2017 December

LinkedIn’s 2017 U.S. Emerging Jobs Report

LinkedIn’s 2017 U.S. Emerging Jobs Report — from economicgraph.linkedin.com

Excerpt:

Here’s what we found:

Tech is king: Jobs with the top growth potential are tech-focused, with demand coming from tech and non-tech companies alike. Machine learning engineer, data scientist, and big data engineers rank among the top emerging jobs — with companies in a wide range of industries seeking those skills.
Soft skills matter: Not all of the emerging tech jobs require technical skills. Sales development representative, customer success manager, and brand partner rank among the top emerging jobs at companies where a technical background is not a necessity. Traditional soft skills like communication and management underpin all of these emerging jobs.
Jobs with high mobility on the rise: Several top emerging jobs reflect broader societal trends, such as wellness, flexibility and location mobility. More people are getting healthy which could explain why barre instructor featured among our emerging jobs. Not quite as surprising, licensed realtors ranked highly as the post-Great Recession recovery of the real estate market rolls forward. Just in the past year, the number of licensed realtors has surged 40 percent. These type of roles tend to be more widely distributed across U.S. regions.
Low supply of talent for top jobs: Data scientist roles have grown over 650 percent since 2012, but currently 35,000 people in the US have data science skills, while hundreds of companies are hiring for those roles – even those you may not expect in sectors like retail and finance – supply of candidates for these roles cannot keep up with demand.
Future-proofing skills is critical: Some of these emerging skills didn’t even exist five years ago, and many professionals are not confident their current skill set will be relevant within the next 1-2 years.

top 20 fastest growing jobs in the united states

Software engineers are feeding into nearly all of these emerging jobs.

Even further, it’s estimated that 65% of children entering primary school today will ultimately hold jobs that don’t yet exist.

Future-proofing skills is critical: Some of these emerging skills didn’t even exist five years ago, and many professionals are not confident their current skill set will be relevant within the next 1-2 years.

Also see:

The Fastest-Growing Jobs in the U.S. Based on LinkedIn Data — from blog.linkedin.com by Rachel Bowley

Amazon Intros Alexa for Business + 3 other items on AI

On 12/07/2017, in 21st century, A/V -- audio/visual, Amazon, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, business, corporate / business world, IT in HE, Microsoft, vendors, web-based collaboration, workplace, by Daniel Christian

Amazon Intros Alexa for Business — from campustechnology.com by Rhea Kelly

Excerpt:

Amazon Web Services today announced Alexa for Business, a new service that provides voice control for office tasks. The Alexa intelligent assistant can help start conference calls, control conference room equipment, schedule meetings, keep track of tasks, notify IT of an equipment issue or reorder supplies, the company noted in a news announcement. The service can also be customized to voice-enable an organization’s specific IT applications and office systems.

Also see:

Shared devices

EDUCAUSE 2017: Microsoft VP Praises the Power of Artificial Intelligence — from edtechmagazine.com
Artificial intelligence and connected systems advancements are creating a foundation where higher education can use insights and data to drive more efficient campus management, Microsoft’s Anthony Salcito explains.

Analysts and AI: A winning combination — from information-age.com
Artificial intelligence is crucial in helping analysts achieve more in day-to-day operations, and drive innovation

Excerpt:

A Capgemini and LinkedIn study of 1,000 companies with revenue of $500 million+ reported that 2 in 3 jobs being created as a result of AI were at management level, and of those that have implemented the technology at scale, 89% believe complex jobs will be made easier, and 88% say humans and machines will co-exist within their business.

A schematic view of #AI & #MachineLearning overlapping with #BigData & #DataAnalytics in #FinServ. @FinStbBoard #DataScience https://t.co/iXT5QDQdwP pic.twitter.com/hP5clqYz8g

— Mike Quindazzi ? (@MikeQuindazzi) December 7, 2017

A new report from The Open University: Innovating Pedagogy 2017

On 12/07/2017, in adjunct faculty, analytics, data related items, education, faculty, higher education, ideas, innovation, K-12 related, learning, learning ecosystem, open courseware and systems, pedagogy, professional development, psychology, relationships, student-related, teachers, teaching & learning, UK, by Daniel Christian

Innovating Pedagogy 2017 — from iet.open.ac.uk

Excerpt:

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This sixth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Learning In a NetworKed Society (LINKS) Israeli Center of Research Excellence (I-CORE). We proposed a long list of new educational terms, theories, and practices. We then pared these down to ten that have the potential to provoke major shifts in educational practice, particularly in secondary and tertiary education. Lastly, we drew on published and unpublished writings to compile the ten sketches of new pedagogies that might transform education. These are summarised below in an approximate order of immediacy and timescale to widespread implementation.

