CORPORATE INSTRUCTION IS STILL DISCONNECTED FROM MILLENNIAL LEARNING STYLES – A LIST BASED ON OBSERVATIONS IN THE WORKPLACE

By this time we all know the tropes that define who millennials (M) are, how they act and their fundamental personality characteristics. You’d think with all of this proven—and nowhere is it more evident than in large corporations—that learning programs would have been adjusted to align instruction with M proclivities for workplace education.

Having just spent some time at an F100 company I can affirm with great certainty, most instruction is still a series of bland courses and in some cases long and winding webinars. It bears remembering we are in business of transmitting only three things: knowledge, skills, and behaviors. I saw few instances where any modifications to training accommodated the ways in which young employees would spark to, tolerate, let alone benefit from anything being taught unless it was compulsory. And of course, pushing training down to a M will just shut down their attention. So, with a grudging acceptance of what had to be learned, skills absorbed only if they had immediate utility, and behaviors, well…let’s just say the millennials I was working with and around were not among the receptive.

You can refer to two articles I had written back in 2014 about multi-generational learning and see even then, there was a clear rubric and tactics for reaching millennials. Unfortunately, making a case to adjust corporate learning programs and actually rewriting and modifying delivery are at polar ends and still out in the frozen tundra. [Overcoming Generation Differences When Building Learning: Part 2

NOW EVERYONE WINS: OVERCOMING GENERATION DIFFERENCES WHEN BUILDING LEARNING]

So, what to do. CLO’s it seems, unless really enlightened, have not passed down by policy the need to make learning aligned to what will soon be their largest contingent (25%) of employees. The company I just left dictated to the CLO that webinars would be the mode of choice for sales enablement and product knowledge – and they were level set to be 60-90 minutes. For sales staff! A double whammy there, right? A young millennial in sales is being taught essentially in the exact opposite learning style that would yield useful results.

A LIST OF WHAT MIGHT ATTRACT AND DELIVER USEFUL LEARNING TO MILLENIALS

1. Learning has to be in small bits and any of these learning elements I’ll mention need not be delivered in any particular order– but they will be repeated in what I call a multi-touch ecology. Hyperconnectivity is baked in to millennials as is multitasking. Millennials are 2.5 times more likely to embrace and use new technology. This approach has elements of microlearning but it benefits the learner because it is repeated in other modalities & technologies.
   • For instance, in a short form course, organizations might deliver one or two elements of knowledge, skills or behaviors, make it interactive and/or with gamification and require responses. Consider collaboration within the methodology. Those responses are recorded and then the course is revisited for learners to rectify any incorrect responses. Nothing radical here except for the amount of time on learning – short attention spans will be honored.

2. Learning with multi-modal exposure. Consider the power of a short, sharp podcast (or many) accessed and aligned to courseware – further amplifying recently introduced content.
   1. Questions posed in the podcast might be pushed out to mobile devices where, once again responses would be entered and tabulated.

3. We’ve just laid out three modes: a short course, a podcast, and mobile learning. Let’s not forget dedicated pages on Facebook for content, polling and collaboration, and Twitter or SnapChat for instant feedback. Short videos right off Smartphones – 10 seconds worth – carry incredible power to influence, to convince, to give testimony. New tech must serve the learning purpose and be considered ‘cool.’ Finally, a mentor or coach would have the opportunity to not only work with the individual millennial but also learn what modalities worked best – and what components of this ecology yielded both cognitive results and emotional commitment. Multiple touches of the same knowledge, skills and behaviors are vital to retention and even more so for sales staff.

4. These elements have all the benefits of autonomous learning, can be collaborative if so designed and tend to be informal. All three criteria are in the personality set of younger employees.

Multiple touches—that is delivering the same content over different methodologies and modalities are essential for millennials. Learning is short – but repeated with multiple touches

1. Learning can be collaborative
2. Learning is couched inside compelling technologies
3. Learning is interactive
4. Learning is delivered on demand
5. Learning is multi-modal
6. Learning has digital with human feedback
7. Learning is autonomous
8. Learning content while repetitious is tolerable with multiple modalities
9. Learning with multiple touches will be the norm
10. Learning will be put to use because it happens over time – not a one sitting – therefore it will always be top of mind

As I looked around the work floor, I noted my millennial colleagues who, to a person were hard working, committed and extraordinarily helpful to an older geezer like me. Nevertheless, they also shared the frustrations they had with long, drawn out courses, for instance during onboarding, that might have been produced in 1999. That’s no way to motivate people who come predisposed to do good work. When learning is delivered to their particular learning characteristics, they become empowered, more loyal and see the corporate culture as honoring their personal temperament. That’s a lot of big wins. It’s up to the corporate masters to commit to modify learning, reach, and reach out to the millions of new workers whom they will be leading and managing now and more so, in the very near future.

