Media literacy. Differentiated instruction. Media literacy guide.
Fake news as part of media literacy. Visual literacy as part of media literacy. Media literacy as part of digital citizenship.
Web design / web development
the roles of HTML5, CSS, Java Script, PHP, Bootstrap, JQuery, React and other scripting languages and libraries. Heat maps and other usability issues; website content strategy. THE MODEL-VIEW-CONTROLLER (MVC) design pattern
Social media for institutional use. Digital Curation. Social Media algorithms. Etiquette Ethics. Mastodon
I hosted a LITA webinar in the fall of 2016 (four weeks); I can accommodate any information from that webinar for the use of the IM students
OER and instructional designer’s assistance to book creators.
I can cover both the “library part” (“free” OER, copyright issues etc) and the support / creative part of an OER book / textbook
“Big Data.” Data visualization. Large scale visualization. Text encoding. Analytics, Data mining. Unizin. Python, R in academia.
I can introduce the students to the large idea of Big Data and its importance in lieu of the upcoming IoT, but also departmentalize its importance for academia, business, etc. From infographics to heavy duty visualization (Primo X-Services API. JSON, Flask).
NetNeutrality, Digital Darwinism, Internet economy and the role of your professional in such environment
I can introduce students to the issues, if not familiar and / or lead a discussion on a rather controversial topic
Digital assessment. Digital Assessment literacy.
I can introduce students to tools, how to evaluate and select tools and their pedagogical implications
Wikipedia
a hands-on exercise on working with Wikipedia. After the session, students will be able to create Wikipedia entries thus knowing intimately the process of Wikipedia and its information.
Effective presentations. Tools, methods, concepts and theories (cognitive load). Presentations in the era of VR, AR and mixed reality. Unity.
I can facilitate a discussion among experts (your students) on selection of tools and their didactically sound use to convey information. I can supplement the discussion with my own findings and conclusions.
eConferencing. Tools and methods
I can facilitate a discussion among your students on selection of tools and comparison. Discussion about the their future and their place in an increasing online learning environment
Digital Storytelling. Immersive Storytelling. The Moth. Twine. Transmedia Storytelling
I am teaching a LIB 490/590 Digital Storytelling class. I can adapt any information from that class to the use of IM students
VR, AR, Mixed Reality.
besides Mark Gill, I can facilitate a discussion, which goes beyond hardware and brands, but expand on the implications for academia and corporate education / world
Instructional design. ID2ID
I can facilitate a discussion based on the Educause suggestions about the profession’s development
Microcredentialing in academia and corporate world. Blockchain
IT in K12. How to evaluate; prioritize; select. obsolete trends in 21 century schools. K12 mobile learning
Podcasting: past, present, future. Beautiful Audio Editor.
a definition of podcasting and delineation of similar activities; advantages and disadvantages.
Gender, race and age in education. Digital divide. Xennials, Millennials and Gen Z. generational approach to teaching and learning. Young vs old Millennials. Millennial employees.
Antitrust laws only go so far when addressing companies that don’t produce any physical goods. It is time to negotiate a new set of rules. Otherwise, our future economy will be dominated by just a few companies.
There are still people out there who think that Amazon is nothing more than an online version of a department store. But it’s much more than that: It is a rapidly growing, global internet giant that is changing the way we shop, conquering more and more markets, using Alexa to suck up our personal data straight out of our living rooms and currently seeking access to our front door keys so it can deliver packages even when nobody’s home.
It wasn’t that long ago that EU efforts to limit the power of Google and Amazon on the European market were decried in the U.S. as protectionism, as an attempt by the Europeans to protect their own inferior digital economy. Now, though, politicians and economists in the U.S. have even begun discussing the prospect of breaking up the internet giants. The mood has shifted.
The digital economy, by contrast, is based on algorithms and its most powerful companies don’t produce any physical products. Customers receive their services free of charge, paying only with their data. The more customers a service provider attracts, the more attractive it becomes to new customers, who then deliver even more data – which is why Google and Facebook need not fear new competition.
first of all, the power of a company, and the abuse of that power, must be redefined. We cannot allow a situation in which these extremely large companies can swallow up potential rivals before they can even begin to develop. As such, company acquisitions must be monitored much more strictly than they currently are and, if need be, blocked.
Second, it must be determined who owns the data collected – whether, for example, it should also be made available to competitors or whether consumers should receive more in exchange than simply free internet search results.
Third, those disseminating content cannot be allowed to reject responsibility for that content. Demonstrably false claims and expressions of hate should not be tolerated.
And finally, those who earn lots of money must also pay lots of taxes – and not just back home but in all the countries where they do business.
It is a name for a premise that, quietly, has come to regulate all we practise and believe: that competition is the only legitimate organising principle for human activity.
we now live in Hayek’s world, as we once lived in Keynes’s.
