I’ve quoted Richard Buchanan previously in a definition of Design Thinking as “the integration of signs, things, actions and environments that addresses the concrete needs and values of people in diverse circumstances.” Design Thinking offers a set of tools to make sense of “wicked problems” and mysteries, and in this post I attempt to narrate my ideational journey in making sense of learning by digital means, the concept that I call learning experiences, and a notional (but far from complete) model for learning activities designed for individuals to experience.
I make this attempt for a number of reasons. Much effort is going into this concept by ADL and, unlike the late 1990s when the Sharable Content Object Reference Model (SCORM) was being developed, there exists an ability to raise the level of awareness for larger audiences that will no doubt be affected over the next 20 to 30 years by the design decisions that are made in the coming months. With this ability to scale public awareness, I feel a sense of responsibility to reach out to the world, to share what is being considered and, in doing so, make better design decisions that are far more difficult to change later on. I also sincerely believe that what I’m proposing has far greater implications than simply the scope of what our industry calls “learning” today, and while what I propose here is a model for a new approach towards learning, it is a model that one could apply tomorrow on the very next course, learning program or lesson plan you design.
I’ve blogged that we must consider how eLearning came to be as it is today. In 2000, there was an attempt to make sense of how people could learn through digital means, and the the solution that seemed to solve the many problems at the time, was an idea that there would be digital objects we (also) called “eLearning” that would work in “learning management systems.” This distinction is important. Outside of an LMS, we might have called this Web-based Training (WBT), which was the move to the web from native applications and content that operated on your computer’s desktop (CBT).
There were challenges that went with the mysterious thing called eLearning: it was very difficult to swap content out of one system into another, which was forcing lock-in to vendors as organizations were adopting learning content that was tethered to the systems that tracked it. Hence, out of the many examples of eLearning and the systems that were tracking them (as well as a number of standards that were in place), a framework called the Sharable Content Object Reference Model (SCORM) emerged as a de facto standard, and it accelerated adoption of a particular framing of how eLearning was defined. Adoption for SCORM grew at the same time as the emergence in Instructional Design of a design-based, prescriptive models of learning leveraging page turner or text/next designs designed using the traditional ADDIE (analysis, design, development, implementation, and evaluation) design and development model. Unfortunately, these designs occurred with very little front end analysis with design and development proceeding before determining what the real instructional needs were.. Baked into SCORM was a pedagogical model that worked well for prescribed single-learner training (presentation, knowledge checks, remediation); an approach for which these traditional instructional designs were particularly effective.
With models for producing content, models for standardizing systems and models for delivering the content to learners, the last ten years have seen a great investment in refining these models and standards to be more efficient and more effective. However, these models (as models tend to do) have embedded within them a theory about how e-learning works and what it is. Unfortunately, as the world (and especially technology – i.e. ICT) evolved, the underlying assumptions about what learning is and how it should be facilitated didn’t. As theories are about explaining and predicting how the world works, they can very easily become the peep-hole for the box camera that is e-learning.
Somewhere along the journey, as we became focused on making these models and standards more efficient and effective, “learning” went from being a verb to being a noun. If you actually think about what learning is and that it is intrinsic to the individual, how could it possibly be delivered? But that’s precisely how learning is perceived by those buying “learning” and, hence, influencing how it is designed, developed, and “delivered.” Korbsynski, of General Semantics fame, might say ‘the eLearning is not learning’ as it is typically designed and implemented today.
“Rather than being an interpreter, the scientist who embraces a new paradigm is like the man wearing inverting lenses. Literally as well as metaphorically, the man accustomed to inverting lenses has undergone a revolutionary transformation of vision.” – Thomas Kuhn (1996)
It is this awareness that led me and many others who have spent ten years invested in a SCORM world to start thinking about the idea of “learning experiences” as a new or inverted lens with which to revisit the phenomenon of learning in the digital and technology mediated landscape.