Learning Design: The Great, The Good and The Good Enough

This could be a story about buggy whips. You might know the classic management tale of the craftsman who was proud of building the most handsome and useful whips to spur on carriage horses at the turn of the last century. Unfortunately, as you you probably know the tale, carriages once replaced by the automobile rendered his lovely product useless.

I have watched from the trenches and sidelines as classes of learning professionals are now being divided —again by technology into two camps; those who know how learning should be constructed and craft it and those who can manufacture, at time and cost savings, the actual product.

Learning designers strategize how to solve problems to achieve performance improvement applying theory to fact and constructing course elements, flows and production processes. They gain agreement with stakeholders about content, audience, time on learning and assessment and the larger components of an experience. They scaffold the project so each step falls into place in a logical progression. In some cases, the learning designer will offer a narrative reflecting the content back to the stakeholders to ensure the critical content is captured. Additionally they might also write the actual storyboard incorporating the elements including the interactive and experiential (as well as social) elements that will make the course interesting if not compelling. The best and greatest courseware, the most inventive and exciting depends on a designer who can sculpt content into a story, then work with an interactive and/or graphic designer to sharpen the user experience across multiple platforms finally passing the work to a developer to program—as designed—for implementation.

Developers are those folks who know how to use the tools chosen by the enterprise to express content online in an effective and dynamic format. For the past number of years, while learning theory and ideas about making courses exciting have evolved growing with the speed and bandwidth available for elements like video, developer tools have been refined exponentially. Think of the industrial model—build an assembly line, now improve the assembly line and the tools—then make better products. However, this works well only when everything being made is a replica set to standardized requirements. Learning is not like that. Even when producing multiple courses with similar content, the opportunity to breathe excitement into each one is more present when designers do what they do best and developers express it. No template, no matter how sophisticated can allow for all the shadings required by great learning. Instead developers take the tools and either use them out of the box or, as I saw in a number of organizations, create, and in most cases struggle to build work-arounds expressing the designers intent while trying for hours to keep within the constraints of the software. An entire industry has been built around PowerPoint (by example) as the foundation for programs like Articulate. And the tide is with them since money flows downhill from big corporate enterprises and their subordinate constituencies. Better, faster, cheaper. And good enough.

The precedent for this was the explosive improvement in desktop publishing more than a decade back; once an associate learned the software they could generate print materials. The problem—and the connection to the current argument, is simply that these folks were not trained as graphic designers. The results spoke for themselves; a lot of bad design, quickly produced and reproduced. Moreover, when it was accepted by many managers as ‘good enough’ the die was cast for the attitudes we see now in learning design and development.

Here lies the collision and connection: In the hopes that ‘rapid’ eLearning cannot only reduce the time to create courseware the tools, ever more nuanced, allow developers to become designers as well. It’s seductive; managers cut down head count, more work can be pushed out the door by learning groups under pressure to deliver fast changing content, and costs drop when the designer, a more highly trained, often senior and knowledgeable resource can be set aside or redeployed. I don’t believe there has been a study conducted on performance improvement or even a Kirkpatrick view of which types of courses yield intended results. But I do know anecdotally that learning designed courses, where each professional works to their strength always seem to have an A-ha factor. Most other courses—those of the template kind—are utilitarian and though they might satisfy the requirements or outcomes, learner satisfaction cannot compare. This is dangerous and grows more so every day as multi-generational learners want different kinds of learning experiences.

The facts are there is room at the learning table for both types of development. However, there is no real lobbying group or organized industry to support the learning designer model. My fear is that learning and instructional design preparation will move even further towards the industrial model, templatized learning produced by individuals whose preparation has introduced them to a fair amount about learning…and the skillsets demanded to operate the tools. Unfortunately, there is too much complexity and uniqueness in learning to allow for excellence when this mashup becomes the status quo.

Those of us who have grown up in the era of learning design are more than ever segregated from access to development. Even with HTML5 used by great developers who can customize components to meet learning design objectives with wonderful precision, I see a rending of the system that will soon go the way of the buggy whip. So much of life today, from the professional sphere to just everyday life seems to be populated by people who figure that good enough is just that. Time is precious, financial strains are everywhere, the speed of life is overtaking the human ability to sustain its own sense of equilibrium in a world of instant everything. So let it go and accept the outlier will be the customization of learning only when absolutely defended by insistent clients with the budget and care to desire excellence. Otherwise, wait for tools to exhibit their next iteration, artificial intelligence.

 

Overcoming Generation Differences When Building Learning: Part 2

When we last visited this topic about a week back I promised to create a visual—a chart of sorts—to encourage learning and instructional designers to consider how generational bias in training delivery. Just looking to start a conversation.

