The process is fairly straightforward, and I’d want to condense it down to something that I’d work with, inspired by Clark. Although I have condensed the process into three simple steps, the details and considerations under each step are what make this process a robust one in my opinion—and I feel that’s an area that Clark makes you think and reflect on. It’s the details of considerations that differentiates this process from everything else.

I would divide this process into three broad steps:

Step One: Determine Big Goals & Metrics

Clark states that we should frame our big goals with respect to business, learning, and performance in a way that they are observable and measurable. He also goes on to say that we should be able to determine when the learner is capable of performance and at what level of expertise and under which contexts.

When we’re framing the business, learning, and performance goals, we should keep in mind the following consideration:

Constraints: Are there any scope, budget, or resource constraints that get stretched with the framing of the goals and metrics?

We have to be precise when we’re framing metrics that we want to achieve with these meaningful learning interventions.

Step Two: Gain insights from SMEs & learners

SMEs are treasure troves of content. As designers, we have to ensure that we probe SMEs and find insights about the content that will help the performance of the learners from the complex knowledge architecture that SMEs possess. Knowledge can be extracted from the SMEs into four different buckets, namely:

• Mental models that SMEs have built over time about the decisions they make or are obvious to them,
• Common misconceptions about the knowledge and common mistakes that occur while they make those decisions,
• Stories around the decisions or knowledge that may be useful, and
• What intrinsic motivators made them develop expertise in the subject they’re an expert in.

Collecting insights across these four buckets should lead to a strong foundation for the learning intervention.

Learning about the learners is also extremely important. It’s not just about gathering the demographic details of the learners. We need to dig deeper to understand what their interests are, what they care about, and what motivates them to do whatever it is that they’re doing. If we’re going to be demanding their time and attention, we must get to know them better to serve them better. This helps us in designing experiences that are as close as possible to the expectations of the learners. These insights also help build better engagement with the learners.

Step Three: The [Goal>Role>World] Process for meaningful learning experiences

This is another (three-step process) within this larger three-step process. Its purpose would be to focus on the quality of experience you’d want to build for your learners. You can learn more about that process here. It’s majorly about determining Goal, Role, and World; choosing the treatment that you deem appropriate; and then running your early prototypes through a creativity checklist to fine-tune the experience.

Important Considerations

It’s not just about getting through these three steps; it’s also about doing them well and in an effective way. The way this can be achieved is by considering the following things:

Continuous Iteration: Keep testing the smallest ideas with outputs that take the lowest possible effort to communicate the idea and then keep building on it and improving it.

Documentation: Document almost everything. We need to borrow the principles of documentation from the world of products and game development. Documentation helps bring all the stakeholders on the same page and helps us stay on track and achieve the set goals.

Testing: We need to rethink the way testing is usually done. Clark has mentioned research where they’ve found that iterating between the expert review and user testing helps, and as few as 5 users can identify up to 80% of usability problems.

There’s a sequence that Clark suggests that we follow for the best results:

• First, do a usability testing,
• Secondly, test for its educational outcome, and
• Only then test for user engagement.

This sequence helps us to spend our testing resources wisely.

As I mentioned in the previous blog, designing meaningful learning experiences is not easy. But it’s fun—it’s hard fun, the thing we should be designing for in these experiences for the learners.

Clark says, “Learning should be hard fun”, who knew this would apply while you design for learning as well? Personally, for me, the learning interventions that I design or am a part of must have people excited. The people here refer to not just the audience now, it also translates to the team I’m working with.

After all (and paraphrasing Clark) we are at the forefront of delivering human transformation through educationally effective and emotionally engaging experiences—and how can that be easy?

The post Make It Meaningful by Clark Quinn – Idea Extractions – Part Four first appeared on The Upside Learning Blog.

The central tenet of making your learning a meaningful experience lies in Chapter Four: Tricks & Tips, according to me. Clark talks about and dives deeper into the idea of determining the [Goals > Role > World] process. He goes into the depths of how storytelling (Rance Greene’s Instructional Story Design is great reference material) can guide us all to designing for meaningful learning experiences.

Before diving deeper into the three-step process that I’ve derived from this chapter, I’d want to speak about a meta-skill that Clark insists that everyone should be nurturing. Clark mentions that whatever it is we want to design, be it courses, games, interactivities, or stories, we should find the inspiration for it by watching more movies, reading more stories, playing more games, visiting amusement parks, etc. just consuming everything that you’d want your learners to feel and just completely immersing ourselves in it. This helps us be more creative and observant, and understand the principles better.

From what I understand, adding creativity appropriately is also what makes the learning experience meaningful. This [Goals > Role > World] three-step process helps you do just that. It’s never easy to demystify a creative endeavor. Clark has done a splendid job of doing just that, so let’s get into it.

Step One: Determine [Goals, Role, and World]

These three also form the core components of a good story.

Determining Goals: We need to first determine the goals that need to be achieved

Key considerations while determining Goals:

• It must accurately convey the real-life task.
• We must not tinker much with the real-life decisions that need to be made to be able to do the task.

Determining Role: We must then define the role of the protagonist who will be achieving the defined goals

Key considerations while determining the Role:

• Put the players in a role they want to be in according to their interests.
• Determine the traits and quirks of the role that excite/relate to the audience.
• Determine the character arc of the role; ensure that the role completes the arc within the experience.

