This article can be read in full at:

https://www.researchgate.net/publication/353451565_Learning_Models_in_Educational_Game_Interactions_A_Review

An archive of all currently available infographics can be found in the Research Infographics page.

The post Educational Games vs Games-based Learning first appeared on Ludogogy.

Understanding Gamification is available on Amazon.

An archive of all currently available infographics can be found in the Research Infographics page.

The post Types of Game Mechanics first appeared on Ludogogy.

And so, the story goes like this: “No one likes to be told they have an ugly baby”. Heavens knows, us game designers regard our games (even very early prototypes) as our babies. Naturally we don’t want anyone saying anything bad about them. And that’s a mistake.

In spite of how compelling this analogy sounds – comparing physical babies [flesh and bone ones] to games we create [brain children] – it falls a bit short. For instance, with flesh and bone babies we cannot take them apart when they don’t perform as expected. We cannot remove features, improve some others and create new versions – someone please explain this to my father. He now has 7 kids and they, us, are not really getting any prettier with each iteration (I don’t have daddy issues… alas, I do).

Something else we are meant to the prototypes of our games that we cannot do to our flesh and bone children is: dress them up in their best clothes, take them to competitions, line them up and let complete strangers judge them and pick a winner, the prettiest.

Oh wait. We do do this. We do have baby beauty pageants. But I’m not ready to open that ugly can of worms at this time.

It would appear that we then need a better analogy. Else, a better explanation as to why we resist, sometimes despise, prototyping our games with strangers.

The reasons we as individuals make decisions and perform activities are complex. These reasons change constantly. Multiple forces simultaneously influence these reasons.

More importantly, these reasons are formed in the unconscious mind. Asking a game designer why they are not playtesting their prototypes is the best way to get the wrong answer.

But look at populations, groups of people, and Eureka. Those elusive reasons turn into patterns. Some of these patterns are easily explained through biases and heuristics.

Ideas are sticky. Whatever thought, conscious or unconscious, we believe is the result of our own making, we will defend viciously. And this is a bias. A very dangerous one for that matter.

A simple explanation about the danger of this bias is that these “original” ideas can be easily implanted in our heads. You, me, all of us can be easily primed to arrive at our unique and expected conclusion. Social media does a great job at amplifying this condition of the human behaviour. But that’s another can of ugly worms to be opened at another time.

Your games. Our games. They all start as ideas. You then invest a lot to take this idea and turn them into physical projects (yes, even digital games). These physical products are now much bigger ideas.

Trends in human behaviour show us that we do not like having our ideas being challenged. We have visceral reactions when we are told point blank “your game sucks”.

Yet, these are biases and we need to find ways to ensure our game is seen and used by other people. We need to seek feedback, collect this data and build it into the design of our games.

In summary, we need to play-test our games multiple times. We need to do this in spite of how loud that little monkey inside our heads screams at us “Your game is perfect as it is”.

Check out Erik’s archive of Ludogogy articles

The post Playtesting and the Ugly Baby Complex first appeared on Ludogogy.

I learnt things the hard way and this article is an attempt to reflect on the mistakes I made while collecting feedback for online games-based learning courses and gamified content. In my experience, the following holds true regardless of the type of content – gamified, storified, serious games, elearning, microlearning or nanolearning.  If you are an online learning designer or just someone who is learning about using online courses, I hope you add to my points to help me and other learning designers become better.

Seeking feedback at the far end of the course

It is very likely that you have witnessed innumerable courses with a feedback link at the very end of the course. There’s nothing wrong with it, but let me pop the bubble for all learning designers out here. This is the most predictable thing you can do with your wonderfully crafted gamified content.

Let’s take a step back

We are here talking about content that is not only educational, but also engaging. This means there should be a healthy dose of unpredictability to it. The obvious problem with this is that many learners may never get to the end, here. If this is the case, you have already lost the opportunity of capturing unheard voices. Let’s also address the elephant in the room – Who is this feedback for? If your answer is – for you, so you can make the course better, that is just one part of the answer.

It is true that after spending hours in content curation and experience testing, as learning designers, we would like to know how we fared. We may also like to jump right in, and course correct in case there are some participants who have shared areas of improvement. However, the overlooked, often ignored part, of this is that a lot of this feedback is for the learners themselves.

Think about it – when they are asked a question such as, “Can you think of an example of something similar from your day-to-day life? “, the learners are really reflecting on how the course related to them. In parallel, for the learning designer, if such a question is being left unanswered, it leaves room for some food for thought. Perhaps, the learners don’t have adequate information to relate it back to their lives, or perhaps this question is too repetitive, or asked too soon.

