Globalization’s cheerleaders, from Columbia University economist Jagdish Bhagwati to New York Times columnist Thomas Friedman, made arguments from classical economics: by buying manufactured products from people overseas who made them cheaper than we did, the United States could get rich concentrating on product design, marketing, and other lucrative services. That turned out to be a mostly inaccurate description of how globalism would work in the developed world, as mainstream politicians everywhere are now discovering.
Certain skeptics, including polymath author Edward Luttwak and Harvard economist Dani Rodrik, put forward a better account. In his 1998 book Turbo-Capitalism, Luttwak gave what is still the most succinct and accurate reading of the new system’s economic consequences. “It enriches industrializing poor countries, impoverishes the semi-affluent majority in rich countries, and greatly adds to the incomes of the top 1 percent on both sides who are managing the arbitrage.”
In The Great Convergence, Richard Baldwin, an economist at the Graduate Institute in Geneva, gives us an idea why, over the past generation, globalization’s benefits have been so hard to explain and its damage so hard to diagnose.
We have had “globalization,” in the sense of far-flung trade, for centuries now.
ut around 1990, the cost of sharing information at a distance fell dramatically. Workers on complex projects no longer had to cluster in the same factory, mill town, or even country. Other factors entered in. Tariffs fell. The rise of “Global English” as a common language of business reduced the cost of moving information (albeit at an exorbitant cost in culture). “Containerization” (the use of standard-sized shipping containers across road, rail, and sea transport) made packing and shipping predictable and helped break the world’s powerful longshoremen’s unions. Active “pro-business” political reforms did the rest.
Far-flung “global value chains” replaced assembly lines. Corporations came to do some of the work of governments, because in the free-trade climate imposed by the U.S., they could play governments off against one another. Globalization is not about nations anymore. It is not about products. And the most recent elections showed that it has not been about people for a long time. No, it is about tasks.
his means a windfall for what used to be called the Third World. More than 600 million people have been pulled out of dire poverty. They can get richer by building parts of things.
The competition that globalization has created for manufacturing has driven the value-added in manufacturing down close to what we would think of as zilch. The lucrative work is in the design and the P.R.—the brainy, high-paying stuff that we still get to do.
But only a tiny fraction of people in any society is equipped to do lucrative brainwork. In all Western societies, the new formula for prosperity is inconsistent with the old formula for democracy.
One of these platitudes is that all nations gain from trade. Baldwin singles out Harvard professor and former George W. Bush Administration economic adviser Gregory Mankiw, who urged passage of the Obama Administration mega-trade deals TPP and Transatlantic Trade and Investment Partnership (TTIP) on the grounds that America should “work in those industries in which we have an advantage compared with other nations, and we should import from abroad those goods that can be produced more cheaply there.”
That was a solid argument 200 years ago, when the British economist David Ricardo developed modern doctrines of trade. In practical terms, it is not always solid today. What has changed is the new mobility of knowledge. But knowledge is a special commodity. It can be reused. Several people can use it at the same time. It causes people to cluster in groups, and tends to grow where those groups have already clustered.
When surgeries involved opening the patient up like a lobster or a peapod, the doctor had to be in physical contact with a patient. New arthroscopic processes require the surgeon to guide cutting and cauterizing tools by computer. That computer did not have to be in the same room. And if it did not, why did it have to be in the same country? In 2001, a doctor in New York performed surgery on a patient in Strasbourg. In a similar way, the foreman on the American factory floor could now coordinate production processes in Mexico. Each step of the production process could now be isolated, and then offshored. This process, Baldwin writes, “broke up Team America by eroding American labor’s quasi-monopoly on using American firms’ know-how.”
To explain why the idea that all nations win from trade isn’t true any longer, Baldwin returns to his teamwork metaphor. In the old Ricardian world that most policymakers still inhabit, the international economy could be thought of as a professional sports league. Trading goods and services resembled trading players from one team to another. Neither team would carry out the deal unless it believed it to be in its own interests. Nowadays, trade is more like an arrangement by which the manager of the better team is allowed to coach the lousier one in his spare time.
Vietnam, which does low-level assembly of wire harnesses for Honda. This does not mean Vietnam has industrialized, but nations like it no longer have to.