Determining the World: Finally, we determine the world in which that protagonist lives to achieve those goals set

Key considerations while determining the world:

• It could be real life or even anything mythical, but we need to ensure that it facilitates effective learning transfer. There’s a possibility of contexts getting lost, so choose your Worlds carefully.
• Worlds may also have inherent conflicts within them that make it difficult for the protagonist to achieve the goal. So, when the protagonist overcomes these conflicts, the conclusion is more fulfilling as the World has changed/evolved.

Step Two: Figure your treatment

Either you know this from the beginning, because of constraints, or because you just finished your step. We will need to determine how you want to treat this experience. It can be a story, game, interactivity, or anything else that we deem fit or suits the audience, as also the requirements, budget, and other constraints of the project.

Depending on the treatment we choose, we will need to move to production accordingly. The production guides are fairly standardized and there aren’t any considerations while at the production stage.

Once we have an early prototype ready, we could look at step number three.

Step Three: Creativity in Learning Checklist

Only when you’ve figured out the first two steps can you move to the creativity in learning checklist. The steps and the names for them are contrived by me, I’ve taken the information from the book and have arranged it in a way that suits my understanding and helps me make meaning out of it.

This checklist ensures that we tighten up the experience that we’re about to build, and is by no means exhaustive. It’s also all of the things that Clark mentions in his Tips and Tricks section. We can use this checklist as a guide to reflect on/improve the experiences that we’ve built/are building:

• Does the experience have a great introduction (especially with a backstory), and does it have an emotional hook at the very beginning that makes you want to know more?
• Are there decisions that have been crafted that initiate/invoke conflicts that make the audiences learn?
• Are the feedbacks that have been crafted individualized and personalized to every option provided?
• Do the character dialogues integrate appropriate humor, exaggeration, or any other emotion to create a suspension of disbelief?
• Is the experience able to adjust to difficulties, and maintain the ebb and flow of tension within the experience?
• Does the experience have flavors of relatedness, autonomy and competence within it to promote engagement within it?
• Are there intentionally built practices and rituals into the experience that help promote learning transfer?
• Are the activities/challenges framed in a way that converts all knowledge-level statements into application-level statements?
• Are there any uses of examples? How effectively have they been used?
• Can you map the quality of the experience against the quality of the objectives that were set?
• Is there a possibility to check if the experience has appropriate levels of learning transfer strategies built into it?

It’s not easy. It never was. Creating meaningful experiences is hard work and creating meaningful learning experiences is a lot harder than that. These three steps, hopefully, make it a little bit easier for me to get started. Hope this ‘note to self’ it helps you too!

The post Make It Meaningful by Clark Quinn – Idea Extractions – Part Three first appeared on The Upside Learning Blog.

In my previous blog, I covered the first big idea of Action-Reflection from Clark Quinn’s book. Now, I want to delve deeper into the next crucial idea: “Hook & Land.” Although Clark covers these concepts in separate chapters, I see them as complementary. On the surface, it sounds simple: hook learners with their motivators, then provide an exceptional experience so that learning sticks and impacts performance outcomes. However, Clark’s explanations have made me rethink my design practice.

(“Hook & Land” is what makes your learning experience meaningful)

Clark starts the chapter by saying, “To get people to engage, you have to open them emotionally before addressing them cognitively. People learn better when they care.” This statement sets the foundation for the entire chapter and highlights the importance of finding the right hook for learning.

In my opinion, you don’t need a single, perfect hook in a learning experience. Instead, many small hooks followed by small learning experiences can create a holistic learning experience.

The Emotional Buy-In

Before discussing how to get learners emotionally invested, Clark mentions two essential conditions that must be met:

• Identify tasks learners want to do but aren’t currently doing
• Identify a clear, observable outcome that determines learner performance

Once these conditions are fulfilled, you can design the hook for the learning experience. The tactics to create a great hook are described in detail in the book, and I wouldn’t do them justice by condensing them into this blog. However, here are some ways Clark suggests to build a great hook:

• Invoke learner curiosity
• Follow the three pillars of Self-Determination Theory: Autonomy, Competence & Relatedness
• Frame the “what’s in it for me” for learners carefully
• Show real-world consequences for learners
• Follow learner motivations

Once you have a great hook, you can focus on landing the learning experience. Clark defines landing as a state where learners are deeply engaged, in a flow, and aware of learning goals. To create a great learning experience that lands, Clark suggests several components:

• Learners should have a clear understanding of learning goals
• Challenges should be well-balanced
• Provide contexts where learning will be useful and can be dealt with creatively
• Show real consequences for wrong/mis-directed options, with feedback first focusing on consequences, followed by didactic feedback.

Clark also mentions that the principles behind great games and engaging learning are the same. He says that learning should be “hard fun,” and I would argue that to make learning engaging, it should be more game-like. Our world is becoming game-like, so why shouldn’t learning follow suit?

Finally, Clark emphasizes the importance of practice, particularly practice that boosts learner confidence to perform and make correct decisions on the job.

I’ve summarized Clark’s main ideas, but haven’t covered every single concept from his book. It’s time to put these concepts into practice!

The post Make It Meaningful by Clark Quinn – Idea Extractions – Part Two first appeared on The Upside Learning Blog.

