In my days as a learning strategy consultant, I always began my discovery discussions with the question, “Do you have a training strategy?” Rarely did I receive a negative answer or a quizzical look; nor did I expect any. So, why ask a question when you already know the answer? Simple – it set up the next question that served as the real stimulus for conversation and meaningful discovery.

“Do you have a learning strategy?” Cue the quizzical looks of silent wondering if I had not just asked that question. Without waiting for an answer, I followed that question with an immediate third question.

“More importantly, do you have a continuous learning strategy?” At this point, I often saw the client’s eyes glaze over and a few even began to blow spit bubbles – a perfect response – and a perfect set-up to incite revolutionary thinking. Thinking had to be revolutionary to consider “continuous learning” as an acceptable shift worthy of breaking the traditional mindset of training. Training still plays a role, and always will, but as a subset of continuous learning, where the focus is on something very different – creation of sustained human capability.

Very often, my clients had a technology solution in mind and needed a consultant to validate their thinking … or worse … have someone to blame when it failed to deliver the desired results. This phenomenon is similar to our internal clients who have a training solution in mind before they contact the training department to validate their requested solution. We have perpetuated that thinking by responding as training order-takers. The age-old hammer and nail thinking, where organizations throw training at every performance gap, is a problem that we created – and it gets worse. If your organization has a learning management system (LMS), the bias affecting the ultimate solution may be even more locked-in than ever. The techno-zealots decree, “All training must reside on the LMS!” I think not, though I am a big fan of appropriately utilizing technology. It may sound like a contradiction for me to say this, but here goes – “Step away from the technology!”

That may sound extreme, but learners increasingly find the need to learn in the same environment where they work – their work context. In fact, the bulk of our learning environment continues to shift away from the classroom, away from formal training, and closer to the actual work performed. In a 2004 interview, Jonathon Levy, an e-Learning visionary, predicted: “Over the next 12-18 months, the end game will finally begin to come into view as traditional learning structures give way to more powerful performance support integration.” Integration into what? Into the work context!

Mr. Levy’s prediction implied we would not always be in the classroom when we learn. Instead, learning moments will increasingly confront our learners within workflows and processes. The need to learn becomes immediate, more urgent, and often encountered in a largely unstructured and uncontrolled context. This is a direct opposite to the stable realm of the formal classroom.

Again, in 2007, Mr. Levy confirmed this trend in a larger scope when he said, “Corporate universities will begin to question their positioning as a ’university,’ and some enlightened Chief Learning Officers (CLOs) will reject the academic model and begin to reposition themselves as performance support and change management specialists.” The references to performance support and change management in the same sentence denotes two major changes:

  • equipping learners to learn within their workflow (performance support); and
  • implementing holistic changes in learning methodologies necessary to drive sustainable capability (change management).

The flow of work, and the relentless demand for producing results, represents key drivers of the continuous learning environment. And, of course, most of the learning is occurring outside of the classroom. 

My purpose in this article is to introduce the necessity of expanded discovery as essential to defining critical, design-influencing attributes of a continuous learning environment. Forget defining knowledge and skill requirements, at least for now. The starting point, and the primary focus of this expanded discovery, is the environment where learners confront opportunities to learn. Learning opportunities span the whole spectrum from premeditated moments (for example, new employee orientation, or annual recertification training), to unplanned, unstructured, and uncontrolled moments, often manifested in the middle of a workflow.

Regardless of the end of the spectrum on which they arise, there are environmental attributes that can invalidate the best design efforts if not considered early in the design process. There are three categories of attributes within the learning environment:

  • Space – a blend of physical location, workflow, risk, and urgency
  • Media – the most compelling mix of mode and venue
  • Systems – the most effective and efficient application of technology

All the attributes that fall under space, media, and systems combine to drive or restrain design decisions. It is essential to define these attributes to ensure the learning solution delivers on one global objective, which is to enable a sustained capability.

Traditional design practices do not typically consider these elements during discovery (also known as the training needs assessment). In many cases, the ability to accomplish this degree of discovery represents a competency gap within the training organization. Recall Jonathon Levy’s 2007 prediction that describes the shift to performance support. That shift centers around the learners in their work context, with the focus zeroed in on sustainable performance and outcomes.