Reaching All Learners by Leveraging Universal Design for Learning in Online Courses [Bowery & Houston]

On 12/06/2017, in adjunct faculty, colleges, community colleges, digital learning, faculty, higher education, instructional design, multimedia, online learning, pedagogy, teaching & learning, teaching online, universities, by Daniel Christian

Reaching All Learners by Leveraging Universal Design for Learning in Online Courses — from by Roy Bowery and Leonia Houston

Key Takeaways

An instructional design team at the University of Memphis focused on helping faculty create inclusive online classrooms, become aware of the diversity of their students’ learning needs, and adapt their instruction to reach all learners.
They did this by helping faculty employ the principles and guidelines of the Universal Design for Learning framework, which consists of three principles: Multiple Means of Engagement, Multiple Means of Representation, and Multiple Means of Action and Expression.
After two years, the UDL Implementation Plan, with its emphasis on experimentation, exploration, and inclusive instruction, yielded significant benefits for instructional effectiveness at the University of Memphis.

…

In an effort to bridge the success gap, our team focused on helping faculty employ the principles and guidelines of the Universal Design for Learning (UDL) framework. According to the National Center on Universal Design for Learning, the UDL framework consists of three principles: Multiple Means of Engagement, Multiple Means of Representation, and Multiple Means of Action and Expression.¹ The principles within the framework focus on the what, how, and why of learning. Each of these key principles helped our faculty address learner variability and include guidelines for encouraging their learners to become more motivated, resourceful, and goal-directed. By incorporating the UDL principles and guidelines into their online program courses, faculty created inclusive learning environments and addressed learner variability. With their newfound skills, most could use the strategies within the framework to design and develop online courses with flexible goals, instructional methods, materials, and assessments.

To assist faculty, we created a UDL Implementation Plan designed to teach them how to gradually incorporate UDL principles into their online classrooms, address learner variability, and create inclusive online instruction. We could customize the framework to meet every course, faculty, or instructional need, and they did not have to follow the principles and guidelines within the framework in a specific order. Instead, faculty could identify instructional methods or assignments affecting success in their course(s) and use specific UDL principles or guidelines to solve their pedagogical issues.

Provosts, Pedagogy, and Digital Learning — from er.educause.edu by Kenneth Green, Charles Cook, Laura Niesen de Abruna and Patricia Rogers
Panel members from an EDUCAUSE 2017 Annual Conference session offer insights about the role of provosts and chief academic officers in digital courseware deployment and the challenges of using technology to advance teaching, learning, and student success.

Excerpt:

At the EDUCAUSE 2017 Annual Conference, Kenneth C. (Casey) Green moderated a panel discussion with two of the CAOs involved in the Association of Chief Academic Officers (ACAO) Digital Fellows Program and with the principal investigator on the Bill & Melinda Gates Foundation grant that created the year-long program. In this session, the three panel members offered their perspectives on campus IT investments, including what the panelists see as working—and what they see as missing—in instructional technology portfolios today.

Green: What about protection and support for faculty—especially young faculty? Often and disproportionately, younger faculty handle the heavy lifting for departments because, being younger, they’re supposed to “do the technology stuff.” Yet, when they do it—and I hear this at all types of institutions—they don’t get credit for the work in terms of review and promotion. The technology work doesn’t count, particularly at four-year colleges and research institutions.² Young faculty are told: “Wait. Get tenured, get through the hurdle, get over the hump, then do it. Because this will not help your career—even if you’re being pressured to be the lead person on a digital learning initiative for your institution.”

