Significant Challenges Impeding Technology Adoption in K–12 Education
Improving Digital Literacy.
Schools are charged with developing students’ digital citizenship, ensuring mastery of responsible and appropriate technology use, including online etiquette and digital rights and responsibilities in blended and online learning settings. Due to the multitude of elements comprising digital literacy, it is a challenge for schools to implement a comprehensive and cohesive approach to embedding it in curricula.
Rethinking the Roles of Teachers.
Pre-service teacher training programs are also challenged to equip educators with digital and social–emotional competencies, such as the ability to analyze and use student data, amid other professional requirements to ensure classroom readiness.
p. 28 Improving Digital Literacy
Digital literacy spans across subjects and grades, taking a school-wide effort to embed it in curricula. This can ensure that students are empowered to adapt in a quickly changing world
Education Overview: Digital Literacy Has to Encompass More Than Social Use
The American Library Association (ALA) defines digital literacy as “the ability to use information and communication technologies to find, evaluate, create, and communicate or share information, requiring both cognitive and technical skills.” While the ALA’s definition does align to some of the skills in “Participate”, it does not specifically mention the skills related to the “Open Practice.”
The library community’s digital and information literacy standards do not specifically include the coding, revision and remixing of digital content as skills required for creating digital information. Most digital content created for the web is “dynamic,” rather than fixed, and coding and remixing skills are needed to create new content and refresh or repurpose existing content. Leaving out these critical skills ignores the fact that library professionals need to be able to build and contribute online content to the ever-changing Internet.
p. 30 Rethinking the Roles of Teachers
Teachers implementing new games and software learn alongside students, which requires
a degree of risk on the teacher’s part as they try new methods and learn what works
p. 32 Teaching Computational Thinking
p. 36 Sustaining Innovation through Leadership Changes
shift the role of teachers from depositors of knowledge to mentors working alongside students;
p. 38 Important Developments in Educational Technology for K–12 Education
Consumer technologies are tools created for recreational and professional purposes and were not designed, at least initially, for educational use — though they may serve well as learning aids and be quite adaptable for use in schools.
Drones > Real-Time Communication Tools > Robotics > Wearable Technology
Digital strategies are not so much technologies as they are ways of using devices and software to enrich teaching and learning, whether inside or outside the classroom.
> Games and Gamification > Location Intelligence > Makerspaces > Preservation and Conservation Technologies
Enabling technologies are those technologies that have the potential to transform what we expect of our devices and tools. The link to learning in this category is less easy to make, but this group of technologies is where substantive technological innovation begins to be visible. Enabling technologies expand the reach of our tools, making them more capable and useful
Affective Computing > Analytics Technologies > Artificial Intelligence > Dynamic Spectrum and TV White Spaces > Electrovibration > Flexible Displays > Mesh Networks > Mobile Broadband > Natural User Interfaces > Near Field Communication > Next Generation Batteries > Open Hardware > Software-Defined Networking > Speech-to-Speech Translation > Virtual Assistants > Wireless Powe
Internet technologies include techniques and essential infrastructure that help to make the technologies underlying how we interact with the network more transparent, less obtrusive, and easier to use.
Bibliometrics and Citation Technologies > Blockchain > Digital Scholarship Technologies > Internet of Things > Syndication Tools
Learning technologies include both tools and resources developed expressly for the education sector, as well as pathways of development that may include tools adapted from other purposes that are matched with strategies to make them useful for learning.
Adaptive Learning Technologies > Microlearning Technologies > Mobile Learning > Online Learning > Virtual and Remote Laboratories
Social media technologies could have been subsumed under the consumer technology category, but they have become so ever-present and so widely used in every part of society that they have been elevated to their own category.
Crowdsourcing > Online Identity > Social Networks > Virtual Worlds
Visualization technologies run the gamut from simple infographics to complex forms of visual data analysis
3D Printing > GIS/Mapping > Information Visualization > Mixed Reality > Virtual Reality
p. 46 Virtual Reality
p. 48 AI
p. 50 IoT
more on NMC Horizon Reports in this IMS blog
The Internet of Things (IoT), augmented reality, and advancements in online learning have changed the way universities reach prospective students, engage with their current student body, and provide them the resources they need.
The Internet of Things has opened up a whole new world of possibilities in higher education. The increased connectivity between devices and “everyday things” means better data tracking and analytics, and improved communication between student, professor, and institution, often without ever saying a word. IoT is making it easier for students to learn when, how, and where they want, while providing professors support to create a more flexible and connected learning environment.
Virtual and augmented reality technologies have begun to take Higher Ed into the realm of what used to be considered science fiction.
By 2020 more than 50 billion things, ranging from cranes to coffee machines, will be connected to the internet. That means a lot of data will be created — too much data, in fact, to be manageable or to be kept forever affordably.
One by-product of more devices creating more data is that they are speaking lots of different programming languages. Machines are still using languages from the 1970s and 80s as well as the new languages of today. In short, applications need to have data translated for them — by an IoT babelfish, if you will — before they can make sense of the information.
