Posts Tagged ‘edad 697’

NISO Webinar IoT

Wednesday, October 19, 2016
1:00 p.m. – 2:30 p.m. (Eastern Time)

About the Webinar

As the cost of sensors and the connectivity necessary to support those sensors has decreased, this has given rise to a network of interconnected devices.  This network is often described as the Internet of Things and it is providing a variety of information management challenges.  For the library and publishing communities, the internet of things presents opportunities and challenges around data gathering, organization and processing of the tremendous amounts of data which the internet of things is generating.  How will these data be incorporated into traditional publication, archiving and resource management systems?  Additionally, how will the internet of things impact resource management within our community?   In what ways will interconnected resources provide a better user experience for patrons and readers?  This session will introduce concepts and potential implications of the internet of things on the information management community.  It will also explore applications related to managing resources in a library environment that are being developed and implemented.

Education in the Internet of Things
Bryan Alexander, Consultant;

How will the Internet of Things shape education? We can explore this question by assessing current developments, looking for future trends in the first initial projects. In this talk I point to new concepts for classroom and campus spaces, examining attendant rises in data gathering and analysis. We address student life possibilities and curricular and professional niches. We conclude with notes on campus strategy, including privacy, network support, and futures-facing organizations.

What Does The Internet of Things Mean to a Museum?
Robert Weisberg, Senior Project Manager, Publications and Editorial Department; Metropolitan Museum of Art;

What does the Internet of Things mean to a museum? Museums have slowly been digitizing their collections for years, and have been replacing index cards with large (and costly, and labor-intensive) CMS’s long before that, but several factors have worked against adopting smart and scalable practices which could unleash data for the benefit of the institution, its collection, and its audiences. Challenges go beyond non-profit budgets in a very for-profit world and into the siloed behaviors learned from academia, practices borne of the uniqueness of museum collections, and the multi-faceted nature of modern museums which include not only curator, but conservators, educators, librarians, publishers, and increasing numbers of digital specialists. What have museums already done, what are they doing, and what are they preparing for, as big data becomes bigger and ever more-networked?
The Role of the Research Library in Unpacking The Internet of Things
Lauren di Monte, NCSU Libraries Fellow, Cyma Rubin Fellow, North Carolina State University

The Internet of Things (IoT) is a deceptively simple umbrella term for a range of socio-technical tools and processes that are shaping our social and economic worlds. Indeed, IoT represents a new infrastructural layer that has the power to impact decision-making processes, resources distribution plans, information access, and much more. Understanding what IoT is, how “things” get networked, as well as how IoT devices and tools are constructed and deployed, are important and emerging facets of information literacy. Research libraries are uniquely positioned to help students, researchers, and other information professionals unpack IoT and understand its place within our knowledge infrastructures and digital cultures. By developing and modeling the use of IoT devices for space and program assessment, by teaching patrons how to work with IoT hardware and software, and by developing methods and infrastructures to collect IoT devices and data, we can help our patrons unlock the potential of IoT and harness the power of networked knowledge.

Lauren Di Monte is a Libraries Fellow at NC State. In this role she develops programs that facilitate critical and creative engagements with technologies and develops projects to bring physical and traditional computing into scholarship across the disciplines. Her current research explores the histories and futures of STEM knowledge practices.

What does the internet of things mean for education?

Bryan Alexander:

I’m not sure if the IoT will hit academic with the wave force of the Web in the 1990s, or become a minor tangent.  What do schools have to do with Twittering refrigerators?

Here are a few possible intersections.

  1. Changing up the campus technology space.  IT departments will face supporting more technology strata in a more complex ecosystem.  Help desks and CIOs alike will have to consider supporting sensors, embedded chips, and new devices.  Standards, storage, privacy, and other policy issues will ramify.
  2. Mutating the campus.  We’ve already adjusted campus spaces by adding wireless coverage, enabling users and visitors to connect from nearly everywhere.  What happens when benches are chipped, skateboards sport sensors, books carry RFID, and all sorts of new, mobile devices dot the quad?  One British school offers an early example.
  3. New forms of teaching and learning.  Some of these take preexisting forms and amplify them, like tagging animals in the wild or collecting data about urban centers.  The IoT lets us gather more information more easily and perform more work upon it.  Then we could also see really new ways of learning, like having students explore an environment (built or natural) by using embedded sensors, QR codes, and live datastreams from items and locations.  Instructors can build treasure hunts through campuses, nature preserves, museums, or cities.  Or even more creative enterprises.
  4. New forms of research.  As with #3, but at a higher level.  Researchers can gather and process data using networked swarms of devices.  Plus academics studying and developing the IoT in computer science and other disciplines.
  5. An environmental transformation.  People will increasingly come to campus with experiences of a truly interactive, data-rich world.  They will expect a growing proportion of objects to be at least addressable, if not communicative.  This population will become students, instructors, and support staff.  They will have a different sense of the boundaries between physical and digital than we now have in 2014. Will this transformed community alter a school’s educational mission or operations?

How the internet could evolve to 2026: responding to Pew Posted on

bid data and school abscence

Data Can Help Schools Confront ‘Chronic Absence’

By Dian Schaffhauser 09/22/16

https://thejournal.com/articles/2016/09/22/data-can-help-schools-confront-chronic-absence.aspx

The data shared in June by the Office for Civil Rights, which compiled it from a 2013-2014 survey completed by nearly every school district and school in the United States. new is a report from Attendance Works and the Everyone Graduates Center that encourages schools and districts to use their own data to pinpoint ways to take on the challenge of chronic absenteeism.

The first is research that shows that missing that much school is correlated with “lower academic performance and dropping out.” Second, it also helps in identifying students earlier in the semester in order to get a jump on possible interventions.

The report offers a six-step process for using data tied to chronic absence in order to reduce the problem.

The first step is investing in “consistent and accurate data.” That’s where the definition comes in — to make sure people have a “clear understanding” and so that it can be used “across states and districts” with school years that vary in length. The same step also requires “clarifying what counts as a day of attendance or absence.”

The second step is to use the data to understand what the need is and who needs support in getting to school. This phase could involve defining multiple tiers of chronic absenteeism (at-risk, moderate or severe), and then analyzing the data to see if there are differences by student sub-population — grade, ethnicity, special education, gender, free and reduced price lunch, neighborhood or other criteria that require special kinds of intervention.

Step three asks schools and districts to use the data to identify places getting good results. By comparing chronic absence rates across the district or against schools with similar demographics, the “positive outliers” may surface, showing people that the problem isn’t unstoppable but something that can be addressed for the better.

Steps five and six call on schools and districts to help people understand why the absences are happening, develop ways to address the problem.

The report links to free data tools on the Attendance Works website, including a calculator for tallying chronic absences and guidance on how to protect student privacy when sharing data.

The full report is freely available on the Attendance Works website.

++++++++++++++
more on big data in education in this IMS blog
https://blog.stcloudstate.edu/ims?s=data