He begins by assuming that nearly all (if not all) human activity is a form of economic calculation, and so can be assimilated to the master concepts of wealth, value, exchange, cost – and especially price. Prices are a means of allocating scarce resources efficiently, according to need and utility, as governed by supply and demand. For the price system to function efficiently, markets must be free and competitive. Ever since Smith imagined the economy as an autonomous sphere, the possibility existed that the market might not just be one piece of society, but society as a whole. Within such a society, men and women need only follow their own self-interest and compete for scarce rewards. Through competition, “it becomes possible”, as the sociologist Will Davies has written, “to discern who and what is valuable”.
Hayek built into neoliberalism the assumption that the market provides all necessary protection against the one real political danger: totalitarianism.
To prevent this, the state need only keep the market free.
This last is what makes neoliberalism “neo”. It is a crucial modification of the older belief in a free market and a minimal state, known as “classical liberalism”. In classical liberalism, merchants simply asked the state to “leave us alone” – to laissez-nous faire. Neoliberalism recognised that the state must be active in the organisation of a market economy. The conditions allowing for a free market must be won politically, and the state must be re-engineered to support the free market on an ongoing basis.
Even his conservative colleagues at the University of Chicago – the global epicentre of libertarian dissent in the 1950s – regarded Hayek as a reactionary mouthpiece, a “stock rightwing man” with a “stock rightwing sponsor”, as one put it.
Milton Friedman who helped convert governments and politicians to the power of Hayek’s Big Idea. But first he broke with two centuries of precedent and declared that economics is “in principle independent of any particular ethical position or normative judgments” and is “an ‘objective’ science, in precisely the same sense as any of the physical sciences”.
The internet is personal preference magnified by algorithm; a pseudo-public space that echoes the voice already inside our head. Rather than a space of debate in which we make our way, as a society, toward consensus, now there is a mutual-affirmation apparatus banally referred to as a “marketplace of ideas”.
“A taste is almost defined as a preference about which you do not argue,” the philosopher and economist Albert O Hirschman once wrote. “A taste about which you argue, with others or yourself, ceases ipso facto being a taste – it turns into a value.”
My note: sometimes around 2011, the Chronicle had a report on Berkeley students listening to coursecasts at 2X (can’t find the reference). Here some other sources about #speedlistening:
the introduction of Overcast, a podcast-playback app designed by the creator of the text-bookmaking app Instapaper. One of Overcast’s key selling points is a feature called Smart Speed. Smart Speed isn’t about simply playing audio content at 150 or 200 percent of the standard rate; it instead tries to remove, algorithmically, the extraneous things that can bulk up the play time of audio content: dead air, pauses between sentences, intros and outros, that kind of thing.
A similar strategy was used in 2008, Dewes said, to deanonymise a set of ratings published by Netflix to help computer scientists improve its recommendation algorithm: by comparing “anonymous” ratings of films with public profiles on IMDB, researchers were able to unmask Netflix users – including one woman, a closeted lesbian, who went on to sue Netflix for the privacy violation.
As a team out of the University of Washington explains in a new paper titled “Synthesizing Obama: Learning Lip Sync from Audio,” they’ve made several fake videos of Obama.
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Fake news: you ain’t seen nothing yet
Generating convincing audio and video of fake events, July 1, 2017
took only a few days to create the clip on a desktop computer using a generative adversarial network (GAN), a type of machine-learning algorithm.
Faith in written information is under attack in some quarters by the spread of what is loosely known as “fake news”. But images and sound recordings retain for many an inherent trustworthiness. GANs are part of a technological wave that threatens this credibility.
Amnesty International is already grappling with some of these issues. Its Citizen Evidence Lab verifies videos and images of alleged human-rights abuses. It uses Google Earth to examine background landscapes and to test whether a video or image was captured when and where it claims. It uses Wolfram Alpha, a search engine, to cross-reference historical weather conditions against those claimed in the video. Amnesty’s work mostly catches old videos that are being labelled as a new atrocity, but it will have to watch out for generated video, too. Cryptography could also help to verify that content has come from a trusted organisation. Media could be signed with a unique key that only the signing organisation—or the originating device—possesses.
A Strategist’s Guide to Industry 4.0. Global businesses are about to integrate their operations into a seamless digital whole, and thereby change the world.
Industrial revolutions are momentous events. By most reckonings, there have been only three. The first was triggered in the 1700s by the commercial steam engine and the mechanical loom. The harnessing of electricity and mass production sparked the second, around the start of the 20th century. The computer set the third in motion after World War II.
Henning Kagermann, the head of the German National Academy of Science and Engineering (Acatech), did exactly that in 2011, when he used the term Industrie 4.0 to describe a proposed government-sponsored industrial initiative.
The term Industry 4.0 refers to the combination of several major innovations in digital technology
These technologies include advanced robotics and artificial intelligence; sophisticated sensors; cloud computing; the Internet of Things; data capture and analytics; digital fabrication (including 3D printing); software-as-a-service and other new marketing models; smartphones and other mobile devices; platforms that use algorithms to direct motor vehicles (including navigation tools, ride-sharing apps, delivery and ride services, and autonomous vehicles); and the embedding of all these elements in an interoperable global value chain, shared by many companies from many countries.