In the work of Thomas Friedman and other boosters you find value chains described as kaleidoscopic, complex, operating in a dozen different countries. Those are rare. There is less to “global value chains” than meets the eye. Most of them, Baldwin shows, are actually regional value chains. As noted, they exist on the periphery of the United States, Europe, or Japan. In this, offshoring resembles the elaborate international transactions that Florentine bankers under the Medicis engaged in for the sole purpose of avoiding church strictures on moneylending.
One way of describing outsourcing is as a verdict on the pay structure that had arisen in the West by the 1970s: on trade unions, prevailing-wage laws, defined-benefit pension plans, long vacations, and, more generally, the power workers had accumulated against their bosses.
In 1993, during the first month of his presidency, Bill Clinton outlined some of the promise of a world in which “the average 18-year-old today will change jobs seven times in a lifetime.” How could anyone ever have believed in, tolerated, or even wished for such a thing? A person cannot productively invest the resources of his only life if he’s going to be told every five years that everything he once thought solid has melted into ait.
The more so since globalization undermines democracy, in the ways we have noted. Global value chains are extraordinarily delicate. They are vulnerable to shocks. Terrorists have discovered this. In order to work, free-trade systems must be frictionless and immune to interruption, forever. This means a program of intellectual property protection, zero tariffs, and cross-border traffic in everything, including migrants. This can be assured only in a system that is veto-proof and non-consultative—in short, undemocratic.
Sheltered from democracy, the economy of the free trade system becomes more and more a private space.
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Caldwell, C. (2014, November). Twilight of Democracy. CRB, 14(4).
Caldwell’s book review of
Fukuyama, Francis. The Origins of Political Order: From Prehuman Times to the French Revolution. New York: Farrar, Straus and Giroux, 2011. SCSU Library: https://mplus.mnpals.net/vufind/Record/007359076 Call Number: JC11 .F85 2011
Fukuyama’s first volume opened with China’s mandarin bureaucracy rather than the democracy of ancient Athens, shifting the methods of political science away from specifically Western intellectual genealogies and towards anthropology. Nepotism and favor-swapping are man’s basic political motivations, as Fukuyama sees it. Disciplining those impulses leads to effective government, but “repatrimonialization”—the capture of government by private interests—threatens whenever vigilance is relaxed. Fukuyama’s new volume, which describes political order since the French Revolution, extends his thinking on repatrimonialization, from the undermining of meritocratic bureaucracy in Han China through the sale of offices under France’s Henri IV to the looting of foreign aid in post-colonial Zaire. Fukuyama is convinced that the United States is on a similar path of institutional decay.
Political philosophy asks which government is best for man. Political science asks which government is best for government. Political decline, Fukuyama insists, is not the same thing as civilizational collapse.
Fukuyama is not the first to remark that wars can spur government efficiency—even if front-line soldiers are the last to benefit from it.
Relative to the smooth-running systems of northwestern Europe, American bureaucracy has been a dud, riddled with corruption from the start and resistant to reform. Patronage—favors for individual cronies and supporters—has thrived.
Clientelism is an ambiguous phenomenon: it is bread and circuses, it is race politics, it is doing favors for special classes of people. Clientelism is both more democratic and more systemically corrupting than the occasional nepotistic appointment.
why modern mass liberal democracy has developed on clientelistic lines in the U.S. and meritocratic ones in Europe. In Europe, democracy, when it came, had to adapt itself to longstanding pre-democratic institutions, and to governing elites that insisted on established codes and habits. Where strong states precede democracy (as in Germany), bureaucracies are efficient and uncorrupt. Where democracy precedes strong states (as in the United States but also Greece and Italy), government can be viewed by the public as a piñata.
Fukuyama contrasts the painstaking Japanese development of Taiwan a century ago with the mess that the U.S. Congress, “eager to impose American models of government on a society they only dimly understood,” was then making of the Philippines. It is not surprising that Fukuyama was one of the most eloquent conservative critics of the U.S. invasion of Iraq from the very beginning.
What distinguishes once-colonized Vietnam and China and uncolonized Japan and Korea from these Third World basket cases is that the East Asian lands “all possess competent, high-capacity states,” in contrast to sub-Saharan Africa, which “did not possess strong state-level institutions.”
