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big data

big-data-in-education-report

Center for Digital Education (CDE)

real-time impact on curriculum structure, instruction delivery and student learning, permitting change and improvement. It can also provide insight into important trends that affect present and future resource needs.

Big Data: Traditionally described as high-volume, high-velocity and high-variety information.
Learning or Data Analytics: The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.
Educational Data Mining: The techniques, tools and research designed for automatically extracting meaning from large repositories of data generated by or related to people’s learning activities in educational settings.
Predictive Analytics: Algorithms that help analysts predict behavior or events based on data.
Predictive Modeling: The process of creating, testing and validating a model to best predict the probability of an outcome.

Data analytics, or the measurement, collection, analysis and reporting of data, is driving decisionmaking in many institutions. However, because of the unique nature of each district’s or college’s data needs, many are building their own solutions.

For example, in 2014 the nonprofit company inBloom, Inc., backed by $100 million from the Gates Foundation and the Carnegie Foundation for the Advancement of Teaching, closed its doors amid controversy regarding its plan to store, clean and aggregate a range of student information for states and districts and then make the data available to district-approved third parties to develop tools and dashboards so the data could be used by classroom educators.22

Tips for Student Data Privacy

Know the Laws and Regulations
There are many regulations on the books intended to protect student privacy and safety: the Family Educational Rights and Privacy Act (FERPA), the Protection of Pupil Rights Amendment (PPRA), the Children’s Internet Protection Act (CIPA), the Children’s Online Privacy Protection Act (COPPA) and the Health Insurance Portability and Accountability Act (HIPAA)
— as well as state, district and community laws. Because technology changes so rapidly, it is unlikely laws and regulations will keep pace with new data protection needs. Establish a committee to ascertain your institution’s level of understanding of and compliance with these laws, along with additional safeguard measures.
Make a Checklist Your institution’s privacy policies should cover security, user safety, communications, social media, access, identification rules, and intrusion detection and prevention.
Include Experts
To nail down compliance and stave off liability issues, consider tapping those who protect privacy for a living, such as your school attorney, IT professionals and security assessment vendors. Let them review your campus or district technologies as well as devices brought to campus by students, staff and instructors. Finally, a review of your privacy and security policies, terms of use and contract language is a good idea.
Communicate, Communicate, Communicate
Students, staff, faculty and parents all need to know their rights and responsibilities regarding data privacy. Convey your technology plans, policies and requirements and then assess and re-communicate those throughout each year.

“Anything-as-a-Service” or “X-as-a-Service” solutions can help K-12 and higher education institutions cope with big data by offering storage, analytics capabilities and more. These include:
• Infrastructure-as-a-Service (IaaS): Providers offer cloud-based storage, similar to a campus storage area network (SAN)

• Platform-as-a-Service (PaaS): Opens up application platforms — as opposed to the applications themselves — so others can build their own applications
using underlying operating systems, data models and databases; pre-built application components and interfaces

• Software-as-a-Service (SaaS): The hosting of applications in the cloud

• Big-Data-as-a-Service (BDaaS): Mix all the above together, upscale the amount of data involved by an enormous amount and you’ve got BDaaS

Suggestions:

Use accurate data correctly
Define goals and develop metrics
Eliminate silos, integrate data
Remember, intelligence is the goal
Maintain a robust, supportive enterprise infrastructure.
Prioritize student privacy
Develop bullet-proof data governance guidelines
Create a culture of collaboration and sharing, not compliance.

more on big data in this IMS blog:

http://blog.stcloudstate.edu/ims/?s=big+data&submit=Search

Horizon Report 2014, Library edition

http://cdn.nmc.org/media/2014-nmc-horizon-report-library-EN.pdf

p. 4 new and rapidly changing technologies, an abundance of digital information in myriad formats, an increased understanding of how students learn evolving research methods, and changing practices in how scholars communicate and disseminate their research and creative work.

Engagement requires an outward focus

A liaison who understands how scholars in a particular discipline communicate and share
information with one another can inform the design and development of new publishing services, such as
digital institutional repositories.

Liaisons cannot be experts themselves in each new capability, but knowing when to call in a
colleague, or how to describe appropriate expert capabilities to faculty, will be key to the new liaison role.

an increasing focus on what users do (research, teaching, and learning) rather than on what librarians do (collections, reference, library instruction).

hybrid model, where liaisons pair their expertise with that of functional specialists, both within and outside of libraries

p. 6 Trend 1: Develop user-centered library services

Many libraries are challenged to brand such a service point, citing a “hub” or “center” to refer to services that can include circulation, reference, computer support, writing assistance, and more.

For liaisons, time at a reference desk has been replaced by anticipating recurrent needs and developing
easily accessible online materials (e.g., LibGuides, screencasts) available to anyone at any time, and
by providing more advanced one-on-one consultations with students, instructors, and researchers who
need expert help. Liaisons not only answer questions using library resources, but they also advise and
collaborate on issues of copyright, scholarly communication, data management, knowledge management,
and information literacy. The base level of knowledge that a liaison must possess is much broader than
familiarity with a reference collection or facility with online searching; instead, they must constantly keep up
with evolving pedagogies and research methods, rapidly developing tools, technologies, and ever-changing
policies that facilitate and inform teaching, learning, and research in their assigned disciplines.

Librarians at many institutions are now focusing on collaborating with faculty to develop thoughtful assignments
and provide online instructional materials that are built into key courses within a curriculum and provide
scaffolding to help students develop library research skills over the course of their academic careers

p. 7 Trend 2: A hybrid model of liaison and functional specialist is emerging.

Current specialist areas of expertise include copyright, geographic information systems (GIS), media production and integration, distributed education or e-learning, data management, emerging technologies,
user experience, instructional design, and bioinformatics.

At the University of Guelph, the liaison model was abandoned altogether in favor of a functional specialist
approach

p. 8 Trend 3: Organizational flexibility must meet changing user needs.

p. 9 provide education and consultation services for personal information management. Tools, workshops, websites, and individual consults are offered in areas such as citation management, productivity tools, managing alerts and feeds, personal archiving, and using social networking for teaching and professional development.

p. 11 data management, knowledge management and scholarly communication

digital scholarship

p. 12 Liaisons need to be able to provide a general level of knowledge about copyright, data management, the need for metadata and the ontologies available in their disciplines.

p. 13 Liaisons need to be able to provide a general level of knowledge about copyright, data management, the need for metadata and the ontologies available in their disciplines.

p. 16 replacing the traditional tripartite model of collections, reference, and instruction

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