There are many perspectives in a broader view of Design, and among them is Experience Design, which applies in any medium and any context (not just learning), including augmented reality, classrooms and “field trips,” print products, web sites, multimedia, apps, customer services, broadcast images and sounds, live performances and events, etc. , I’m going to take a bit of time to explain what “experiences” mean in a learning context as well as describe some foundational information that goes into the design of a learning experience. As a nod to K-12 educators, this is not unfamiliar territory as they have most likely been designing what they would call learning experiences for their students for a long time. However, unlike traditional instructional design, educators don’t necessarily have the same considerations of replication or reproduceability. I believe this is crucial as we tap into collective learning experiences, and leverage self-organization to tackle issues of scale (Thomas and Brown, 2011).
Bringing learning experiences into the design lexicon and infrastructure of the instructional designers, developers, and the everyday learner will help bridge a gap that exists in eLearning and allow for such highly desirable types of learning outcomes to be realized.
What Are Some Prototype Experiences?
I’d like to first narrate some scenarios to describe what kinds of things we are looking to do in the design of learning experience with domain examples including military, enterprise, academic, career changes and recreation. There are some who may think these scenarios fit into the category of wicked problems and upon analysis it is easy to see why. However, it is my position that using definitions and attributes of experiences and goals, it will be possible to realize these scenarios and to define, categorize, model, and generalize experiences enabling the discrete linking to activities and outcomes.
Someone graduating from an ROTC program will be deployed as a commissioned officer into combat. What are the set of experiences that will provide them with the “stance,” or wisdom, needed to survive and lead in their first days of deployment? If commanders can ascertain the experiences that have forged the young officer and better assess “where” he or she is “at,” a range of experiences, aggregated by similar young officers who successfully headed into harm’s way can serve as a guide to provide a compressed but full set of developmental experiences that close the gaps between a young officer’s assignment and their readiness to perform.
In an annual review of her employees, a Manager and her Director identify someone as having high potential to grow into a leader inside the organization. What are the set of experiences that will both develop that person into the right kind of leader for the organization AND retain that employee’s interests and commitment to the organization intrinsically? With a variety of assistive tools to gauge the employee’s strengths and gaps in their experience, organization leaders can leverage better support in coaching and mentoring the employee to make sure that he or she builds and accelerates the kinds of performance and leadership acumen that the organization needs for both short-term and long-term growth.
When I Grow Up…
Every teacher and parent is familiar with declarations of children, old and young, about what they want to be when they grow up. Beyond the sage, tried-and-true mantras of “stay in school,” “get good grades” and “keep trying,” teachers, parents and students themselves will have access to guidance on suggested “next” activities and experiences that will develop the young learner towards their aspirations. Like a GPS, when the individual changes their mind and/or new experiences are captured by the learner, a variety of assistance will be available to recalculate their learning journey and suggest “next” activities and experiences that tailor the learning journey for the individual towards their same (or new) aspirational goals.
With a changing (and challenging) economy, shifts in career opportunities often seem unpredictable and sometimes impossible to imagine for workers who have invested time, effort and practice towards one profession, only to find themselves with almost no preparation in need of a whole new set of job skills and experiences to take on new, potentially rewarding careers far outside the “adjacent possible” to their existing skillsets. With the help of intelligent assistants, a tailored developmental plan can be suggested that eases the burden of figuring out how to navigate a career change and offers compressed developmental experiences that accelerate one’s ability to shift from one industry to another.
Becoming a Better “Me”
Wellness goals like losing weight or becoming “fit;” performance goals like improving one’s golf swing, learning to play a musical instrument or improving one’s math literacy; achievement goals like running a marathon or presenting at a TED conference: having goals inherently describes an individualized state that takes place in the future that is (contextually) an improvement from the present. By leveraging tools that help “make sense” of how others achieve similar goals, individuals can learn by performing in activities that prove to support others; taking away some of the burden of “figuring out how” and lowering the barriers to having enjoyable, sustainable and helpful experiences.
In short, these prototypical views of experiences contain a means to aggregate individual experiences, captured discretely as activities towards explicated goals. The aggregated “journeys” are then harnessed via intelligent assistants to help subsequent individuals identify where they are oriented along a journey and can advise what to experience “next.”