Companies that embrace Industry 4.0 are beginning to track everything they produce from cradle to grave, sending out upgrades for complex products after they are sold (in the same way that software has come to be updated). These companies are learning mass customization: the ability to make products in batches of one as inexpensively as they could make a mass-produced product in the 20th century, while fully tailoring the product to the specifications of the purchaser
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Three aspects of digitization form the heart of an Industry 4.0 approach.
• The full digitization of a company’s operations
• The redesign of products and services
• Closer interaction with customers
Making Industry 4.0 work requires major shifts in organizational practices and structures. These shifts include new forms of IT architecture and data management, new approaches to regulatory and tax compliance, new organizational structures, and — most importantly — a new digitally oriented culture, which must embrace data analytics as a core enterprise capability.
Klaus Schwab put it in his recent book The Fourth Industrial Revolution (World Economic Forum, 2016), “Contrary to the previous industrial revolutions, this one is evolving at an exponential rather than linear pace.… It is not only changing the ‘what’ and the ‘how’ of doing things, but also ‘who’ we are.”
This great integrating force is gaining strength at a time of political fragmentation — when many governments are considering making international trade more difficult. It may indeed become harder to move people and products across some national borders. But Industry 4.0 could overcome those barriers by enabling companies to transfer just their intellectual property, including their software, while letting each nation maintain its own manufacturing networks.
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more on the Internet of Things in this IMS blog https://blog.stcloudstate.edu/ims?s=internet+of+things
a study, the “Why We Post” project, has just been published by nine anthropologists, led by Daniel Miller of University College, London. worked independently for 15 months at locations in Brazil, Britain, Chile, China (one rural and one industrial site), India, Italy, Trinidad and Tobago, and Turkey.
In rural China and Turkey social media were viewed as a distraction from education. But in industrial China and Brazil they were seen to be an educational resource. Such a divide was evident in India, too. There, high-income families regarded them with suspicion but low-income families advocated them as a supplementary source of schooling. In Britain, meanwhile, they were valued not directly as a means of education, but as a way for pupils, parents and teachers to communicate.
How would you answer if addressed by this study? How do you see social media? Do you see it differently then before?
On a recent visit in 2015, I found the social media landscape dramatically changed, again. Facebook began actively steering reading practices through changes in 2013 to the News Feed algorithm, which determines content in the site’s central feature. That year, Facebook announced an effort to prioritize “high quality content,” defined as timely, relevant, and trustworthy—and not clickbait, memes, or other viral links. This policy, along with changing practices in sharing news content generally, meant that current events can unfold on and through social media.
how much of your news do you acquire through social media? do you trust the information you acquire through social media? #FakeNews – have explored this hashtag? What is your take on fake news?
meaning management :
Anthropologists and the culturally sensitive analysts take complex bits of data and develop a higher-order sense of them. Information and meaning work at cross purposes. In managing meaning, context is everything while in managing information context is error and noise. When we give our social listening projects to information specialists, we lose an appreciation of context and with it the ability to extract the meanings that provide insight for our companies and brands.
Meaning management also involves a deeper appreciation of social listening as a component of a broader meaning-making system, rather than as, simply, a data source to be exploited.
How do you perceive meaning management? Do you see yourself being a professional with the ability to collect, analyze and interpret such data for your company?
Twitter is updating its top search results so that tweets will be ranked based on relevance instead of by time, bringing those search results in line with what users have experienced on their timeline for the past 10 months. Based on early trials, the company claims there has been more engagement in search results and tweets, with more time spent using the service.
In February, Twitter announced that it was shaking up the user timeline for everyone. Previously, it had offered the algorithmic change as an opt-in program, but it became mandatory a month later. The effort was intended to make the service more appealing to new and casual users,
Twitter’s search was broken into various categories, such as most popular or the latest (a live stream), and segmented by people, photos, videos, and more. Now it appears that there’s one more signal being used to algorithmically control how at least the top tweets are shown to you.
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more about Twitter in this IMS blog
Alice and Bob have figured out a way to have a conversation without Eve being able to overhear, no matter how hard she tries.
They’re artificial intelligence algorithms created by Google engineers, and their ability to create an encryption protocol that Eve (also an AI algorithm) can’t hack is being hailed as an important advance in machine learning and cryptography.
Martin Abadi and David G. Andersen, explained in a paper published this week that their experiment is intended to find out if neural networks—the building blocks of AI—can learn to communicate secretly.
As the Abadi and Anderson wrote, “instead of training each of Alice and Bob separately to implement some known cryptosystem, we train Alice and Bob jointly to communicate successfully and to defeat Eve without a pre-specified notion of what cryptosystem they may discover for this purpose.”
same in German
Googles AI entwickelt eigenständig Verschlüsselung
Google-Forscher Martin Abadi und David G. Andersen des Deep-Learning-Projekts “Google Brain” eine neue Verschlüsselungsmethode entwickelt beziehungsweise entwickeln lassen. Die Forscher haben verschiedene neurale Netze damit beauftragt, eine abhörsichere Kommunikation aufzustellen.