Niesen de Abruna: …Now the CIO has to be a partner with the CAO. Their joint enterprise is to leverage learning in their community and to work together and translate things for one another, acting as partners in terms of trying to benefit from what’s happening in instructional design. It’s very exciting for CIOs and CAOs to have that sort of relationship.

Also see:

Insights from Campus Leaders on Current Challenges and Expectations of IT — from er.educause.edu by Kathryn Gates and Joan Cheverie
IT’s role across a higher education institution is crucial, yet campus leaders typically understand IT challenges and opportunities based largely on their functional roles. Interviews with campus leaders offer insights into these views, as well as how to understand IT more broadly to better serve an institution’s mission.

Robots in the Classroom: How a Program at Michigan State Is Taking Blended Learning to New Places — from news.elearninginside.com by Henry Kronk; with thanks to my friend and colleague, Mr. Dave Goodrich over at MSU, for his tweet on this.

Excerpt:

Like many higher education institutions, Michigan State University offers a wide array of online programs. But unlike most other online universities, some programs involve robots.

Here’s how it works: online and in-person students gather in the same classroom. Self-balancing robots mounted with computers roll around the room, displaying the face of one remote student. Each remote student streams in and controls one robot, which allows them to literally and figuratively take a seat at the table.

Professor Christine Greenhow, who teaches graduate level courses in MSU’s College of Education, first encountered these robots at an alumni event.

“I thought, ‘Oh I could use this technology in my classroom. I could use this to put visual and movement cues back into the environment,’” Greenhow said.

From DSC:
In my work to bring remote learners into face-to-face classrooms at Calvin College, I also worked with some of the tools shown/mentioned in that article — such as the Telepresence Robot from Double Robotics and the unit from Swivl. I also introduced Blackboard Collaborate and Skype as other methods of bringing in remote students (hadn’t yet tried Zoom, but that’s another possibility).

As one looks at the image above, one can’t help but wonder what such a picture will look like 5-10 years from now? Will it picture folks wearing VR-based headsets at their respective locations? Or perhaps some setups will feature the following types of tools within smaller “learning hubs” (which could also include one’s local Starbucks, Apple Store, etc.)?

Excerpt:

Artificial Intelligence has leapt to the forefront of global discourse, garnering increased attention from practitioners, industry leaders, policymakers, and the general public. The diversity of opinions and debates gathered from news articles this year illustrates just how broadly AI is being investigated, studied, and applied. However, the field of AI is still evolving rapidly and even experts have a hard time understanding and tracking progress across the field.

Without the relevant data for reasoning about the state of AI technology, we are essentially “flying blind” in our conversations and decision-making related to AI.

Created and launched as a project of the One Hundred Year Study on AI at Stanford University (AI100), the AI Index is an open, not-for-profit project to track activity and progress in AI. It aims to facilitate an informed conversation about AI that is grounded in data. This is the inaugural annual report of the AI Index, and in this report we look at activity and progress in Artificial Intelligence through a range of perspectives. We aggregate data that exists freely on the web, contribute original data, and extract new metrics from combinations of data series.

All of the data used to generate this report will be openly available on the AI Index website at aiindex.org. Providing data, however, is just the beginning. To become truly useful, the AI Index needs support from a larger community. Ultimately, this report is a call for participation. You have the ability to provide data, analyze collected data, and make a wish list of what data you think needs to be tracked. Whether you have answers or questions to provide, we hope this report inspires you to reach out to the AI Index and become part of the effort to ground the conversation about AI.

From DSC:
In this video, I look at how the pace of change has changed and I also provide some examples that back up this assertion. I end with a series of relevant questions, especially for those of us working within higher education.

What are we doing to get ready for the massive change that’s heading our way?

