Serendipity35

There are so many posts I have the past few weeks about trend for education and technology, but one way of seeing what trends may emerge this year is by looking at the tracks, presentations and keynote speakers at EdTech conferences. 

I'll be moderating a track next week at NJEdge.Net's Annual Conference: NJEdgeCon2018 "DIGITAL LEADERSHIP & ENTERPRISE TRANSFORMATION" January 11 & 12, 2018 in New Jersey.  My track is, naturally, Education and Technology which has presentations on best practices, innovations and the effectiveness associated with current LMS and online learning tools, effective infrastructure, resources, sustainability models and integrated assessment tools.

But if you look at the other tracks offered, you can see that INFORMATION Technology outweighs instructional technology here. Other tracks at the conference are Big Data & Analytics, Networking & Data Security, Customer Support & Service Excellence,  Aligning Business & Technology Strategies. and Transformation Products & Services.

Amber Mac (as in MacArthur) will talk about adaptation and the accelerating pace of corporate culture in the digital economy.

I have followed her career for a decade from her early tech TV and podcast venture to her current consulting business. She helps companies adapt to, anticipate, and capitalize on lightning-quick changes—from leadership to social media to the Internet of Things, from marketing to customer service to digital parenting and beyond. It’s not about innovation, she says; it’s about adaptation.

When it comes to teachers and technologies, the battle cry of Virginia Tech professor John Boyer is embrace, not replace. In his talk, he presents his view that the best teachers will embrace technologies that help them better communicate with students, but do not fear because those technologies will never replace human to human interaction. But blending the best communicators with the best technology has to offer will produce some amazing and unpredictable opportunities!

Wayne Brown, CEO and Founder of Center for Higher Ed CIO Studies (CHECS), will talk in his session on longitudinal higher education CIO research and the importance of technology leaders aligning technology innovations and initiatives with the needs of the higher education institution. His two-part survey methodology enables him to compare and contrast multiple perspectives about higher education technology leaders. The results provide essential information regarding the experiences and background an individual should possess to serve as a higher education CIO. In collaboration with NJEdge, Wayne will collect data from NJEdge higher education CIOs and will compare the national results with those of the NJ CIOs.

Timothy Renick (a man of many titles: Vice President for Enrollment Management and Student Success, Vice Provost, and Professor of Religious Studies at Georgia State University) is talking about "Using Data and Analytics to Eliminate Achievement Gaps."  The student-centered and analytics-informed programs at GSU has raised graduation rates by 22% and closed all achievement gaps based on race, ethnicity, and income-level. It now awards more bachelor’s degrees to African Americans than any other college or university in the nation. Through a discussion of innovations ranging from chatbots and predictive analytics to meta-majors and completion grants, the session covers lessons learned from Georgia State’s transformation and outlines several practical and low-cost steps that campuses can take to improve outcomes for underserved students.

Greg Davies' topic is "The Power of Mobile Communications Strategies and Predictive Analytics for Student Success and Workforce Development." The technology that has been used to transform, to both good and bad ends, most other major industries can connect the valuable resources available on campus to the students who need them most with minimal human resources. Technology has been used to personalize the digital experience in such industries as banking, retail, information and media, and others by reaching consumers via mobile technology. Higher Education has, in some cases, been slow to adapt innovative and transformative technology. Yet, its power to transform the student engagement and success experience has been proven. With the help of thought leaders in industry and education, Greg discusses how the industry can help achieve the goal of ubiquity in the use of innovative student success technologies and predictive data analytics to enable unprecedented levels of student success and, as a consequence, workforce development.

The headline came up this week in my feed, "5 Education themes that impacted the industry in 2017." The caveat, perhaps, is that this story ran in the India Times, which made me curious how different those trends might be from the U.S.

They mention that trying to show ROI from earlier trends (flipped classrooms, multilingual learning, faculty professional development, gamification, personalized and adaptive learning, online secure infrastructure, knowledge networks and virtual simulated practice environments etc.) and being pushed to stay ahead of the technology curve might make adoption of newer trends more difficult. Education apps for content, distribution, and collaboration are also in the mix.

