can be an even better educational institution, we can be even technology people, even better support personnel. Even better teachers and administrators. There’s opportunity for growth and continued success, even in the face of the challenges that we have in our near future.”

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Using satellites and AI to help fight poverty in Africa

Utilizing satellites and AI to assist battle hardship in Africa

In combating hardship, like any battle, it’’ s great to understand the areas of your targets.

Stanford scientists have actually developed a brand-new effective tool that can assist approximate the level of hardship throughout African towns and modifications in their advancement in time. ( Image credit: Getty Images)

That’’ s why Stanford scholars Marshall Burke , David Lobell and Stefano Ermon have actually invested the previous 5 years leading a group of scientists to house in on an effective method to discover and track impoverished zones throughout Africa.

The effective tool they’’ ve established combines totally free, openly available satellite images with expert system to approximate the level of hardship throughout African towns and modifications in their advancement gradually. By examining existing and previous information, the measurement tool might supply valuable details to companies, federal government firms and services that provide services and requirements to the bad.

Details of their endeavor were revealed in the May 22 concern of Nature Communications .

““ Our huge inspiration is to much better establish tools and innovations that enable us to make development on truly essential financial concerns. And development is constrained by an absence of capability to determine results,” ” stated Burke, a professors fellow at the Stanford Institute for Economic Policy Research (SIEPR) and an assistant teacher of earth system science in the School of Earth, Energy &&Environmental Sciences (Stanford Earth). ““ Here ’ s a tool that we believe can assist. ”

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Lobell, a senior fellow at SIEPR and a teacher of Earth system science at Stanford Earth, states recalling is important to recognizing elements and patterns to assist individuals leave from hardship.

““ Amazingly, there hasn’’ t truly been any great way to comprehend how hardship is altering at a regional level in Africa,” ” stated Lobell, who is likewise the director of the Center on Food Security and the Environment and the William Wrigley Fellow at the Stanford Woods Institute for the Environment. ““ Censuses aren ’ t regular enough, and door-to-door studies hardly ever go back to the exact same individuals. If satellites can assist us rebuild a history of hardship, it might open a great deal of space to much better ease and comprehend hardship on the continent.””

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The measurement tool utilizes satellite images both from the daytime and nighttime. During the night, lights are a sign of advancement, and throughout the day, pictures of human facilities such as roadways, farming, roof products, real estate structures and waterways, supply qualities associated with advancement.

Then the tool uses the innovation of deep knowing –– calculating algorithms that continuously train themselves to find patterns –– to produce a design that evaluates the images information and forms an index for property wealth, a financial part typically utilized by property surveyors to determine family wealth in establishing countries.

The scientists evaluated the determining tool’’ s precision for about 20,000 African towns that had current property wealth information from studies, going back to 2009. They discovered that it carried out well in evaluating the poverty line of towns over various amount of times, according to their research study.

Here, Burke –– who is likewise a center fellow at the Stanford Woods Institute for the Environment and the Freeman Spogli Institute for International Studies –– goes over the making of the tool and its prospective to assist enhance the wellness of the world’’ s bad.

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Why are you delighted about this brand-new technological resource?

For the very first time, this tool shows that we can determine financial development and comprehend hardship interventions at both a broad scale and a regional level. It works throughout Africa, throughout a great deal of various years. It works quite darn well, and it operates in a great deal of really various kinds of nations.

Can you provide examples of how this brand-new tool would be utilized?

If we wish to comprehend the efficiency of an anti-poverty program, or if an NGO wishes to target a particular item to particular kinds of people, or if a service wishes to comprehend where a market’’ s growing– all of those need information on financial results. In numerous parts of the world, we simply wear’’ t have those’information. Now we ’ re utilizing information from throughout sub-Saharan Africa and training these designs to take in all the information to determine for particular results.

How does this brand-new research study build on your previous work?

Our preliminary poverty-mapping work , released in 2016, was on 5 nations utilizing one year of information. It depended on pricey, high-resolution images at a much smaller sized, pilot scale. Now this work covers about 2 lots nations –– about half of the nations in Africa –– utilizing much more years of high-dimensional information. This offered underlying training datasets to establish the measurement designs and enabled us to confirm whether the designs are making great hardship quotes.