To produce an outcome, the learner must “do” something, not just “know” something. Once more, we exceed the tenets of knowledge and skills found at the root of traditional training design. It may sound as though Instructional Systems Design (ISD) methodology is getting a bad rap. Far from it! My team uses it daily to design solutions to improve performance. The difference now is the starting point of our discovery efforts:

  • Identify the performance outcomes to be produced, and
  • The work context where the learner produces them.

It is within the work context where the moments of learning need take shape. Keep in mind, individualized learning moments reflect upon the level of knowledge, skill, and capability of the learner. Permit me to add some contextual definition around some of the jargon I have thrown your way, and then we can dig into the discovery components. Let us begin with the moments of learning need.

The five moments of learning need

Learning moments are those snippets in time where capability and competency must simultaneously co-exist to produce sustainable outcomes. Unfortunately, my learning moments will be different from yours, as will yours be different from the next learner’s moment. Safe to say then, these individualized learning moments make a one-size-fits-all learning solution impossible, if not obsolete. Not only are learning solutions impacted by the environment, they are impacted by the capability of the learner. The concept of individualized needs alone takes us well beyond the limits of traditional, linear training design models.

Individualized learning moments are as continuous as the work performed. As such, we face a non-standard set of variables that drive training design decisions. Where the learner stands on their path from novice to mastery-level competency influences the frequency and depth of learning support required to complete a task. Likewise, their degree of competency affects which learning moment will arise, and when. Conrad Gottfredson has identified five moments of learning need:

  1. Learning something new or for the first time
  2. Learning more of something
  3. Trying to remember something
  4. Adjusting performance/behavior because something has changed
  5. Figuring out what to do when something goes wrong or fails

Any learning solution we create must consider the work environment within which the learners confront their moment(s) of learning need. Additionally, since continuous learning is an on-going process, the learner could transition through several, if not all, of the five moments of need on their path to competency. Odds are increasingly good that several of those moments are going to occur in the middle of a workflow, not in a classroom.

Different learning solutions will likely be required to satisfy the variability of learning moments. It follows then that our design methodology must be holistic enough to anticipate that variability. Based on when and where learning moments arise, the mix of attributes related to space, media, and systems may also differ. This simple fact, that when and where matter, implies the existence of timelines. This makes sense when we join time to the learners’ path to competency, that is, their learning continuum. Hence, accurate discovery must include the space, media, and systems attributes of a learning environment, as well as the learner’s location along the learning continuum.

An iterative model for the learning continuum: PD&R

Learning moments are as unique as the learners who must overcome them as they progress along the learning curve from novice to mastery levels of competency. Since work is continuous, why would learning to perform that work not be continuous as well? In a continuous learning environment, each learner will follow an individualized learning continuum that overlaps with the actual work and tasks accomplished. This learning continuum is discrete for each individual user, since no two learners take the same path at the same pace to reach mastery. In fact, the learning path a learner follows – a path that spans both formal learning (training) and informal learning (job aids, collaboration, coaching, and so on) must fit individual timing and individual needs. That is a tall order for our traditional design models.

A key characteristic of a learning continuum is reinforcing an important thread of continuity between the learning methodology and the work and tasks performed. The learning continuum serves as a foundational design tenet that can be best described using a three-phase model – Prepare, Deploy, and Reinforce (P,D, & R).