Part One – Action & Reflection

Clark starts the book by saying, “The ability to make better decisions is why we learn.” As a gamification designer, I tend to think about everything from the perspective of a game, and it amazes me how this statement holds true for every single game.

We predict/suspect things working a certain way, and then act according to our prediction/suspicion in life as well as in a game. One of the common things in most games and in real life is RNG (Random Number Generators) or randomness, and however you choose to act, the outcome will always be laced with randomness.

Clark goes on to mention that according to a neuroscientist ‘Karl Friston’, “We learn to minimize the gap between our predictions and the real outcomes.”

Therefore, Learning = Better Decisions = Accurate Predictions & Outcomes

So our actions are essentially the calculated predictions that lead us to our desired outcomes.

A great poker player Annie Duke, the author of ‘Thinking in Bets’ would definitely agree with this as poker is about constantly trying to increase your odds of winning the hand through better decisions that you make by learning more about the play styles of other players.

(Oh, the interconnectedness!)

Clark goes on to mention, “Learning in life, I maintain, is action & reflection. We do things, and when we reflect on them, we can detect patterns and build explanatory models that guide our choices.” He also mentions that usually the action-reflection bit isn’t always consciously attained, but when we make a conscious effort to learn through the loops of action-reflection, we learn deeply – that’s how our cognitive architecture is designed.

All Chess Grandmasters reflect on their games and remember all the move sequences that were made by them and their opponents from 20 years back and the nuances of why those moves were made. Expert gamers have always similarly reflected on their games and actions.

While deliberate action reflection makes total sense within gaming contexts and is widely adopted by professional gamers and athletes, designing for guided reflections within learning experiences may get tricky in corporate settings, especially if the problem to be solved for isn’t diagnosed with clinical accuracy. This would be my only bone to pick with Clark.

What I understand from the broader idea of action-reflection is that effective learning transfer happens when we design actions that help the learners become better decision-makers in their role. This has to be supported by guiding them towards reflecting on those decisions so that better decisions and the reason for them being better are cemented in the learners’ brains. A continuous loop of action-reflection would make for a formidable learning experience.

Clark also stresses the idea that the focus of learning experiences should be decisions. He mentions that “What will typically make a difference in performance is the ability to make the right decisions.“ He also goes on to quote one of my favorite game designers ‘Sid Meier’, the designer of the famous Civilisation series who stated, “A game is a series of interesting decisions.” Clark adds to this by saying, ”Good learning is a series of important decisions.”

For those who haven’t played the Civilisation series, there’s no plot as such in Civilisation and yet every campaign has a different path to success, and you make stories that are extremely unique to you. So, Civilisation is essentially a series of game mechanics that, if put together, give you a different story every single game depending on how you play it and what decisions you make.

While ‘Good Learning’ according to Clark is a series of important decisions, can it also be a unique and personal experience every time you choose to go through those decisions to help guide your reflection with a lot more ease? Watch this space for more on this.

The post Make It Meaningful by Clark Quinn – Idea Extractions – Part One first appeared on The Upside Learning Blog.

There is a myriad of factors that learning designers are supposed to consider while designing for deeper learning experiences. The key one among them is ensuring impactful learning transfer, which just never jumped at me, even though it’s a very important topic in the realm of learning design and science.

Only a high-stakes game?

Well, imagine that you’re responsible for training the cadets in the defense forces and you’re supposed to train them on the weapons systems. What if the transfer of learning among the cadets falls short and there are errors in the way the weapons are used? The consequences would be brutal.

Every error in a job that anyone does has consequences, some lighter than others. But the consequences exist. To eliminate errors that lead to consequences, increase the proficiency of the individuals, and drastically reduce the risks associated with the task, it’s important to consider how the transfer of learning happens.

The higher the stakes, the more serious transfer of learning is as a consideration. Just to illustrate this, the research by Fingerman and Wheaton (1978) indicates that there was actually a formula used to calculate the transfer of learning for accurate weapon system usage.

The formula went like this:

Percentage Transfer = T – C / Max – C x 100

Where T = (Trained Group Weapon Score), C = (Control Group Weapon Score), and Max = (Maximum Possible Weapon Score)

The stakes are getting higher with all of our jobs over time. Our workplace performance data is a lot more accessible and in better shape than before. It’s only inevitable that we become more economical with our learning initiatives and efforts. Currently, I feel we’re learning very little from all the content consumption that we’re doing.

So what exactly is learning transfer?

In my opinion, it’s basically a measurement of how well the learner has understood the subject matter to utilize it in the context of their work. It is the intended impact of a learning effort on the job.

Interestingly, there are four types of learning transfers according to Larry W. Brooks and Donald F. Dansereau:

1. CONTENT TO CONTENT TRANSFER

This type of transfer involves easier learning and understanding of certain subject matter from previously known/mapped subject matter.
E.g.: From General Psychology to Abnormal Psychology.

2. SKILLS TO SKILLS TRANSFER

This type of transfer occurs when an individual’s previously known or mastered skill helps the acquisition/mastery of another complementary skill.
E.g.: From riding a bicycle to riding a motorcycle.

3. CONTENT TO SKILLS TRANSFER

This type of transfer occurs when an individual’s knowledge influences the acquisition of a new skill.
E.g.: From learning about computers to learning how to program.

