“patient sovereignty” will now become an important debate. In particular, the ownership of data in healthcare, while already an important topic of discussion, will become an even more complex argument.

m-health offers predominantly interconnectivity between patients and healthcare professionals while IoT devices offer the ability to collect information and perform procedures with increasingly minimal invasion. Finally, big data gives healthcare professionals an opportunity to spot trends and patterns for both individual patients and groups of patients, improving the speed of diagnosis and disease prevention. In the next section the third and final pillar of Health 4.0; design, is discussed

In marketing, familiar uses of big data include “recommendation engines” like those used by companies such as Netflix and Amazon to make purchase suggestions based on the prior interests of one customer as compared to millions of others.

They have a very simplistic view of the activity being monitored by only distilling it down into only a few dimensions for the rule to interrogate

often private companies whose technologies power the systems universities use for predictive analytics and adaptive courseware

the use of data in scholarly research about student learning; the use of data in systems like the admissions process or predictive-analytics programs that colleges use to spot students who should be referred to an academic counselor; and the ways colleges should treat nontraditional transcript data, alternative credentials, and other forms of documentation about students’ activities, such as badges, that recognize them for nonacademic skills.

I could have easily chosen a different prepositional phrase. "Convivial Tools in an Age of Big Data.” Or “Convivial Tools in an Age of DRM.” Or “Convivial Tools in an Age of Venture-Funded Education Technology Startups.” Or “Convivial Tools in an Age of Doxxing and Trolls."

"We know the day before the course starts which students are highly unlikely to succeed,"

“fundamentally if we want to realize the potential of human networks to change how we work then we need analytics to transform information into insight otherwise we will be drowning in a sea of content and deafened by a cacophony of voices”

Dominique Cardon is calling on businesses to disclose the purpose of their algorithms.

it’s more the harmful threat of algorithms that we should be worried about.

However, a Fitbit device Risley was wearing told a different story, the affidavit shows.

your system is able to flag at least a critical mass of videos taught in the Mueller method as having a bigger educational impact on the students the average educational video by some measure you have identified

sufficiently rich information

It’s educators who come up with hypotheses and test them using a large data set.

Some were done this way on purpose but based on intuitions by classroom teachers.

hadoop thingamabob back end

a good example of the kind of insight that big data is completely blind to

As long as the content in SmartBooks is locked down, then it is possible to run machine learning algorithms against the clicks of millions of students using that content. To the degree that the platform is opened up for custom, newly created books, the controlled experiment goes away and the possibility of big data analysis goes with it.

they are making a bet against the software as a replacement for the teacher and against big data

numbers have to be interpreted by those who do the daily work of classroom teaching

That's why I say that data is the new oil for the digital age

grows exponentially.

Ein Start-up aus den USA testet ein neues Hilfsmittel zur Minimierung der Folgen von Datendiebstählen: Es prüft, ob in versteckten Teilen des Web fremde Daten zum Kauf angeboten werden.