A Quick Review
You might want to pop back to the original article: http://tiny.cc/qpsrax

We know we’re engaging three distinct groups in today’s workplace, Baby Boomers, Generation X, and Generation Y (Millenials). Each has specific preferences for general communication and they carry over in training as well. Whether creating a training program when all three groups are in the room or accessing courses online demands the learning designer incorporate specific ways of delivering information with the appropriate assets, techniques, and technologies. Initially, we would hope learners, right from the first word or screen, slide or handout, would buy-in and see value; a predisposition that his will be a good experience. During the training, we build formative experiences to keep all groups interested and motivated to continue, committed that the investment in time is worthwhile. Finally we would want participants to exit the training experience appreciating it was translatable into their work life. If this is accomplished, the next training experience will be viewed much more favorably and meet with less resistance.

Acknowledging their generational age, and considering their technological age (how savvy are they to tech) as well as comfort with social media, influences how they will respond to courseware. Though there are three distinct groups, many learners exhibit the preferences for learning outside the generational ‘norm’. These people are to be commended for either learning new technology, appreciating other ways of ‘seeing’ learning or just curious enough to drop a toe in the fast flowing stream of change. We need to depend on these folks to help convert those who tend to be inflexible.

Caveats abound:

• This is not a fully scientific approach nor based on academic, androgogical research
• It is the product of crowdsourcing, anecdotal research and discussion with hundreds of learning/instructional designers and clients not to mention intuition
• My professional experience over thousands of hours of course building across more than twenty verticals and five geos and over 25 years of design have informed these findings, too

I am fully prepared to hear from all quarters. It’s a living document—a work in progress— so send your ideas to rshadrin@wonderfulbrain.com. I’m hoping criticism will help improve this instrument not merely tell me where to get off or how narrow-minded, oblique or stupid this exercise is.

Anyway, someone had to put a stake in the ground. Apparently me. I hope it doesn’t end up in my heart.

Ultimately, the learning designer has to make everyone happy if information transfer is to take place. Elements that ‘favor’ one group more than another will always be necessary. If knowledge, skills and behaviors are to be transmitted, absorbed and used than instructional design should seek balance. Occasionally this compromise is not appreciated nor well tolerated across the generations. Nevertheless, it is absolutely necessary to honor each aspect of the generation’s learning preferences and mitigate those that irritate others. Skillful designers know how to navigate these choppy waters and subtle mixtures of learning preferences can always be developed. Can the design ever be perfect. Well, no. But reasonable learners in all generations can recognize when attempts are made to entice them into a learning experience. And the organization expects each generation, besides tolerance, adapt as necessary to improve performance and solve problems through learning and training experiences.

Big Data, Good Information and A Way For You To Use It

In this article I want to explore 3 connected ideas. The first is about big data, the phenomenon that now makes available enormous, staggering, volumes of information almost instantaneously. The second is a condition that says information already known to us can limit how big data can be used because there are other types of knowing to expand thinking. And the third idea is the sum of the first two: that the intersection of big data and a different way of seeing information means a model must be designed to utilize large amounts of validated information in a reasonable way.

So the era of big data is here. Imagine Niagara Falls and the millions of gallons of water that shoot over the precipice virtually every minute. That’s the scale of information we envision when thinking of the amount of data we can reach out and grab—or in some cases is pushed to us—everyday.  It would be impossible to know it all. But one benefit of massive volume is, when looked at through a certain lens, we have an opportunity to connect seemingly unrelated bits of data and discover trends, make predictions, even pre-position products and services long before we click, point or touch. It’s the compilation of colossal amounts of data that presents a challenge. How do we pluck just the right information we need from this torrent of bits?  This is the difficulty with information management in the era of big data; it’s like trying to take a sip from a fire hose. Our need is not to get information it’s how to get just the right content to help us work with more accurate and insightful facts and, smarter and faster?

Clearly then we see how working out a process to employ big data and make quality business decisions is difficult. Furthermore consider this context, our second condition:

“There are known knowns” began an answer to a question at a US Department of Defense News Briefing made by Donald Rumsfeld while serving as United States Secretary of Defense in February 2002. Actually, here’s the whole tortured phrase… “there are known knowns; there are things we know that we know. There are known unknowns; that is to say, there are things that we now know we don’t know. But there are also unknown unknowns – there are things we do not know we don’t know.” Though it may seem convoluted it is a “brilliant distillation of a quite complex matter,” said Mark Steyn, a Canadian columnist and echoed by many others, even legions of his detractors.

While good information on its own is valuable its utility when combined with other data to discover other, perhaps new data and still newer meanings is really profound. Sometimes the information is known and we need to fasten it in context, other times we don’t know there is… and what is…  trustworthy information but have to discover it; and more abstract yet, as unknowns the potential of useful but opaque information demands we peer into the future and ask ‘what if’ and proceed to manufacture information on (hopefully intelligent and intuitively perceptive) speculation.