Fukuyama does not think ethnic homogeneity is a prerequisite for successful politics
the United States “suffers from the problem of political decay in a more acute form than other democratic political systems.” It has kept the peace in a stagnant economy only by dragooning women into the workplace and showering the working and middle classes with credit.
public-sector unions have colluded with the Democratic Party to make government employment more rewarding for those who do it and less responsive to the public at large. In this sense, government is too big. But he also believes that cutting taxes on the rich in hopes of spurring economic growth has been a fool’s errand, and that the beneficiaries of deregulation, financial and otherwise, have grown to the point where they have escaped bureaucratic control altogether. In this sense, government is not big enough.
Washington, as Fukuyama sees it, is a patchwork of impotence and omnipotence—effective where it insists on its prerogatives, ineffective where it has been bought out. The unpredictable results of democratic oversight have led Americans to seek guidance in exactly the wrong place: the courts, which have both exceeded and misinterpreted their constitutional responsibilities. the almost daily insistence of courts that they are liberating people by removing discretion from them gives American society a Soviet cast.
“Effective modern states,” he writes, “are built around technical expertise, competence, and autonomy.”
the sociologists Richard Sennett and Jonathan Cobb call the “hidden injuries of class.” These are dramatized by a recent employment study, in which the sociologists Lauren A. Rivera and Andras Tilcsik sent 316 law firms résumés with identical and impressive work and academic credentials, but different cues about social class. The study found that men who listed hobbies like sailing and listening to classical music had a callback rate 12 times higher than those of men who signaled working-class origins, by mentioning country music, for example.
The college-for-all experiment did not work. Two-thirds of Americans are not college graduates. We need to continue to make college more accessible, but we also need to improve the economic prospects of Americans without college degrees.
the United States has a well-documented dearth of workers qualified for middle-skill jobs that pay $40,000 or more a year and require some postsecondary education but not a college degree. A 2014 report by Accenture, Burning Glass Technologies and Harvard Business School found that a lack of adequate middle-skills talent affects the productivity of “47 percent of manufacturing companies, 35 percent of health care and social assistance companies, and 21 percent of retail companies.”
Skillful, a partnership among the Markle Foundation, LinkedIn and Colorado, is one initiative pointing the way. Skillful helps provide marketable skills for job seekers without college degrees and connects them with employers in need of middle-skilled workers in information technology, advanced manufacturing and health care.For more information, see my other IMS blog entries, such as: https://blog.stcloudstate.edu/ims/2017/01/11/credly-badges-on-canvas/
how data is produced, collected and analyzed. make accessible all kind of data and info
ask good q/s and find good answers, share finding in meaningful ways. this is where digital literacy overshadows information literacy and this the fact that SCSU library does not understand; besides teaching students how to find and evaluate data, I also teach them how to communicate effectively using electronic tools.
connecting people tools and resources and making it easier for everybody. building collaborative, open and interdisciplinary
robust data computational literates. developing workshops, project and events to practice new skills. to position the library as the interdisciplinary nexus
what are data: definition. items of information, facts, traces of content and form. higher level, conception discussion about data in terms of social effects: matadata capturing information about the world, social political and economic changes. move away the mystic conceptions about data. nothing objective about data.
the emergence of IoT – digital meets physical. cyber physical systems. smart objects driven by industry. . proliferation of sensor and device – smart devices.
what does privacy looks like ? what is netneutrality when IoT? library must restructure : collaborate across institutions about collections of data in opien and participatory ways. put IoT in the hands of make and break things (she is maker space aficionado)
make and break things hackathons – use cheap devices such as Arduino and Pi.
data literacy programs with higher level conception exploration; libraries empower the campus in data collection. data science norms, store and share data to existing repositories and even catalogs. commercial services to store and connect data, but very restrictive and this is why libraries must be involved.
linked data and dark data
linked data – draw connections around online data most of the data are locked. linked data uses metadata to link related information in ways computers can understand.
libraries take advantage of link data. link data opportunity for semantics, natural language processing etc. if hidden data is relative to our communities, it is a library responsibility to provide it. community data practitioners
dark data
massive data, which cannot be analyzed by relational processing. data not yield significant findings. might be valuable for researchers: one persons trash is another persons’ treasure. preserving data and providing access to info. collaborate with researchers across disciplines and assist decide what is worth keeping and what discarding and how to study.