4. SKILLS TO CONTENT TRANSFER

This type of transfer involves the learning of skills that subsequently facilitate the acquisition, retention, retrieval, and transfer of knowledge.
E.g.: From construction of electronic circuits to electronic theory.

How to start considering for transfer of learning and how to better the transfer of the learning you’re designing?

I’ve just discovered this discipline, so I’m still exploring. However, Dr. Michael Allen suggests a few techniques in his book (1) that could help better the learning transfer:

1. Provide feedback from a simulated supervisor or co-worker.

2. Ask learners how they think what they are learning applies to their actual jobs.

3. Create an unreal world.

4. Use job tasks as the basis for lesson design, case studies, and examples, or follow-up projects.

5. Use guided discovery or cognitive apprenticeship.

6. Incorporate case studies and examples that reflect best practices of proficient employees.

7. Provide a variety of examples and problems based on documented events.

8. Use a high-fidelity simulation while training procedural tasks.

9. Assign projects to be completed during or after the class.

10. Space out the time between review periods.

11. Give practice assignments identifying the key features of new situations wherein learners might apply their new skills appropriately.

12. Provide skill-based training at a time when learners actually need it (just-in-time training). Embed the physical and psychological cues of the job into the instruction.

Considering the transfer of learning while designing for deeper learning is definitely a step up from designing purely for engagement. I’m just getting started with incorporating this concept in the learnings that I’m designing – I guess it’s never too late to start.

After all, good knowledge transfer seems like an important link that separates novices from experts. Research has now found that experts in most fields are differentiated from novices not by their strategies but by their rich stores of knowledge. (2)

Well done to you for getting to level one of Transfer of Learning! See you at level two soon!

References:

1. Michael Allen’s Guide to e-Learning: Building Interactive, Fun, and Effective Learning Programs for Any Company

2. How People Learn: Brain, Mind, Experience, and School

The post Transfer of Learning: Level One first appeared on The Upside Learning Blog.

Elizabeth and Robert Bjork, who coined the phrase “desirable difficulties,” write that difficulties are desirable because “they trigger encoding and retrieval processes that support learning, comprehension, and remembering.”

Unlike Vygotsky’s Zone of Proximal Development, which is eerily similar to the concept of Desirable Difficulties, Robert Bjork states that in order to improve fast, the teachers should use and practice retrieval with the methods of spacing, interleaving, generation, etc. individually or in a combination to get the best learning results.

This does make learning an extremely stretched affair, however, with the improved knowledge retention over longer time periods, it’s an efficient strategy compared to its alternative, which is learning in blocks and testing the knowledge.

Now, you may think that in a modern workplace, desirable difficulties is just the usage of various retrieval methods and you’re sorted with your learning design. Well, from whatever I’ve understood, it’s not that easy.

Desirable Difficulties is inherently about slowing down learning, like how we slow down to move fast in business and life. It’s a similar philosophy that we have to employ while designing with desirable difficulties.

Not only do we require clarity about the business and the need for learning, but we also need to understand and experiment with new ways of how learning happens, new scientific ways instead of previously, mutually accepted and agreed upon ways of learning that are barely relevant today.

We also have to fend off the desire to constantly stay in the now – newer technologies have devised a way to keep our attention by feeding us everything that’s happening in the now, without letting us process the events of yesterday. So, limiting half-baked knowledge snacking.

Employing Desirable Difficulties is about walking the thin line of everything between what was and what is, and all of it to improve performance. Well, it’s difficult to implement – and desirable because of its promise of improved performance.

How does it work?

My answer would be – difficultly.

Bjork considers three retrieval practices in spaced, interleaving, and generation to aid desirable difficulties. I will take the liberty here to add a few more in the form of reflection and elaboration to expand on generation along with calibration to adjust the spaced and interleaving.

Learning designers need to use these six techniques – creatively to not just deliver knowledge through a learning event, but also ensure practice over a long period for sustenance of performance.

The closest phenomenon that could explain this would be to think of it like how marketers plan their marketing campaign. They figure out their audiences, build a message funnel to guide their audiences through the various digital experiences, and deliver value to their audience – from top of the funnel – SEO and AdWords to bottom of the funnel – audience purchasing and leaving a nice testimonial. Every stage is meticulously planned and executed and the data that they get from every iteration of funnel usage is utilised to improve the experiences of the audiences.

Different companies have varied marketing funnels to suit their needs. Similarly, different organisations will have varied learning needs and requirements; some may want to improve the skill stack of their entire organisation, some might want to improve their leadership.

There’s no secret sauce with regards to ideal duration or spacing; learning designers will have to experiment and design the campaign experiences from the learning transfer events in the beginning with high feedback to practice interventions with lower feedback towards the end of the campaign, with the six learning tools mentioned above, till the data suggests that certain level of mastery has been attained by the learner in that subject.

It sounds overwhelming – but once put into practice, it may yield special results and that’s the promise that makes it desirable. Maybe, it’s time to experiment by making learning a slow, drawn-out campaign, rather than just making a learning event out of it for better performance.

The post Desirable Difficulties: Making learning slow, to improve performance fast first appeared on The Upside Learning Blog.

One of the prominent strategies that many good learning programs utilize, is the idea of starting with questions / challenges / situations that force you to think deeper about that subject and create a sense of intrigue and motivation for you to learn more about it.

