Toolwire and Muzzy Lane, two digital game-based learning (DGBL) vendors that are making significant strides in higher education through their “serious game” products. The state of DGBL in higher ed is not nearly as prevalent and accepted as it is in K-12, but growing quickly.
Serious games feature evidenced-centered design, whereby data is collected, analyzed and adapted to the knowledge level of the player
Andy Phelps, director of the Rochester Institute of Technology Center for Media, Arts, Games, Interaction and Creativity (MAGIC) and executive committee member of the Higher Education Video Game Alliance (HEVGA),adds that “game-based learning has the opportunity to really challenge our assumptions about linear modes of educational interaction.”
Muzzy Lane, s higher-education-oriented Practice Series games, in partnership with McGraw Hill, feature titles in Marketing, Spanish, Medical Office and Operations.
The Challenge of Creating Worthy GamesBoth Toolwire and Muzzy Lane DGBL products are not of the “Triple A” PlayStation 4 and Xbox One variety, meaning they do not have all the high-fidelity, digital-media bells and whistles that are inside the heavily advertised war games and sports games geared toward the more than $99 billion global video game consumer marketplace, according to gaming market intelligence company Newzoo.
the state of DGBL in higher education consists of very effective digital games of less-than-Triple A fidelity coming out of private companies like Toolwire and Muzzy Lane, as well as from a good number of college and university game design innovation centers similar to RIT’s MAGIC. These include the Games+Learning+Society (GLS) Center at the University of Wisconsin-Madison; the University of Southern California Interactive Media and Games Division, the Carnegie Mellon University Entertainment Technology Center and the New York University Game Center.
While Pew Research from 2015 puts adult smartphone ownership in the U.S. at 72 percent, there’s some debate about smartphone ownership among children. The average age for a child to get their first smartphone is currently 10.3 years according to the recent Influence Central report, Kids & Tech: The Evolution of Today’s Digital Natives.
An average of 65 percent of children aged between 8 and 11 have their own smartphone in the U.K. according to a survey by Internet Matters. That survey also found that the majority of parents would like a minimum age for smartphone ownership in the U.K. to be set at age 10.
However, some kids are using smartphones from a very young age. One study by the American Academy of Pediatrics that focused on children in an urban, low-income, minority community suggested that almost all children (96.6 percent) use mobile devices and that 75 percent have their own mobile device by the age of four.
Lauricella, A., Wartella, E., & Rideout, V. (2015). Young children’s screen time: The complex role of parent and child factors. Journal of Applied Developmental Psychology, 36, 11–17. https://doi.org/10.1016/j.appdev.2014.12.001
Percentage of moms whose children used device by age 2.(THE DATA PAGE)(Statistical data). (2011). Editor & Publisher, 144(10).
PERCENTAGE OF MOMS WHOSE CHILDREN USED DEVICE BY AGE 2
Gen Y moms Gen X moms
Laptop 34% 29%
Cell Phone 34% 26%
Smart Phone 33% 20%
Digital Camera 30% 18%
iPod 34% 13%
Videogame System 13% 8%
Hand-held gaming device 13% 10%
Source: Frank N. Magid & Associates, Inc./Metacafe
Russia and far right spreading disinformation ahead of EU elections, investigators say
‘The goal here is bigger than any one election. It is to constantly divide, increase distrust and undermine our faith in institutions and democracy itself’
Matt Apuzzo, Adam Satariano 2019-05-12T13:13:04+01:00″
Microcredentials, or short-form online learning programs, is the latest buzzword that higher education providers are latching onto. They come with diminutive names such as Micromasters (by several universities working with edX) and nanodegrees (by Udacity). But they have the potential to shake up graduate education, potentially reducing demand for longer, more-traditional professional programs. At the core of the trend is the idea that professionals will go “back to school” repeatedly over their lifetimes, rather than carving out years at a time for an MBA or technical degree.
Credential Engine, a nonprofit funded by the Lumina Foundation, Microsoft and JPMorgan Chase, today launched its Credential Registry, a digital platform where institutions can upload degrees and credentials so prospective students can search for and compare credentials side-by-side.
Udacity won a trademark for Nanodegree last year. And in April, the nonprofit edX, founded by MIT and Harvard University to deliver online courses by a consortium of colleges, applied for a trademark on the word MicroMasters. And MicroDegree? Yep, that’s trademarked too, by yet another company.
colleges and universities that seek to meet corporate needs must move beyond monolithic programs and think in terms of competencies, unbundling curriculum, modularizing and “microlearning.” Many institutions are already pioneering efforts in this direction, from the certificate- and badge-oriented University of Learning Store (led by the Universities of Wisconsin, California, Washington and others) to Harvard Business School’s HBX, and the new “iCert” that we developed at Northeastern University. These types of shorter-form, competency-oriented programs can better fit corporate demands for targeted and applied learning.
T-Mobile Chief Technology Officer Neville Ray wrote in a blog post that millimeter-wave spectrum used for 5G “will never materially scale beyond small pockets of 5G hotspots in dense urban environments.”
With 4G, carriers prioritized so-called “beachfront spectrum” below 1GHz in order to cover the entire US, both rural areas and cities.
5G networks will use both low and high frequencies, but they’re supposed to offer their highest speeds on millimeter waves.
Because of technological advances and the sheer amount of data now available about billions of other people, discretion no longer suffices to protect your privacy. Computer algorithms and network analyses can now infer, with a sufficiently high degree of accuracy, a wide range of things about you that you may have never disclosed, including your moods, your political beliefs, your sexual orientation and your health.
There is no longer such a thing as individually “opting out” of our privacy-compromised world.
In 2017, the newspaper The Australian published an article, based on a leaked document from Facebook, revealing that the company had told advertisers that it could predict when younger users, including teenagers, were feeling “insecure,” “worthless” or otherwise in need of a “confidence boost.” Facebook was apparently able to draw these inferences by monitoring photos, posts and other social media data.
In 2017, academic researchers, armed with data from more than 40,000 Instagram photos, used machine-learning tools to accurately identify signs of depression in a group of 166 Instagram users. Their computer models turned out to be better predictors of depression than humans who were asked to rate whether photos were happy or sad and so forth.
Computational inference can also be a tool of social control. The Chinese government, having gathered biometric data on its citizens, is trying to use big data and artificial intelligence to single out “threats” to Communist rule, including the country’s Uighurs, a mostly Muslim ethnic group.
Zeynep Tufekci and Seth Stephens-Davidowitz: Privacy is over
This position paper is meant to i) support the dialog among European and national policy makers, industry, research, public sector and civic society in the definition of a common roadmap for the development and adoption of a pan-European Data Sharing Space, and ii) guide public and private investments in this area in the next Multiannual Financial Framework.