Reflections on “How AI-powered enterprise chatbot platforms are transforming the future of work” [Shaw]

On 12/05/2017, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assistive technologies, bots, business, career development, change, computer science, corporate / business world, corporate universities / corporate training, platforms, programming, tools, training / L&D, trends, workplace, by Daniel Christian

How AI-powered enterprise chatbot platforms are transforming the future of work — from chatbotsmagazine.com by Gina Shaw

Excerpts:

WHAT IS AN ENTERPRISE CHATBOT PLATFORM?
To sum it up in a few words, a chatbot platform is a toolset which is used to build and deploy chatbots. Every organization has its own set of unique challenges that can be overcome by convenient automation provided by chatbots. After establishing a clear-cut chatbot strategy, enterprises can use a bot builder platform to build, train and manage customized bots. Before the advent of chatbot platforms, building a bot was a strenuous task and required sophisticated toolsets and advanced coding knowledge. However with time, several bot building platforms flooded the chatbot market and led to the creation of safe AI bots which need minimum deployment time and almost zero coding knowledge. Enterprise chatbot platforms also allow IT departments to have complete control and access to monitoring bots.

From DSC:
It is with some hesitation that I post this article. Why? Because:

I started out my career in a customer service related position at Baxter Healthcare, and it was one of the most important jobs that I’ve had because it taught me the value of a customer. Ever since then, I have treated everyone as my customer — whether they be internal or external to the organization that I was working for.
Then, there’s the idea of calling a Voice Response Unit (VRU) — which sometimes works well and sometimes I can’t stand it. There are times when I/we simply want to speak to a fellow human being.

So it is with some hesitation that I post this article. But I do so because it is yet another example of:

The increased usage of algorithms, software, bots, personal assistants, AI, etc. to obtain answers and information
The changing skillset employees will need and job seekers may want to develop (if such things are interesting to them)
The massive changes heading our way

Six common micro-learning myths [Shepherd]

On 12/05/2017, in adult learning, corporate / business world, corporate universities / corporate training, heutagogy, instructional design, learning, learning ecosystem, lifelong learning, microlearning, pedagogy, training / L&D, UK, workplace, by Daniel Christian

Six common micro-learning myths — from linkedin.com by Clive Shepherd

Excerpt:

Micro-learning can justifiably be accused of being the latest digital learning bandwagon, here today, gone tomorrow. Real cynics might regard it as just another way of re-branding self-study e-learning, a medium which has spent too long in the compliance ghetto and has suffered in terms of popularity as a result.

I am not one of those cynics. I believe there is ample evidence to show how, when it is designed and implemented well, it can achieve great results. But it is not a panacea and works best as a strategic element in an overall architecture for workplace learning.

Before we can reach that happy state of affairs we need to agree our terminology and then lay bare the most common myths about how micro-learning works. I’ve come with six ideas that need some careful examination.

As Pedagogy Changes, Learning Spaces Are Transforming Too — from thejournal.com by Dennis Pierce
The American architect Louis Sullivan coined the phrase “form follows function,” and this is true of classrooms as well.

Excerpt:

In Johnson’s classroom at H.D. Isenberg Elementary School in Salisbury, NC, students can choose from a variety of seating options. There are tables for students to collaborate in groups of four, as well as bar-style seating on taller stools and even a few couches where they can sit comfortably while they work or read independently. The school provided the tables, and Johnson supplied the rest of the furniture himself.

To teach his students about citizenship, Johnson operates his classroom like a community. “I call it the Johnsonville Learning Community,” he said.

His fourth- and fifth-grade students can earn currency by coming to class each day and successfully completing assignments, and they also hold various classroom jobs. “The students who keep the classroom clean are part of our janitorial service,” he explained. “The student who brings things to the office is our delivery service.” Students use part of their currency to pay “rent” each month, and that entitles them to sit where they want.

Johnson’s school system is a 1-to-1 district, and every student is given an iPad to take home. Much of his instruction is project-based, with students working in small groups on tasks using curriculum from sources such as Defined STEM. In one recent project, his students used 3D modeling software on their iPads to create a multi-touch book about the human body systems.

Johnson’s classroom is an example of how changes in both the design of the learning space and the teaching that takes place there have combined to making learning much more engaging and effective for students.

A growing body of research suggests that the design of a learning space can have a significant effect on student success. For instance, a study by researchers at the University of Salford in England found that classroom design can have a 25 percent impact, either positive or negative, on student achievement over the course of an academic year — with factors such as color, complexity, flexibility, lighting and student choice having the most influence.