If you’re in the business of solving problems—and who isn’t really—you’ll need an information life cycle model to regard big data and the ‘knowns issue’ to manage a collection of information for maximum use. And beware; too much data without vetting and affirmation, means you might miss the really important stuff, an effect that keeps security services awake at night. And therein lies the third concern of massive information management.

By summary then, we face three elements in our quest to make big data work for organizations:

1. Gathering information factoring the effect gained when combinations of content reveal even newer more, newer, meaningful data
2. Respecting knowns and unknowns as  fact and as potential ‘black swans’ (an unpredictable or unforeseen event, typically one with extreme consequences) that can and will skew results if not discovered prior or during information capture or application
3. Culling the really useful information or data—those bits directly related to the problem at hand—from the gargantuan amount of information flying about making it accessible, contextual and changeable.

Here’s a model than might help us slow down a bit, turn down the faucet and cull out know information and potentially new content when big data offers additional tonnage of content.

The flow chart illustrates how information would be categorically organized; a model for the standardization of an information life cycle in big data world.

Ultimately culling useful information from an almost limitless stream comes down to energy, resourcefulness and commitment. When building a learning course for example, your subject matter experts deliver very specific information as they must do. However, is there other data in text, as visuals, in video that might provide a different way to see the information? Clarifying content by shifting the context just a little bit can often shine a light into corners formerly unseen. Whether one has the time or inclination to make the effort to go shopping for more information is dependent on time and budget, yes, however, when looking to make learning better and richer, drinking from the stream is often a task worth enduring. Creating metaphors mined from a combination of newly discovered information can improve the user experience—and enjoyment—like spinning a kaleidoscope and seeing new patterns. Using a model such as the one proposed might make such an effort more reasonable.

5.1 Reasons How and Why to Build Learning with Social Media

Using social media (SM) to prepare material for instructional design, courseware and webinars and such is the flip side of the same coin that encourages social media as intake media.  We read a lot about using SM to learn, but how about to build?

Here are 5.1 reasons to build learning via SM.

1. A Social Collective

People learn best in a social context and are self-directed, particularly when focused on a specific task. Leveraging the collective intelligence of the group as they start producing information has never been easier with the portability, low threshold of technical savvy, and interconnectedness of these devices.

Therefore: Use small groups within the larger cohort to decide which content they should tackle and how to share their results.

2. Information for All on Demand

Build a place where information can be shared and critiqued – focusing on warehousing findings. This could be in the cloud, on a server or a Facebook page.  Point…since social media is an online ecology shouldn’t its construction be too?  The nature of this media also permits first person interview, audio, and video together with images that are as emotionally rich as cognitively necessary.

Therefore: Encourage saving and sharing discoveries, research and learning elements via Facebook by example, and tweet to instigate more ideas, even from outside the workgroup

3. Think Like a Designer  

When brainstorming their next auto, designers and engineers built huge concept boards on which anything related to the target audience for the vehicle is on public display.Everything of potential value, in any medium, should be posted in the project space even if it might bear the thinnest of relativities – someone might be tweaked into thinking differently.

Therefore: Practicing creativity and its principles must be part of course builders, and webinar maker’s toolsets.  Social media by its nature is a low key, playful environment providing the opportunities to express emotions to spur on a panoramic view of the problem/project easily refocusing as needed.

4. Communicate, then Synthesize Ideas

Communicate frequently with the group to help them synthesize information.  Stir the mix to change perspectives.  Use social media tools to communicate and report; and the leader can check the group’s progress by looking at metrics with tools (Social Oomph, etc.)

Therefore: Leadership/management plays a mentoring role – rather than command and control – social media is totally holistic.  A manager plays dual roles: to inspire and encourage, seeing the connections, guiding the research while attending to milestones and deadlines as an outcome, on deadline is expected.

5. Content Grows from Stories

Learn to build conversations that can morph into a big story.  This narrative, acquired from group work sourced far away from the cube farm must be organized to bridge the gap between the problem or project to be addressed and a method of delivering the required knowledge, skills, and behaviors.  At this point, anything not directly zeroed in on objectives is pushed off the side.

Therefore: The end result of the building phase is to generate the kind of accuracy that hits the objectives.  Learners will be guided through the course using all the opportunities brought about by social media for course production and learning involvement must be two sides of the same coin.

5.1 We are now capitalizing on the great enthusiasm for this wave of an ecology that could reinvent learning.

The hardware, software, connectivity already exists.  Already most people are up to or nearly up to speed and participating casually—and frequently.  No longer cut off from their colleagues with learners sequestered like monks, the potential for course builders is staggering.

Therefore we close the distance between those who make learning from those who take learning.

Whoever can exploit SM to build learning first will own the processes and methods to release education from a dark, complex, unrealistic environment into the sunshine of real life work.