Speaking of “next,” let’s put some definition to the very notion of “experiences.”
What Are “Experiences?”
An “experience” is the sensation of interaction with “content” (at the broadest possible interpretation) through all of our senses, over time, and on both physical and cognitive levels. The boundaries of an experience can be expansive and include one’s senses, what’s symbolic to an individual, how someone puts the experience in a time and place, and what is meaningful to the individual. In other words, an experience is an instance of an activity as performed by a specific individual.
Everything that has already occurred in one’s past are personal experiences. The personal nature of experiences can’t be overstated — one can’t participate in other people’s experiences. As soon as I participate in someone else’s experience, it’s my experience as I live it.
Let me share an example: Surrounding any football game, we have several different “first-order” experiences: The people on the field are playing the football game. A group of friends may observe the same football game on the couch, watching it on TV. All over the country/world, others are experiencing the same football game from their homes, pubs, etc. The people in the football stadium are watching it too. Every single person in this scenario experiences something different because each person is participating in a different way.
With multiple senses, there are many channels of input hitting a person all the time, yet an individual is still able to selectively pay attention, identify symbols or totems, and derive some meaning while setting the experience in a time and place.
What Are Activities?
Activities are something that we can design, and people who participate in activities experience those activities.
Above, I defined an experience as an instance of an activity as performed by a specific individual. This suggests a need to define “activity.” An activity is an abstraction of something that can be done (performed) by an individual; key in this idea is that an activity occurs within a “unit of time” or is time-bound in some measured manner.
Thinking about how activities happen in some timeframe is helpful for linking activities together and for observing (“tracking”). A woman, Lisa, buying a soda from a vending machine is an example of an activity. One could observe what Lisa does in a few minutes as a whole (purchasing a soda from the vending machine), or the activity could be sliced into much smaller pieces. Such time-slices might contain actions in a sequence like…
- Lisa looked at the selection
- Lisa took money from her purse
- Lisa counted the money
- Lisa evaluated the need for more money
- Lisa inserted money into the vending machine
- Lisa selected a soda
- Lisa pushed the button to get the soda
- Lisa removed the soda from the machine.
If an activity is planned in advance, one can estimate how long (a time-box) that activity may take; when the activity is performed (read: experienced) the activity can be tracked at some granularity within that time-box. The specifics and details (granularity) of what one might observe is specific to the type of activity and the type of evaluation(s) to be performed in the future. Each time slice can have one or more channels, related to the design factors of experience detailed above. Some of these channels are difficult, if not impossible, to observe.
Activities can be planned since they happen in the future. Due to the fact that we can timeslice activities, every activity is a container and may have within it a multiple of activities (even performed by a multiple of individuals — remember that an activity is an abstraction), but the larger activity can be thought of as a whole.
How can activities be described?
There is a framework or descriptive meta-theory that thinks about activity as a system and accounts for environment, a person’s history, culture, roles or objects, motivation, and other things called Activity Theory. This framework was originated by educational psychologists including Vygotsky and discusses people as socio-culturally embedded actors with hierarchical levels of human action or activity. What’s really useful in this framework is what is called a motivated activity directed at an object or, simply put, goal. Goals are essential for motivation of the performance of any activity and when the goals are for the attainment of new knowledge then it is easy to see how activities become learning activities.
What Distinguishes Learning Activities?
The notion that the future can enhance the present is a wonderful and insightful concept. Very nice: “The latent potential of a future experience.” – Don Norman
In his “Experience Design Manifesto”, Andrë Braz describes an approach to the design of experiences that creates, in a present tense, a drive towards empowerment; a present state for people that is better because of the latent potential of future experiences. I like his notion of “future” experiences because it describes a state that is likely different (read: “better”) than “now” — which in my view describes when we learn something.
Such experiences are described by Braz as fostering the following qualities:
- The belief that the individual can improve
- An ability to solve pragmatic problems
- Joy, Surprise and Awe
- A desire to connect with others in support of sharing the experience, thus making it richer for the sharing
- A shared sense that relationships are strengthened as a result of the experience.
