VR Devices to Hit 110 Million

Virtual reality (VR) is ready to thrive off a swath of new and compelling content choices. ABI Research forecasts total VR device shipments will reach 110 million by 2021. While mobile device-reliant VR ship- ments—such as Samsung Gear VR and Google Daydream—dwarf today’s other VR device types, standalone devices will see a 405% CAGR through 2021, compared to a 42% CAGR for mobile VR.

“Mobile VR built a solid foundation for the overall market over the past few years, but standalone VR devices will even- tually drive it,” says Eric Abbruzzese, Senior Analyst at ABI Research. “However, a trend toward standalone devices is sur- facing, and will continue over the next five years until mobile and standalone VR devices see parity in terms of shipments.”

With an influx of standalone VR devices incoming, a greater range of use cases will be explored. ABI Research anticipates a total market size of $64 billion by 2021 [for gaming.] VR applications in retail and marketing will see a 124% CAGR through 2021. Video, education, and tourism are expected to see significant growth, as well.

—Source: ABI Research http://bit.ly/2l8gE3j

Published in Trends

The global e-learning market is poised to grow at a 7.2% CAGR over the next decade to reach approximately $325 billion by 2025 reports Research & Markets study.

Some of the prominent trends that the market is witnessing include learning through gaming, implementation of I.T. security and Cloud-based solutions, rapid growth in online content & digitization, innovations in wearable technologies for e-learning industry, and learning management systems are switching over to cloud-based systems.

—Source: http://www.researchandmarkets.com/research/qgq5vf/global_elearning

Published in Trends

Learning Tree International has been awarded a five-year contract by the NATO Communications and Information (NCI) Agency as its strategic learning partner for the provision of training solutions for up to 33,000 NATO staff across 28 European and North American countries. Learning Tree will provide training in project, program and portfolio management; cyber security; service management; and technical I.T. to support NATO in remaining resilient through continuous, rapid innovation.

Under the contract, Learning Tree will provide commercial training services to the NCI Agency, plus the wider community of NATO agencies. The training will be delivered through a combination of on-site courses provided at over 40 different NATO locations, including permanent classrooms on NATO sites, fully equipped by Learning Tree; at publicly scheduled training events in Learning Tree Education Centers; and through AnyWare — Learning Tree’s virtual learning environment.

Published in Deals

The 7th Annual Enterprise Learning! Conference is now accepting submissions for the September event. The theme “Building the High Performance Organization” focuses on the strategy, best practices and technologies that drive performance. The event seeks thought leaders and presenters with expertise in learning, talent development, business perfor- mance, and learning and workplace technologies.

ELC17 is also host to the 2017 Learning! 100 and Learning! Champions Awards honoring the top 100 learning organizations and those making extraordinary contributions to the learning industry. Attendees herald from Amazon Web Services, AT&T, NASCAR, the U.S. Department of Defense and others.

—To submit to ELC17, visit: http://www.2elearning.com/rss2/item/56671-enterprise-learning-conference-2017-call-for-papers

 

Published in Latest News

Artificial intelligence (A.I.) is playing a bigger role in our every- day lives, but how are enterprises adopting this technology? En- ter cognitive computing and predictive analytics, and so much more. According to the National Business Research Institute, A.I.’s most important benefit is the ability to predict future tasks (38%) and automation of tasks (27%).

—Test your AI knowledge at: https://www.emarketer.com/quiz/artificial-intelligence?ecid=1014#/q/1

 

Published in Latest News

The top consumer technology transformations were revealed by Dr. Shawn Dubravac, Research Director, Consumer Technology Association. These trends will impact enterprise technology over the coming months and years.

1. The Next Computer Interface is Voice

The word error rate is now at human parity, meaning the graphic user interface will disappear ushering in an era of faceless computing. Voice will be the command function for digital devices including robotics, A.I., etc.

2. Increasing Intelligent Systems  will Connect Diverse Objects

Software is now found in hardware out of the box, and hard- ware is eating software. Alexa is found in refrigerators and automobiles. While google’s newest smartphone is embedded with AR/VR software out of the box.  “This creates a ‘physical manifestation of data’ in our lives,” says Dubravac.

3. Transportation Transformation

The self-driving car was the catalyst for intelligent systems. With connected systems reporting to other cars, the vehicles can respond and react without human intervention. This is a model of many “robotic” type activities that may complement or replace human interactions.