Then there are analytics and data storage.
security becomes even more important as there is little human interaction in the flow of data from device to datacentre — so called machine-to-machine communication.
a report from ISACA, a nonprofit association focused on knowledge and practices for information systems. The 2017 State of Cyber Security Study surveyed IT security leaders around the globe on security issues, the emerging threat landscape, workforce challenges and more.
53 percent of survey respondents reported a year-over-year increase in cyber attacks;
62 percent experienced ransomware in 2016, but only 53 percent have a formal process in place to address a ransomware attack;
78 percent reported malicious attacks aimed at impairing an organization’s operations or user data;
Only 31 percent said they routinely test their security controls, while 13 percent never test them; and
16 percent do not have an incident response plan.
65 percent of organizations now employ a chief information security officers, up from 50 percent in 2016, yet still struggle to fill open cyber security positions;
48 percent of respondents don’t feel comfortable with their staff’s ability to address complex cyber security issues;
More than half say cyber security professionals “lack an ability to understand the business”;
One in four organizations allot less than $1,000 per cyber security team member for training; and
About half of the organizations surveyed will see an increase in their cyber security budget, down from 61 percent in 2016.
IoT to Represent More Than Half of Connected Device Landscape by 2021
Industrial revolutions are momentous events. By most reckonings, there have been only three. The first was triggered in the 1700s by the commercial steam engine and the mechanical loom. The harnessing of electricity and mass production sparked the second, around the start of the 20th century. The computer set the third in motion after World War II.
Henning Kagermann, the head of the German National Academy of Science and Engineering (Acatech), did exactly that in 2011, when he used the term Industrie 4.0 to describe a proposed government-sponsored industrial initiative.
The term Industry 4.0 refers to the combination of several major innovations in digital technology
These technologies include advanced robotics and artificial intelligence; sophisticated sensors; cloud computing; the Internet of Things; data capture and analytics; digital fabrication (including 3D printing); software-as-a-service and other new marketing models; smartphones and other mobile devices; platforms that use algorithms to direct motor vehicles (including navigation tools, ride-sharing apps, delivery and ride services, and autonomous vehicles); and the embedding of all these elements in an interoperable global value chain, shared by many companies from many countries.
Companies that embrace Industry 4.0 are beginning to track everything they produce from cradle to grave, sending out upgrades for complex products after they are sold (in the same way that software has come to be updated). These companies are learning mass customization: the ability to make products in batches of one as inexpensively as they could make a mass-produced product in the 20th century, while fully tailoring the product to the specifications of the purchaser
Three aspects of digitization form the heart of an Industry 4.0 approach.
• The full digitization of a company’s operations
• The redesign of products and services
• Closer interaction with customers
Making Industry 4.0 work requires major shifts in organizational practices and structures. These shifts include new forms of IT architecture and data management, new approaches to regulatory and tax compliance, new organizational structures, and — most importantly — a new digitally oriented culture, which must embrace data analytics as a core enterprise capability.
Klaus Schwab put it in his recent book The Fourth Industrial Revolution (World Economic Forum, 2016), “Contrary to the previous industrial revolutions, this one is evolving at an exponential rather than linear pace.… It is not only changing the ‘what’ and the ‘how’ of doing things, but also ‘who’ we are.”
This great integrating force is gaining strength at a time of political fragmentation — when many governments are considering making international trade more difficult. It may indeed become harder to move people and products across some national borders. But Industry 4.0 could overcome those barriers by enabling companies to transfer just their intellectual property, including their software, while letting each nation maintain its own manufacturing networks.
more on the Internet of Things in this IMS blog http://blog.stcloudstate.edu/ims?s=internet+of+things
What is library leadership? a library leader is defined as the individual who articulates a vision for the organization/task and is able to inspire support and action to achieve the vision. A manager, on the other hand, is the individual tasked with organizing and carrying out the day-to-day operational activities to achieve the vision.Work places are organized in hierarchical and in team structures. Managers are appointed to administer business units or organizations whereas leaders may emerge from all levels of the hierarchical structures. Within a volatile climate the need for strong leadership is essential.
Leaders are developed and educated within the working environment where they act and co-work with their partners and colleagues. Effective leadership complies with the mission and goals of the organization. Several assets distinguish qualitative leadership:
Mentoring. Motivation. Personal development and skills. Inspiration and collaboration. Engagement. Success and failure. Risk taking. Attributes of leaders.
Leaders require having creative minds in shaping strategies and solving problems. They are mentors for the staff, work hard and inspire them to do more with less and to start small and grow big. Staff need to be motivated to work at their optimum performance level. Leadership entails awareness of the responsibilities inherent to the roles of a leader. However, effective leadership requires the support of the upper management.
p. 36. Developments in Technology for Academic and Research Libraries
Digital strategies are not so much technologies as they are ways of using devices and software to enrich teaching, learning, research and information management, whether inside or outside the library. Effective Digital strategies can be used in both information and formal learning; what makes them interesting is that they transcended conventional ideas to create something that feels new, meaningful, and 21st century.
this group of technologies is where substantive technological innovation begins to be visible.
social media technologies. could have been subsumed under the consumer technology category, but they have become so ever-present and so widely used in every part of society that they have been elevated to their own category. As well-established as social media is, it continues to evolve at a rapid pace, with new ideas, tools, and developments coming online constantly.