We’’ re positive we can use this technique and this innovation to get dependable price quotes for all the nations in Africa.

A crucial distinction compared to the earlier work is now we’’ re utilizing entirely openly readily available satellite images that returns in time –– and it’’ s totally free, which I believe equalizes this innovation. And we’’ re doing it at a thorough, huge spatial scale.

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How do you utilize satellite images to get hardship price quotes?

We’’ re structure on fast advancements in the field of computer technology –– of deep knowing –– that have actually taken place in the last 5 years which have actually truly changed how we draw out details from images. We’’ re not informing the device what to try to find in images; rather, we’’ re simply informing it, ““ Here ’ s an abundant location. Here is a bad location.”Figure it out.”

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The computer system is plainly choosing city locations, farming locations, roadways, waterways –– functions in the landscape that you may believe would have some predictive power in having the ability to different abundant locations from bad locations. The computer system states, ‘‘ I discovered this pattern’ ’ and we can then appoint semantic significance to it.

These wider qualities, analyzed at the town level, end up being extremely connected to the typical wealth of the families because area.

What’’ s next?

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Now that we have these information, we wish to utilize them to attempt to discover something about financial advancement. This tool allows us to resolve concerns we were not able to ask a year earlier due to the fact that now we have local-level measurements of crucial financial results at broad, spatial scale and with time.

We can examine why some locations are doing much better than other locations. We can ask: What do patterns of development in incomes appear like? Is the majority of the variation in between nations or within nations? If there’’ s variation within a nation, that currently informs us something essential about the factors of development. It’’ s most likely something going on in your area.

I’’ m an economic expert, so those are the sorts of concerns that get me delighted. The technological advancement is not an end in itself. It’’ s an enabler for the social science that we wish to do.

In addition to Burke, Lobell and Ermon, a teacher of computer system science, the co-authors of the released research study are Christopher Yeh and Anthony Perez, both computer system science graduate trainees and research study assistants at the Stanford King Center on Global Development; Anne Driscoll, a research study information expert, and George Azzari, an associated scholar, both at the Center on Food Security and the Environment at Stanford; and Zhongyi Tang, a previous research study information expert at the King.

This research study was supported by the Data for Development effort at the Stanford King Center on Global Development and the USAID Bureau of Food Security.

To check out all stories about Stanford science, sign up for the biweekly Stanford Science Digest .

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Sony IMX500 – The World’s First AI Image Sensor Announced

The new Sony IMX500 Intelligent Vision series of image sensors contain AI image analysis systems directly on the chip, which opens up some new, and faster abilities for cameras.

Sony IMX500 Intelligent Vision sensor

Sony’s new Intelligent Vision IMX500 series chips offer capabilities that are only limited by the imagination. Image: Sony Electronics

The announcement describes two new Intelligent Vision CMOS chip models, the Sony IMX500 and IMX501. From what I can tell these are the same base chip, except that the 500 is the bare chip product, whilst the 501 is a packaged product.

They are both 1/2.3” type chips with 12.3 effective megapixels. It seems clear that the one of the primary markets for the new chip is for security and system cameras. However having AI processes on the chip offers up some exciting new possibilities for future video cameras, particularly those mounted on drones or in action cameras like a GoPro or Insta 360.

Sony IMX500 Intelligent Vision sensor

Sony’s new Intelligent Vision IMX500 series chips. The IMX500 on the left, the IMX501 on the right. Image: Sony Electronics

What can the Sony IMX500 sensor do?

One prominent ability of the new chip lies in functions such as object or person identification. This could be via tracking such objects, or in fact actually identifying them. Output from the new chip doesn’t have to be in image form either. Metadata can be output so that it can simply send a description of what it sees without the accompanying visual image. This can reduce the data storage requirement by up to 10,000 times.

For security or system camera purposes, a camera equipped with the new chip could count the number of people passing by it, or identifying low stock on a shop shelf. It could even be programmed to identify customer behaviour by way of heat maps.