4. A.I.’s Infusion into Real Life

Blending data from diverse devices is improving signal, functionality, and recommendations for users to follow. Hub de- vices will be used for vocal computing. A.I. will boost informa- tion processing geometrically. For example, Google cars have already driven more miles than a human can in 75 years. The speed, experiences, data collection and sharing has increased geometrically.

5. Digitizing the Consumer Experience

From wearables to smart home, online and mobile characterizes consumers tastes. Drone purchases reached 1.1 million units in 2016; VR 700,000 units; smart watches 5.5 million units and fitness trackers 12.6 million.

—Source: CTA.tech  bit.ly/CES2017TRENDS

Published in Insights

BY PRADEEP KHANNA

The other day, I went to meet someone in downtown Sydney, Australia. On my way, back on the local train, I looked at my mobile to check my emails and found a message asking me whether I would like to meet the person I had just connected with on my LinkedIn network. So, was this some form of artificial intelligence (AI) at play?

Yes! We now live in a brave new world where AI is the next frontier. We keep hearing about bots, chatbots, teacherbots, digital assistants, machine learning, deep learning and many more such words and often wonder what do they mean.

Just like virtual reality (VR), AI has been around for quite some time. In fact, I remember taking AI as a subject when doing my second master’s degree in computer science at University of Technology in Sydney 17 years ago. So, why so much fuss about AI now? AI will reshape how we live and work, but will AI also reshape the way we learn?

ABOUT BOTS, CHATBOTS, TEACHERBOTS AND A.I.

A bot is software that is designed to automate repetitive tasks. Bots have been around for quite some time. An example is use of bots for searching and cataloguing Web pages for search engines. Another example is shopping bots which pull out prices of an item from different vendors from the Internet. Some recent examples are bots making dinner reservations, adding an appointment to the calendar, or fetching and displaying information.

Chatbots are bots that conduct a conversation mirroring potentially a real-life conversation. Chatbots can either be simple rule-based or more sophisticated AI-based. AI-based chatbots get smarter as more interactions take place. The popularity of messaging apps has been lifting the demand for chatbots. Another way to look at the rise of chatbots is the user migration from Web to apps and now from apps to chatbots.

What are teacherbots? Just like a bot or a chatbot, a teacherbot can be a simple rule-based or smart AI-based. Simple rule-based teacherbots can automate simple teaching tasks whereas a smart AI-based teacherbot can become a teaching assistant (TA). A yet smarter AI-based teacherbot can also be personal tutor.

TEACHERBOTS AT WORK

There are two well known instances of teacherbot pilot projects at the University of Edinburgh in the U.K. and Georgia Tech in the U.S.A. The University of Edinburgh teacherbot project was led by its School of Education in collaboration with the School of Informatics and the Edinburgh College of Art. It was launched in April 2015 by Siân Bayne, professor of Digital Education. “Botty,” as this teacherbot was affectionately called, was created to engage on Twitter with students of Edinburgh’s e-learning and Digital Cultures MOOC on Coursera. This MOOC has had 70,000 enrollments across three course runs. The teacherbot’s primary role was to act like a TA. It could answer simple questions on deadlines, course content, etc. It was also able to answer some complex questions as well, based on AI that had been developed on stored tweets with Twitter hashtag #edcmooc. In “Botty’s” case, the students were aware that a teacherbot and not a human being was answering their questions.

Georgia Tech’s teacherbot was developed by Ashok Goel, a professor of Artificial Intelligence at Georgia Tech. Typically, the 300 students at Georgia Tech’s online AI course posted around 10,000 messages in online forums during a semester. Many of these questions were repetitive in nature. This was enough of a driver for Ashok to initiate work on the teacherbot. Leveraging IBM Watson’s technology platform and a databank of 40,000 questions and answers from past semesters, Ashok developed the smart AI overlay for the teacherbot, calling it “Jill Watson. The students were not told that TA “Jill Watson” was a teacherbot.

“Jill Watson” was launched in Jan 2016. As expected, its responses were not very accurate in the beginning, so responses were moderated by the human TAs before posting in the online forums. But by April, it had become sufficiently “intelligent” to answer the questions without human intervention.

The table on the following page compares the two pilot teacherbot projects.

ELM March A.I. Already Reshaping

Many factors determine the accuracy level of any AI project, including the AI technology layer at the infrastructure level, the size of the database, and the contextualizing smart AI layer. Looking at the above comparison between the two projects, the Georgia Tech project does have an advantage of using IBM Watson as a technology platform and having a database of 40,000 questions and answers from previous courses. No wonder, it performed better.

AI NEXT IN LEARNING?

