We Need to Help Our Students Build Solid Online-Based Footprints
I used a tool called VideoScribe to create this piece. The video relays how important it is that our students have solid, sharp, online-based footprints.

 

We need to help our students build their own online-based footprints

 

 

We need to help our students build their own online-based footprints

 

 

 

We need to help our students build their own online-based footprints

 

 

 

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.

 

 

 

High-Tech, High Touch: Digital Learning Report and Workbook, 2017 Edition — from Intentional Futures, with thanks to Maria Andersen on Linkedin for her posting therein which was entitled, “Spectrums to Measure Digital Learning
Excerpt (emphasis DSC):

Our work uncovered five high-tech strategies employed by institutions that have successfully implemented digital learning at scale across a range of modalities. The strategies that underscore the high-tech, high-touch connection are customizing through technology, leveraging adaptive courseware, adopting cost-efficient resources, centralizing course development and making data-driven decisions.

Although many of the institutions we studied are employing more than one of these strategies, in this report we have grouped the institutional use cases according to the strategy that has been most critical to achieving digital learning at scale. As institutional leaders make their way through this document, they should watch for strategies that target challenges similar to those they hope to solve. Reading the corresponding case studies will unpack how institutions employed these strategies effectively.

Digital learning in higher education is becoming more ubiquitous as institutions realize its ability to support student success and empower faculty. Growing diversity in student demographics has brought related changes in student needs, prompting institutions to look to technology to better serve their students. Digital courseware gives institutions the ability to build personalized, accessible and engaging content. It enables educators to provide relevant content and interventions for individual students, improve instructional techniques based on data and distribute knowledge to a wider audience (MIT Office of Digital Learning, 2017).

PARTICIPATION IN DIGITAL LEARNING IS GROWING
Nationally, the number of students engaged in digital learning is growing rapidly. One driver of this growth is rising demand for distance learning, which often relies on digital learning environments. Distance learning programs saw enrollment increases of approximately 4% between 2015 and 2016, with nearly 30% of higher education students taking at least one digital distance learning course (Allen, 2017). Much of this growth is occurring at the undergraduate level (Allen, 2017). The number of students who take distance learning courses exclusively is growing as well. Between 2012 and 2015, both public and private nonprofit institutions saw an increase in students taking only distance courses, although private, for-profit institutions have seen a decrease (Allen, 2017).

 

 

 

 

 

 

 

How to be an ed tech futurist — from campustechnology.com by Bryan Alexander
While no one can predict the future, these forecasting methods will help you anticipate trends and spur more collaborative thinking.

Excerpts:

Some of the forecasting methods Bryan mentions are:

  • Trend analysis
  • Environmental scanning
  • Scenarios
  • Science fiction

 

 

 

 

From DSC:
I greatly appreciate the work that Bryan does — the topics that he chooses to write about, his analyses, comments, and questions are often thought-provoking. I couldn’t agree more with Bryan’s assertion that forecasting needs to become more realized/practiced within higher education. This is especially true given the exponential rate of change that many societies throughout the globe are now experiencing.

We need to be pulse-checking a variety of landscapes out there, to identify and put significant trends, forces, and emerging technologies on our radars. The strategy of identifying potential scenarios – and then developing responses to those potential scenarios — is very wise.

 

 

 

 

 

 

 

 

 

 

 

 

 

From DSC:
I’m posting this in an effort to:

  • Help students learn how to learn
  • Help students achieve the greatest possible returns on their investments (both their $$ and their time) when they are trying to learn about new things

I’d like to thank Mr. William Knapp, Executive Director at GRCC for Distance Learning & Instructional Technology, for sharing this resource on Twitter.


A better way to study through self-testing and distributed practice — from kqed.org

Excerpts (emphasis DSC):

As I prepared to write this column, I relied on some pretty typical study techniques. First, as I’ve done since my student days, I generously highlighted key information in my background reading. Along the way, I took notes, many of them verbatim, which is a snap with digital copying and pasting. (Gotta love that command-C, command-V.) Then I reread my notes and highlights. Sound familiar? Students everywhere embrace these techniques and yet, as it turns out, they are not particularly good ways to absorb new material. At least not if that’s all you do.