rich learning experience working with lined and dark data enable fresh perspective and learning how to work with data architecture. data literacy programming.
in context of data is different from open source and open projects. the social side of data science . advising researchers on navigation data, ethical compilations.
open science movement .https://cos.io/ pushing beyond licences and reframe, position ourselves as collaborators
analysis and publishing ; use tools that can be shared and include data, code and executable files.
reproducibility and contestability https://www.lib.ncsu.edu/events/series/summer-of-open-science
In the age of Big Data, there is an abundance of free or cheap data sources available to libraries about their users’ behavior across the many components that make up their web presence. Data from vendors, data from Google Analytics or other third-party tracking software, and data from user testing are all things libraries have access to at little or no cost. However, just like many students can become overloaded when they do not know how to navigate the many information sources available to them, many libraries can become overloaded by the continuous stream of data pouring in from these sources. This session will aim to help librarians understand 1) what sorts of data their library already has (or easily could have) access to about how their users use their various web tools, 2) what that data can and cannot tell them, and 3) how to use the datasets they are collecting in a holistic manner to help them make design decisions. The presentation will feature examples from the presenters’ own experience of incorporating user data in decisions related to design the Bethel University Libraries’ web presence.
silos, IT barrier, focusing on student success, retention, server space is cheap, if
promotion and tenure for faculty can include incentive to work with the librarian
lack of fear, changing the mindset.
deep collaboration both within and cross-consortia
don’t rely on vendor solutions. changing mindset
development = oppty (versus development as “work”)
private higher education is PALNI
3d virtual picture of disastrous areas. unlock the digital information to be digitally accessible to all people who might be interested.
they opened the maps of Katmandu for the local community and they were coming up with the strategies to recover. democracy in action
i can’t stop thinking that the keynote speaker efforts are mere follow up of what Naomi Klein explains in her Shock Doctrine: http://www.naomiklein.org/shock-doctrine: a government country seeks reasons to destroy another country or area and then NGOs from the same country go to remedy the disasters
A question from a librarian from the U about the use of drones. My note: why did the SCSU library have to give up its drone?
Douglas County Library model. too resource intensive to continue
Marmot Library Network
ILS integrated library system – shared with other counties, same sever for the entire consortium. they have a programmer, viewfind, open source, discovery player, he customized viewfind community to viewfind plus. instead of using the ILS public access catalogue, they are using the Vufind interface
Caiifa Enki. public library – single access collection. they purchase ebooks from the publisher and they are using also the viewfind interface. but not integrated with the library catalogs. Kansas public library went from OverDrive to Viewfind. CA State library is funding for the time being this effort.
types of content – publisher will not understand issue, which clear for librarians
PDF and epub formats
purchase content –
title by title selection – academia is tired of selections. although it is intended to buy also collections
library – owned ( and shared collections)
host content from libraries – papers in academic lib, genealogy in pub lib.
options in license models .
e resource content. not only ebooks, after it is taken care of, add other types of digital objects.
instead of replicate, replacement of the commercial aggregators,
Amigos Shelf interface is the product of the presenter
instead of having a young reader collection as SCSU has on the third floor, an academic library is outsourcing through AMigos shelf ebooks for young readers
Harper Collins is too cumbersome and the reason to avoid working with them.
security issues. some of the material sent over ftp and immediately moved to sftp
decisions – use of internal resources only, if now – amazon
programmer used for the pilot. contracted programmers. lack of the ability to see the large picture. eventually hired a full time person, instead of outsourcing. RDA compliant MARC.
ONIX, spreadsheet MARC.
Decision about who to start with : public or academic.
attempt to keep pricing down –
own agreement with the customers, separate from the agreement with the Publisher
current development: web-based online reading, shared-consortial collections and SIP2 authentication
continued practice, clear goals and immediate feedback
project-based learning, Minecraft and SimCity EDU
Gamification of learning versus learning with games
organizations to promote gaming and gamification in education (p. 6 http://scsu.mn/1F008Re)
the “chocolate-covered broccoli” problem
Discussion: why gaming and gamification is not accepted in a higher rate? what are the hurdles to enable greater faster acceptance? What do you think, you can do to accelerate this process?