This intrigue and motivation could also be generated organically when you realize that you can’t solve a particular business problem without knowing the details of certain other subjects. Ex: I realized extremely late into my gamification career that there aren’t any great ways to measure the effectiveness of gamified learning programs—which led me to learn more about data, which in turn provided me a direction to now measure the effectiveness of gamified learning programs.

So, whether it’s done organically or inorganically, intrigue and motivation could be generated right at the very beginning—by going through a challenge that makes you contextualize and think deeper about a particular subject. Post the challenge, the content presentation could be done to fill the gaps and holes and the learner walks away with a lot more than a traditional content presentation.

Challenges thus become the trigger to learn deeper, better, faster, and they also fuel curiosity.

Here’s something interesting that Dr. Michael Allen does with his designers—I call it the Switcheroo post the first prototype—where the testing comes first and the telling comes second.

‘Getting novice designers to break the tendency to begin their applications with a lot of presented information (telling) is not simple. Indeed, almost everyone has the tendency to launch into content presentation as the natural, appropriate, and most essential thing to do. I have been frustrated over the years as my learners and employees, especially novices to instructional design, have found themselves drawn almost magnetically to this fundamental error. I have, however, discovered a practical remedy: After designers complete their first prototype, I simply ask them to switch it around in the next iteration. This makes content presentations available on demand and subject to learner needs.

Just a slight alteration of an instructional approach often makes a dramatic difference. This is one of those cases. There is very little expense or effort difference between tell-and-test on the one hand and test-and-tell on the other, but the learning experiences are fundamentally different.

Learners in well-designed test-and-tell environments become active learners; they are encouraged to ask for help when they cannot handle test items.’

If you think about these challenges, they could be a simulation, a puzzle, or a game that tests you or even just plain multiple-choice questions—the point is to challenge the learners.

The difference between the percentages of games that do Test-then-Tell onboarding vs. the percentage of courses that do the Test-then-Tell is too high, even in 2021.

We need to create two extremely important feelings in learners before we prime them for learning.

1. Intrigue/Interest/Motivation to buy-in to the idea of trading their time for your content.
2. Creating an ‘Aha! Now I understand it’ moment and not ‘I figured it out’ moment, before they even begin sifting through the content.

These two feelings are foundational to the idea of Test-then-Tell or Solving before Learning. I feel that using puzzles to test the learners at the beginning makes for a perfect/ideal solution. Puzzles, take for an example, even a simple crossword communicates a lot! A puzzle is never just a puzzle. It’s a communication of an idea: especially a complex one from the designer to the player. And solving the puzzle is the players way of saying “I understand”.

Solving puzzles over a period of time will make you realize that there’s a stark difference between “I understand” and “I’ve figured it out”.

And that is exactly what puzzles give you! It gives you the opportunity to create, “I understand” moments before the learners actually delve into the content that dives deeper into that subject, which learners now are already motivated for. It gives learners the first meaningful win, even before they begin going through the content.

‘Trying to come up with an answer rather than having it presented to you, or trying to solve a problem before being shown the solution, leads to better learning and longer retention of the correct answer or solution, even when your attempted response is wrong, so long as corrective feedback is provided.’

‘Knowledge is more durable if it’s deeply entrenched, meaning that you have firmly and thoroughly comprehended a concept, it has practical importance or keen emotional weight in your life, and it is connected with other knowledge that you hold in memory.’

–Make it Stick

And this is exactly what Solving before Learning attempts to create, a more durable, deeply entrenched, and meaningful comprehension of the knowledge that is presented. It is something that can only be achieved by inverting the way we design courses. The challenges – organic or inorganic ultimately also help solve for performance goals of the individual and the organization.

The post Solving before Learning: A Case for Inverting the Way Courses are Designed first appeared on The Upside Learning Blog.

One common thread that connects my deep personal choice to learn those subjects was inspiration — something, someone, some event inspired me to explore and learn more about those subjects.

David Perell mentions that there are two kinds of learning, one that happens to avoid failure in life — which is a fight or flight response through learning. It’s useful, but maybe not enjoyable, so it’s not sustainable. However, the second one is learning because you get joy through it, it satiates your curiosity. It’s the learning that’s led by inspiration. He also mentions, ‘The way I see it, the need for inspiration inverts the learning process: instead of starting with the building blocks and moving toward curiosity, students start with curiosity and move towards the building blocks. Guided by the light of inspiration, the benefits of memorization become self-evident, and the motivation to learn comes intrinsically.’

How much of the learning that happens in the classroom or through the learning management system is inspiration-led? This question led to another insight.

Teacher centric learning vs student centric learning

It’s unnerving for many to give away control or design learning keeping the learner at the centre of things — like human centred design — learner centred learning has started to take small steps towards its evolution. One of the steps is designing meaningful intentional self – directed learning. The teacher/learning designer is just a mere guide — not an authority in this case. The teacher/learning designer can also become the coach and provide motivational boosts to the learner to continue his/her exploration. Like I mentioned before, with the positives, come the negatives — It might become an intensive, time-consuming approach.

In her book, Evidence Informed Learning, the author mentions that. ‘Learning Designers can help learners to get better at Self-Directed Learning/Self-Regulated Learning through integrating support and guidance into formal learning contexts as well as in the workflow. That way, Learning Designers can help learners to become more conscious of the things they need to consider when learning.’