Researchers have devoted decades to studying how to study. The research literature is frankly overwhelming. Luckily for all of us, the journal Psychological Science in the Public Interest published a review article a few years ago that remains the most comprehensive guide out there. Its 47 pages hold valuable lessons for learners of any age and any subject — especially now, with end-of-semester exams looming.

The authors examined ten different study techniques, including highlighting, rereading, taking practice tests, writing summaries, explaining the content to yourself or another person and using mnemonic devices. They drew on the results of nearly 400 prior studies. Then, in an act of boldness not often seen in academic research, they actually awarded ratings: high, low or moderate utility.

The study strategies that missed the top rating weren’t necessarily ineffective, explains the lead author John Dunlosky, a psychology professor at Kent State University, but they lacked sufficient evidence of efficacy, or were proven useful only in certain areas of study or with certain types of students. “We were trying to find strategies that have a broad impact across all domains for all students,” Dunlosky says, “so it was a pretty tough rating scale.”

 

In fact, only two techniques got the top rating: practice testing and “distributed practice,” which means scheduling study activities over a period of time — the opposite of cramming.

Practice testing can take many forms: flashcards, answering questions at the end of a textbook chapter, tackling review quizzes online. Research shows it works well for students from preschool through graduate and professional education.

Testing yourself works because you have to make the effort to pull information from your memory — something we don’t do when we merely review our notes or reread the textbook.


As for distributed practice vs. cramming, Dunlosky and his fellow authors write that “cramming is better than not studying at all,” but if you are going to devote four or five hours to studying for your biology mid-term, you would you be far better off spacing them out over a several days or weeks. “You get much more bang for your buck if you space,” Dunlosky told me.

 

 

Also see:

Improving Students’ Learning With Effective Learning Techniques — from journals.sagepub.com by John Dunlosky, Katherine A. Rawson, Elizabeth J. Marsh, Mitchell J. Nathan, and Daniel T. Willingham
Promising Directions From Cognitive and Educational Psychology

Excerpt:

In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice.

 

 

 

In fact, only two techniques got the top rating: practice testing and “distributed practice,” which means scheduling study activities over a period of time — the opposite of cramming.

 

 

From DSC:
This is yet another reason that I like the approach of using streams of content to help people learn something new. Because you can implement distributed practice, encourage recall, etc. when you put the content out there at regular intervals.

 

 

 

How artificial intelligence could transform government — from Deloitte University Press
Cognitive technologies have the potential to revolutionize the public sector—and save billions of dollars

Excerpt:

The rise of more sophisticated cognitive technologies is, of course, critical to that third era, aiding advances in several categories:

  • Rules-based systems capture and use experts’ knowledge to provide answers to tricky but routine problems. As this decades-old form of AI grows more sophisticated, users may forget they aren’t conversing with a real person.
  • Speech recognition transcribes human speech automatically and accurately. The technology is improving as machines collect more examples of conversation. This has obvious value for dictation, phone assistance, and much more.
  • Machine translation, as the name indicates, translates text or speech from one language to another. Significant advances have been made in this field in only the past year.8 Machine translation has obvious implications for international relations, defense, and intelligence as well as, in our multilingual society, numerous domestic applications.
  • Computer vision is the ability to identify objects, scenes, and activities in naturally occurring images. It’s how Facebook sorts millions of users’ photos, but it can also scan medical images for indications of disease and identify criminals from surveillance footage. Soon it will allow law enforcement to quickly scan license plate numbers of vehicles stopped at red lights, identifying suspects’ cars in real time.
  • Machine learning takes place without explicit programming. By trial and error, computers learn how to learn, mining information to discover patterns in data that can help predict future events. The larger the datasets, the easier it is to accurately gauge normal or abnormal behavior. When your email program flags a message as spam, or your credit card company warns you of a potentially fraudulent use of your card, machine learning may be involved. Deep learning is a branch of machine learning involving artificial neural networks inspired by the brain’s structure and function.9
  • Robotics is the creation and use of machines to perform automated physical functions. The integration of cognitive technologies such as computer vision with sensors and other sophisticated hardware has given rise to a new generation of robots that can work alongside people and perform many tasks in unpredictable environments. Examples include drones, robots used for disaster response, and robot assistants in home health care.
  • Natural language processing refers to the complex and difficult task of organizing and understanding language in a human way. This goes far beyond interpreting search queries, or translating between Mandarin and English text. Combined with machine learning, a system can scan websites for discussions of specific topics even if the user didn’t input precise search terms. Computers can identify all the people and places mentioned in a document or extract terms and conditions from contracts. As with all AI-enabled technology, these become smarter as they consume more accurate data—and as developers integrate complementary technologies such as machine translation and natural language processing.