Gaming in an academic library
why the academic library? sandbox for experimentation
the connection between digital literacy and gaming and gamificiation
Gilchrist and Zald’s model for instruction design through assessment
Discussion: based on the example (http://web.stcloudstate.edu/pmiltenoff/bi/), how do you see transforming academic library services to meet the demands of 21st century education?
Gaming, gamification and assessment (badges)
inability of current assessments to evaluate games as part of the learning process
“microcredentialing” through digital badges
Mozilla Open Badges and Badgestack
leaderboards
Discussion: How do you see a transition from the traditional assessment to a new and more flexible academic assessment?
High Impact ePortfolio Practice and the New Digital Ecosystem
A regional ePortfolio conference jointly sponsored by AAEEBL, City University of New York and Pace University, ReBundling Higher Education will offer sessions that highlight best practices, evidence of impact, and exciting innovations.
In March, 2017, the Association for Authentic, Experiential and Evidence-Based Learning (AAEEBL), the City University of New York (CUNY) and Pace University invite you to a conference exploring and discussing ePortfolio practice and its role in the future of higher education. Use the links above to review the Call for Proposals (which outlines the themes of the conference), to register for the conference or to submit a proposal.
Conference proposals are due Dec. 2, 2016, and notification will take place by January 15, 2017.
Special note: Due to recent budget cuts to NYC area colleges, registration fees will be kept to a minimum for this conference. Students (graduate or undergraduate) will be admitted free, and registration for all others will be $25, payable at the door.
AAEEBL (The Association for Authentic, Experiential and Evidence-Based learning) starts the Baston Blog
Blockchain Credentialing: What Impact Will it Have?
Posted By Trent Batson Ph. D.
blockchain credentialing, big news since the MIT Media Lab offered an open source means of credentialing using blockchain technology (the technology behind bitcoin).
Blockchain credentialing makes verification of credentials much simpler and less time consuming, according to the articles I’ve collected below. Even IBM has entered the arena.
As with badges, we in the eportfolio world need to be aware of the trend toward blockchain credentialing. I’ve sorted through the links below so I could select those I thought would be most useful for you.
W3Schools – Fantastic set of interactive tutorials for learning different languages. Their SQL tutorial is second to none. You’ll learn how to manipulate data in MySQL, SQL Server, Access, Oracle, Sybase, DB2 and other database systems.
Treasure Data – The best way to learn is to work towards a goal. That’s what this helpful blog series is all about. You’ll learn SQL from scratch by following along with a simple, but common, data analysis scenario.
10 Queries – This course is recommended for the intermediate SQL-er who wants to brush up on his/her skills. It’s a series of 10 challenges coupled with forums and external videos to help you improve your SQL knowledge and understanding of the underlying principles.
TryR – Created by Code School, this interactive online tutorial system is designed to step you through R for statistics and data modeling. As you work through their seven modules, you’ll earn badges to track your progress helping you to stay on track.
Leada – If you’re a complete R novice, try Lead’s introduction to R. In their 1 hour 30 min course, they’ll cover installation, basic usage, common functions, data structures, and data types. They’ll even set you up with your own development environment in RStudio.
Advanced R – Once you’ve mastered the basics of R, bookmark this page. It’s a fantastically comprehensive style guide to using R. We should all strive to write beautiful code, and this resource (based on Google’s R style guide) is your key to that ideal.
Swirl – Learn R in R – a radical idea certainly. But that’s exactly what Swirl does. They’ll interactively teach you how to program in R and do some basic data science at your own pace. Right in the R console.
Python for beginners – The Python website actually has a pretty comprehensive and easy-to-follow set of tutorials. You can learn everything from installation to complex analyzes. It also gives you access to the Python community, who will be happy to answer your questions.
PythonSpot – A complete list of Python tutorials to take you from zero to Python hero. There are tutorials for beginners, intermediate and advanced learners.
Read all about it: data mining books
Data Jujitsu: The Art of Turning Data into Product – This free book by DJ Patil gives you a brief introduction to the complexity of data problems and how to approach them. He gives nice, understandable examples that cover the most important thought processes of data mining. It’s a great book for beginners but still interesting to the data mining expert. Plus, it’s free!