This list immediately reminds me of flow states as described by Mihály Csíksentmihályi, though there are other models for positive-psychology (Seligman, Vygotsky, Weiner to name just a few) that describe self-motivated and self-rewarding (“autotelic”) activities. Vygotsky’s work also merge social connections with meaning making in social negotiation and social experiences in attaining greater results with his concept of the Zone of Proximal Development. In Jane McGonigal’s book, “Reality is Broken: Why Games Make Us Better and How They Can Change the World” (2011) she summarizes intrinsic rewards identified by Csíksentmihályi and others in the following ways:
- People crave satisfying work that immerses them in clearly defined, demanding activities that allow them to see the direct impact of their efforts.
- People crave the experience (or the hope) of being successful, and they want to share that success with others.
- People crave social connections forged by shared experiences that build bonds by doing things that matter together.
- People crave meaning — the chance to be part of something larger than themselves.
There is much I would borrow from designing games when it comes to the design of learning activities. Game designs are often invested in the intrinsic rewards identified above, and while the experience of gameplay is highly personal and often shared with others, such experiences happen often within a preset context. Games, are by their definition, designed. Someone sets the conditions for a game to exist.
With this stated, I want to differentiate between (a) how I draw elements from game design into learning experience design from (b) the ideas behind gamification. Gamification is the application of gameplay mechanics to activities and experiences that aren’t games. Examples of gamification include services that help web content publishers add badges, virtual currency, and other gaming features to existing websites and web services. Gamification could apply to many things, including learning experiences. The emerging applications of gamification enable behaviorist models really well but where they really shine is in the enabling of inductive thinking skills which, when guided, promote understanding and facilitate the construction of new knowledge. For the purposes of learning experiences, I want to enable flexibility and an eclectic approach to gamification in the application of learning paradigms which not only include behaviorism but expand to cognitivism, constructivism and humanism (to name a few).
What Elements Go Into Learning Activities?
In Sasha Barab’s paper “Meaningful Play: Designing Games for Education,” (Barab, Warren & Ingram-Goble, 2006) a model was presented that described elements of Academic Play and is based on activity theory. The model was similar to models presented by McGonigal (2011) and this triggered in me a way to possibly abstract the like elements in both models to apply to general “activities” (beyond just gaming activities).
I propose the integration of four core elements that form any activity that can be experienced: balancing the learning of content and supporting participation; and, by the same token, balancing interaction within boundary conditions and engagement within a context through which the learning experience takes on meaning.
Barab et alia write about the need for the appropriate balance of these elements:
“It is when the user experience meaningfully intersects with all these features that rich learning.. can occur. While it is possible to develop [boundary conditions] or even a [context], it is difficult to develop activities that also include [content] and meaningfully engage the learner [to participate] in disciplinary-relevant practices. If one focuses too heavily on the content, then the experience too closely resembles school; if one focuses too heavily on the [participation], then there is no assurance that learning will occur.”
Boundary Conditions are what I would consider the “rules” that guide how one experiences content. As people participate in an experience, they cross a boundary (or a frame) that defines the activity in a time and space. The activity of “reading” might be informal, such as picking up a magazine in the doctor’s office; the same activity might be quite formal, as an exercise in a school setting or even as a game. The point is that there is a beginning, a middle and (perhaps) a quantifiable outcome at the end of the activity.
These boundary conditions are linked to a given context and influence the way in which individuals tend to participate in a learning experience. Consider how people participate in activities involving paintball. There are ways people participate in activities, such as the above example of “reading” that are acceptable in informal contexts. However one might describe (or define) that participation, it is a very different thing to participate in a “like” manner in a classroom, even if the subject of both activities is connected.
Content is a data artifact created and possibly provided as part of an activity. Content can be stored, managed, tracked, manipulated, reappropriated, etc. Whether it is man-made or system-generated, content has a lifecycle. When primary schoolchildren go on a field trip to a forest and identify leaves, the leaves are content. Whether they use paper and lead to create reliefs of the leaves or they take pictures with their mobile phones, in such a learning experience all of these means of capture and the artifacts created as a result are content, which can be all be stored, managed, tracked, manipulated (and so on) in any number of ways.
Content is also the means by which individuals receive feedback which is highly contextual and sensitive to how individuals participate with respect to the boundary conditions. Feedback is important in keeping individuals aware, in a learning experience, of their progress towards the explicated goal or objective (in formal learning experiences), possibly what competencies an individual may have vicariously achieved (possibly in informal learning experiences).
In “Rules of Play: Game Design Fundamentals,” Katie Salen and Eric Zimmerman (2004) describe how people learn what something “means” through interaction. Finding meaning in an experience relies on what Salen and Zimmerman describe as “the movement between known and unknown information.” Where boundary conditions are presented as rules (read: tools, instead of constraints) to help an individual navigate through an experience, the context can be engineered (and often constructed) by the interactions people have through participation.
In many ways, context is an aggregation of paradata. Paradata describes one aspect of an interaction, such as how a piece of content is used. When one clicks a “Like” button, Facebook is collecting paradata: the “Like” button describes how one has used a piece of web content. There are many possible channels for paradata which provide evidence of an individual’s activity; there is paradata only when an individual captures this evidence (clicking the “Like” button, making an evaluation, etc).
Context is negotiated socially. In this sense, how we describe to children the expectations for attending school or church is very much a form of paradata; when explanations about school or church are collected by a child it sets their context for experiencing school or church. Collected anecdotes about shared activities are similar, in this vein, to comments on a blog post and even “reviews” of movies or retail items — all are examples of a capture of individual’s experience with “content” (by the broadest use of the word) that provide meaning to other individuals and reinforce meaning to an individual.
There must be a willingness on the part of the individual to accept the boundary conditions, the content and the context. As McGonigal (2011) might put it, participation is where this model is prone to the most challenges. She writes, “to participate wholeheartedly in something means to be self-motivated and self-directed, intensely interested and genuinely enthusiastic. If we’re forced to do something, of if we do it halfheartedly, we’re not really participating. If we don’t care how it all turns out, we’re not really participating. If we’re passively waiting it out, we’re not really participating.”
There are any number of implicit and explicit motivating factors that can be applied here, as in every possible model of learning through time ad memoriam. Great focus has been paid to promote the individual benefits in this model, starting with the prototype experiences described at the beginning of this writing. Ultimately, for any learning experience to be successful, the learner must be actively, enthusiastically motivated to participate in the experience and as designers, facilitators, engineers, mentors, coaches, parents and peers, the best we can do for individuals is to help them participate more fully, lower the barriers to their full engagement in such experiences.
As alluded to in the previous paragraphs on participation, there are probably many more things that need to be considered as we plow forward. For example, as motivation is embodied in goals, to facilitate teacher, learner, organizational, institutional and any other goal to be attained, there may need to be a way to describe, articulate, and match goals. Also, what about assessment? If activities can be described and goals made explicit, then there should be ways to apply assessment models. In any institutional context, some form of assessment will need to occur for viability. However, using this approach, assessments would now have the option to be authentic and activity based – just another activity – and would convey much more meaning. When activities and performance outcomes are linked, it becomes easier to have assessments that are truly performances of understanding.
If you’re a K-12 teacher, consider the lesson plan you have ready for tomorrow. If you’re an Instructional Designer, consider the class or the course you are currently designing. What are the performance outcomes you expect of the individual partaking in your learning activity?
If you’re a manager reviewing a training regimen, use the above model of Boundary Conditions and Context; Content and Participation; and put yourself in the seat of an employee about to experience this training activity. Imagine going through the experience that has been designed for him or her. Are there clear boundary conditions established for the individual to “find their way” in the greater narrative context of the activity that’s been designed? Is the content such that it will encourage the employee’s meaningful and active participation? I contend that if the answer any of these questions is anything but “yes” that the learning and performance outcomes sought in the activity are greatly at risk.