The potential of AI to disrupt education and skills training sectors is immense. As Microsoft’s Bill Gates remarked sometime back, we already have online tutoring services where humans provide the services while the platform is online. Smart AI-based teacherbots can replace the humans to provide personalized learning. This has special relevance in lifelong learning scenarios where we will be dipping in and out the learning continuum all through our life.

Automated assessments are a natural application of AI in education and skills training. This application gets further amplified when  large number of assessments are being done in an online environment. Use of technologies like Facebook’s facial recognition technology and proctoring are classic examples.

Are we already there in the brave new world where AI is reshaping the way learn? IN these early days, where we are seeing AI-based projects being rolled out in different parts of the world. In the first instance, the focus appears to be on automating routine teaching tasks. This is akin to the Robotic and Process Automation (RPA) implementation onslaught we are seeing in other industries.

“Jill Watson” is estimated to have taken 1500 hours to develop. When many “Jill Watsons” are produced in 15 hours is when we will see real disruption in education and skills training.

Developments in AI in education and skills training will to an extent follow the developments in AI in general. With all major technology innovators investing heavily in AI, it appears certain that our working and learning will get reshaped by AI in future.

—Pradeep Khanna is founder & CEO of Global Mindset (www.globalmindset.com.au) and Technology-enabled Innovations in Learning & Teaching (TILT). He works on enhancing collaborative learning across boundaries and by leveraging technology. Khanna has also been Global Delivery Leader for IBM GBS Australia/New Zealand. He lives in Sydney, Australia, and can be contacted via email at This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Published in Insights

6 STRATEGIES FOR MAKING YOUR TRAINING STICK - BY DEAN PICHEE, CEO, BIZLIBRARY, INC.

THE SCIENCE OF LEARNING

Many professions use science to improve the outcomes of their work. For example, architects use the principles of physics and math to design buildings that will function safely and last decades or even centuries. Architecture is often equated with art, but it's the science behind the art that truly makes it work.

In much the same way, we as learning and HR professionals need to understand and use our knowledge of the science of learning to improve the outcomes of our efforts in training employees. What does science tell us we should do to improve the way employees learn?

Here are six things you can start doing today:

1. Make learning bite-sized. Use short, relevant, video-based training (microlearning) focused on individual concepts.

2. Space training out over time. Employees should use the information they learn during training within the first 24 hours after the training event and in the days and weeks to come. Time is on our side here!

3. Add post-training reinforcement. Use quizzes, polls, videos and other resources to reinforce key concepts.

4. Mix it up. Combine training of multiple related skills rather than focusing on one skill at a time. Scientists call this learning concept interleaving.

5. Make it difficult. Resist the temptation to make training easy for learners. Challenging them actually increases the learning impact. One of the ways to make it more difficult is to increase the amount of time between testing and retrieval opportunities.

6. Write to remember. Your brain will recognize more of what's important when you write what you learn.

WHAT WORKS?

We call microlearning and post-training reinforcement "Burst and Boost Training." Using a combination of "bursts and boosts" is a proven way to get more ROI from your employee training program. Bursts of microlearning have been proven by cognitive psychology to be the most effective way learners receive information. Cognitive load theory states that we have mental "bandwidth" restrictions. The brain can only process a certain amount of information before reaching overload. To improve training content, chunk it down into bite-sized bursts to lower the cognitive load. Microlearning is very popular today and is a key component of BizLibrary's online training solutions.

Boosts, or post-training reinforcement, has been shown to increase long-term memory. Testing can actually INCREASE learning more than any other study method. Scientists call this idea "The Testing Effect," and numerous studies have shown that long-term memory is increased when some of the learning time is devoted to retrieving the to-be-remembered information. Incorporating tests and quizzes into employee training programs is more than just measuring the amount of learning that has taken place ... it's a critical part of the learning itself. Resist the temptation to skip testing and boost learning!

THE GREAT TRAINING ROBBERY

Stop the great training robbery that occurs when we deliver programs that are too long, too boring and easily forgotten. Microlearning is the first step. It's also crucial to add on-going reinforcement. Think of post- training reinforcement as the deadbolt on the door of your house, keeping the valuable information you're delivering to your employees from being forgotten and ultimately, maximizing the ROI of your program.

Published in Insights

Economists have predicted that a rapid period of innovation follows an economic downturn. We are in that innovation cycle. We once could count on an obsolescence cycle of 24 months (thanks to Moore’s law), which was condensed to six months (the life of a smartphone). Now, we are learning and evolving instantly thanks to A.I. and machine learning.

