The top learning trend in K-12 learning in 2018 was active learning spaces–from double classrooms in old buildings from California’s Central Valley to the west tip of Texas in El Paso and multiage pods in new spaces from Redwood City to Charlottesville.
The flexible spaces facilitate project-based learning and competency-based progressions. Students move from project teams to skill groups to activity centers building skills and developing agency and self-management.
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Competency: The Trend to Watch in 2019 A year from now people will be talking about competency frameworks–how learners progress as they demonstrate mastery.
The shift from marking time to measuring learning will be generational in length, but our landscape analysis suggests several interesting signs of progress that will be evident in 2019:
In the most interesting merger of the year, LRNG, the leading youth badging platform, joined forces with SNHU, the leading online university. Look for badges capturing in and out of school learning that stack into college credit.
More schools, like Purdue Polytech, will embrace project-based learning and competency-based progressions with support from XQ, NGLC funds, and NewSchools Venture Fund.
More platform partnerships where districts/networks are working in development cycles with platform providers (e.g. Brooklyn LAB and Cortex, Purdue Polytech and Course Networking, Lindsay USD and Empower).
More artificial intelligence is showing up in learning platforms improving personalization, formative feedback, and student scheduling.
More demand for interoperability will be evident as a result of efforts like Project Unicorn.
It’s going to be a good new year. Find a couch or pull up a bar stool–your choice. Work on a badge or microcredential, it’s likely to be more widely recognized next year.
Brickstuff is the perfect way to light up Lego builds. This starter kit includes everything you need to get started. No electronics or soldering knowledge is necessary to set up these lights and start using them right away. Each flexible 2-LED Light Strip has a self-adhesive backing, which allows easy mounting to almost any surface. The strips are flexible, allowing you to mount them even on curved surfaces. This kit also includes a battery pack, so you can be up and running right away. This kit is ready to use with any microcontroller or robotics project too.
A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.
The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.
For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.
LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.
LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.
And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.
LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms.
Is there demand for staying relevant? For learning new skills? For reinventing oneself?
From DSC: So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out.
Microsoft/LinkedIn/Lynda.com are nicely positioned to be a major player who can offer society a next generation learning platform at an incredible price — offering up-to-date, microlearning along with new forms of credentialing. It’s what I’ve been calling the Amazon.com of higher ed(previously the Walmart of Education) for ~10 years. It will take place in a strategy/platform similar to this one.
Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney Johnson Excerpt (emphasis DSC):
Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people.And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.
Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.
It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in arecommendations system that now runs on a totally new machine-learning infrastructure.Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.
“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”
Maybe the force.
From DSC: When will we begin to see more mainstream recommendation engines for learning-basedmaterials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!
Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
Voice-driven interfaces.
Matching employees to employers.
Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
From cradle to grave. Lifelong learning.
Multimedia-based, interactive content.
Asynchronously and synchronously connecting with others learning about the same content.
We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”
Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.
In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.
OBJECTIVES FOR CONVENINGS
Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.
Develop implications for work, workers, students, working learners, employers, and policymakers.
Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.
Three key questions guided the discussions:
What are the LEAST and MOST essential skills needed for the future?
Where and how will tomorrow’s workers and learners acquire the skills they really need?
Who is accountable for making sure individuals can thrive in this new economy?
This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.
In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.
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In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.
Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.
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Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:
Coding. Systems will be self-programming.
Building AI systems. Graphic interfaces will turn AI programming into drag-and-drop operations.
Calendaring, scheduling, and organizing. There won’t be need for email triage.
Planning and even decision-making. AI assistants will pick this up.
Creating more personalized curricula. Learners may design more of their own personalized learning adventure.
Writing and reviewing resumes. Digital portfolios, personal branding, and performance reputation will replace resumes.
Language translation and localization. This will happen in real time using translator apps.
Legal research and writing. Many of our legal systems will be automated.
Validation skills. Machines will check people’s work to validate their skills.