From DSC:
I saw the word CHOICE (or some variant of it) mentioned several times in this article. That’s a helpful step in developing the kind of mindset that our students will need in the future. Making choices, thinking on their feet, being able to adapt and pivot, NOT looking to be spoon fed by anyone — because that’s likely not going to happen once they graduate.

When redesigning learning spaces, let the type of learning experiences you want to foster be your guide, Jakes advised. “Focus on experiences, not things,” he said. “This is not about furniture; it’s about the learning. What experiences do I want to create for students? Then, what design would support that?”

David Jakes

Amazon & Google have started their own consulting operations, lending out some of their prized AI talent to customers.

On 12/01/2017, in Amazon, analytics, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, business, career development, cloud-based computing / apps / other cloud-related, computer science, corporate / business world, data related items, emerging technologies, Google, workplace, by Daniel Christian

Google, Amazon Find Not Everyone Is Ready for AI — from wired.com by Tom Simonite

Excerpt:

Yet as Amazon and Google seek greater riches by infusing the world with artificial intelligence, they’ve started their own consulting operations, lending out some of their prized AI talent to customers. The reason: Those other businesses lack the expertise to take advantage of techniques such as machine learning.

…

The expertise shortage upsets the usual dynamic of the cloud market, where Amazon, Google, and others mostly compete on price and technical features. “If you’re a random manufacturing company in the midwest you may have money, but it’s hard to attract a $250,000-a-year Stanford PhD to work for you,” says Diego Oppenheimer, whose Google-backed startup provides tools that help companies deploy machine-learning software. Companies in that situation may be more swayed by an offer of help building AI, than pricing and performance, he says.

Ask About AI: The Future of Learning and Work — from gettingsmart.com by Tom Vander Ark

Excerpts:

Code that learns may prove to be the most important invention in human history. But in 2016, there was almost no discussion of the implications of artificial intelligence (AI) in K-12 education—either the immense implications for the employment landscape or the exciting potential to improve learning.

We spent two years studying the implications of AI and concluded that machine intelligence turbocharged by big data and enabling technologies like robotics is the most significant change force facing humanity. Given enormous benefits and challenges we’re just beginning to understand, we believe it is an important time to Ask About AI (#AskAboutAI).

…

After interviewing experts, hosting a dozen community conversations, and posting more than 50 articles we’re summarizing what we’ve learned in a new paper Ask About AI: The Future of Learning and Work.

The paper explores what’s happening in the automation economy, the civic and social implications, and how to prepare ourselves and our children for exponential change.

With this launch we’re also launching a new microsite on Future of Work.

To initiate lifelong learning, secondary schools should encourage students to be reflect on how they learn, and build habits of success. There are an increasing number of organizations interested in being lifelong learning partners for students—college alumni associations, professional schools and private marketplaces among them.

Self-directed learning is most powerfully driven by a sense of purpose. In our study of Millennial employment, Generation Do It Yourself, we learned that it is critical for young people to develop a sense of purpose before attending college to avoid the new worst-case scenario—racking up college debt and dropping out. A sense of purpose can be developed around a talent or issue, or their intersection; both can be cultivated by a robust guidance system.

We’ve been teaching digital literacy for two decades, but what’s new is that we all need to appreciate that algorithms curate every screen we see. As smart machines augment our capabilities, they will increasingly influence our perceptions, opportunities and decisions. That means that to self- and social awareness, we’ll soon need to add AI awareness.

Taken together, these skills and dispositions create a sense of agency—the ability to take ownership of learning, grow through effort and work with other people in order to do the learning you need to do.

Learning Ecosystems

Amazon Intros Alexa for Business + 3 other items on AI

Reaching All Learners by Leveraging Universal Design for Learning in Online Courses [Bowery & Houston]

Nice experimentation going on at Michigan State — connecting remote learners with each other in new ways

AI Index Report for 2017 — i.e., where are we, as of November 2017, with artificial intelligence?

The Pace of Change Has Changed — With Massive Ramifications! [A video by Daniel Christian]

Reflections on “How AI-powered enterprise chatbot platforms are transforming the future of work” [Shaw]

Six common micro-learning myths [Shepherd]

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