While asking for feedback at the end of the course is the most used mechanism of asking for feedback, there are several subtle ways to ask for feedback all through the course too.  Here are some of the ways that I have tried, tested, failed and then course corrected. I hope they help you, too.

1. Include reflective questions

Reflections or drawing from past experiences is one of the best ways to bring awareness to what learners already know. As a learning designer, you could use reflective questions throughout the course. An effective way to do so is to use a cocktail of video, photo, multiple choice, and text submissions. This ensures that the feedback does not feel repetitive for the learners. It also adds a layer of fun to questions that can otherwise become really mundane.

2. Gauging engagement levels

Social engagement within the learning group, whether it is through upvoting the submissions made by their fellow learners, or comments, or even based on the promptness of the submissions, voluntary engagement (gauged by minimal nudges) – these are all effective measures of seeking feedback. An alternate way to put this is – if the learners are not automatically gravitating towards the gamified content, despite the push notifications and reminders, it is time to course correct as a learning designer.

3. Social media

Of course, this may not work for all situations. It goes without saying that most people are on at least one social media platform. Encouraging opportunities such that learners can share their experience on social media platforms of their choice, using unique hashtags given by the learning designer, is a wonderful way of creating a community that engages in playful way of learning.

Furthermore, if the course is designed to be an open course, this may even create a positive spiral that attracts more participants.

4. Difficult questions

Most of the questions for seeking feedback are usually implemented in the form of a scale ranging from 1-10. The questions reading as – ‘How would you rate your experience?’ There’s no doubt that this is a great starting question but what about asking difficult questions such as “what made you skip a question?”, or “Would you still take this course if your organization did not make it mandatory?”, Or “Did you ever think that this course is not worth your time?” These are the questions that can help elicit real feedback. As learning designers, you want participants to look at the course objectively.

5. Crafting the right questions

As a learning designer, you should consider keeping a mix of questions that are multiple choice (like a star rating), and specific open-ended questions (such as “How you will apply the learning in work / life?”)

Creating a mix of questions will ensure that the learners don’t feel overwhelmed and interrogated, and yet feel heard.

6. Go beyond asking questions just about the content

To a learner, the course is an entire package from registration, payment, ease of access, ease of navigation, to the elements of gamification such as the points systems and badges, etc. Hence, there need to be questions that capture each pain point that the participant may have felt. Even those participants who were not able to access the course at all, should be able to reach the learning designer and provide feedback mentioning their difficulties.

7. Critiques are equally important

If all questions are worded to seek positive feedback, such as “How this course has helped you?” or “What will you do differently?”, learners will automatically let you know *just* that, or skip the question altogether (marking an N/A and moving on falls under this bracket too.) However, asking open ended questions about what the learners would want to change, or what the learners did not like in the course, are good ways to collect feedback that truly helps you design better courses.

8. Personalisation

An abrupt question at the end of the course is the worst way of ending well-curated content. The learners have spent time in engaging with the content. This is especially true if the content is spread out over a few days/ weeks. Hence, it is important to take a moment to acknowledge all the time the learners have devoted to the content. A note that is personalised to that group of learners is a wonderful way of letting the learners feel valued.

Conclusion

Personally, I love going through every feedback that I receive for the online gamified content, and I take the time to reply to each one. It is worth the time and has been my biggest mentor and constructive critic. In case you are not a learning designer but a consumer, please know that as learning designers, you are our greatest strength and supporters. And I really hope that you are able to share candid feedback each time you take up an online course.

If there is anything that has helped you, I’d love to hear your views. Know that I value each and every feedback, regardless of whether it is positive or not.

The post How To Collect Feedback For Gamified & Digital Learning first appeared on Ludogogy.

The Ubuntu Game is a physical and virtual board game designed to teach teenagers the wonders of diversity, inclusion and equality as well as empowering them to discuss critical issues facing us as a society like climate control, overfishing of the oceans and sustainable farming.

It does this through game play that challenges its players through questions, conversation, collaborative activities, experiential media (videos and virtual reality) and discovery about themselves, their beliefs and their likenesses and differences through culture, race, creed and other differentiators.