She goes onto mention that, ‘Learning professionals can invest in measuring Self-Directed Learning/Self-Regulated to give us insight into how learners in the workplace approach their learning, which can in turn help us to figure out how learning professionals can best support them. Examples of Self-Directed Learning/Self-Regulated measurement are questionnaires, self-reporting tools, think-aloud protocols, unstructured interviews, and tracing.

Which leads me to another insight, Learning Designers will have to transform into performance coaches/mentors when Self-Directed Learning/Self-Regulated Learning Practices is chosen as a preferred way of learning.

Learning is like a song

Initially, you’re only attracted to songs that move you emotionally. If they’re catchy, you’ll listen to them enough to get stuck in your head. If the song keeps resonating with you, you’ll learn about the artist and explore the lyrics in-depth. Talk to an obsessive fan and in addition to singing the lyrics for you, they’ll tell you the backstory behind the music.

Learning works the same way.

I hate it when strict directives are provided to me to learn a subject a specific way, it takes me away from exploring the subject and understanding it from its roots, its deepest principles.

Of course — exceptions exist and they may help too. But that shouldn’t take away from the fact that we have systems of thinking, working, and learning that worked great in the age of manufacturing, that are still thriving in the age of knowledge work.

We’re making humans sort of stupid, by taking away their ability to think – independently. Even a box set of Legos is doing that.

Seth Godin decides to frame it differently, “LEGO isn’t the problem, but it is a symptom of something seriously amiss. We’re entering a revolution of ideas while producing a generation that wants instructions instead.”

Instructions Kill Deep Understanding

The instructional designers, teachers, and admins meticulously plan their learning for the learners and the students. They do all the creative thinking so that they can do their bit really well for the apparent benefit of the students, whereas the learners and the students are forced to follow. Isn’t that a sign of toxic relationship? What is the learner or the student getting out of it apart from some instructions to follow?

We’ve constantly underestimated the ability of our learners to think deeply. The limitations on creativity and exploration that’ve been promoted recently will lead to ill-equipped and less dynamic professionals in the real world.

The biggest concern here would be that forced (external) learning would take away/deteriorate the curiosity muscle of individuals that render them to become average learners.

Even though inspiration is hard to define and self-directed/exploratory learning lacks structure, I firmly believe that the learning that happens this way is faster, cheaper, and more effective than other formats.

You can either learn to become literate or you could learn to understand more. Ex: ‘There is the kind of reading that you want just so that you can look at street signs when you’re on the highway and say okay this is Valley Forge Casino — need to get off this stop here but then there’s another kind of reading which is actually being able to grapple with likes of Immanuel Kant’s critique of pure reason’ – David Perell.

While David makes complete sense from an emotional standpoint, he’s not a 100% accurate. Only when the learner knows how to even read the Valley Forge Casino sign, she will, with additional effort, be able to grapple with the writings of Kant.

Evidence Informed Learning the author mentions that there’s a collective understanding amongst the learning practitioners that, ‘Factual and procedural knowledge is extremely useful and also necessary (how can you think deeply and/or conceptually about something that you know nothing or little about?), however, you also need to know when to apply it and how to adapt it to new situations.

Instruction alone, even high-quality instruction, isn’t enough. Learners need to actively participate in the learning process. Without this, they won’t be able to achieve deeper conceptual understanding of what they’ve learned.’

The authors of Make It Stick also mention the following that makes a strong case for exploratory learning. ‘Remember that the most successful students are those who take charge of their own learning and follow a simple but disciplined strategy. You may not have been taught how to do this, but you can do it, and you will likely surprise yourself with the results.’

Maybe we’ve got it wrong, all along. Maybe it’s time to course correct? Have we completely ignored self-directed/exploratory learning or ignored it because of its complexity? What could be possibly be stopping us from enabling this form of learning in our classrooms and workplaces? Why aren’t we moving towards making our workforce expert at Self-Directed/Exploratory Learning within our organisations, especially when there are well documented facts that Self-Directed Learners/Self-Regulated Learners are more knowledgeable and high performers^[1].

Would love to know your thoughts. Please reach out to elearning@upsidelearning.com in case you would like a candid discussion on the forgotten art of exploratory learning.

The post The Forgotten Art of Exploratory Learning first appeared on The Upside Learning Blog.

Being Social: If you’ve played games with your friends, you will realise that playing with friends is a lot more fun than playing alone. Gaming with friends keeps you accountable and in check for your growth, sometimes they carry you and sometimes you carry them. Friends make you want to come back to the game when your interest starts to wane. You happen to learn a lot more about the game world with their knowledge.

Could we imagine learning in the workplace similarly? There are many challenges that one can think of. But, with social systems that have existed in games and designing them for learning would surely help. Learning won’t be tiring and many would get by with a little help from their friends.

Clarity & Direction: Most of the games, except for a few sandboxes and exploratory games have clear and well-defined quests and to-dos. We play as individuals or teams to achieve that goal, beat that level, or overcome the boss and an unending spawn of minions. Even though there may be many to-do’s, we know roughly while playing the game what the beginning, the mid-game and the end-game objectives are. That’s the way level designers communicate and manage to engage the gamers and keep them in the realm of the game world, without their interest levels dropping, until they complete the game, even if it takes upwards of 50 hours to complete.

How many people in the organization do you think to understand the beginnings, the mid-game, and the end-game of the learning that they’re undertaking. Are the quests and the to-do’s even vaguely present for them? Learning without understanding the end-game just doesn’t make sense to me yet, that’s the reality that we are living with.

Speed & Agility: Gamers have this unique ability called ‘pushing’, where they will be able to complete a huge task and progress quickly in unbelievably surprising time. Pushing usually happens to post a session of grinding, which is essentially putting in the grunt work in games.

Grind and Push, with efficient use of the feedback loop available in most games helps gamers complete some real-life tasks with unreal speed and agility.

Could we design learning content and systems that allow for the grind and push in real-life learning experiences? Sometimes, fast progress really motivates the learner to achieve more. This of course cannot be uncoupled from efficient feedback loops.

Mentors & Support Systems: Unlike any other online communities, most of the gaming communities are super helpful, the pro’s who’ve spent a lot of time in a specific game world will spend their time guiding and supporting a novice in that game world (exceptions do exist), gaming communities understand the positive-sum nature of games. There are guilds and parties in games, they help promote a sense of belonging with players and the game world.

If there isn’t a social aspect to games for the pros to guide the novices, there is usually a journal, quest-book, library in a game that guides the player with regards to everything that exists in the game world and keeps them up to date with their progress.

Is there a way to design mentorship and support systems in our learning initiatives in a way that encourages experts to help the novices and encourages novices to ask for help and guidance? Obviously, challenges do exist here with human insecurities and humans understanding this process as zero-sum, but it does benefit everyone in the larger scheme of things.

Of Purpose & Belonging:

Games do a great job of binding players to their broader narrative. Be it overcoming sorrow from their personal life or understanding and knowing more about history or even learning a new language. Games help you eventually find the reason for you playing. Players keep playing till they find their purpose and once they find it, they jump to another purpose. Gameworlds have created environments for the players to be at ease with, to feel a sense of belonging with and that is one of the biggest reasons why games work.

Is there a way to ensure that learning helps the learner bind themselves with their broader narratives? Helps them understand their purpose and achieve what they really desire? Is there a way in which we can look at learning to help learners understand and solve their real-world problems? There won’t be a greater motivator than this.

These five elements through content and systemic gamification could help reshape the way we learn in the workplace along with a host of other mechanics from the world of gaming. However, having said that, there’s no one way to play a game. There are different types of people in this world, with different motivators and different objectives. Everyone is at a unique place and time in their own lives and their journeys are as diverse as they could be. There’s a reason why different genres exist in games, movies, music, etc.

This is exactly where the use of data comes to play. Through traditional data science, we could look at classification models that help us with the recommendation of topics, subjects, skills, media that will help us excel in the workplace in the short and long term. These recommendations could be made basis the parameters that make us who we are and what others like us are doing. This might help us get clarity and directions to our learning initiatives.

Individuals and teams would also benefit from exposure to their learning analytics and would help them set realistic targets, grow and improve their work with their performance. This would make them fast & agile learners, which would help the people as well as the organisation. Learning analytics would definitely help build a decent feedback loop for the learners and many learning initiatives.

Recommendations and analytics aren’t just limited to hard skills that help us perform our workplace tasks with ease, they could also be about the soft skills and hobbies that make us more human.

As far as modern data science is concerned, it may help the learners with predicting their performance in learning as well as in their workplace. With these predictions, the learners could continually fine-tune the way they study and work to achieve higher levels of performance. This could possibly help us push the boundaries of learning and workplace performance with a sense of ease that we haven’t imagined before. Wouldn’t it be nice for everyone to find their own recipe to optimum performance levels in learning and the workplace?

While thinking and designing with gamification and data, we need to ensure that these systems and content are inclusive and equitable. Onwards to a future with better learning initiatives.

The post Reimagine Learning with Gamification first appeared on The Upside Learning Blog.

If only we were given an opportunity to experience it all in the real world.

Let’s first stop thinking that people play games for fun; fun is extremely arbitrary and is difficult to measure. I would be more comfortable with knowing that people play games to fulfill some unmet needs. Games help us access ‘our story’ through ‘our actions’ to fulfil ‘our needs’, and since this is intrinsically appealing to us humans, we are drawn more to games.

“Having looked at more than 20,000 gamers across all types of games, we consistently see that video games are most successful, engaging, and fun when they are satisfying specific intrinsic needs: those of competence, autonomy, and relatedness” – Scott Rigby, Glued to Games.

(All the quotes in this article are from Scott Rigby’s Glued to Games)

Of Competence

We as humans, want our work to be more challenging every day. We want to keep growing to enjoy our work; the more difficult it gets and the more responsibility gets added, the higher the chances are of enjoying that job over a period of time.

We observe something similar in sports as well, sportspersons strive to overcome challenges, they push through pain, reaching their limits to achieve a level of performance that no one else could reach.

We admire people who perform at their peak because there’s an inherent desire for us to become like them. This inherent desire is of competence. (This is why a platform like twitch exists.)

Competence need-satisfaction through games – a term that has been taken from Scott Rigby, measures the competence needs that are satisfied through various genres of games.

A few examples of competence satisfaction features from the world of games:

Competence Satisfaction in FPS Games
Granular: Blood and enemy reaction when hit.
Cumulative: Increase in strength, reputation, and receipt of new weapons and skills as player advances.

Competence Satisfaction in Driving/Sports Games

Granular: Smoke, sound, rumbles, and representational feedback from on-screen meters.
Sustained: The increasing roar of the crowd and other environmental feedback.
Cumulative: Increase in abilities, advancing in tournaments, and improving win-loss records.

Competence Satisfaction in Platform Games
Granular: Constant stream of micro-challenges (e.g., jumping, simple combat)
Sustained: Power-ups; Chaining actions successfully to overcome obstacles and reach new goals.
Cumulative: Game “collectables”, score/points.

(Glued to Games)

Competence satisfaction in a modern workplace

There might be some obvious answers that might pop in our heads while we think about competence in our workplaces, but the question we should be really asking here is do we need to rethink competence in the workplace? especially when the world and workplace are skewing so much more towards knowledge work, towards managing emotions, towards ensuring good mental & physical health, towards ensuring inclusivity ,and towards being environmentally responsible.

Of Autonomy

We’ve all inducted ourselves into a club, a club that loves the weekends and hates Mondays. Collectively, we must’ve published at least one message on social media about our love for the weekend or our hate for the Mondays. There are books, podcasts, social media pages that talk about this, week-in and week-out. It’s become a huge part of our culture.

This club is called the weekend effect.

“Studies looking at the experience of autonomy at work have similarly found that employees ’ job satisfaction and productivity are significantly related to the degree to which they feel autonomous at their jobs and experience their managers as supportive of their autonomy in the workplace. This doesn’t mean that the “boss” is not in charge, but again it means that employees found in their work opportunities to make inputs regulate their time or efforts and that they feel they have a voice when things go wrong. No matter where they are in the hierarchy of the company, every worker feels better and produces more when they experience some sense of control and agency on a daily basis.”

Let’s look at a few examples from the world of gaming to understand how games fulfill the need for autonomy.

RPGs combine meaningful choices with a heroic narrative that inspires personal agency in one’s actions.

Modern simulations excel at providing you with the tools to build a self-directed story, along with enough structure (missions, goals) to not feel lost.

Long-range victory goals in real-time strategy games provide a sense of meaning, while strategy choices are fully in player control. Games that provide multiple paths to victory further deepen player volition.

(Glued to Games)

Autonomy satisfaction in a modern workplace

The modern workplace can borrow a lot from the genres of RPGs, simulations and real-time strategy games to set new standards on how we look at lifelong learning, goal setting, task management, reviewing, growth management and most importantly, to finding a purpose, a mission to make your time more meaningful here.

Of Relatedness

We must not forget, even when we work with the best data models, robot assistants, AR devices and autonomous cars, that businesses are about humans. We are humans ( some debate that we’re part cyborgs) but that’s a debate for another blog. We are humans and “at the heart of all our happy interpersonal moments, both large and small, is the feeling that we matter to others.”

As the great American writer, Elie Wiesel said, “The opposite of love is not hate; It is indifference.” Even during brief moments of interaction with those that we may never see again, we can feel relatedness operating powerfully.”

and that’s why relatedness is important. “We feel related when we matter—when we are acknowledged, when we are seen as significant, and when we get to express to others similar feelings and be understood.”

Let’s look at a few examples from the world of gaming to understand how games fulfil our need for relatedness.

NPCs(Non Player Characters) in many genres of games help you within the game in multiple ways, from just giving you directions to being your partner who stays with you till the end of the game.

MMOs(Massively Multiplayer Online) are multiplayer games where you can possibly interact with each other, trade and help the community. The mechanics of party, guilds etc help you perform tasks together against other set of players who might attack your base, or help each other by slaying a difficult monster together.

Co-Ops is a unique genre of games for relatedness since only when all the players in a co-op synergise and play, you can complete the game.

MOBAs(Massive Online Battle Arena) gained popularity as eSports came to the forefront, MOBA’s help promote a sense of belonging between teammates as they grind and perform together with a chemistry that is unparalleled. The teammates almost become like your family.

Battle Royale a format popularised by Fortnite and PUBG, essentially a last man/last team standing format that brings together the best of MMOs and MOBA.

Relatedness satisfaction in a modern workplace

From trust to teamwork, from being good communicators to being great decision-makers, the modern workplace will benefit from introducing relatedness need satisfiers inspired from the world of games.

Adopting the Gamers Mindset

Learning in the modern workplace is not something that happens in a silo. We, as humans, are complex, every team is different and every organisation is unique. There isn’t a one-size-fits-all solution and context should be treated as of utmost importance. Having said that, I’m almost certain that we will be heading to a place where complexities in learning will increase. The fusion and intersections of multiple specialisations will be in vogue and leaders & managers will have to deal with many more variables than before.

Learning cannot happen the way it always has, it needs to evolve to keep pace with the new realities, and with it, we need to as well. Gamers surprisingly evolve every single time they choose to play and complete their game. We need to adopt the mindset of the gamer to navigate this space and figure how we can design experiences along with learning content that helps fulfill the competency-related, autonomy-related & relatedness based needs of the humans that we’re associated with and with it the needs of our business’.

Onwards to the metaverse!

(Quotes are taken from the book Glued to Games – Scott Rigby & Richard Ryan)

The post How Mindset of a Gamer Help Us Navigate Learning in Modern Workplace first appeared on The Upside Learning Blog.