Sony IMX500 stacked sensor diagram

How the new Sony Intelligent Vision sensor is arranged. Image: Sony Electronics

For traditional cameras it could make autofocus systems better by being able to much more precisely identifying and tracking subjects. With AI systems like this, it could make autofocus systems more intelligent by identifying areas of a picture that you are likely to be focussing on. For example if you wanted to take a photograph of a flower, the AF system would know to focus on that rather than, say, the tree branch behind it. Facial recognition would also become much faster and more reliable.

Autofocus systems today are becoming incredibly good already, but if they were backed up by ultra fast on-chip object identification they could be even better. For 360 cameras, too, the ability to have more reliable object tracking metadata will help with post reframing.

Sony IMX500 output examples

The new chip doesn’t have to output images. It could just output a description of what it sees. Image: Sony Electronics.

Why do we need AI on chip?

There are two main impetuses behind placing the AI capabilities directly on the chip. The first is that it makes processing much, much quicker. The Sony IMX500 is able to perform its abilities in the speed of one frame of video, rather than having to send that data along a pipeline to be processed elsewhere. The other advantage is higher security. Quite often data is sent over the cloud for AI image analysis. Having these systems on chip takes away that potential security loophole.

Cloud AI cannot be used offline either, and in addition it restricts the ability to perform analysis in realtime reliably. The energy and cost of cloud computer is also increasing, and that’s not good for the environment.

In terms of small cameras like GoPros, it means that this type of processing doesn’t need to be performed by another chip elsewhere in the camera. This saves power, but it also means that the cameras main processing chip and memory can be freed up to do other things, such as better electronic stabilisation or colour processing.

Sony IMX500 sensor at a checkout

An example of realtime tracking at a shop counter. Note how it is tracking the shop assistants limb movement as well. Image: Sony Electronics

It’s only limited by your imagination

But the abilities of the new chip, which can be custom programmed by developers to do precisely what they need, are only limited by the imagination. Sony uses a car as one example of how it could be used, identifying the driver and adjusting the car’s seating position automatically. Another example is being able to recognise whether the driver was falling asleep.

For sports cameras it might be possible for the device to identify your form during movement. If you want to improve your yoga or martial arts for instance, it could help identify areas for improvement by comparing you to a ‘perfect’ example. Speech recognition from lip movement could also be made much faster potentially, and be included in all cameras. For people filming drama, this would have huge potential when it comes to logging shots or identifying them from a script if the camera is outputting actors performances in text form at the same time it is recording the image. 

The IMX500 looks like a highly capable chip from a pure video perspective, too. It is capable of 4K at up to 60fps and 1080p at up to 240fps. Although currently the chip is restricted to 30fps for full video and AI processing together.

All told while this is only the first generation of chip, you can expect this type pf capability to be rolled out into other more conventional chips as time moves along, and therefore it is a significant development worth covering.

Have you any ideas how on-chip AI would make a camera feature you would like to see possible? Let us know in the comments below!

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Surface Go 2 review: Microsoft’s smaller, cheaper Windows 10 tablet

New design squeezes larger screen in very same body, for an exceptional, budget friendly ultraportable PC

The Surface Go 2 is Microsoft’’ s 2nd version of its low-cost, smaller sized tablet computer system and continues to show that low-cost Windows PCs wear’’ t need to be horrible.

The Surface Go 2 starts at ££ 399, however for that you wear’’ t get the £ 100 Type Cover keyboard, which is an essential. That positions the Surface Go 2 in the low-end PC bracket and makes it Microsoft’’ s most affordable present PC, damaging the Surface Pro 7 by ££ 300.

Continue reading … .

Read more: theguardian.com

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Microsoft Surface Laptop 3 review: still sleek, just no longer unique

USB-C, faster processors and brand-new style choices continue to keep Microsoft’’ s Windows 10 laptop computer near the top of the stack

Microsoft’’ s premier laptop computer is now in its 3rd generation, with brand-new ports, brand-new processors and a small redesign, with the alternative to ditch the distinct Alcantara for plain old aluminium.

The ££ 999 and up Surface Laptop 3 is Microsoft’’ s vision of what a standard laptop computer need to be. For the many part that’’ s the like everybody else, with conventional aluminium body, glass-covered screen and hinge that does not turn all the method round to the back.

Continue reading … .

Read more: theguardian.com