Today’s Teens are Problem Solvers

At Ubuntu Game we believe today’s youth are smarter, more opinionated and have greater access to information and therefore greater capability in thought processing and problem solving than any prior generation. Because of this, it is essential that their viewpoint on board game design and even their direct input be cultivated and encouraged. The majority of board games are designed by white males who dominate the space but also restrict its diversity, a known industry issue.

To combat this limited view in design, we released a beta or Minimal Viable Product (MVP) version of our game, designed to be played by beta customers to garner feedback and constructive improvements towards the game. It is a generally accepted practice that an MVP is a preliminary beta product with some clear cut shortcomings that can be iteratively improved or even pivoted on, depending on the nature of the feedback. Ubuntu Game solicited direct feedback from teenagers playing the beta game themselves.

With the success of the Ubuntu Game directly tied to the power or quality of our questions, our questions were derived from a diverse collection of young and older team members, some of whom were well versed in the diversity/inclusion space. We plan to crowdsource our game content and all-important game questions through our players ultimately.

This initial vetting of the game is all typically part of a lean startup or EXO initiative, which we adopted during the formative stages of Ubuntu Game to validate what we were doing.  In the EXO framework, much up front thought is given by the game developers towards identifying the Massive Transformative Purpose or MTP. What is the critical impact the game will have in a positive way?

Our Massive Transformative Purpose

With Ubuntu Game, our MTP was to create a movement where diversity and inclusion and equality became the norm in the world to counter the recent outbreak of derision, bullying, racism and marginalization that bubbled to the surface due to Black Lives Matter and other incidents.  This is considered alongside the specific problem which is being solved and how our game can solve the problem. Finally, of course, it makes the mechanics of the game much easier to design.

We felt that the route we wanted to take was getting teens into conversations to explore and discover their differences and to better understand and accept them. Initially, our focus groups validated this hypothesis as a core approach to diversity and inclusion understanding! This allowed us to formulate a Value Proposition Canvas to sketch out the benefits and problems solved by our game.

Within the game, we built online questionnaires and surveys to obtain feedback from game players to improve the game. We also had a Breakthrough Wheel which each player spins at the game’s conclusion,  to determine what was their top takeaway from the game, their biggest personal breakthrough, or who they would like to share something with that they learned from the game.

In addition, they may be asked “What would you do differently after today’s game, or what action will they immediately take after today’s game?” or “What discussion will you have with your parent(s) after today’s game?”

Sharing as Learning

This is all intended to memorialize or anchor the key impacts or impressions from the game for each player, and to get them to verbalize it so that it becomes more present to them. Given the game play is a shared experience with other game players, this sharing can lead to significant breakthroughs and discovery by players.

This learning process sets the players up to look forward to future play sessions and clearly places their shared peer experience as a paramount feature of the game. The crystallization of the game’s outcome for the players makes them more mindful of their own growth, which is perhaps the game’s most important objective.

In conclusion, getting young adults to talk about their experience, contribute to the game’s content and seeking their ongoing feedback is what sets Ubuntu Game apart.

HOW THE UBUNTU GAME IS PLAYED

Players traverse the board using mini cultural icons by rolling a die. They land on spaces that trigger questions and conversations in six categories that matter, including diversity, connection, understanding our differences, our similarities, controversial topics and fun facts.   A mobile app is used to add context, enlightenment or information to kindle the conversation. Players can play as individuals, as pairs or teams. Some players will spin to see what kind of barrier to play they will experience.

Virtual and Augmented Reality

Additionally, players will get to role play as “Avatars” and see themselves, literally, through a Virtual Reality experience, as someone from another culture, creed or place in life. Augmented Reality with accentuate some of the images they’re familiar with in their surroundings.

Players will also participate in activities, one on one or with the group, solving riddles about society and diversity, work collaboratively towards a common goal or even just have fun pitching in together to make a recipe!

The game is over when every player reaches the end of the board. The player, pair or team with the highest score wins. Winners get to spin the “Breakthrough” wheel landing on various options to explain what’s changed in their perceptions and what actions they will take.

Read Richard’s other article about Ubutntu game and watch the play session.

The post Debriefing and Feedback for Ubuntu Game first appeared on Ludogogy.

At the end of a training serial, tank commanders will immediately conduct a ‘hot-debrief’, discussing what went well, what went badly and how they can improve next time.

After several serials the commanders congregate in a trailer and watch video analysis of their performance. Data is gathered throughout the process, everything from exact grid locations to radio chatter snippets.

Throughout the process, there is always a frank, honest and open discussion between the team which doesn’t seek to apportion blame, but simply wishes to be better next time.

