Sensors are cheap and abundant. They’re already in our devices, and soon enough, many of us may elect to carry sensors in and on our bodies, and embed them in our homes, offices, and cities. This terrifies people, Jason Silva says in a new video.
Who hasn’t heard of Big Brother or feared the rise of the surveillance state? But Silva says there’s an upside.
As the world is reduced to “algorithmic cascades of data” he thinks we’ll get what Steven Johnson calls the “long view,” like a microscope or telescope for previously invisible information and datasets.
Billions of sensors measuring location, motion, orientation, pressure, temperature, vital signs and more—each of these will be like a pixel. Seen up close, a modestly flashing primary color. But at a distance, individual pixels dissolve. Discrete points will smooth out into a contiguous image no one could have guessed by looking at looking at each pixel alone.
Understanding how an educational intervention is implemented is essential to evaluating its effectiveness. With the increased use of digital tools in classrooms, however, traditional methods of measuring implementation fall short. Fortunately, there
“ Using data to drive learning outcomes isn’t a new concept, really. For as long as teachers have been giving students assessments, the assessments and results have been used by both students and teachers (even if only loosely) to determine how to move forward. What needs to be reviewed more? What was covered/studied well? Learning analytics takes this concept and kicks it up a notch. Well, more like a thousand notches, especially if you’re considering things like adaptive computer based testing that changes as students use it.”
Adaptive learning technologies may pave the way to a "pedagogical renaissance." Although still in the early stages, these technologies have already shown some of their potential, as fewer students are failing or dropping out of classes that use these programs.
I believe the move to large-scale adoption of learning analytics, with the attendant rise in institution-level decisions, should motivate us to spend some time thinking about how concepts such as validity and reliability apply in this practical setting. Motivation comes from: large scale adoption has “upped the stakes”, and non-experts are now involved in decision-making. This article is a brief look at some of the issues with where we are now, and some of the potential pit-falls going forwards.
The search for data that impacts student success may lead to more questions than answers.
When we first sketched out a topic for this month's feature on the quest for data that impacts student success, we had a slightly different story in mind. We wanted to come up with a handful of data types that any higher ed institution pursuing learning analytics should have on its list — say, five key data points that really impact student outcomes.The search for data that impacts student success may lead to more questions than answers.
This past year welcomed widespread Internet of Things (IoT) adoption and hype, big data implementation, and growing concerns around data privacy and cloud deployment. As 2014 draws to a close, we look ahead with much anticipation for what promises to be a signature year for machine learning, predictive analytics, new IoT pioneers and a full overhaul in the distribution of the IoT.
In their discussions over the past year, the EDUCAUSE IT Issues Panel touched several times on the issue of analytics and strategies on how best to implement analytics in higher education. Discussions ranged from implementing analytics to improve core administrative and business functions to how best to implement analytics in a predictive sense to ensure student success in academic programs.
In answering five questions, the following IT Issues panelists provided their thoughts on how analytics can improve higher education and how best to implement analytics:
The rapidly evolving ecosystems associated with personal data is creating an entirely new field of scientific study, say computer scientists. And this requires a much more powerful ethics-based infrastructure.
Learning Analytics, just as with analytics in business, web or healthcare, has the power to empower the people in the training department of your organization with the information they need. Learning managers no longer have to rely on making educated guesses to determine the most useful components of a training module. Incorporating Learning Analytics tools within your enterprise LMS does that far more easily and efficiently.
UK universities are monitoring students’ information to help them to improve their academic performance but are giving insufficient thought to the effectiveness of the technology they use and the rights of those they track.
This is according to Sharon Slade, senior lecturer in the Faculty of Business, Management and Law at The Open University, which is believed to have become the first institution in the UK to produce a publicly available written policy on the ethical use of student data for learning analytics – the practice of collecting and analysing student data with the intention of optimising their educational experience.
Work on a transparent ethical policy at The Open University highlighted concerns about technology and privacy
The initiative will be led by researchers at Carnegie Mellon University, who propose to construct a new data-sharing infrastructure that is distributed across multiple institutions, including third-party and for-profit vendors.