The corporate training market, which is over $130 billion in size, is about to be disrupted. Companies are starting to move away from their Learning Management Systems (LMS), buy all sorts of new tools for digital learning, and rebuild a whole new infrastructure to help employees learn. And the impact of GSuite, Microsoft Teams, Slack, and Workplace by Facebook could be enormous.
The corporate L&D market has been through wrenching change over the last decade. In only 15 years we’ve come from long, page-turning courses to a wide variety of videos, small micro-learning experiences, mobile apps, and intelligent, adaptive learning platforms.
A new marketplace of tools vendors has emerged, most less than five years old, each trying to stake out a new place in the landscape. These includes tools for external content curation, tools to build MOOCs internally, tools to deliver adaptive, micro-learning content, and intelligent tools to help recommend content, assess learning, practice and identify skills gaps.
We know employees badly need these kinds of tools. Employees are pretty overwhelmed at work ,and typically only have 20 minutes a week to set aside for learning. So rather than produce two to three hour “courses” that require page-turning and slow video or animation, we need to offer “learning on-demand” and recommended content just as needed.
These changes will disrupt and change the $4 billion-plus for corporate learning management systems (LMS). Companies like IBM, Sears, and Visa are starting to turn off their old systems and build a new generation of learning infrastructure that looks more like a “learning network” and less like a single integrated platform.
The key campus tech issues are no longer about IT (in the past e.g.: MS versus Apple). IT is the “easy part” of technology on campus. The challenges: people, planning policy, programs, priorities, silos, egos, and IT entitlements
How do we make Digital Learning compelling and safe for the faculty? provide evidence of impact, support, recognition and reward for faculty; communicate about effectiveness of and need for IT resources.
technology is not capital cost, it is operational cost. reoccurring.
underlying issues; can i do this? why should i do this? evidence of benefit?
the more things change, the more things stay the same. new equilibrium.
change: from what did you do wrong to how do we do better. Use data as a resources, not as a weapon. there is a fear of trying, because there is no recognition or reward
Machiavelli: 1. concentrate your efforts 2. pick your issues carefully, know when to fight 3. know the history 4. build coalitions 5. set modest goals – and realistic 6. leverage the value of data (use it as resource not weapon) 7. anticipate personnel turnover 8. set deadlines for decisions
We apologize for the short notice, but wanted to make you aware of the following opportunity: provide
From Ken Graetz at Winona State University:
As part of our Digital Faculty Fellows Program at WSU, Dr. Kenneth C. Green will be speaking this Thursday, March 22nd in Stark 103 Miller Auditorium from 11:30 to 12:30 on “Innovation, Infrastructure, and Digital Learning.” We will be streaming Casey’s talk using Skype Meeting Broadcast and you can join as a guest using the following link: Join the presentation. This will allow you to see and hear his presentation, as well as post moderated questions. By way of a teaser, here is a recent quote from Dr. Green’s blog, DigitalTweed, published by Inside Higher Ed:
“If trustees, presidents, provosts, deans, and department chairs really want to address the fear of trying and foster innovation in instruction, then they have to recognize that infrastructure fosters innovation. And infrastructure, in the context of technology and instruction, involves more than just computer hardware, software, digital projectors in classrooms, learning management systems, and campus web sites. The technology is actually the easy part. The real challenges involve a commitment to research about the impact of innovation in instruction, and recognition and reward for those faculty who would like to pursue innovation in their instructional activities.”
Dr. Green is the founding director of The Campus Computing Project, the largest continuing study of the role of digital learning and information technology in American colleges and universities. Campus Computing is widely cited as a definitive source for data, information, and insight about IT planning and policy issues affecting higher education. Dr. Green also serves as the director, moderator, and co-producer of TO A DEGREE, the postsecondary success podcast of the Bill & Melinda Gates Foundation. He is the author or editor of some 20 books and published research reports and more than 100 articles and commentaries that have appeared in academic journals and professional publications. In 2002, Dr. Green received the first EDUCAUSE Award for Leadership in Public Policy and Practice. The EDUCAUSE award cites his work in creating The Campus Computing Project and recognizes his, “prominence in the arena of national and international technology agendas, and the linking of higher education to those agendas.”
special guest Steven Bell, Associate Librarian at Temple University Libraries
Tuesday, February 27 when the #DLNchatcommunity got together to discuss: What Is the Role of Libraries in Digital Learning Innovation?