Data Mining: Concepts and Techniques – The third (and most recent) edition will give you an understanding of the theory and practice of discovering patterns in large data sets. Each chapter is a stand-alone guide to a particular topic, making it a good resource if you’re not into reading in sequence or you want to know about a particular topic.
Mining of Massive Datasets – Based on the Stanford Computer Science course, this book is often sighted by data scientists as one of the most helpful resources around. It’s designed at the undergraduate level with no formal prerequisites. It’s the next best thing to actually going to Stanford!
Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners – This book is a must read for anyone who needs to do applied data mining in a business setting (ie practically everyone). It’s a complete resource for anyone looking to cut through the Big Data hype and understand the real value of data mining. Pay particular attention to the section on how modeling can be applied to business decision making.
Hadoop: The Definitive Guide – As a data scientist, you will undoubtedly be asked about Hadoop. So you’d better know how it works. This comprehensive guide will teach you how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. Make sure you get the most recent addition to keep up with this fast-changing service.
Online learning: data mining webinars and courses
DataCamp – Learn data mining from the comfort of your home with DataCamp’s online courses. They have free courses on R, Statistics, Data Manipulation, Dynamic Reporting, Large Data Sets and much more.
Coursera – Coursera brings you all the best University courses straight to your computer. Their online classes will teach you the fundamentals of interpreting data, performing analyzes and communicating insights. They have topics for beginners and advanced learners in Data Analysis, Machine Learning, Probability and Statistics and more.
Udemy – With a range of free and pay for data mining courses, you’re sure to find something you like on Udemy no matter your level. There are 395 in the area of data mining! All their courses are uploaded by other Udemy users meaning quality can fluctuate so make sure you read the reviews.
CodeSchool – These courses are handily organized into “Paths” based on the technology you want to learn. You can do everything from build a foundation in Git to take control of a data layer in SQL. Their engaging online videos will take you step-by-step through each lesson and their challenges will let you practice what you’ve learned in a controlled environment.
Udacity – Master a new skill or programming language with Udacity’s unique series of online courses and projects. Each class is developed by a Silicon Valley tech giant, so you know what your learning will be directly applicable to the real world.
Treehouse – Learn from experts in web design, coding, business and more. The video tutorials from Treehouse will teach you the basics and their quizzes and coding challenges will ensure the information sticks. And their UI is pretty easy on the eyes.
Learn from the best: top data miners to follow
John Foreman – Chief Data Scientist at MailChimp and author of Data Smart, John is worth a follow for his witty yet poignant tweets on data science.
DJ Patil – Author and Chief Data Scientist at The White House OSTP, DJ tweets everything you’ve ever wanted to know about data in politics.
Nate Silver – He’s Editor-in-Chief of FiveThirtyEight, a blog that uses data to analyze news stories in Politics, Sports, and Current Events.
Andrew Ng – As the Chief Data Scientist at Baidu, Andrew is responsible for some of the most groundbreaking developments in Machine Learning and Data Science.
Bernard Marr – He might know pretty much everything there is to know about Big Data.
Gregory Piatetsky – He’s the author of popular data science blog KDNuggets, the leading newsletter on data mining and knowledge discovery.
Christian Rudder – As the Co-founder of OKCupid, Christian has access to one of the most unique datasets on the planet and he uses it to give fascinating insight into human nature, love, and relationships
Dean Abbott – He’s contributed to a number of data blogs and authored his own book on Applied Predictive Analytics. At the moment, Dean is Chief Data Scientist at SmarterHQ.
Practice what you’ve learned: data mining competitions
Kaggle – This is the ultimate data mining competition. The world’s biggest corporations offer big prizes for solving their toughest data problems.
Stack Overflow – The best way to learn is to teach. Stackoverflow offers the perfect forum for you to prove your data mining know-how by answering fellow enthusiast’s questions.
TunedIT – With a live leaderboard and interactive participation, TunedIT offers a great platform to flex your data mining muscles.
DrivenData – You can find a number of nonprofit data mining challenges on DataDriven. All of your mining efforts will go towards a good cause.
Quora – Another great site to answer questions on just about everything. There are plenty of curious data lovers on there asking for help with data mining and data science.