Driving. Driverless vehicles will replace the need to learn how to drive.
Here’s a list of the most essential skills needed for the future:
Quantitative and algorithmic thinking.
Managing reputation.
Storytelling and interpretive skills.
First principles thinking.
Communicating with machines as machines.
Augmenting high-skilled physical tasks with AI.
Optimization and debugging frame of mind.
Creativity and growth mindset.
Adaptability.
Emotional intelligence.
Truth seeking.
Cybersecurity.
The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.
We just lived through the biggest shift in learning since the printing press—a 25-year shift from print to digital. While it extended access and options to billions, it didn’t prove as transformational as many of us expected. It did, however, set the stage for three shifts that will change what and how people learn.
This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.
Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more.
How many of us have those kinds of skills?Did we get that training in the community colleges, colleges, and universities that we went to?Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace.
This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.
This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies.
* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:
IBM: Vice President, Data, AI & Offering Strategy, HR
Kraft Heinz Senior Vice President Global HR, Performance and IT
SunTrust Senior Vice President Employee Wellbeing & Benefits
What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.
An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy
Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.
Since its inception, Western Governors University (WGU) has aimed to serve learners otherwise shut out of the traditional system. Now, the groundbreaking institution has both graduated 100,000 students and has over 100,000 students currently enrolled. These milestones demonstrate WGU’s ability to scale its high-quality, low-cost model, signaling a momentous shift in the higher education landscape.
In the mid-1990s, governors of 19 states across the western United States were concerned about bringing accessible college education to rural populations, especially working adults.These governors, led by Utah Governor Mike Leavitt, decided to explore building a new university to address the challenge. As the memorandum of understanding between those governors that officially marked the founding of WGU stated, “The strength and well-being of our states and the nation depend increasingly on a strong higher education system that helps individuals adapt to our rapidly changing economy and society. States must look to telecommunications and information technologies to provide greater access and choice to a population that increasingly must have affordable education and training opportunities and the certification of competency throughout their lives.”
Now in its third decade, WGU has students in every U.S. state and has over 100,000 enrolled students—a 230% increase since 2011.
The potential of competency-based education
Competency-based education is an approach to learning that allows students to determine the pace of their learning and move ahead once they demonstrate mastery in a concept. As described by Clayton Christensen and Michelle Weise:
Competency-based programs have no time-based unit. Learning is fixed, and time is variable; pacing is flexible. Students cannot move on until they have demonstrated proficiency and mastery of each competency but are encouraged to try as many times as necessary to demonstrate their proficiency. Although skeptics may question the “rigor” behind an experience that allows students to keep trying until they have mastered a competency, this model is actually far more rigorous than the traditional model, as students are not able to flunk or get away with a merely average understanding of the material; they must demonstrate mastery—and therefore dedicated work toward gaining mastery—in any competency.
Competency-based education first took hold in the K-12 education system, but it is also growing in higher education. As of fall 2015, roughly 600 institutions were using or exploring competency-based programs in higher education.13 However, only a handful of institutions are using competency-based education exclusively and have designed their business models around it.
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WGU offers programs across four industry areas: education, business, information technology, and healthcare. All of these programs are offered online; unlike most higher education institutions, WGU has no physical campus. Instead, it has invested heavily in a technology platform that allows it to deliver curriculum asynchronously, to wherever students are. In addition to its online platform, another unique aspect of WGU’s resources is its approach to faculty. In traditional institutions, faculty are responsible for academic research, course development, teaching, assessment, and advising students. Alternatively, WGU’s model unbundles the faculty role into component parts, with specialists in each role.
A learning ecosystem is a system of people, content, technology, culture, and strategy, existing both within and outside of an organization, all of which has an impact on both the formal and informal learning that goes on in that organization.
The word “ecosystem” is worth paying attention to here. It’s not just there to make the term sound fancy or scientific. A learning ecosystem is the L&D equivalent of an ecosystem out in the wild. Just as a living ecosystem has many interacting species, environments, and the complex relationships among them, a learning ecosystem has many people and pieces of content, in different roles and learning contexts, and complex relationships.