“it will definitely be a more sustainable initiative if it is collaborative—-whether it’s OER, open access journals, etc…if the library wants to go alone it will go fast but if it goes with others it will go much further.”
The #DLNchat community concurred there are ample opportunities for library-led collaborations in digital learning across campus. “Curation is key
OER = “Faculty + Librarians + Digital Media Experts = Engaging Content 4 learners.”
considering exactly that-how to create “librarians on demand” to meet students and faculty in dining halls, coffee shops, study lounges or wherever they may be conducting their scholarly work.
a learning management system (LMS) is never the solution to every problem in education. Edtech is just one part of the whole learning ecosystem and student experience.
Therefore, the next generation digital learning environment (NGDLE), as envisioned by EDUCAUSE in 2015 … Looking at the NGDLE requirements from an LMS perspective, I view the NGDLE as being about five areas: interoperability; personalization; analytics, advising, and learning assessment; collaboration; accessibility and universal design.
Content can easily be exchanged between systems.
Users are able to leverage the tools they love, including discipline-specific apps.
Learning data is available to trusted systems and people who need it.
The learning environment is “future proof” so that it can adapt and extend as the ecosystem evolves.
The learning environment reflects individual preferences.
Departments, divisions, and institutions can be autonomous.
Instructors teach the way they want and are not constrained by the software design.
There are clear, individual learning paths.
Students have choice in activity, expression, and engagement.
Analytics, Advising, and Learning Assessment
Learning analytics helps to identify at-risk students, course progress, and adaptive learning pathways.
The learning environment enables integrated planning and assessment of student performance.
More data is made available, with greater context around the data.
The learning environment supports platform and data standards.
Individual spaces persist after courses and after graduation.
Learners are encouraged as creators and consumers.
Courses include public and private spaces.
Accessibility and Universal Design
Accessibility is part of the design of the learning experience.
The learning environment enables adaptive learning and supports different types of materials.
Learning design includes measurement rubrics and quality control.
The core analogy used in the NGDLE paper is that each component of the learning environment is a Lego brick:
The days of the LMS as a “walled garden” app that does everything is over.
Today many kinds of amazing learning and collaboration tools (Lego bricks) should be accessible to educators.
We have standards that let these tools (including an LMS) talk to each other. That is, all bricks share some properties that let them fit together.
Students and teachers sign in once to this “ecosystem of bricks.”
The bricks share results and data.
These bricks fit together; they can be interchanged and swapped at will, with confidence that the learning experience will continue uninterrupted.
Any “next-gen” attempt to completely rework the pedagogical model and introduce a “mash-up of whatever” to fulfil this model would fall victim to the same criticisms levied at the LMS today: there is too little time and training to expect faculty to figure out the nuances of implementation on their own.
The Lego metaphor works only if we’re talking about “old school” Lego design — bricks of two, three, and four-post pieces that neatly fit together. Modern edtech is a lot more like the modern Lego. There are wheels and rocket launchers and belts and all kinds of amazing pieces that work well with each other, but only when they are configured properly. A user cannot simply stick together different pieces and assume they will work harmoniously in creating an environment through which each student can be successful.
As the NGDLE paper states: “Despite the high percentages of LMS adoption, relatively few instructors use its more advanced features — just 41% of faculty surveyed report using the LMS ‘to promote interaction outside the classroom.'”
But this is what the next generation LMS is good at: being a central nervous system — or learning hub — through which a variety of learning activities and tools are used. This is also where the LMS needs to go: bringing together and making sense of all the amazing innovations happening around it. This is much harder to do, perhaps even impossible, if all the pieces involved are just bricks without anything to orchestrate them or to weave them together into a meaningful, personal experience for achieving well-defined learning outcomes.