These discussions are guided by an external facilitator, but the direction of the discussion is dictated from within.

Within this dynamic the data is the essential building block of accountability, it takes the debate beyond what happened (we can see that, live and in real time) and moves into why it happened – because when you understand the why you can make different decisions in similar situations.

So how can this translate into the Corporate Environment?

As an Army Officer, turned Escape Room Designer I’ve always been fascinated by how the participants interact within our experiences – why certain participants speak continuously or why some of the best puzzle solvers say nothing at all.

We knew that what we were observing was immensely valuable; it was gamified, visual, and showcased teamwork at its very best (and worst) but we needed to understand what we were seeing. By working with Michelle Mills-Porter, a leading behavioural analysist, to understand what was going on within the room we learned that individuals were showcasing their core behaviours.

So how to design an experience which would provide us the best data

The crafting of the experience needed to reflect the problems teams encounter during their working day, allowing the gamified data to prompt team action towards actually achieving tangible change. This was done through the design and implementation of ‘loops’ – specific puzzles and challenges which showcase individual and team dynamics.

We use a wide range of loops, for example:

Time: Of course, the experience is timed, but we also introduce timed challenges within the overall experience, forcing teams to hit tough deadlines – only achievable by managing their priorities.

Asymmetric Communication: ‘I know something you don’t know’ – by sending some individuals out on tasks which are outside of the room, participants rely on their communication via radio to achieve team goals.

Collaboration and Prioritisation: Elements of the puzzle cannot be solved without participants working together, but to achieve all group aims, teams will need to understand where their and (more importantly) where their colleagues’ skills lie.

Of course, there are many more, which gives our facilitators the opportunity to select those most relevant to the team.

And so to feedback

The experience is filmed throughout, we have an analyst on site who observes in real time and can provide the feedback that day or, if client time allows, we can come back the following day armed with more information.

The headings are delivered by us; based on the data we have observed, but the discussions are led by the team – it is critical they find the solutions to where they’ve been going wrong together, whilst also highlighting group successes.

We’ve seen transformational moments during this process; incidents of participants being spoken over, despite having the correct solution and then not proffering this again. It is not a gigantic leap to suggest this may be happening in the work environment.

How to confirm the change

Though this process is transformational, it is critical that actions are agreed on. We base our workshop on how different personality types prefer to be communicated with – from youth we’re told to ‘treat others as you would wish to be treated’ why not go on step further and treat them as they wish to be treated.

To showcase the power of this change we mix behavioural types and use immersive VR exercises to practise these skills, so that participants leave having understood the power of their words and behaviours.

The post Feedback – Creation and Delivery through Live Experience first appeared on Ludogogy.

The pandemic, however forced us to think about taking these workshops online, initially with the idea of improving engagement and seeing how close we could get to “the face-to-face experience” (see this article from Kanban Zone. What we discovered, though, was that we could make the de-brief and learnings from the workshops extremely relevant and engaging, and thus more convincing, in an online setting.

Light-bulb Moments

The debrief part of all of these games is designed to give an epiphanising “light-bulb” moment where participants suddenly “get” the idea. However, many of the explanations rely heavily on data, and it is often tricky to calculate this data quickly enough to replay it in the debrief. Hence, we must use either use stock datasets and graphs to illustrate the concept or have a break while we do calculations and draw graphs. The former doesn’t always convince, however, and the latter leads to us “losing the moment” which lessens the impact.

Taking the workshops online necessarily meant writing software, and that gave us the opportunity to do any data analysis in real-time, based on the actual behaviours of the participants. We quickly realised this was much more relevant and convincing. Sceptics can easily argue against stock datasets, but it is much harder to do so when the conclusions are based on their behaviour in a game they have just played.

We saw a great example of this when playing the No Estimates game at the recent Agile 20 Reflect conference. The No Estimates game demonstrates that estimating is futile, as it is impossible to do it accurately – quite a big mindset change for many people! In the game, we give players more information (e.g. the exact number of tasks to do, and the effort required for each task) than they would have in real-life, so they believe – as they are convinced they can estimate 100% accurately in real-life – that they will be able to do the same in the game.

The image below shows, for two of the teams in the game, their initial estimate, their estimate for the first 11 tasks, and the final number of days it took to do the. As you can see, even though both teams took the same amount of time – 40(ish) days – and had exactly the same information to start with, their initial estimates were wildly different.