Just like a living ecosystem, a learning ecosystem can be healthy or sick, nurtured or threatened, self-sustaining or endangered. Achieving your development goals, then, requires an organization to be aware of its own ecosystem, including its parts and the internal and external forces that shape them.
From DSC: Yes, to me, the concept/idea of a learning ecosystem IS important. Very important. So much so, I named this blog after it.
Each of us as individuals have a learning ecosystem, whether we officially recognize it or not. So do the organizations that we work for. And, like an ecosystem out in nature, a learning ecosystem is constantly morphing, constantly changing.
We each have people in our lives that help us learn and grow, and the people that were in our learning ecosystems 10 years ago may or may not still be in our current learning ecosystems. Many of us use technologies and tools to help us learn and grow. Then there are the spaces where we learn — both physical and virtual spaces. Then there are the processes and procedures we follow, formally and/or informally. Any content that helps us learn and grow is a part of that ecosystem. Where we get that content can change, but obtaining up-to-date content is a part of our learning ecosystems. I really appreciate streams of content in this regard — and tapping into blogs/websites, especially via RSS feeds and Feedly (an RSS aggregator that took off when Google Reader left the scene).
The article brings up a good point when it states that a learning ecosystem can be “healthy or sick, nurtured or threatened, self-sustaining or endangered.” That’s why I urge folks to be intentional about maintaining and, better yet, consistently enhancing their learning ecosystems. In this day and age where lifelong learning is now a requirement to remain in the workforce, each of us needs to be intentional in this regard.
From DSC: According to the article below, bootcamps appear to be filling several (perceived and/or real) gaps. Quoting from the article:
Why are students enrolling in coding bootcamps? One reason may be the adaptability of these accelerated computer science programs, where students are taught web and mobile development skills that align with industry demands. Programs are offered in-person or online, providing students with flexible learning options. The payoff is decent too: At a typical coding bootcamp, Course Report estimates average tuition is $11,400 for about 14 weeks of instruction, from which the majority students complete on-time and find relevant jobs.
Cost.
Time.
Responsiveness to industry demands.
Greater flexibility.
These are some of the things for traditional institutions of higher education to grapple with, and I would argue the sooner, the better — before this trend finds its legs and gains even more traction/momentum.
For example, in your own mind/thinking…how long do you think it will take bootcamps to begin offering programs that help learners develop content for augmented reality (AR), virtual reality (VR), and mixed reality (MR) — as compared to programs coming out of institutions of traditional higher education?
Whatever your answers are in regards to the reasons for that time difference are likely the exact sort of things institutions need to be working on. For me, at least one of the answers has to do with our current accreditation systems. Other reasons come to my mind as well, but I don’t have time to go there right now.
The five-year coding bootcamp industry estimated at $266 million is rapidly expanding, according to a new market study from Course Report.
The study counted 94 full-time coding bootcamps across the United States and Canada (with programs in 74 U.S. cities). Compared to 2012, there will be 10 times as many graduates this year — or roughly one coding bootcamp graduate for every 3.5 graduates from a traditional university or college. Course Report estimates that 22,814 developers will graduate from coding bootcamps this year — an increase from 15,048 graduates last year.
From DSC: I’ve been thinking about Applicant Tracking Systems (ATSs) for a while now, but the article below made me revisit my reflections on them. (By the way, my thoughts below are not meant to be a slam on Google. I like Google and I use their tools daily.) I’ve included a few items below, but there were some other articles/vendors’ products that I had seen on this topic that focused specifically on ATSs, but I couldn’t locate them all.
In mid-June, Google announced the implementation of an AI-powered search function aimed at connecting job seekers with jobs by sorting through posted recruitment information. The system allows users to search for basic phrases, such as “jobs near me,” or perform searches for industry-specific keywords. The search results can include reviews from Glassdoor or other companies, along with the details of what skills the hiring company is looking to acquire.