Making a commitment to build easy, flexible, and smart technology
Working with colleges and universities to remove barriers to adopting new tools in the ecosystem
Standardizing the vetting of accessibility compliance (the Strategic Nonvisual Access Partner Program from the National Federation of the Blind is a great start)
Advancing standards for data exchange while protecting individual privacy
Building integrated components that work with the institutions using them — learning quickly about what is and is not working well and applying those lessons to the next generation of interoperability standards
Letting people use the tools they love [SIC] and providing more ways for nontechnical individuals (including students) to easily integrate new features into learning activities
My note: something just refused to be accepted at SCSU
Technologists are often very focused on the technology, but the reality is that the more deeply and closely we understand the pedagogy and the people in the institutions — students, faculty, instructional support staff, administrators — the better suited we are to actually making the tech work for them.
Under the Hood of a Next Generation Digital Learning Environment in Progress
The challenge is that although 85 percent of faculty use a campus learning management system (LMS),1 a recent Blackboard report found that, out of 70,000 courses across 927 North American institutions, 53 percent of LMS usage was classified as supplemental(content-heavy, low interaction) and 24 percent as complementary (one-way communication via content/announcements/gradebook).2 Only 11 percent were characterized as social, 10 percent as evaluative (heavy use of assessment), and 2 percent as holistic (balanced use of all previous). Our FYE course required innovating beyond the supplemental course-level LMS to create a more holistic cohort-wide NGDLE in order to fully support the teaching, learning, and student success missions of the program.The key design goals for our NGDLE were to:
Create a common platform that could deliver a standard curriculum and achieve parity in all course sections using existing systems and tools and readily available content
Capture, store, and analyze any generated learner data to support learning assessment, continuous program improvement, and research
Develop reports and actionable analytics for administrators, advisors, instructors, and students
These gaps and others “suggest a disconnect, the report stated, “between the impacts that many administrators perceive and the reality of how digital learning is changing the market.” Open-ended responses suggested that expectations for the impact of digital learning were “set too high” or weren’t being “measured or communicated well.” Another common refrain: There’s inadequate institutional support.
While most administrators told researchers that “faculty are crucial to the success of digital learning initiatives — serving as both a bolster and a barrier to implementation success,” the resources for supporting faculty to implement digital learning are insufficient. Just a quarter of respondents said faculty professional development was implemented “effectively and at scale.” Thirty-five percent said implementation was in progress. And a third (33 percent) reported that faculty professional development was “incomplete, inconsistent, informal and/or optional.”
The report offered recommendations for improving and expanding digital learning adoption. Among the guidance:
Get realistic. While the data suggested that digital learning could improve scheduling flexibility and access, among other benefits, schools need to identify which goals are most important and “clearly articulate how and to what extent its digital learning programs are expected to help.”
Measure impact and broadcast it. Forget about small pilots; go for a scale that will demonstrate impact and then share the findings internally and with other institutions.
Use buying power to influence the market. Connect faculty with vendors for “education, product discovery and feedback.” Insist on accessibility within products, strong integration features and user friendliness.
Prepare faculty for success. Make sure there are sufficient resources and incentives to help faculty “buy into the strategy” and follow through on implementation.
meetings with Chief Learning Officers, talent management leaders, and vendors of next generation learning tools.
The corporate L&D industry is over $140 billion in size, and it crosses over into the $300 billion marketplace for college degrees, professional development, and secondary education around the world.
Digital Learning does not mean learning on your phone, it means “bringing learning to where employees are.” In other words, this new era is not only a shift in tools, it’s a shift toward employee-centric design. Shifting from “instructional design” to “experience design” and using design thinking are key here.
1) The traditional LMS is no longer the center of corporate learning, and it’s starting to go away.
LMS platforms were designed around the traditional content model, using a 17 year old standard called SCORM. SCORM is a technology developed in the 1980s, originally intended to help companies like track training records from their CD-ROM based training programs.
the paradigm that we built was focused on the idea of a “course catalog,” an artifact that makes sense for formal education, but no longer feels relevant for much of our learning today.
not saying the $4 billion LMS market is dead, but the center or action has moved (ie. their cheese has been moved). Today’s LMS is much more of a compliance management system, serving as a platform for record-keeping, and this function can now be replaced by new technologies.