In India, the e-learning market hit almost 11 billion in USD in 2016. Here are the 5 trends seen there this year in brief (in this article's perspective).

Personalized learning - bundling content in a specific learning environment that meets the individual student's needs. Content is generally delivered through online and micro learning.

The Cloud - has become cheaper, faster and green.

Safeguarding Personal Identifiable Information (PII) - Our digital footprints - both intentional and unintentional ones - leave learners open to even more vulnerabilities than the average citizen, but losing data and reputation besides the financial damage and emotional distress and overall risk. 4

Gamification, Simulations and Digital Badging - this has been a "trend" for so many years without ever being fully realized that I wonder if it belongs on trend lists any more. Yes, phone apps use gamification as a technique to keep you hooked through notifications, points, and rewards, so that learners are already used to using to them - and probably expect them in many instances. I still don't see a widely accepted of awarding achievement or recognition. 

Leveraging Learning Analytics - AI plays a role in making it possible for a machine to learn over millions of interaction inputs and predict student errors, trends and projections.

The Federal Communications Commission (FCC) recently voted to repeal the net neutrality framework put in place by the Obama administration. This opens the path for restructuring internet traffic. There are many in education that this will have negative implications on both K-12 and higher education. The five-member, Republican-majority board voted along party lines (3-2) to pass the “Restoring Internet Freedom Order.” Efforts by activists, educators, consumers and U.S. lawmakers to stop or reschedule the vote until the commission had heard more public concerns on the matter were ignored.

At edscoop.com, they write that Net neutrality changes are expected to have big implications for education.

Excerpt: 

There’s a major concern that commercial, revenue-generating internet traffic will take precedence. The quality and consistency of access to research, libraries, educational institutions and learning materials could be degraded as those resources are moved to the slow lane to make room for commercial and entertainment traffic that can pay for speed.

 After Dec. 14, higher education will face a new online world — one in which the almighty dollar, not equity, will reign,” wrote Joseph South, the chief learning officer at the International Society for Technology in Education (ISTE), and Eden Dahlstrom, the executive director of the New Media Consortium, in a commentary featured in The Chronicle of Higher Education earlier this month."

 

Deep learning is a hot topic right now, but it is not lightweight or something I would imagine learners who are not in the computer science world to take very seriously. But I stumbled upon this video introduction that certainly goes for an edgier presentation of this serious subject and obviously is trying to appeal to a non-traditional audience.

That audience would be part of what I refer to as both Education 2.0 and also that segment of learners who are The Disconnected.  I see these disconnected learners as a wider age group than "Millennials." They are the potential students in our undergraduate and graduate programs, but also older people already in the workplace looking to move or advance their careers. The younger ones have never been connected to traditional forms of media consumption and services and have no plan to ever be connected to them. And that is also how they feel about education. You learn where and when you can learn with little concern for credits and degrees.

The video I found (below) is an "Intro to Deep Learning" billed as being "for anyone who wants to become a deep learning engineer." It is supposed to take you from "the very basics of deep learning to the bleeding edge over the course of 4 months." That is quite a trip. 

The sample video is on how to predict an animal’s body weight given it’s brain weight using linear regression via 10 lines of Python.

Though the YouTube content (created by and starring Siraj Raval) is totally free, he also has a partnership with Udacity in order to offer a new Deep Learning Nanodegree Foundation program. Udacity will also be providing guaranteed admission to their Artificial Intelligence and Self-Driving Car Nanodegree programs to all graduates. 

Is this a good marketing effort bu Udacity? Will it reach new and disconnected learners? Will they simply use the videos and resources to learn or make that connection to some kind of degree/certification that might tell an employer that they know something about deep learning? I don't have the deep learning program that can predict that. I'm not sure it exists. Yet.

RESOURCES

This is the code via GitHub for "How to Make a Prediction - Intro to Deep Learning #1' by Siraj Raval on YouTube

This lesson uses simple linear regression. "Simple" is a relative term here, as many people would not find it simple, as in "easy." It is a statistical method that allows us to summarize and study relationships between two continuous (quantitative) variables. This lesson via Penn State introduces the concept and basic procedures of simple linear regression.

You might also want to look at this tutorial on the topic via machinelearningmastery.com.