As this is a relatively new development, what the system will mean is still an open question. To help, members from the Forbes Coaches Council offer their analysis on how the search system will impact candidates or companies. Here’s what they said…
5. Expect competition to increase. Google jumping into the job search market may make it easier than ever to apply for a role online. For companies, this could likely tax the already strained-ATS system, and unless fixed, could mean many more resumes falling into that “black hole.” For candidates, competition might be steeper than ever, which means networking will be even more important to job search success. – Virginia Franco
10. Understanding keywords and trending topics will be essential. Since Google’s AI is based on crowd-gathered metrics, the importance of keywords and understanding trending topics is essential for both employers and candidates. Standing out from the crowd or getting relevant results will be determined by how well you speak the expected language of the AI. Optimizing for the search engine’s results pages will make or break your search for a job or candidate. – Maurice Evans, IGROWyourBiz, Inc
Before then, 21-year-old Ms. Jaffer had filled out a job application, played a set of online games and submitted videos of herself responding to questions about how she’d tackle challenges of the job. The reason she found herself in front of a hiring manager? A series of algorithms recommended her.
The debate is on, whether man or machine will win the race, as they are pitted against each other in every walk of life. Experts are already worried about the social disruption that is inevitable, as artificial intelligence (AI)-led robots take over the jobs of human beings, leaving them without livelihoods.The same is believed to happen to the HR profession, says a report by Career Builder. HR jobs are at threat, like all other jobs out there, as we can expect certain roles in talent acquisition, talent management, and mainstream business being automated over the next 10 years. To delve deeper into the imminent problem, Career Builder carried out a study of 719 HR professionals in the private sector, specifically looking for the rate of adoption of emerging technologies in HR and what HR professionals perceived about it.
The change is happening for real, though different companies are adopting technologies at varied paces. Most companies are turning to the new-age technologies to help carry out talent acquisition and management tasks that are time-consuming and labor-intensive.
From DSC: Are you aware that if you apply for a job at many organizations nowadays, your resume has a significant chance of not ever making it in front of a human’s eyeballs for their review? Were you aware that an Applicant Tracking System (an ATS) will likely syphon off and filter out your resume unless you have the exact right keywords in your resume and unless you mentioned those keywords the optimal number of times?
And were you aware that many advisors assert that you should use a 1 page resume — a 2 page resume at most? Well…assuming that you have to edit big time to get to a 1-2 page resume, how does that editing help you get past the ATSs out there? When you significantly reduce your resume’s size/information, you hack out numerous words that the ATS may be scanning for. (BTW, advisors recommend creating a Wordle from the job description to ascertain the likely keywords; but still, you don’t know which exact keywords the ATS will be looking for in your specific case/job application and how many times to use those keywords. Numerous words can be of similar size in the resulting Wordle graphic…so is that 1-2 page resume helping you or hurting you when you can only submit 1 resume for a position/organization?)
Vendors are hailing these ATS systems as being major productivity boosters for their HR departments…and that might be true in some cases. But my question is, at what cost?
At this point in time, I still believe that humans are better than software/algorithms at making judgement calls. Perhaps I’m giving hiring managers too much credit, but I’d rather have a human being make the call at this point. I want a pair of human eyeballs to scan my resume, not a (potentially) narrowly defined algorithm. A human being might see transferable skills better than a piece of code at this point.
Just so you know…in light of these keyword-based means of passing through the first layer of filtering, people are now playing games with their resumes and are often stretching the truth — if not outright lying:
A new study shows huge increase in lies on job applications.
Excerpt (emphasis DSC):
Employer Applicant Tracking Systems Expect an Exact Match Most companies use some form of applicant tracking system (ATS) to take in résumés, sort through them, and narrow down the applicant pool. With the average job posting getting more than 100 applicants, recruiters don’t want to go bleary-eyed sorting through them. Instead, they let the ATS do the dirty work by telling it to pass along only the résumés that match their specific requirementsfor things like college degrees, years of experience, and salary expectations. The result? Job seekers have gotten wise to the finicky nature of the technology and are lying on their résumés and applications in hopes of making the cut.