We have come from a world of CD ROMs to online courseware (early 2000s) to an explosion of video and instructional content (YouTube and MOOCs in the last five years), to a new world of always-on, machine-curated content of all shapes and sizes. The LMS, which was largely architected in the early 2000s, simply has not kept up effectively.
2) The emergence of the X-API makes everything we do part of learning.
In the days of SCORM (the technology developed by Boeing in the 1980s to track CD Roms) we could only really track what you did in a traditional or e-learning course. Today all these other activities are trackable using the X-API (also called Tin Can or the Experience API). So just like Google and Facebook can track your activities on websites and your browser can track your clicks on your PC or phone, the X-API lets products like the learning record store keep track of all your digital activities at work.
3) As content grows in volume, it is falling into two categories: micro-learning and macro-learning.
4) Work Has Changed, Driving The Need for Continuous Learning
Why is all the micro learning content so important? Quite simply because the way we work has radically changed. We spend an inordinate amount of time looking for information at work, and we are constantly bombarded by distractions, messages, and emails.
5) Spaced Learning Has Arrived
If we consider the new world of content (micro and macro), how do we build an architecture that teaches people what to use when? Can we make it easier and avoid all this searching?
Neurological research has proved that we don’t learn well through “binge education” like a course. We learn by being exposed to new skills and ideas over time, with spacing and questioning in between. Studies have shown that students who cram for final exams lose much of their memory within a few weeks, yet students who learn slowly with continuous reinforcement can capture skills and knowledge for decades.
6) A New Learning Architecture Has Emerged: With New Vendors To Consider
One of the keys to digital learning is building a new learning architecture. This means using the LMS as a “player” but not the “center,” and looking at a range of new tools and systems to bring content together.
On the upper left is a relatively new breed of vendors, including companies like Degreed, EdCast, Pathgather, Jam, Fuse, and others, that serve as “learning experience” platforms. They aggregate, curate, and add intelligence to content, without specifically storing content or authoring in any way. In a sense they develop a “learning experience,” and they are all modeled after magazine-like interfaces that enables users to browse, read, consume, and rate content.
The second category the “program experience platforms” or “learning delivery systems.” These companies, which include vendors like NovoEd, EdX, Intrepid, Everwise, and many others (including many LMS vendors), help you build a traditional learning “program” in an open and easy way. They offer pathways, chapters, social features, and features for assessment, scoring, and instructor interaction. While many of these features belong in an LMS, these systems are built in a modern cloud architecture, and they are effective for programs like sales training, executive development, onboarding, and more. In many ways you can consider them “open MOOC platforms” that let you build your own MOOCs.
The third category at the top I call “micro-learning platforms” or “adaptive learning platforms.” These are systems that operate more like intelligent, learning-centric content management systems that help you take lots of content, arrange it into micro-learning pathways and programs, and serve it up to learners at just the right time. Qstream, for example, has focused initially on sales training – and clients tell me it is useful at using spaced learning to help sales people stay up to speed (they are also entering the market for management development). Axonify is a fast-growing vendor that serves many markets, including safety training and compliance training, where people are reminded of important practices on a regular basis, and learning is assessed and tracked. Vendors in this category, again, offer LMS-like functionality, but in a way that tends to be far more useful and modern than traditional LMS systems. And I expect many others to enter this space.
Perhaps the most exciting part of tools today is the growth of AI and machine-learning systems, as well as the huge potential for virtual reality.
7) Traditional Coaching, Training, and Culture of Learning Has Not Gone Away
8) A New Business Model for Learning
he days of spending millions of dollars on learning platforms is starting to come to an end. We do have to make strategic decisions about what vendors to select, but given the rapid and immature state of the market, I would warn against spending too much money on any one vendor at a time. The market has yet to shake out, and many of these vendors could go out of business, be acquired, or simply become irrelevant in 3-5 years.