We’ve developed a framework that can help government agencies assess their own opportunities for deploying these technologies. It involves examining business processes, services, and programs to find where cognitive technologies may be viable, valuable, or even vital. Figure 8 summarizes this “Three Vs” framework. Government agencies can use it to screen the best opportunities for automation or cognitive technologies.

 

 

 

 

From DSC:
One of the biggest gifts that we can give our students today is learning how to learn. Along those lines, I was thinking about note-taking the other day.

Many students may not know how to take good notes, and to make the notes/thoughts their own. So I was thinking, wouldn’t it be great if, for each professor’s class, there was a place where students could go to see what exemplary notes look like for several — even many — of the sessions of a particular class?! If there were an accompanying audio-based or a video-based commentary that could relay the note-taker’s thinking/information processing, all the better.

These notes could be provided by the professor herself/himself or by a 4.0-type of student who has demonstrated solid study habits and shows a strong capacity for processing information.  The notes would want to:

  • Demonstrate what good note taking looks like
  • Provide examples of one’s own wording/understanding of the material
  • Identify/show any gaps in understanding by listing their own remaining questions. This type of gap analysis could help the learners see what a metacognitive check-in might look like.

By doing something like this, students could see what the main points were, what effective note taking looks like, and to see that the note-taker has taken the time to put some of their own reflections/summaries alongside the larger set of notes.

It would also be interesting to provide a platform whereby students could contribute/share their own notes to help others better understand not only the materials covered, but what different methods of note-taking might look like. Perhaps a certain style of note-taking would jump out at any given learner. Also, doing so would foster a more collaborative approach, as is often needed in the real-world.

An accompanying forum could be made available for students’ discussions of a particular class/topic. This forum could highlight for the professor what the areas of struggle are as well as how the material is being processed by the students.

 


On a separate thought…we also need to help students form habits of learning, such as regularly checking into streams of content (i.e., micro-learning).  If we can model this in the ways that we relay content and encourage dialog around a topic, then they will be that much better equipped to:

  • Deal with the new pace of exponential change
  • Reinvent themselves, if need be
  • Practice lifelong learning
  • Learn how to pulse-check their surroundings

 

 

 

WE ARE NOT READY FOR THIS! Per Forrester Research: In US, a net loss of 7% of jobs to automation — *in 2018*!

Forrester predicts that AI-enabled automation will eliminate 9% of US jobs in 2018 — from forbes.com by Gil Press

Excerpt (emphasis DSC):

A new Forrester Research report, Predictions 2018: Automation Alters The Global Workforce, outlines 10 predictions about the impact of AI and automation on jobs, work processes and tasks, business success and failure, and software development, cybersecurity, and regulatory compliance.

We will see a surge in white-collar automation, half a million new digital workers (bots) in the US, and a shift from manual to automated IT and data management. “Companies that master automation will dominate their industries,” Forrester says. Here’s my summary of what Forrester predicts will be the impact of automation in 2018:

Automation will eliminate 9% of US jobs but will create 2% more.
In 2018, 9% of US jobs will be lost to automation, partly offset by a 2% growth in jobs supporting the “automation economy.” Specifically impacted will be back-office and administrative, sales, and call center employees. A wide range of technologies, from robotic process automation and AI to customer self-service and physical robots will impact hiring and staffing strategies as well as create a need for new skills.

 

Your next entry-level compliance staffer will be a robot.

 

From DSC:

Are we ready for a net loss of 7% of jobs in our workforce due to automation — *next year*? Last I checked, it was November 2017, and 2018 will be here before we know it.

 

***Are we ready for this?! ***

 

AS OF TODAY, can we reinvent ourselves fast enough given our current educational systems, offerings, infrastructures, and methods of learning?

 

My answer: No, we can’t. But we need to be able to — and very soon!

 

 

There are all kinds of major issues and ramifications when people lose their jobs — especially this many people and jobs! The ripple effects will be enormous and very negative unless we introduce new ways for how people can learn new things — and quickly!

That’s why I’m big on trying to establish a next generation learning platform, such as the one that I’ve been tracking and proposing out at Learning from the Living [Class] Room. It’s meant to provide societies around the globe with a powerful, next generation learning platform — one that can help people reinvent themselves quickly, cost-effectively, conveniently, & consistently! It involves providing, relevant, up-to-date streams of content that people can subscribe to — and drop at any time. It involves working in conjunction with subject matter experts who work with teams of specialists, backed up by suites of powerful technologies. It involves learning with others, at any time, from any place, at any pace. It involves more choice, more control. It involves blockchain-based technologies to feed cloud-based learner profiles and more.

But likely, bringing such a vision to fruition will require a significant amount of collaboration. In my mind, some of the organizations that should be at the table here include:

  • Some of the largest players in the tech world, such as Amazon, Google, Apple, IBM, Microsoft, and/or Facebook
  • Some of the vendors that already operate within the higher ed space — such as Salesforce.com, Ellucian, and/or Blackboard
  • Some of the most innovative institutions of higher education — including their faculty members, instructional technologists, instructional designers, members of administration, librarians, A/V specialists, and more
  • The U.S. Federal Government — for additional funding and the development of policies to make this vision a reality

 

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

 

2018 Tech Trends for Journalism & Media Report + the 2017 Tech Trends Annual Report that I missed from the Future Today Institute

 

2018 Tech Trends For Journalism Report — from the Future Today Institute

Key Takeaways

  • 2018 marks the beginning of the end of smartphones in the world’s largest economies. What’s coming next are conversational interfaces with zero-UIs. This will radically change the media landscape, and now is the best time to start thinking through future scenarios.
  • In 2018, a critical mass of emerging technologies will converge finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. News organizations should devote attention to emerging trends in voice interfaces, the decentralization of content, mixed reality, new types of search, and hardware (such as CubeSats and smart cameras).
  • Journalists need to understand what artificial intelligence is, what it is not, and what it means for the future of news. AI research has advanced enough that it is now a core component of our work at FTI. You will see the AI ecosystem represented in many of the trends in this report, and it is vitally important that all decision-makers within news organizations familiarize themselves with the current and emerging AI landscapes. We have included an AI Primer For Journalists in our Trend Report this year to aid in that effort.
  • Decentralization emerged as a key theme for 2018. Among the companies and organizations FTI covers, we discovered a new emphasis on restricted peer-to-peer networks to detect harassment, share resources and connect with sources. There is also a push by some democratic governments around the world to divide internet access and to restrict certain content, effectively creating dozens of “splinternets.”
  • Consolidation is also a key theme for 2018. News brands, broadcast spectrum, and artificial intelligence startups will continue to be merged with and acquired by relatively few corporations. Pending legislation and policy in the U.S., E.U. and in parts of Asia could further concentrate the power among a small cadre of information and technology organizations in the year ahead.
  • To understand the future of news, you must pay attention to the future of many industries and research areas in the coming year. When journalists think about the future, they should broaden the usual scope to consider developments from myriad other fields also participating in the knowledge economy. Technology begets technology. We are witnessing an explosion in slow motion.

Those in the news ecosystem should factor the trends in this report into their strategic thinking for the coming year, and adjust their planning, operations and business models accordingly.

 



 

 

2017 Tech Trends Annual Report — from the Future Today Institute; this is the first I’ve seen this solid report

Excerpts:

This year’s report has 159 trends.
This is mostly due to the fact that 2016 was the year that many areas of science and technology finally started to converge. As a result we’re seeing a sort of slow-motion explosion––we will undoubtedly look back on the last part of this decade as a pivotal moment in our history on this planet.

Our 2017 Trend Report reveals strategic opportunities and challenges for your organization in the coming year. The Future Today Institute’s annual Trend Report prepares leaders and organizations for the year ahead, so that you are better positioned to see emerging technology and adjust your strategy accordingly. Use our report to identify near-future business disruption and competitive threats while simultaneously finding new collaborators and partners. Most importantly, use our report as a jumping off point for deeper strategic planning.

 

 



 

Also see:

Emerging eLearning Tools and Platforms Improve Results — from learningsolutionsmag.com

  • Augmented and virtual reality offer ways to immerse learners in experiences that can aid training in processes and procedures, provide realistic simulations to deepen empathy and build communication skills, or provide in-the-workflow support for skilled technicians performing complex procedures.
  • Badges and other digital credentials provide new ways to assess and validate employees’ skills and mark their eLearning achievements, even if their learning takes place informally or outside of the corporate framework.
  • Chatbots are proving an excellent tool for spaced learning, review of course materials, guiding new hires through onboarding, and supporting new managers with coaching and tips.
  • Content curation enables L&D professionals to provide information and educational materials from trusted sources that can deepen learners’ knowledge and help them build skills.
  • eBooks, a relative newcomer to the eLearning arena, offer rich features for portable on-demand content that learners can explore, review, and revisit as needed.
  • Interactive videos provide branching scenarios, quiz learners on newly introduced concepts and terms, offer prompts for small-group discussions, and do much more to engage learners.
  • Podcasts can turn drive time into productive time, allowing learners to enjoy a story built around eLearning content.
  • Smartphone apps, available wherever learners take their phones or tablets, can be designed to offer product support, info for sales personnel, up-to-date information for repair technicians, and games and drills for teaching and reviewing content; the possibilities are limited only by designers’ imagination.
  • Social platforms like Slack, Yammer, or Instagram facilitate collaboration, sharing of ideas, networking, and social learning. Adopting social learning platforms encourages learners to develop their skills and contribute to their communities of practice, whether inside their companies or more broadly.
  • xAPI turns any experience into a learning experience. Adding xAPI capability to any suitable tool or platform means you can record learner activity and progress in a learning record store (LRS) and track it.

 



 

DevLearn Attendees Learn How to ‘Think Like a Futurist’ — from learningsolutionsmag.com

Excerpt:

How does all of this relate to eLearning? Again, Webb anticipated the question. Her response gave hope to some—and terrified others. She presented three possible future scenarios:

  • Everyone in the learning arena learns to recognize weak signals; they work with technologists to refine artificial intelligence to instill values. Future machines learn not only to identify correct and incorrect answers; they also learn right and wrong. Webb said that she gives this optimistic scenario a 25 percent chance of occurring.
  • Everyone present is inspired by her talk but they, and the rest of the learning world, do nothing. Artificial intelligence continues to develop as it has in the past, learning to identify correct answers but lacking values. Webb’s prediction is that this pragmatic optimistic scenario has a 50 percent chance of occurring.
  • Learning and artificial intelligence continue to develop on separate tracks. Future artificial intelligence and machine learning projects incorporate real biases that affect what and how people learn and how knowledge is transferred. Webb said that she gives this catastrophic scenario a 25 percent chance of occurring.

In an attempt to end on a strong positive note, Webb said that “the future hasn’t happened yet—we think” and encouraged attendees to take action. “To build the future of learning that you want, listen to weak signals now.”

 



 

 

 

 

 

Nearly all prospective students want a tech-savvy institution — from campustechnology.com by Joshua Bolkan

Excerpt:

Nearly nine in 10 college students — 87 percent — said it was important to them that the institutions they applied for were technologically savvy, according to a new survey from ed tech provider Ellucian.

The report, “Students Are Looking for Personalized Digital Experiences: Do Colleges Deliver?” is based on responses of 1,000 students, including 265 from two-year institutions and 735 from four-year schools, who were invited to take the survey online via email.

More than half of students surveyed, 58 percent, said that of all the companies and institutions they engage with, their college is the one least likely to have personalized their experience.

 

Also see:

 

 

 

From DSC:
With our students using Uber, Lyft, AirBnB, and other such personalized services from Amazon.com and others, expectations are now being impacted. That is, what they expect in terms of their learning experiences are being influenced from other areas of their every day lives. This impacts credibility, which impacts enrollments.

As Ellucian asserts:

 

 

For those who would minimize or outright discard the impacts that technologies have on higher education, or the impacts of — and relevance of — technologies within higher education, how are you going to deal with this tidal wave?

 

From Daniel S. Christian

 

 

 

 

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