From DSC:
I don’t see this as being very helpful. But perhaps that’s because I don’t like playing games with people and/or with other organizations. I’m not a game player. What you see is what you get. I’ll be honest and transparent about what I can — and can’t — deliver.
But students, you should know that these ATS systems are in place. Those of us in higher education should know about these ATS systems, as many of us are being negatively impacted by the current landscape within higher education.
Is Your Resume ATS Friendly?
Did you know that an ATS (applicant tracking system) will play a major role in whether or not your resume is selected for further review when you’re applying to opportunities through online job boards?
It’s true. When you apply to a position a company has posted online, a human usually isn’t the first to review your resume, a computer program is. Scouring your resume for keywords, terminology and phrases the hiring manager is targeting, the program will toss your resume if it can’t understand the content it’s reading. Basically, your resume doesn’t stand a chance of making it to the next level if it isn’t optimized for ATS.
To ensure your resume makes it past the evil eye of ATS, format your resume correctly for applicant tracking programs, target it to the opportunity and check for spelling errors. If you don’t, you’re wasting your time applying online.
Moheeb is part of a new program that is challenging the way teachers and students think about academic accomplishments, and his school is one of hundreds that have done away with traditional letter grades inside their classrooms. At M.S. 442, students are encouraged to focus instead on mastering a set of grade-level skills, like writing a scientific hypothesis or identifying themes in a story, moving to the next set of skills when they have demonstrated that they are ready. In these schools, there is no such thing as a C or a D for a lazily written term paper. There is no failing. The only goal is to learn the material, sooner or later.
For struggling students, there is ample time to practice until they get it. For those who grasp concepts quickly, there is the opportunity to swiftly move ahead. The strategy looks different from classroom to classroom, as does the material that students must master. But in general, students work at their own pace through worksheets, online lessons and in small group discussions with teachers. They get frequent updates on skills they have learned and those they need to acquire.
Mastery-based learning, also known as proficiency-based or competency-based learning, is taking hold across the country. Vermont and Maine have passed laws requiring school districts to phase in the system. New Hampshire is adopting it, too, and piloting a statewide method of assessment that would replace most standardized tests. Ten school districts in Illinois, including Chicago’s, are testing the approach. In 2015, the Idaho State Legislature approved 19 incubator programs to explore the practice.
More than 40 schools in New York City — home to the largest school district in the country, with 1.1 million students — have adopted the program. But what makes that unusual is that schools using the method are doing so voluntarily, as part of a grass-roots movement.
Grush: Then what are some of the implications you could draw from metrics like that one?
Christian: As we consider all the investment in those emerging technologies, the question many are beginning to ask is, “How will these technologies impact jobs and the makeup of our workforce in the future?”
While there are many thoughts and questions regarding the cumulative impact these technologies will have on our future workforce (e.g., “How many jobs will be displaced?”), the consensus seems to be that there will be massive change.
Whether our jobs are completely displaced or if we will be working alongside robots, chatbots, workbots, or some other forms of AI-backed personal assistants, all of us will need to become lifelong learners — to be constantly reinventing ourselves.This assertion is also made in the aforementioned study from McKinsey: “AI promises benefits, but also poses urgent challenges that cut across firms, developers, government, and workers. The workforce needs to be re-skilledto exploit AI rather than compete with it…”
A side note from DSC: I began working on this vision prior to 2010…but I didn’t officially document it until 2012.
Learning from the Living [Class] Room:
A global, powerful, next generation learning platform
What does the vision entail?
A new, global, collaborative learning platform that offers more choice, more control to learners of all ages – 24×7 – and could become the organization that futurist Thomas Frey discusses here with Business Insider:
“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider.