9) The Impact of Microsoft, Google, Facebook, and Slack Is Coming
The newest versions of Microsoft Teams, Google Hangouts and Google Drive, Workplace by Facebook, Slack, and other enterprise IT products now give employees the opportunity to share content, view videos, and find context-relevant documents in the flow of their daily work.
We can imagine that Microsoft’s acquisition of LinkedIn will result in some integration of Lynda.com content in the flow of work. (Imagine if you are trying to build a spreadsheet and a relevant Lynda course opens up). This is an example of “delivering learning to where people are.”
10) A new set of skills and capabilities in L&D
It’s no longer enough to consider yourself a “trainer” or “instructional designer” by career. While instructional design continues to play a role, we now need L&D to focus on “experience design,” “design thinking,” the development of “employee journey maps,” and much more experimental, data-driven, solutions in the flow of work.
lmost all the companies are now teaching themselves design thinking, they are using MVP (minimal viable product) approaches to new solutions, and they are focusing on understanding and addressing the “employee experience,” rather than just injecting new training programs into the company.
Todd Rose, the director of the Mind, Brain, and Education program at the Harvard Graduate School of Education, has emerged as a central intellectual figure behind the movement. In particular, his 2016 book, “The End of Average,” is seen as an important justification for and guide to the personalization of learning.
what Rose argues against. He holds that our culture is obsessed with measuring and finding averages—averages of human ability and averages of the human body. Sometimes the average is held to be the ideal.
The jaggedness principle means that many of the attributes we care about are multi-faceted, not of a whole. For example, human ability is not one thing, so it doesn’t make sense to talk about someone as “smart” or “dumb.” That’s unidimensional. Someone might be very good with numbers, very bad with words, about average in using space, and gifted in using of visual imagery.
Since the 1930s, psychologists have debated whether intelligence is best characterized as one thing or many.
But most psychologists stopped playing this game in the 1990s. The resolution came through the work of John Carroll, who developed a third model in which abilities form a hierarchy. We can think of abilities as separate, but nested in higher-order abilities. Hence, there is a general, all-purpose intelligence, and it influences other abilities, so they are correlated. But the abilities nested within general intelligence are independent, so the correlations are modest. Thus, Rose’s jaggedness principle is certainly not new to psychology, and it’s incomplete.
The second (Context Principle) of Rose’s principles holds that personality traits don’t exist, and there’s a similar problem with this claim: Rose describes a concept with limited predictive power as having none at all. The most commonly accepted theory holds that personality can be described by variation on five dimensions
Rose’s third principle (pathways principle) suggests that there are multiple ways to reach a goal like walking or reading, and that there is not a fixed set of stages through which each of us passes.
Rose thinks students should earn credentials, not diplomas. In other words, a school would not certify that you’re “educated in computer science” but that you have specific knowledge and skills—that you can program games on handheld devices, for example. He think grades should be replaced by testaments of competency (my note: badges); the school affirms that you’ve mastered the skills and knowledge, period. Finally, Rose argues that students should have more flexibility in choosing their educational pathways.
Digital tools can transform, not just replicate, the teaching and learning experience
Commentary: The Substitution Augmentation Modification Redefinition Model (SAMR) and the Technological Pedagogical Content Knowledge (TPACK) models of technology implementation can help schools as they transition to using more digital tools.
Call for Papers The Journal of Emerging Learning Design special issue: The Digital Humanities
Submissions due date
On/before November 14, 2016.
Editors Jerry Alan Fails (Boise State University) and AJ Kelton (Montclair State University)
Introduction The Journal of Emerging Learning Design is pleased to announce the Call for Papers for its first Special Issue: The Digital Humanities.
With roots reaching back as far as 1940, the term Digital Humanities came into wide usage in late 2012 and has slowly risen in popularity since then. A Google Scholar search for “digital humanities” yields just under 30 results during the year 2000 and over 4,700 during 2015. The increase in the number of published articles in 15 years is second only to the diversity of the research that is included.
About the ELDj
The Journal of Emerging Learning Design (ELDj) is an open access, peer-reviewed, online journal that provides a platform for academics and practitioners to explore emerging learning design theories, concepts, and issues and their implications at national and international levels.