In 2017’s Annual E-learning User Study conducted by Elearning! magazine, 65.6% of respondents are using machine learning today, and 46.9% are planning to purchase. Artificial intelligence is deployed by 31.8% of respondents with 72.7% planning to deploy over the next 12 months, a 228% compounded annual growth rate (CAGR). Augmented reality and virtual reality are close behind with 68.6% and 67.6% planning to deploy. (See article E-learning User Study.)

These advancements are transforming our practices, ecosystems and knowledge base. In the article titled, “Three Disruptive Macro Trends Shaping Enterprise Technology,” we tapped Gartner and leading learning technologists to share their insights and implications (see article Disruptions in Enterprise Technology). Dr. Shawn Dubravac from Consumer Technology Association also identified five transformational technology trends (see article 5 Transformational Technology Trends). Pradeep Khanna also shares his views on A.I. in learning (see article The AI Effect: Are You Ready), and Joe DiDonato makes five learning predictions for 2017 (see Top 5 Learning Predictions for 2017). All conclude that technology’s rapid evolution is spurring transformation at home and at work.

Nothing is gained without the steadfast commitment by our peers, partners and technologists. Elearning! magazine recognizes 28 Learning! Champions who have made extraordinary contributions to the learning industry. Three professionals earned our Lifetime Achievement Award: Elliot Masie, Kevin Oakes and Joe DiDonato. We are honored to feature all 28 thought leaders, trail blazers, innovators, mentors, and high performers inside (see article 2017 Learning! Champion Awards). You will hear from these champions across the year via articles, conferences, Web seminars and blogs. The 2016 Learning! Champion, Dr. Christopher L. Washington, shares his article titled “The Evolution of E-learning and Learning Analytics” on article The Evolution of E-learning and Learning Analytics  .

Thank you to all the learning professionals, technologists and colleagues who continue to advance learning everywhere.

Let’s keep learning!

—Catherine Upton, Group Publisher

Published in Ideas

Every day the enterprise learning ecosystem becomes more complex making a few questions even more important for learning and development leaders. What is the current state of the training function in your organization large or small? How do you evaluate the effectiveness of your training?

Only 8% of CEO’s in LinkedIn’s 2017 Workplace Learning Report say they can see a measurable impact from their company’s Learning and Development. These CEO’s are getting quantifiable activity data from other business functions, so why not L&D?

Chances are, your learning has now spilled out of the confines of an LMS, and touches a TMS, HRIS etc. You may have many of these systems in your organization along with new 3rd party providers, self-directed learning, or apps and portals available to your learners. You are probably spending L&D budget on micro-learning, self- paced learning, gamification, mobile, and more. Surveying aside, how effective are those new initiatives and training techniques? Are you able to track anything more than completions? Are you even able to track completions?

The first step to providing measurable impact is to baseline the effectiveness of your current training by getting better interaction data wherever learning occurs. You can baseline ALL of your current training across multiple learning technologies and you can start today.

It is relatively easy to get all of your training initiatives reporting better learning activity data in the form of Experience API (xAPI) activity streams to a Learning Record Store (LRS). Think of xAPI as a digital mesh that will get all of your proprietary learning technologies talking in the same analytics language. You can mine xAPI activity streams for patterns and react to them. You can keep your LRS data totally anonymous if you would like. xAPI is also technology agnostic so when you add new technologies or remove technologies within your ecosystem it is non- disruptive to your learning activity reporting. But most importantly, an LRS will provide you the learner activity data for formative and summative evaluation.

BENEFITS OF LRS:

1. Baseline your current training with better evaluation data.

2. Begin to build learner competency and performance profiles.

3.  The proper implementation of xAPI/LRS is the first step toward:

  1. Intelligent/Automated Tutoring
  2. Adaptive Learning
  3. Predictive Analysis
  4. Sustainment and Improvement of Training Systems

 

The path to modern training technology and the future of learning starts with xAPI and the implementation of a Learning Record Store. At Riptide, we have been working and engineering learning technology using xAPI since just after it’s inception. Before it was even called xAPI we were generating activity streams to early versions of our LRS, which is now our Storepoints LRS product. We are on the workgroup that created xAPI 1.0 and we are working with it daily.

Interested in learning more on how a Learning Record Store would work within your unique learning ecosystem? Visit www.RiptideLearning.com and request a free consultation today!

—Nick Washburn is Director of Learning at Riptide Software. Contact him at This email address is being protected from spambots. You need JavaScript enabled to view it.

Published in Ideas
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