  • Preparation Phase – Establishes a state of readiness in learners prior to participation in formal learning interventions. Emphasis in the preparation phase addresses, defines, and delivers theory to the learner for maximum impact in the next phase in the learning continuum. Preparation could be as minimal as sharing an agenda in advance of the formal learning event, or more complex where completion of a related work activity or an on-line course are required as pre-requisites.
  • Deployment Phase – Represents the application (delivery, or consumption) of the actual learning intervention. The event could include a formal learning program that utilizes instructor-led classroom training, self-paced, on-line learning, live distance (synchronous) learning, a Webinar to a remote audience, a collaborative event, or a blend of all of the above. Surprisingly, an effective preparation phase can dramatically enhance the deployment phase. Adequate preparation can reduce formal training time. Handling the theory during preparation enables redeployment of time and activity in classroom training events. The learners spend more time on application where they engage in interactivity, collaboration exercises, role-plays, use of job aids in scenario-based simulations, etc. Emphasis shifts heavily toward demonstrating ability to “do” rather than validating their ability to “remember.”
  • Reinforcement Phase – Represents the most critical of the three phases of the learning continuum, and the most extended phase in terms of time. Reinforcement promotes implementation. Reinforcement extends the knowledge retention necessary for effective execution that drives sustainability. The reinforcement phase often includes the use of Performer Support (job aids, quick reference materials, coaching guides, help-desk support tools, and the like) and other methods of follow-up. The reinforcement phase also serves as fertile ground for instructional designers to harvest feedback that indicate the need for follow-up programs or improved content/object design.

Attributes affecting design in a continuous learning environment

So far, we have added several new considerations into our discovery efforts that compound our challenges as authors of learning solutions:

  • The variability, and unpredictability, of the five learning moments of need,
  • When and where those moments occur along the learning continuum,
  • To whom they occur, and
  • The individual’s level of competency at the time.

These variables complicate our ability to design effective, traditional training that can sustain capability. However, there is still more to consider.

With learning moments surfacing closer to, if not within, the context of our work, it is essential that we now include the attributes of the learning environment (space, media, and systems) in our discovery efforts. Including these attributes defines a composite environment that encourages expanded design of a holistic learning solution. The attributes have degrees of dependency: attributes of space impact media decisions, and the composite of space and media attributes influence the mix of systems.

Where is the learner in the learning continuum? Could the activities for each of the three phases of PD&R take place in different locations, using different content, and delivered by different methods? Absolutely! Therefore, when we design holistic solutions, the different phases of PD&R require us to consider the combined attributes of space, media, and system iteratively. Permit me to put some definition around these three attributes.

Attributes of space

The attributes of space are inclusive of physical, geographical, and operational aspects of the learner’s environment. They are not limited only to the learner. When we consider space, we must include those who provide support along the continuum as well as the individual learner. To that end, attributes of space and the variability of learning moment(s) should include:

  • Learning stakeholders 
    • Who are the stakeholders involved in satisfying the learner’s moment of need in the phases of P, D, & R? (That is, the learner, the trainer, the manager, the SME, and so on.)
    • What are the job roles or performance requirements of the learning stakeholders specific to their work or learning context? (That is, the learner’s role or function in their workflow, the trainer facilitating a virtual classroom session, the subject matter expert answering a question, the course designer, the manager, the mentor, the Help Desk, and so on.)  
  • Physical location 
    • Where are the learning stakeholders physically located during the learner’s moment(s) of learning need? (For example, at their desk, in a classroom, at home, mobile, at the bedside, in a hotel, at a conference, etc.) 
  • Work flow 
    • Where is the learner within the context of the workflow or work process when confronted with the moment(s) of need? (For example, using an on-line system while providing care at bedside, seeking (re-)certification through an on-line training program, participating in a live classroom event, participating remotely in a Webinar or distance learning venue, etc.)
  • Level of urgency and risk 
    • What is the level of urgency associated with flawless execution at the learning moment of need? (For example, planning a certification class event 90 days in the future, or accessing a job-aid “just-in-time” for completing a critical workflow task.) 
    • What is the level of risk if performance is not effective? (Such as death or injury of a patient, excessive material waste, loss of business continuity, incurring unnecessary costs, and so forth.)  

Attributes of media

The concept of media addresses format (modes and venues) that contributes to a compelling transfer of content (information or knowledge). There are dependencies within the space attributes to consider that can influence the viability of whatever media options represent the optimal blend. Consider this common example:

  • There is a high level of urgency to perform by the learner, and 
  • The learner is untethered from the corporate network (in other words, using a smart phone).

The two attributes of space shown above preclude consumption of learning designed for a classroom setting. Therefore, urgency and mobility influence the media blend to serve this learner’s moment. Do not forget – the blend may change – depending upon what stage of the learning continuum (P, D, or R) the learner is in at the time. Sitting in a classroom versus standing at the bedside illustrate two completely different venues, and two completely different design considerations influenced solely by attributes of the learner’s work environment.

The scenario above is a simple example of a learning moment experienced in the context of actual work. Most often such moments would occur in the reinforcement phase of the continuum. It is entirely possible to emulate this work task in a classroom-based simulation, that is, in the deployment phase. In the classroom environment, of course, there are absolutely no real-world urgency or risk factors present. At the same time, the classroom offers the learner full audio and visual support, instructors to facilitate the scenario face-to-face, and fully wired access to the corporate network.

Can you see why integrating attributes of space and media into the design process is a meaningful consideration? Space attributes in the deployment phase of the learning continuum were radically different from those in the reinforcement phase and the choices for media varied as a result. Can you also see why the iterative nature of this approach matters? Without iteration, the media selection for the deployment phase would not have supported the work context encountered in reinforcement phase of the learning continuum.

Attributes of blended systems

Understanding the dependencies represented by the media mix delivered within the context of the learner’s work environment (space) gives us the influencers that drive the third set of attributes – the systems technology. In reality, a different technology mix may be required to accommodate each phase of the learning continuum. The learner may physically be in three different “spaces” and need to consume three different “media” blends. Therefore, technology is not a one-size-fits-all proposition if the objective is effective delivery of continuous learning into the hands of the learner.

LMS systems handle formal learning activities. Electronic Performance Support Systems (EPSS) handle informal “just-in-time” learning demands. Learning Content Management Systems (LCMS) do both, but not well enough to serve either camp as a stand-alone system. Those three technologies are mainstream systems, but my intent is not to drill down into the virtues of any of them; rather, the concept of “systems” addressed here is broader than technology platforms. Building a holistic learning technology solution requires consideration of additional peripheral systems criteria. Following are a few examples of peripheral systems that can influence design decisions:

End-user devices
  • What technology is in the hands of, or is accessible to, the learner when confronted with their learning moment(s) of need? (Such as individually assigned computer, shared workstation, DVD player, smart phone, etc.)
  • What technology is available to the other learning stakeholders? (That is, to the trainer, the manager, the Help Desk, etc.)
  • Is more than one device required at different points on the P, D, & R continuum? (Such as a DVD player for preparing pre-work, a computer used to deploy simulations in the classroom, or smart phone access to job-aid reinforcement back on the unit.)
Internet access
  • Is access to the internet required to serve the learning moment(s), and if so, what bandwidth requirements must be available to accommodate anticipated content transfer rates? (Are all users on-Net, or are there non-employees participating using non-company computers; are there 10 participants or 200; did you say broadcast quality video to all?)
  • How do Internet access requirements differ across the phases of P.D. & R? (Such as on-Net wireless used for preparing pre-work, Ethernet-connected computer used to deploy simulations in the classroom, or off-Net Wi-Fi support required for smart phone access to job-aid reinforcement back in the field.)
  • Will the learning event take place on-Net, off-Net, or will it be a blend?
  • Will there be a broadcast (one-to-many)?
  • Will there be a need for interactivity? (Such as polling, Q&A, participant surveys, application sharing, interactive discussion, moderated chat, and so on.)
Access to content
  • Will the system “push” content to the learner, or will the learner download or “pull” content on demand?
  • Must the learner remain connected to the network to use the learning asset?
  • How will the learner retrieve the content?
  • Will the content be searchable? (If so, what are the metadata requirements?)
  • Who among the learning stakeholders must have access to the content?
  • Do access rights and restrictions vary across roles with access to the content?
Content repositories
  • Are there re-use requirements that require recording learning programs?
  • Where will you archive content?
  • Are there special content capabilities supported by the repository? (Static content versus streamed media.)
  • Who is accountable for content management and currency?
  • Do access permission levels vary across roles with access to the content?
  • Is version control important?
Tracking utilization and participation
  • Will consumption of the learning asset or participation in the event require a record of participation and completion? If so, describe acceptable recording format. (Training history in the LMS, printed certificate of completion, registration record is sufficient, etc.)
  • Will tracking utilization of informal content be required? (How many times did a learner access a specific job aid?)
Evaluation, Testing, and Feedback
  • Will consumption of a learning asset or participation in an event require evaluation or testing? If so, describe format. (Hard-copy instrument or on-line access.) 
  • How will you capture feedback on object usability and relevance? (Ranking scale embedded within the objects, embedded e-mail response link, and so on.)
  • How do learners access help? (Help Desk, content owner, subject-matter-expert, or other source.)

Iterative design process

Traditional design methodologies do not consider attributes of a continuous learning environment, or the concept of learners confronting learning moments along a continuum. As such, traditional methodology does not aggressively embrace re-use mentality; hence “objects” tend to be entire modules, and in some cases, entire courses.

The P,D, & R phases of the learning continuum create excellent opportunities to design smaller “chunks,” increasing the potential for re-use. To accomplish this “shrinkage,” the designers must look across the P, D, & R continuum at the implications of how the attributes of space and media differ in each phase. In other words, design must adopt an iterative approach.  

A learning continuum requires the use of blended media modes and venues that serve different learning functions and have different renderings depending on the P, D, & R phases where used. This variability can influence the choice of authoring platform. The following example illustrates the variety of design options, and the need for an iterative approach:

Preparation On-net wireless used for pre-work completed by the learner from their laptop docking station.
  • Re-used legacy content authored in PowerPoint.
Deployment Ethernet-connected computers used to launch simulations in multiple regional office classrooms. Instructor located in room 929 of the Philadelphia Marriott. Performer Support objects (job aids) used to support on-line simulations.
  • Simulations authored in Captivate.
  • Virtual classroom technology used to support distance learning.
  • Performer Support re-used Captivate screen shots in hard-copy PDF format.
Reinforcement – Off-Net wireless smart phone support used by learners to access job-aids on demand. Help Desk personnel access on-line knowledge base to push Performer Support to learner on demand via e-mail or FAX.
  • Captivate objects re-purposed for smart-phone delivery.
  • Hot-key access to Help Desk.
  • Performer Support sent to learner by Help Desk re-used same Captivate screen shots for e-mail “push” or printed as hard-copy PDF format for FAX delivery.

As you can see in the example above, multiple authoring platforms played a role. The learner’s transit through the P, D, & R learning continuum engaged multiple learning stakeholders. Content objects were re-used, all or in part, and in some cases repurposed in a second authoring platform to fit a different delivery venue. The secret to effective re-use demands advance knowledge of how small – how granular – the learning objects must be. How can we acquire advance knowledge without accomplishing discovery that considers the iterative nature of learning design inherent across the P, D, & R learning continuum?

Developing stand-alone, linear training courses often follows a popular instructional design methodology known as ADDIE (Analyze, Design, Develop, Implement, and Evaluate). Because ADDIE has been around since the 1960s, some call it “old school” in its approach. Some are bold enough to say ADDIE has out-lived its usefulness. I do not buy into that line of thinking. ADDIE is not old school; however, our application of the model can be limited by old-school thinking. ADDIE remains intact as a logical guideline that still works – if used iteratively.

Since we need to develop learning to align with multiple phases of a continuum and with the attributes of the learner’s environments, we must adapt our application of ADDIE. This adaptation requires that we address the design criteria three times – prepare, deploy, and reinforce. As illustrated above, each continuum phase may have a different blend of attributes across space, media, and systems. By ignoring the environmental implications that may be radically different across the continuum, our design, development, and delivery decisions are rife with potential to generate redundant effort after deployment. That translates into addressing lingering performance gaps in post-training world. Those results confirm that a one-size-fits-all training solution will not render a sustainable capability.

Holistic discovery is the key. Expanded discovery precedes application of the ADDIE model. (No, I did NOT just set up a new acronym called DADDIE, but you have to admit the thought crossed your mind.)

The expansion of discovery and the iterative approach do not translate into slogging through the entire ADDIE model three times; however, it does require consideration of the three stages of the continuum within the first “D,” the design phase. Ultimately, development renders multiple objects, setting the stage for wider re-use of smaller objects.

 “Create once – use many times” becomes our goal, and for two reasons: to minimize redundant development efforts, and to embed a thread of continuity into the learning continuum. How many times have we storyboarded ourselves into a coma, only to then turn around and re-build job aids as a separate effort? Following the tenets of P, D, & R, the job aids have potential to serve as objects re-used throughout the entire continuum. Consider this re-use scenario:

Example of continuity through re-use:

  • Insertion of a job aid (Performer Support Object – PSO) into the preparation phase e-Learning course. The intent is to introduce a reference tool for use in future classroom simulations coming later in the deployment phase.
  • Scenario-based simulations during the classroom component of the deployment phase re-use the same job aid (PSO).
  • Once again, we embed the same job aid (PSO) in the reinforce phase as just-in-time Performer Support for a learner confronting a moment of need.

In this example, we introduce the learners to a tool (PSO), and they use the tool in a controlled environment and validate proficiency in the presence of a subject matter expert. Then they utilize the same tool in the context of their jobs. While re-use reduced redundant effort, it also provided a thread of continuity to the learning experience.


Remember Jonathon Levy’s predictions? Well, it is 2009, and we are right in the middle of what he predicted. Learning opportunities are shrinking in size and going through a shift in venue to match up with our work context. More and more learning moments are confronting our learners at the point of attack, outside of the classroom. Our approach to training development is under pressure to shift learning assets to support learners under fire. The pressure we see comes in the form of diminished training budgets, falling attendance in elective training classes, and high rates of e-Learning non-completion on the LMS.

The most damning evidence of change is the perceived ineffectiveness of training solutions on rendering sustained human performance. Stellar Level One evaluation and learners exceeding Level Two thresholds do not serve as accurate predictors of performance outside of the classroom. Should that matter? Definitely! Learners rarely fail in the safe environment of the classroom, and even if they did, the organization faces minimal risk.

Sustainable performance occurs in a post-training environment, in the work context. If we fail the learner here, the stakes are higher, as are the costs to the organization. The time is now for training organizations to shift resources beyond the classroom and beyond e-Learning, to the environment where the learner must perform. This shift requires breaking some ingrained paradigms regarding instructional design. I know I am walking on hallowed ground when I say this, but if we, as training organizations, do not contribute to a sustained capability we deserve to lose every penny of budget that gets whacked.

Mr. Levy said something else that is critical. He mentioned a shift to performance support, also to improved change management, both as specialists. Zeroing in on performance support as an authored asset is not his intent. Performance support implies we have accomplished discovery to identify where it is needed. It also implies we have accomplished discovery related to the work context where they consume the asset. This represents a significant shift in thinking – a significant change.

A continuous learning environment is a holistic blend of the formal learning (training) that we do so well today, and a robust approach to informal learning (performer support, collaboration, knowledge bases, and the list goes on and on). Integrating this “continuous learning thinking” into the training department is not easy, hence Mr. Levy’s change management prediction. It has been my experience that some instructional designers feel threatened by these implications. I have had platform trainers show concern that their jobs are at risk. Truly, if we cannot deliver sustained capability, more than the training department is at risk. These are not the economic times to have your corporate contribution measured by the weight of your cost center on the budget.

The question you must answer now is simply, “Is your training department ready to support a continuous learning environment, or are you at a state of readiness to support a continuous learning environment?” The change management plan you devise to reach critical mass and sustain your own team’s capability must build upon the gaps between ready and readiness.


Gottfredson, Conrad. (November 1, 2007) “A Beginning Discussion: What is Performance Support?” PERFORMER Support: Learning @ the Moment of Need (weblog). Accessed June 26, 2009 at

Levy, Jonathon. (February 6, 2004) In “Predictions for 2004: E-learning Visionaries Look to the Future.” (Interviews by Lisa Neal) eLearn Magazine. Accessed June 29, 2009 at 

Levy, Jonathon. (January 9, 2009) In “Predictions for 2007” (Interviews by Lisa Neal) eLearn Magazine. Accessed June 29, 2009 at§ion=articles