An outgrowth of the annual Emerging Learning Design Conference, which makes its home at Montclair State University (MSU), the ELDj invites scholarly communication in the emerging learning design field and will present best practices in design and implementation by offering articles that present, propose, or review engaging and dynamic approaches to pedagogy and how technology can better enhance it.
The ELDj has purposefully kept the focus of the theme for this special issue broad. The intent is to continue to break down traditional academic silos and allow for an open dialogue and sharing with respect to what is considered the Digital Humanities. ELDj is intentionally taking a broad consideration for what is included in the digital humanities with the clear understanding that this issue, and the articles within, will contribute to this growing field and provide a groundwork for further reflection and research.
Deadline for Submission: November 14, 2016
Notification of Acceptance: March 1st, 2017
Final Revised Submission: April 21, 2017
Publication: June 2, 2017
Publication and Presentation
The issue will be published prior to, and featured at, the 7th Annual Emerging Learning Design Conference (ELDc17) on June 2nd, 2017.
Based on when a submission is accepted, authors may be offered the opportunity to present their research at the 7th Annual Emerging Learning Design Conference in June, 2017. Presentations must be given in an appropriate presentation format for the conference: panel (full conference audience), workshop (120 minutes), concurrent (45 minutes), or Sparks! (5 minutes to full conference audience).
Manuscripts should be the appropriate length for the material being presented.
Full paper manuscripts can vary from 2500-4500 words in addition to an abstract of 250 words and a works cited section of appropriate length.
Briefs or Trends papers have a limit of 1000 words.
A description of each type of submission and guidelines can be found at http://eldj.montclair.edu/submission-guidelines/ELDj uses a double-blind, peer-review process. Submissions should not have been published previously or be under consideration for publication elsewhere. Authors should review the above linked guidelines for important and relevant information.
Submissions should be sent to email@example.com: questions and information requests may be sent to the Editors at the same address.
more on digital humanities and publications for digital humanities in this IMS blog
The Conference at Notre Dame May 12-13 is intriguing as you can see from some of the session titles below. It’s time to register and book lodging.
How do we know they are learning? Digital Evidence of and for Learning
Peruse the titles below to get an idea of the dynamism of this eportfolio conference:
Balancing Summative, Formative, and Transformative ePortfolio Functions within Participatory Learning and Assessment
Competency Based Badging and ePortfolios for the Youth and Adult Workforce in Philadelphia
Show your SPuRS: Bridging Academics and Co-Curricular Professional Readiness
Buckeye Badges: A Pilot Project at Ohio State University
Developing an Integrative Toolkit for Engagement at Michigan (iTeam)
Ethics, ePortfolios, and Badges: Envisaging Privacy and Digital Persistence in Student-Level Learning Evidence
Balancing Summative, Formative, and Transformative ePortfolio Functions within Participatory Learning and Assessment
Plus 15 other sessions.
The keynote address will be given by Daniel T. Hickey on Open Digital Badges + ePortfolios: Searching for and Supporting Synergy. an internationally-known speaker and leader on the changes in higher education around digital technologies.
Here is a description of another session:
By sharing challenges, practices, and examples of maker portfolios, we highlight the importance of makerspaces and community development in the design of portfolios that capture rich learning.
These are the institutions represented in the program:
Grand Valley State University
Rose-Hulman Institute of Technology
University of Michigan
Ohio State University
Kendall College; Laureate Universities
Western Michigan University
University of Charleston
The full program will be posted by late Thursday of this week. This is a must-attend event to know about the latest developments in the eportfolio field.
Registration rates (note that AAEEBL members receive a $100 discount on registration; a student rate is available as well):
$250 before April 25
$290 after April 25
$150 before Aprial 25
$190 after April 25
$75 before Aprial 25
$115 after April 25
Includes 2 breakfasts, one lunch and one reception. One and a half days of sessions.
Register now. Book lodging. Notre Dame is just outside of Chicago in Northern Indiana. Midway Airport is probably the closest major airport to the Notre Dame campus. Conference facilities at Notre Dame are excellent — lodging and conference space are adjacent.
More on badges in this IMS blog: