Education Trends Are Technology Trends

lines

I title this article "Education Trends Are Technology Trends" but I'm not sure I really agree with that statement. It does seem that way though if you look at the many articles about education trends and developments that appear at he end and beginning of years.

Reading one article by Bernard Bull about things to watch in this new year, he lists ten curricular trends to watch. But what I first noticed was how many involve technology.

Some from his list are obviously rooted in digital technologies:
AR and VR Education Software Tied to Curricular Standards
Citizenship and Digital Citizenship Curricula
Cartoon-ish and Simplistic Game-Based Learning Tied to State Testing
Increasingly Sophisticated Game-Based Curricula Across Disciplines
Reductionist Data Analysis Driving Curricular Decisions
Curricula Focused upon Non-Cognitive Skill Development
Self-Directed Learning Management Tools

I have been reading for years about how gamification and then it combined with applications of AR and VR would change education, but I still don't see it happening to any great extent. I wouldn't ignore it, but I don't believe 2018 will be dramatically different than 2017 in these areas.

But some items on his list that seem less tech-based, such as "Integration of Curricular and Co-Curricular Learning," still use tech. In writing about community-based programs, after-school programs, informal learning, self-directed projects, personal reading and experimentation, personal learning networks, and in-school and out-of-school extracurricular activities/hobbies/sports, Bull brings in things like digital badges. And the competency-based education movement, workforce development, corporate training, and continuing education are all areas that rely a great deal on digital applications.

Obviously, big data and learning analytics have made inroads into education, more at the administrative level I would say than in with individual teachers. This will expand this year. I agree with Bull that unfortunately we will pull more and more data, but still have "data-illiterate people trying to make sense of new data sources, dashboards, and incremental reports." This in the short-term will not be as useful as it could be.

Perhaps I am just old school, but I am still more interested in things like experiential education curricula and student-centered and self-directed learning projects that may not require any additional technology. What they may require is better partnerships with places that can offer students experiential education.

If you can look beyond test scores and ways to document progress based on state and national standards - and that is not easy for someone in a classroom, especially in K-12 - then self-directed learning can grow. I'm not sure that "Self-Directed Learning Management Tools" will be the reason it succeeds.

You could flip this post's title and ask if technology trends are education trends. If the new things for TV and media consumption is on-demand and streaming, will that move into education? It already has moved in. 

But who is driving the changes - technology or education? I would say it is technology, though it should be education. 

If I had to make one prediction for education in 2018, it would be: More of the Same.

Going Horizontal

vertical horizontalIn microeconomics and management, going vertical or vertical integration occurs when the supply chain of a company is owned by that company. For example, if a car manufacturer also produces its own steel, tires and batteries.

This is in contrast with horizontal integration, wherein a company produces several items which are related to one another.

Higher education has been a vertical enterprise for centuries. We keep knowledge creation, teaching, testing, and credentialing all under one company/college banner.

These are terms from economics and business. Are they applicable to discussions about education?

Horizontal integration often occurs in the business world by internal expansion, acquisition or merger. Of course, that might happen in education too, but there are also signs that it is happening in other ways.

When MOOCs were the big news five years ago, some people saw this as a shift from a vertically integrated model to a horizontally integrated one by decoupling teaching and learning from the campus testing and credentialing.

In looking for further examples of vertical and horizontal integration in education, the examples I found were mostly in medical education. 

"Vertical and horizontal integration of knowledge and skills - a working model" (Snyman WD, Kroon J.) looks at an integrated outcomes-based curriculum for dentistry at the University of Pretoria in 1997.

In "Horizontal and vertical integration of academic disciplines in the medical school curriculum (Vidic B, Weitlauf HM) looks at pedagogical shifts caused by the rapid expansion of new scientific information and the introduction of new technology in operative and diagnostic medicine.

In more general terms, assessment alignment is often the reason for both horizontal and vertical alignment in education. Alignment is typically understood as the agreement between a set of content standards and an assessment used to measure those standards. By establishing content standards, stakeholders in an education system determine what students are expected to know and be able to do at each grade level.

Probably, it is best when education goes both vertically and horizontally. 

Horizontal information exchange can be teachers sharing methodology, students sharing information, students helping each other learn.

When a curriculum is truly vertically aligned or vertically coherent, what students learn in one lesson, course, or grade level prepares them for the next lesson, course, or grade level. I know teaching is supposed to be structured and logically sequenced so that learning progressively prepares them for more challenging, higher-level work. I saw that structured sequencing more in my K-12 teaching than I do in higher education which is more siloed. 

Let's work on going more horizontal, higher ed.

Is Our Group a Learning Community, Learning Circle or Community of Practice?

Though there are differences, you will often find the terms Learning Community, Learning Circle and Community of Practice used interchangeably. They are all groups of individuals who learn from each other, and with each other, on an ongoing basis with the goal of improving their work. 

Like any network of people, communities of practice are generally self-organized by people who share common work practice. As with the other labels, any of these relationship groupings have a desire to share what they know, support one another, and create new knowledge for their field of practice.

But communities of practice (CoP) differ from networks in that they are intended to be "communities" in which people make a commitment to be there for each other. They should participate not just for their own needs, but to serve the needs of others.

A CoP is very "open source" with a commitment to advance the field of practice and to make their resources and knowledge available to anyone, especially those doing related work.

A learning circle is a highly interactive, participatory structure for organizing group work. The goal is to build, share, and express knowledge though a process of open dialogue and deep reflection around issues or problems with a focus on a shared outcome.

Online learning circles take advantage of social networking tools to manage collaborative work over distances following a timeline from the open to close of the circle. Learning circles usually have a final project or goal which collects the shared knowledge generated during the interactions. Learning circles are a way to organize learning in global projects. They are also being used in Massive Open Online Courses (MOOCs).

But again, there is crossover with these terms. I have even seen articles about "Creating a Community of Practice Using Learning Circles

Almost anyone can facilitate a learning circle, whether it is a single learning circle in your home or multiple circles across a an organization like a university or library system. 

Bleeding Edgy Deep Learning

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.

The Highest Paid Majors Demythified

gradsA newsletter from Jeff Selingo pointed to an upcoming piece forThe New York Times that he wrote about the biggest myths surrounding the college major.

How did you pick your major? You probably got guidance from school counselors but also less formally from family and friends,  and from news articles and headlines in the media that talked about the "fastest-growing fields" and who gets paid what.

Selingo cites a report that says all that advice on what to study in college perpetuates myths. This Gallup report details that the majority (55%) of U.S. adults with at least some college but no more than a bachelor's degree list their informal social network as providing advice about their college major. This is the most often-cited source of advice when choosing a major for the majority of U.S. adults.

The past few decades have seen a push to STEM fields. That push last occurred in the 1950s in the U.S. when we were in a space race and seemed to be falling behind other countries. In the 1950s, we were lagging behind Russia and Japan, but today most of the talk is about China and India. 
 
Yes, STEM fields do generally pay well and are we still have fewer students prepared to work in those fields. But the newsletter points to an interactive graphic from Doug Webber at Temple University that shows there is a lot of overlaps plenty of overlap between earnings in different fields. There also is a big difference in being an average or below-average engineering employee and at the top of earners with an English major.  
 
The most popular undergraduate major now is not in STEM but in business. The lifetime earnings of the typical business graduate is $2.85 million, but an English major is $2.76 million, and psychology is $2.57 million and even a history major totals up at $2.46 million.
 
Perhaps the lesson for high school students is that you shouldn't pick a major based on projected earnings.