Showing this information is much more convincing than saying “typically, people’s estimates are up to 50% out”, and is the first step towards dismantling participants belief in how accurate their estimates actually are.

The reason that estimates are always wrong is that people make many, many assumptions when estimating. Merely pointing this out never convinces anybody, but if we use the actual game data, we can demonstrate this very powerfully. As an example, there is an implicit assumption that bigger tasks will take longer. In the game, we can demonstrate this is not the case by showing the correlation between task size and time taken, as for one of the teams here:

A correlation of 1 means the bigger a task, the longer it will take. As you can see, this is far from the case; 0.49 is quite low. If we plot a distribution of the size of tasks, and how long they took, we will often see very small tasks taken longer than very large tasks. Again, showing this for the actual work the team has just done in the game really highlights this incorrect assumption.

In the face of these challenges to people’s prowess in estimating, one thing they often say “but we know there are variations, so we use an averages and standard deviations to give a range”. Unfortunately, to do this kind of statistical analysis relies on a normal distribution of data, and this is also an incorrect assumption. The game data comes to our rescue to demonstrate this as well. Here is the distribution of how long tasks took for two of the teams in the game

As you can see, neither is close to a normal distribution, so using mean and standard deviation is invalid.

There are many other graphs and datasets we show to highlight incorrect assumptions, but we finish the game with this real light-bulb:

This is a monte carlo simulation showing how long it will take to do N task in the future. It allows us to answer the question everyone wants answering when estimating – “when will it be delivered”. This is the real light bulb moment; given how you just performed in the game, we can predict when 100 tasks will be completed.

And this is the real power of using the real game data. Using the actual data that players have generated themselves, we have not only come to objective conclusions about their incorrect assumptions, but we have also given them tools to rectify the situation that they can use in the real world. We have come full circle; we started by stripping the situation right back to isolate the concept in a game situation, and have ended by demonstrating concepts and techniques that are applicable in the real-world.

We can see the contrast when using real data if we look at another game we implemented – The Coin Game – we haven’t yet implemented the real-time data features, so we just show the graph we usually draw in the face-to-face version of the game. This shows the amount of value delivered (y-axis) over time (x-axis).

This does get the concept across, but how much more convincing would a graph be if it showed the actual amount delivered by participants over time? We could even show the curve developing in real-time as the game is being played to really ram home the point that it is always better to deliver the next highest value items first.

One of the main reasons we brought workshops online was that they are really improved if played in a number of teams; the competitive element gets participants concentrating on the game rather than thinking too much about the concept, and this makes the light-bulb moment even more of a reveal! Break out rooms allow us to re-create this multi-team atmosphere online, but it also allows us to take the concept further; teams can play asynchronously – in different time zones, on different days – making scheduling easier, and, with some games, we can trend performance and scores over time to demonstrate improvements and changes. Again, all this is made possible through the recording of game data.

Online workshops have really given us an opportunity to use real data, in real-time, to convincingly demonstrate complex concepts to often sceptical participants, and has revolutionised how we present our learnings and feedback.

Check out Corrado’s Ludogogy author archive

The post Engaging and Relevant Feedback from Online Agile Workshops first appeared on Ludogogy.

Enter Rocksmith!

Rocksmith is a game which claims to be “the fastest way to learn guitar”.

Load up the game, plug your guitar into your computer and play a song. The game detects the notes you play, and when you play them. It then gives you feedback to help you learn and improve your performance.

Amazing concept right?

I found playing Rocksmith to be an incredible learning experience, particularly as a beginner. There is a lot of inspiration to take from Rocksmith on how to make learning more fun and engaging. Here are two insights along with one caution/consideration!

Let’s start with a couple of areas where Rocksmith rocks.

Adapts to the Learners Skill Level

What makes someone feel like a rockstar? Help them feel like they are smashing out their favourite songs as soon as possible.

Rocksmith has a feature called ‘Dynamic Difficulty’. The difficulty of a song adjusts based on how well you are playing it. When you start out a new song, you are only given 10-20% of the notes to play. As you get better the game adds in additional notes. It also removes notes or segments you find tricky. There are elements of scaffolding at play here too, including built-in videos and mini-games to learn more complex skills. ‘Dynamic Difficulty’ works a treat at creating engagement, even though there are some issues about developing bad habits (which I’ll cover later)

Why ‘Dynamic Difficulty’ creates engagement? Flow Theory

The elegant model from Csíkszentmihályi shows when you get the match between challenge and skill right you can enter a flow state. It’s a beautiful place to be, where you become “completely involved in an activity for its own sake.”