A learner-centered platform that is enabled by – and reliant upon – human beings but is backed up by a powerful suite of technologies that work together in order to help people reinvent themselves quickly, conveniently, and extremely cost-effectively
A customizable learning environment that will offer up-to-date streams of regularly curated content (i.e., microlearning) as well as engaging learning experiences
Along these lines, a lifelong learner can opt to receive an RSS feed on a particular topic until they master that concept; periodic quizzes (i.e., spaced repetition) determines that mastery. Once mastered, the system will ask the learner whether they still want to receive that particular stream of content or not.
A Netflix-like interface to peruse and select plugins to extend the functionality of the core product
An AI-backed system of analyzing employment trends and opportunities will highlight those courses and streams of content that will help someone obtain the most in-demand skills
A system that tracks learning and, via Blockchain-based technologies, feeds all completed learning modules/courses into learners’ web-based learner profiles
A learning platform that provides customized, personalized recommendation lists – based upon the learner’s goals
A platform that delivers customized, personalized learning within a self-directed course (meant for those content creators who want to deliver more sophisticated courses/modules while moving people through the relevant Zones of Proximal Development)
Notifications and/or inspirational quotes will be available upon request to help provide motivation, encouragement, and accountability – helping learners establish habits of continual, lifelong-based learning
(Potentially) An online-based marketplace, matching learners with teachers, professors, and other such Subject Matter Experts (SMEs)
(Potentially) Direct access to popular job search sites
(Potentially) Direct access to resources that describe what other companies do/provide and descriptions of any particular company’s culture (as described by current and former employees and freelancers)
(Potentially) Integration with one-on-one tutoring services
Addendum from DSC (regarding the resource mentioned below): Note the voice recognition/control mechanisms on Westinghouse’s new product — also note the integration of Amazon’s Alexa into a “TV.”
The key selling point, of course, is the built-in Amazon Fire TV, which is controlled with the bundled Voice Remote and features Amazon’s Alexa assistant.
Holographic storytelling— from jwtintelligence.com The stories of Holocaust survivors are brought to life with the help of interactive 3D technologies. New Dimensions in Testimony is a new way of preserving history for future generations. The project brings to life the stories of Holocaust survivors with 3D video, revealing raw first-hand accounts that are more interactive than learning through a history book. Holocaust survivor Pinchas Gutter, the first subject of the project, was filmed answering over 1000 questions, generating approximately 25 hours of footage. By incorporating natural language processing from the USCInstitute for Creative Technologies (ICT), people are able to ask Gutter’s projected image questions that trigger relevant responses.
Learning from the Living [Class] Room: A vision for a global, powerful, next generation learning platform
By Daniel Christian
NOTE: Having recently lost my Senior Instructional Designer position due to a staff reduction program, I am looking to help build such a platform as this. So if you are working on such a platform or know of someone who is, please let me know: danielchristian55@gmail.com.
I want to help people reinvent themselves quickly, efficiently, and cost-effectively — while providing more choice, more control to lifelong learners. This will become critically important as artificial intelligence, robotics, algorithms, and automation continue to impact the workplace.
Learning from the Living [Class] Room:
A global, powerful, next generation learning platform
What does the vision entail?
A new, global, collaborative learning platform that offers more choice, more control to learners of all ages – 24×7 – and could become the organization that futurist Thomas Frey discusses here with Business Insider:
“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider.