Meet your fellow data miner: social networks, groups and meetups
Facebook – As with many social media platforms, Facebook is a great place to meet and interact with people who have similar interests. There are a number of very active data mining groups you can join.
LinkedIn – If you’re looking for data mining experts in a particular field, look no further than LinkedIn. There are hundreds of data mining groups ranging from the generic to the hyper-specific. In short, there’s sure to be something for everyone.
Meetup – Want to meet your fellow data miners in person? Attend a meetup! Just search for data mining in your city and you’re sure to find an awesome group near you.
Data storytelling is the realization of great data visualization. We’re seeing data that’s been analyzed well and presented in a way that someone who’s never even heard of data science can get it.
Google’s Cole Nussbaumer provides a friendly reminder of what data storytelling actually is, it’s straightforward, strategic, elegant, and simple.
Students, teachers, and organizations will join together online to celebrate and demonstrate global collaboration on September 15, 2016. On Global Collaboration Day, educators and professionals from around the world will host connective projects and events and invite public participation. This event is brought to you by VIF International Education,Google for Education, iEARN-USA and Edmodo.
The primary goals of this 24-hour, worldwide event are to:
demonstrate the power of global connectivity in classrooms, schools, institutions of informal learning and universities around the world
introduce others to the collaborative tools, resources and projects that are available to educators today
to focus attention on the need for developing globally competent students and teachers throughout the world
Global Collaboration Day will take place on September 15 in participant time zones. Classrooms, schools, and organizations will design and host engaging online activities for others to join. Events will range from mystery location calls to professional development events to interviews with experts. All events will be collated in an online calendar viewable in participants’ individual time zones. Participants will be connected on Twitter via the hashtag #globaled16.
An optional new activity this year will be the Great Global Project Challenge. Between now and October 1, 2016, global educators will design collaborative projects using a variety of platforms in which other students and teachers may participate during the course of the 2016-2017 school year. The objective is to create and present as many globally connective projects for students and educators as possible. The final deadline for submissions into our project directory is October 1, but participants are also encouraged to do an introductory activity for their project on Global Collaboration Day as well.
Global Collaboration Day is a project of the Global Education Conference Network, a free online virtual conference that takes place every November during International Education Week. GCD, along with Global Education Day at ISTE and Global Leadership Week, are events designed to connect educators and keep global conversations going year round.
Help us spread the word. Here are some sample Tweets:
Join us for Global Collaboration Day! Details here: http://bit.ly/2016GCD #globaled16
YOUR ORG’S TWITTER HANDLE is pleased to partner with @GlobalEdCon and educators around the globe for Global Collaboration Day: http://bit.ly/2016GCD
Are you an education leader? Inspire global collaboration on Global Collaboration Day 9/15. http://bit.ly/2016GCD #globaled16
Learn more about participating in the Global Collaboration Day celebration: http://bit.ly/2016GCD #globaled16
Project hosts are sought for Global Collaboration Day. Details here: http://bit.ly/2016GCD #globaled16
Logos and Badges for Participants, Hosts, Partners and Sponsors are located here:http://bit.ly/gcdimages
Interested in serving as an outreach partner?
Send an email to Lucy Gray (lucy@globaledevents.com) indicating your interest. Include information on how you can help us get the word out to networks with 5000 members or more.
Seeking to bring the qualities of well-designed games to pedagogical assessment, the University of Michigan created a learning management system that uses gaming elements such as competition, badges and unlocks to provide students with a personalized pathway through their courses.
a new type of learning management system called GradeCraft. GradeCraft borrows game elements such as badges and unlocks to govern students’ progress through a course. With unlocks, for example, you have to complete a task before moving to the next level.
Written in Ruby on Rails and hosted on Amazon Web Services, GradeCraft was created by a small team of students and faculty with additional software support from Ann Arbor-based developer Alfa Jango. Their work received support from UM’s Office of Digital Education and Innovation and the Office of the Provost. GradeCraft can work as a stand-alone platform or in conjunction with a traditional LMS via the LTI (Learning Tools Interoperability) protocol.
Here is how it works: Instructors create a course shell within GradeCraft (similar to the process with any LMS). Students use a tool called the “Grade Predictor” to plan a personalized pathway through the course, making predictions about both what they will do and how they will perform. When assignments are graded, predictions turn into progress; students are then nudged to revisit their semester plan, reassessing what work is available and how well they need to do to succeed overall. Students are able to independently choose an assessment pathway that matches their interests within the framework of learning objectives for the course.