It is precisely to guide this kind of audit of learning activities that will make a transition from learning activities and training as they may exist today into a more focused and engaging experience in the future — experiences designed with explicit performance outcomes in-mind which will allow individuals who learn, designers, facilitators, teachers and managers to meaningfully understand the return on their efforts.
Additionally, I assert that there is a need to modify (instantiate, for engineers and developers who might be reading), if not extend the ADDIE model. As ADDIE is a prescriptive top-down approach to designing instruction as currently implemented, it should be possible to do ADDIE “on the fly.” In other words, analysis could occur based upon true learning needs and goals resulting in self-organized learning experiences that are not extrinsically developed but organized by intrinsic attributes using models of activities and goals. Also, to tailor learning activities to the individual, intelligent assistance technologies will need to leverage previous experiences of an activity to tap into the collective experiences of others. Where SCORM supported a predictive instructional model that assumed learner independence, the notion of learning experiences (at this time) assumes a self-organizing nature of collective experience, which will require the up-front design of dynamic and variable aspects to a learning activity that considers both the “micro” of the personal experience and the “macro” of collective experiences — something many Instructional Designers using ADDIE don’t typically do today.
What I hope you, the reader, takes away from this writing is that in revisiting the mystery of how people learn via digital means, I have drawn a new heuristic of how people can learn that I believe more holistically supports “learning” as it has occurred throughout human history and makes use of the ability to capture and record experiences of learners, leveraging network effects much in the same way “social tools leave a digital audit trail, documenting our learning journey—often an unfolding story—and leaving a path for others to follow” (Bingham and Connor, 2010). I couch this heuristic in terms of “experiences” which are captures of an individual’s learning activities, consisting of four core elements: Boundary Conditions, Content, Context and Participation.
I’ve tried to address what I feel is fundamental to understanding this concept and (based only on what I edited out in my drafting of this article) what I’ve presented is far from “complete.” I hope that this is enough to start the many conversations that take this idea from a construct to an applicable reality.
I look forward to our conversations 🙂
Barab, Sasha, Scott Warren, and Adam Ingram-Goble. Academic Play Spaces: Designing Games for Education. Indiana University, 23 Mar. 2006. Web. 11 Feb. 2011. <http://inkido.indiana.edu/upload/aps7.doc>.
Bingham, Tony, and Marcia L. Conner. The New Social Learning: a Guide to Transforming Organizations through Social Media. Alexandria, VA: ASTD, 2010. Print.
Braz, Andrë. “Experience Design Manifesto.” André Braz – Experience Design. Web. 11 Feb. 2011. <http://www.brazandre.com/manifesto/>.
Kuhn, Thomas S. The Structure of Scientific Revolutions. Chicago, IL: University of Chicago, 1996. Print.
McGonigal, Jane. Reality Is Broken: Why Games Make Us Better and How They Can Change the World. New York: Penguin, 2011. Print.
Salen, Katie, and Eric Zimmerman. Rules of Play: Game Design Fundamentals. Cambridge, MA: MIT, 2003. Print.
Shedroff, Nathan. “Nathan: Experience Design: Glossary.” Nathan Shedroff’s World. Web. 13 Feb. 2011. <http://nathan.com/ed/glossary/index.html>.
Shedroff, Nathan. “Nathan: Experience Design.” Nathan Shedroff’s World. Web. 13 Feb. 2011. <http://nathan.com/ed/>.
Silvers, Aaron E. “Aaron Silvers – How Can E-Learning, or Computer Based Training, Be More Effective? [Quora].” Aaron Silvers. 3 Jan. 2011. Web. 13 Feb. 2011. <https://aaronsilvers.com/2011/01/how-can-e-learning-or-computer-based-training-be-more-effective-quora/>.
Thomas, Douglas, and John Seely Brown. A New Culture of Learning: Cultivating the Imagination for a World of Constant Change. Lexington, KY: S.n., 2011. Print.
Update: This is a cross-post from https://sites.google.com/a/adlnet.gov/future-learning-experience-project/project-updates/fundamentaldesignoflearningactivities