A learner-centered platform that is enabled by – and reliant upon – human beings but is backed up by a powerful suite of technologies that work together in order to help people reinvent themselves quickly, conveniently, and extremely cost-effectively
An AI-backed system of analyzing employment trends and opportunities will highlight those courses and “streams of content” that will help someone obtain the most in-demand skills
A system that tracks learning and, via Blockchain-based technologies, feeds all completed learning modules/courses into learners’ web-based learner profiles
A learning platform that provides customized, personalized recommendation lists – based upon the learner’s goals
A platform that delivers customized, personalized learning within a self-directed course (meant for those content creators who want to deliver more sophisticated courses/modules while moving people through the relevant Zones of Proximal Development)
Notifications and/or inspirational quotes will be available upon request to help provide motivation, encouragement, and accountability – helping learners establish habits of continual, lifelong-based learning
(Potentially) An online-based marketplace, matching learners with teachers, professors, and other such Subject Matter Experts (SMEs)
(Potentially) Direct access to popular job search sites
(Potentially) Direct access to resources that describe what other companies do/provide and descriptions of any particular company’s culture (as described by current and former employees and freelancers)
Further details:
While basic courses will be accessible via mobile devices, the optimal learning experience will leverage two or more displays/devices. So while smaller smartphones, laptops, and/or desktop workstations will be used to communicate synchronously or asynchronously with other learners, the larger displays will deliver an excellent learning environment for times when there is:
A Subject Matter Expert (SME) giving a talk or making a presentation on any given topic
A need to display multiple things going on at once, such as:
The SME(s)
An application or multiple applications that the SME(s) are using
Content/resources that learners are submitting in real-time (think Bluescape, T1V, Prysm, other)
The ability to annotate on top of the application(s) and point to things w/in the app(s)
Media being used to support the presentation such as pictures, graphics, graphs, videos, simulations, animations, audio, links to other resources, GPS coordinates for an app such as Google Earth, other
Other attendees (think Google Hangouts, Skype, Polycom, or other videoconferencing tools)
An (optional) representation of the Personal Assistant (such as today’s Alexa, Siri, M, Google Assistant, etc.) that’s being employed via the use of Artificial Intelligence (AI)
This new learning platform will also feature:
Voice-based commands to drive the system (via Natural Language Processing (NLP))
Language translation (using techs similar to what’s being used in Translate One2One, an earpiece powered by IBM Watson)
Speech-to-text capabilities for use w/ chatbots, messaging, inserting discussion board postings
Text-to-speech capabilities as an assistive technology and also for everyone to be able to be mobile while listening to what’s been typed
Chatbots
For learning how to use the system
For asking questions of – and addressing any issues with – the organization owning the system (credentials, payments, obtaining technical support, etc.)
For asking questions within a course
As many profiles as needed per household
(Optional) Machine-to-machine-based communications to automatically launch the correct profile when the system is initiated (from one’s smartphone, laptop, workstation, and/or tablet to a receiver for the system)
(Optional) Voice recognition to efficiently launch the desired profile
(Optional) Facial recognition to efficiently launch the desired profile
(Optional) Upon system launch, to immediately return to where the learner previously left off
The capability of the webcam to recognize objects and bring up relevant resources for that object
A built in RSS feed aggregator – or a similar technology – to enable learners to tap into the relevant “streams of content” that are constantly flowing by them
Social media dashboards/portals – providing quick access to multiple sources of content and whereby learners can contribute their own “streams of content”
In the future, new forms of Human Computer Interaction (HCI) such as Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) will be integrated into this new learning environment – providing entirely new means of collaborating with one another.
Likely players:
Amazon – personal assistance via Alexa
Apple – personal assistance via Siri
Google – personal assistance via Google Assistant; language translation
Facebook — personal assistance via M
Microsoft – personal assistance via Cortana; language translation
IBM Watson – cognitive computing; language translation
The 2017 Dean’s List: EdTech’s 50 Must-Read Higher Ed Blogs — from edtechmagazine.com by Meghan Bogardus Cortez These administrative all-stars, IT gurus, teachers and community experts understand how the latest technology is changing the nature of education.
Excerpt:
With summer break almost here, we’ve got an idea for how you can use some of your spare time. Take a look at the Dean’s List, our compilation of the must-read blogs that seek to make sense of higher education in today’s digital world.
Follow these education trailblazers for not-to-be-missed analyses of the trends, challenges and opportunities that technology can provide.