“Colorado’s Digital Badging Initiative: A New Model of Credentialing Technical Math Skills and More”.
Educators and innovative industry leaders agree that digital badges are evolving into a key credential that can be used to meet current education and workforce needs. As part of its TAACCCT grant, the Colorado Community College System is leading a collaborative effort to develop micro-credentials or digital badges to serve post-secondary and workforce in partnership. Learn about early pilot uses of digital badges in technical math and advanced manufacturing, as well as plans for the future. The presenter will also share perspectives garnered from her participation in the Badge Alliance/OPEN badges workgroup that is shaping the national conversation on this emerging topic.
Presenter: Brenda Perea, Instructional Design Project Manager, Colorado Community College System
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badges are integrated with the industry partners of the educational institution
how to determine the value of a badge.
Faculty writing a competencies, online and blended environment. All agree that this means competency. Need to faculty buy in, if issuing badges. Objective versus subjective measures. Faculty member is the one who tells students how to earn badges. Not punitive, but a reward.
building the eco system in Colorado. But it can be taken on a national level. Employers in other states to accept. MS, Sisco are issuing badges, which will be internationally.
badges are transferable. not person to person, but repository
of 200 issues badges, they were shared 6K+ times over social media: LinkedIn, FB etc. by employers.
backpack, or stored in Mozilla backpack. Most of LMS developing badging capabilities.
some LMS want to create their own badging, gatekeep in LMS, but losing
Canvas allows any badging
LCI in any LMS. LMS allow the vehicle to be issued, but does not create it.
Please develop a one hour workshop for faculty on using a new (or old but new to them) technology tool. The aim is not to only show the technical operation, but the pedagogical use of the tool helping faculty think about what this might mean in their own teaching.
Who: students, faculty and staff
Where: TBD
When: Friday, June 17, 2016. 10-11:30 AM
5 min introduction of workshop presenter Plamen Miltenoff and workshop participants
5 min plan of the workshop
5 min introduction to the topic:
Outline In financially-sparse times for educational institutions, one viable way to save money is by rethinking pedagogy/methodology and adapt it to the burgeoning numbers of mobile devices (BYOD) owned by students, faculty and staff.
In 5 min,
we will be playing a game, using Kahoot (https://kahoot.it). Kahoot is an application from Norway, which is increasingly popular in K12 and gradually picking momentum at higher ed.
Why Kahoot and not any of the other similar polling apps (AKA formative assessment tools), such as PollEverywhere, PollDaddy etc. (https://blog.stcloudstate.edu/ims/2016/01/13/formative-assessment-tools/)?
1. Kahoot has gained momentum; at least one third of your undergraduates have used it in high school and are familiar with the interface.
2. I personally like Kahoot for the kahoots. J
3. I like badges as “badges in gamification.” Let me know, if you want to work on this topic some other time and lets schedule work time after this session (https://blog.stcloudstate.edu/ims?s=badges).
In 10-15 min,
lets try to create an account and build our first kahoot (https://getkahoot.com/). You can use any topic and focus on the features, which Kahoot provides. Split in groups and help each other; if you feel stuck, please let me know and I will do my best to help advance further.
Here are two YouTube lectures how to create an account and a kahoot quiz (5 min) and how to play a kahoot (3 min): https://blog.stcloudstate.edu/ims/2016/06/13/how-to-kahoot/
In 5-10 min,
let’s display 1-2 kahoot’s to the entire audience and think about situations, when and where such kahoots can be used for educational purposes.
Let’s think about the implications, which the use of kahoots on BOYD may trigger in the classroom
Let’s think about the preparation needed for the smooth use of the kahoots (is your WiFi in that particular classroom robust enough to hold the action of 20? 200? Students?
Let’s think about students’ engagement: what constitutes it? would a kahoot on their BYOD will be sufficient to pick their interest and if not, what else must be added to the magic elixir?
In 5 min, lets discuss Kahoot’s similarities with other educational technologies used in the classroom
Let’s assess the potential of Kahoot.
how does it compare
how does it transfer
is it compatible with Canvas