Visualization technologies. from simple infographics to complex forms of visual data analysis. What they have in common is that they tap the brain’s inherent ability to rapidly process visual information, identify patterns, and sense order in complex situations. These technologies are a growing cluster of tools and processes for mining large data sets, exploring dynamic processes, and generally making the complex simple.
p. 38 Big Data
Big data has significant implications for academic libraries in their roles as facilitators and supporters of the research process. big data use in the form of digital humanities research. Libraries are increasingly seeking to recruit for positions such as research data librarians, data curation specialists, or data visualization specialists
p. 40 Digital Scholarship Technologies
digital humanities scholars are leveraging new tools to aid in their work. ubiquity of new forms of communication including social media, text analysis software such as Umigon is helping researchers gauge public sentiment. The tool aggregates and classifies tweets as negative, positive, or neutral.
p. 42 Library Services Platforms
Diversity of format and materials, in turn, required new approaches to content collection and curation that were unavailable in the incumbent integrated library systems (ILS), which are primarily designed for print materials. LSP is different from ILS in numerous ways. Conceptually, LSPs are modeled on the idea of software as a service (SaaS),which entails delivering software applications over the internet.
p. 44 Online Identity.
incorporated the management of digital footprints into their programming and resources
simplify the idea of digital footprint as“data about the data” that people are searching or using online. As resident champions for advancing digital literacy,304 academic and research libraries are well-positioned to guide the process of understanding and crafting online identities.
Libraries are becoming integral players in helping students understand how to create and manage their online identities. website includes a social media skills portal that enables students to view their digital presence through the lens in which others see them, and then learn how they compare to their peers.
beacons are another iteration of the IoT that libraries have adopted; these small wireless devices transmit a small package of data continuously so that when devices come into proximity of the beacon’s transmission, functions are triggered based on a related application.340 Aruba Bluetooth low-energy beacons to link digital resources to physical locations, guiding patrons to these resources through their custom navigation app and augmenting the user experience with location-based information, tutorials, and videos.
students and their computer science professor have partnered with Bavaria’s State Library to develop a library app that triggers supplementary information about its art collection or other points of interest as users explore the space
My note: I listened to the report in my car yesterday. It is another sober reminder for being proactive rather then reactive (or punitive). We must work toward digital literacy and go beyond that comfortably numb stage of information literacy.
An Experiment Shows How Quickly The Internet Of Things Can Be Hacked
We have basic security in place in modern devices that screen out the most obvious attacks. Really getting phished, if you will, is more of a problem where you are tricked in surrendering your password or username to a common service. If you plug in your webcam into your router or to your Wi-Fi, you’re relatively safe.
I think the biggest security concern for folks at home would be if their router actually is old, it might have an easily guessed password that someone could gain control. Most modern devices don’t have that problem, but that certainly is a concern for older devices.
The first step to becoming an IoT Product Manager is to understand the 5 layers of the IoT technology stack.
Devices constitute the “things” in the Internet of Things. They act as the interface between the real and digital worlds.
2. Embedded software
Embedded software is the part that turns a device into a “smart device”. This part of the IoT technology stack enables the concept of “software-defined hardware”, meaning that a particular hardware device can serve multiple applications depending on the embedded software it is running.
Embedded Operating System
The complexity of your IoT solution will determine the type of embedded Operating System (OS) you need. Some of the key considerations include whether your application needs a real-time OS, the type of I/O support you need, and whether you need support for the full TCP/IP stack.
This is the application(s) that run on top of the embedded OS and provide the functionality that’s specific to your IoT solution.
Communications refers to all the different ways your device will exchange information with the rest of the world. This includes both physical networks and the protocols you will use.
4. Cloud Platform
The cloud platform is the backbone of your IoT solution. If you are familiar with managing SaaS offerings, then you are well aware of everything that is entailed here. Your infrastructure will serve as the platform for these key areas:
Data Collection and Management
Your smart devices will stream information to the cloud. As you define the requirements of your solution, you need to have a good idea of the type and amount of data you’ll be collecting on a daily, monthly, and yearly basis.
Analytics are one of they key components of any IoT solution. By analytics, I’m referring to the ability to crunch data, find patterns, perform forecasts, integrate machine learning, etc. It is the ability to find insights from your data and not the data alone that makes your solution valuable.
The Internet of Things is all about connecting devices and sharing data. This is usually done by exposing APIs at either the Cloud level or the device level. Cloud APIs allow your customers and partners to either interact with your devices or to exchange data. Remember that opening an API is not a technical decision, it’s a business decision.
This is the part of the stack that is most easily understood by Product teams and Executives. Your end-user applications are the part of the system that your customer will see and interact with. These applications will most likely be Web-based, and depending on your user needs, you might need separate apps for desktop, mobile, and even wearables.
The Bottom Line
As the Internet of Things continues to grow, the world will need an army of IoT-savvy Product Managers. And those Product Managers will need to understand each layer of the stack, and how they all fit together into a complete IoT solution.
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.
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.
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.
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.
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.
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.
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?