1. Using a blockchain for automatic recognition and transfer of credits
The decline in first-time, first-year student enrollments is having a real financial impact on a number of institutions across the United States and focusing on transfer students (a pool of prospects twice as large) has become an important strategy for many. But credit articulation presents a real challenge for institutions bringing in students from community colleges. While setting standardized articulation requirements across the nation presents a high hurdle, blockchain-supported initiatives may hold great promise for university and city education systems looking to streamline educational mobility in their communities.
2. Blockchains for tracking intellectual property and rewarding use and re-use of that property
If researchers were able to publish openly and accurately assess the use of their resources, the access-prohibitive costs of academic book and journal publications could be circumvented, whether for research- or teaching-oriented outputs. Accurately tracking the sharing of knowledge without restrictions has transformative potential for open-education models.
3. Using verified sovereign identities for student identification within educational organizations
The data footprint of higher education institutions is enormous. With FERPA regulations as well as local and international requirements for the storage and distribution of Personally Identifiable Information (PII), maintaining this data in various institutional silos magnifies the risk associated with a data breach. Using sovereign identities to limit the proliferation of personal data promotes better data hygiene and data lifecycle management and could realize significant efficiency gains at the institutional level.
4. Using a blockchain as a lifelong learning passport
Educational institutions and private businesses partner with online course delivery giants to extend the reach of their educational services and priorities. Traditional educational routes are increasingly less normal and in this expanding world of providers, the need for verifiable credentials from a number of sources is growing. Producing a form of digitally “verifiable CVs” would limit credential fraud, and significantly reduce organizational workload in credential verification.
5. Using blockchains to permanently secure certificates
The open source solution Blockcerts already enables signed certificates to be posted to a blockchain and supports the verification of those certificates by third parties.
When an institution issues official transcripts, obtaining copies can be expensive and burdensome for graduates. But student-owned digital transcripts put the power of secure verification in the hands of learners, eliminating the need for lengthy and costly transcripts to further their professional or educational pursuits. An early mover, Central New Mexico Community College, debuted digital diplomas on the blockchain in December of 2017.
6. Using blockchains to verify multi-step accreditation
As different accreditors recognize different forms of credentials and a growing diversity of educational providers issue credentials, checking the ‘pedigree’ of a qualification can be laborious. Turning a certification verification process from a multi-stage research effort into a single-click process will automate many thousands of labor hours for organizations and institutions
Join us for an online training program that will provide faculty with critical information about FERPA, the federal statute that governs nearly all student records. Beginning with an overview of the FERPA framework, we will address issues that faculty commonly face—often without realizing the implications and risks—including:
Posting grades
Emailing with, and about, students
Writing recommendation letters
Using online tools and collaborative pedagogies
Speaking with (helicopter) parents
Administrators requesting student information
If you are searching for relevant scenarios and practical tips for better understanding how FERPA applies to everyday work of faculty, this online training is right for you.
Bonus Training Material and Quiz
Included in registration is a bonus lesson covering specific nuances of FERPA as it relates to faculty and an accompanying quiz which will provide a chance for you and your team to test your knowledge immediately before or after the webcast. This 20-minute training will cover:
Taking attendance, posting grades, and other course communication
The Do’s and Don’ts of identifying students online, in person, and on paper
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.