Archive of ‘Digital literacy’ category

21
Nov
2019

AI laptops

categories: Digital literacy, educational technology, technology literacy

https://www.cnet.com/news/intel-will-build-ai-brains-into-your-laptop-for-tomorrows-speed-boost/

AI computing involves two phases: training and inference. Training requires computers that can process enormous amounts of data. For example, getting an AI system to recognize what’s in photographs requires a computer to sort through billions of labeled photos to create a model. That model is used in the second step to infer, or identify, what’s in a specific photo.

Intel already sells its Nervana chips for training and inference to data centers packed with servers, computing infrastructure that often powers services at AI-heavy companies such as Google and Facebook. Intel is now shipping its larger, more expensive and power-hungry Nervana NNP-T chips for training and its smaller NNP-I chips for inference, the chipmaker announced.

20
Nov
2019

phone camera for landscapes

categories: Digital literacy, educational technology, instructional technology, mobile learning, technology literacy

https://www.cnet.com/how-to/how-to-take-amazing-landscape-photos-using-your-phones-camera

he latest crop of phones like the iPhone 11, 11 Pro, Samsung Galaxy S10 Plus, OnePlus 7 Pro or Google Pixel 4

If your phone doesn’t have a built-in wide-angle mode (as you’ll find on the iPhone 11 ($699 at Amazon) series or Galaxy S10 Plus), you should take a look at Moment’s range of clip-on phone lenses, available for all recent iPhones, Galaxy phones, Pixels and OnePlus phones.

Moment also makes filter adapters for screw-in 62mm filters, such as polarizers, which can help reduce reflections on water or boost the blues in the sky. Filter adapters also let you use professional-quality square Lee Filters, which slide into a holder connected to the adapter via a 62mm adapter ring.

15
Nov
2019

Digital Equity Act 2019

categories: Digital literacy

https://www.digitalinclusion.org/blog/2019/09/25/representatives-mcnerney-lujan-and-clarke-introduce-digital-equity-act-in-u-s-house/

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more on digital equity in this IMS blog
https://blog.stcloudstate.edu/ims/2019/04/02/net-inclusion-2019/

13
Nov
2019

Intrinsic Motivation Digital Distractions

categories: Digital literacy, e-learning, educational technology, gamification, information technology, instructional technology

How Intrinsic Motivation Helps Students Manage Digital Distractions

By Ana Homayoun     Oct 8, 2019

According to the Pew Research Center, 72 percent of teenagers check their phones as soon as they get up (and so do 58 percent of their parents), and 45 percent of teenagers feel as though they are online on a nearly constant basis. Interestingly, and importantly, over half of U.S. teenagers feel as though they spend too much time on their cell phones.

Research on intrinsic motivation focuses on the importance of autonomy, competency and relatedness in classroom and school culture.

According to one Common Sense Media report, called Social Media, Social Life, 57 percent of students believe social media use often distracts them when they should be doing homework. In some ways, the first wave of digital citizenship education faltered by blocking distractions from school networks and telling students what to do, rather than effectively encouraging them to develop their own intrinsic motivation around making better choices online and in real life.

Research also suggests that setting high expectations and standards for students can act as a catalyst for improving student motivation, and that a sense of belonging and connectedness in school leads to improved academic self-efficacy and more positive learning experiences.

Educators and teachers who step back and come from a place of curiosity, compassion and empathy (rather than fear, anger and frustration) are better poised to deal with issues related to technology and wellness.

 

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more on intrinsic motivation in this IMS blog
https://blog.stcloudstate.edu/ims?s=intrinsic

https://blog.stcloudstate.edu/ims/2017/04/03/use-of-laptops-in-the-classroom/

10
Nov
2019

In the Age of AI

categories: Digital literacy, educational technology, information technology, instructional technology, learning, technology literacy

In The Age Of A.I. (2019) — This just aired last night and it’s absolutely fantastic. It presents a great look at AI, and it also talks about automation, wealth inequality, data-mining and surveillance.
byu/srsly_its_so_ez inDocumentaries

13 min 40 sec = Wechat

14 min 60 sec = data is the new oil and China is the new Saudi Arabia

18 min 30 sec = social credit and facial recognition

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more on deep learning in this IMS blog
https://blog.stcloudstate.edu/ims?s=deep+learning

10
Nov
2019

information gerrymandering

categories: Digital literacy, information literacy, information technology

Information gerrymandering in social networks skews collective decision-making

https://www.nature.com/articles/d41586-019-02562-z

https://www.facebook.com/mariana.damova/posts/10221298893368558

An analysis shows that information flow between individuals in a social network can be ‘gerrymandered’ to skew perceptions of how others in the community will vote — which can alter the outcomes of elections.

The Internet has erased geographical barriers and allowed people across the globe to interact in real time around their common interests. But social media is starting to compete with, or even replace, nationally visible conversations in print and on broadcast media with ad libitum, personalized discourse on virtual social networks3. Instead of broadening their spheres of association, people gravitate towards interactions with ideologically aligned content and similarly minded individuals.

n information gerrymandering, the way in which voters are concentrated into districts is not what matters; rather, it is the way in which the connections between them are arranged (Fig. 1). Nevertheless, like geographical gerrymandering, information gerrymandering threatens ideas about proportional representation in a democracy.

Figure 1 | Social-network structure affects voters’ perceptions. In these social networks, ten individuals favour orange and eight favour blue. Each individual has four reciprocal social connections. a, In this random network, eight individuals correctly infer from their contacts’ preferences that orange is more popular, eight infer a draw and only two incorrectly infer that blue is more popular. b, When individuals largely interact with like-minded individuals, filter bubbles arise in which all individuals believe that their party is the most popular. Voting gridlock is more likely in such situations, because no one recognizes a need to compromise. c, Stewart et al.1 describe ‘information gerrymandering’, in which the network structure skews voters’ perceptions about others’ preferences. Here, two-thirds of voters mistakenly infer that blue is more popular. This is because blue proponents strategically influence a small number of orange-preferring individuals, whereas orange proponents squander their influence on like-minded individuals who have exclusively orane-preferring contacts, or on blue-preferring individuals who have enough blue-preferring contacts to remain unswayed.

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