If you’d like to check out the Must-Read IT blogs from previous years, view our lists from 2016, 2015, 2014 and 2013.
From DSC: I would like to thank Tara Buck, Meghan Bogardus Cortez, D. Frank Smith, Meg Conlan, and Jimmy Daly and the rest of the staff at EdTech Magazine for their support of this Learning Ecosystems blog through the years — I really appreciate it.
Thanks all for your encouragement through the years!
The Future of Jobs and Jobs Training — from by Lee Rainie and Janna Anderson As robots, automation and artificial intelligence perform more tasks and there is massive disruption of jobs, experts say a wider array of education and skills-building programs will be created to meet new demands. There are two uncertainties: Will well-prepared workers be able to keep up in the race with AI tools? And will market capitalism survive?
Several policy and market-based solutions have been promoted to address the loss of employment and wages forecast by technologists and economists. A key idea emerging from many conversations, including one of the lynchpin discussions at the World Economic Forum in 2016, is that changes in educational and learning environments are necessary to help people stay employable in the labor force of the future. Among the six overall findings in a new 184-page report from the National Academies of Sciences, the experts recommended: “The education system will need to adapt to prepare individuals for the changing labor market. At the same time, recent IT advances offer new and potentially more widely accessible ways to access education.”
In the next 10 years, do you think we will see the emergence of new educational and training programs that can successfully train large numbers of workers in the skills they will need to perform the jobs of the future?
From DSC: The following questions (from the article) might be fodder for initial conversations regarding what changes need to immediately occur within higher education. Those changes might be to establish teams/task forces/etc. charged with answering these kinds of questions.
What are the most important skills needed to succeed in the workforce of the future?
Which of these skills can be taught effectively via online systems – especially those that are self-directed – and other nontraditional settings?
Which skills will be most difficult to teach at scale?
Will employers be accepting of applicants who rely on new types of credentialing systems, or will they be viewed as less qualified than those who have attended traditional four-year and graduate programs?
The following section further supports a vision that I’ve been tracking entitled, “Learning from the Living [Class] Room” — where I see the “New Amazon.com of Higher Education” unfolding. Blockchain-based technologies will likely be involved here.
A diversifying education and credentialing ecosystem: Most of these experts expect the education marketplace – especially online learning platforms – to continue to change in an effort to accommodate the widespread needs. Some predict employers will step up their own efforts to train and retrain workers. Many foresee a significant number of self-teaching efforts by jobholders themselves as they take advantage of proliferating online opportunities.
Respondents see a new education and training ecosystem emerging in which some job preparation functions are performed by formal educational institutions in fairly traditional classroom settings, some elements are offered online, some are created by for-profit firms, some are free, some exploit augmented and virtual reality elements and gaming sensibilities, and a lot of real-time learning takes place in formats that job seekers pursue on their own.
A considerable number of respondents to this canvassing focused on the likelihood that the best education programs will teach people how to be lifelong learners. Accordingly, some say alternative credentialing mechanisms will arise to assess and vouch for the skills people acquire along the way.
DC: Many societies around the globe are looking at massive change coming at them. What changes should those of us working in higher education begin to make — immediately? In the longer term?
These respondents suggest that workers of the future will learn to deeply cultivate and exploit creativity, collaborative activity, abstract and systems thinking, complex communication, and the ability to thrive in diverse environments.
Addendum on 5/6/17:
How to Prepare for an Automated Future — from nytimes.com by Claire Cain Miller Excerpt:
We don’t know how quickly machines will displace people’s jobs, or how many they’ll take, but we know it’s happening — not just to factory workers but also to money managers, dermatologists and retail workers. The logical response seems to be to educate people differently, so they’re prepared to work alongside the robots or do the jobs that machines can’t. But how to do that, and whether training can outpace automation, are open questions.
![The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV](http://danielschristian.com/learning-ecosystems/wp-content/uploads/2012/07/The-Living-Class-Room-Daniel-S-Christian-July-2012.jpg)