Because the challenge in the game frequently adapts to meet your skill level it creates lots of moments of flow. Whilst I haven’t (yet) mastered playing ‘Seven Nation Army‘, I could start playing parts of the incredibly distinctive and catchy riff pretty quickly. And you know what? That feels great and that creates a motivating effect to continue to improve.

Insight: How can you create more moments of flow for your learners?

We’ve all been there as facilitators. When some of the group are going blazing fast, and others are finding things tricky or prefer going slower. This causes problems for both parties. The ‘faster’ group start getting bored, distracted, checking e-mails. The ‘slower’ group feel the pressure to keep up and can feel less adequate. It’s a lose/lose. Whilst it’s fairly common practice to flex difficulty at the program/workshop level, how can you go beyond this and better flex challenge within your programs/workshops to suit the diversity of every learner you work with?

If you can find ways to create ‘Dynamic Difficulty within your programs, you’ll create more moments of flow. And that’s good for building learners confidence to apply learning back in the real world.

? Make Practice Rewarding for Learners

How do you really become a rockstar? Practice. Lots of practice.

But for most people practising the same songs and notes over and over again can get pretty tedious.

Rocksmith has two clever features to help overcome this problem. Firstly it gives you a mastery score for every song you’ve played. You only need to improve your mastery by .1% to feel like your practice is making a difference and you are improving. And this keeps you playing the same songs over, and over, and over again. It’s a great feedback loop!

And when you get stuck on a tricky segment or can’t improve your mastery score? ‘Riff Repeater’ is here to help. ‘Riff Repeater’ allows you to isolate individual segments you are struggling with, it then allows you to slow those segments right down, and repeat until you’ve mastered them, before gradually ramping up the speed.

When I hit 100%+ mastery on La Sera – Love That’s Gone, (which has a lovely, melodic, yet simple bassline), I got a tremendous sense of satisfaction which immediately made me want to get 100% on another song.

Why is creating a sense of progress and mastery is so important? The Progress Principle

Professor Teresa Amabile and Steven Kramer wrote about “The Progress Principle” in their book, which is also summarised very well in their HBR article “The Power of Small Wins“. The essence of the principle is that making progress, however small, can increase people’s motivation and happiness.

Couple this together with the universal need people have to improve and attain mastery over tasks (Self Determination Theory, Deci & Ryan) and you can see how giving learners visible signs of progress that relate to their mastery is so powerful.

Insight: How can you create a better sense of progress for your learners?

Most people find it challenging to practice new skills back in the workplace, outside of the training environment. Part of the issue is that practising in the workplace feels high-risk for most people. People don’t like messing up and feeling foolish in front of their team members. And this is why creating psychological safety is so important. If there is a high level of psychological safety within your team/company, then people are going to be more willing to try something new, take a risk and be okay with messing up.

From a learning design perspective, this is where it’s essential to think about the whole learning experience and not just the workshop. And this is where many learning programs fall short in my opinion. There usually isn’t enough opportunities following a workshop for learners to repeat and practice their skills. The AGES model by the Neuroldership Institute covers off the key principles for effective long-term learning. Here are some examples of how you can easily build in more practice and a sense of progress in your learning programs:

• Take one of the activities used as part of of a workshop, and repeat it again at a team meeting
• Schedule in micro sessions which are just about creating safe spaces to practice and try out new skills, rather than learn and new theory or concepts
• Set skills-based challenges every week/fortnight which require learners to apply the concepts they’ve been learning about. Start these off nice and easy and incrementally make them more challenging.

? How Rocksmith Hits the Wrong Notes: Picking Up Bad Habits

“I guess I got a bad habit, and it ain’t goin’ away, yeah”

(Offspring, Bad Habit)

Whilst the game gives you tons of feedback, this feedback is focused on if you hit the notes at the right time, not how you do it. So it looks at the outcome, not the process. And when learning something new, the process is the most important thing to really focus on.

I may be hitting all the right notes and the right time, but it can still sound bad (and from experience it does!). The game tries to get around this with in-built lessons. But in reality, I have picked up poor techniques from self-teaching, especially in search of trying to get a higher score.

And whilst ‘Dynamic Difficulty’ is generally well implemented, sometimes you pick up bad habits to learn the easy sequence, habits which are hard to unlearn when you need to play the harder sequence. Some point soon I will need to get a teacher/coach to help me focus on technique and take my performance to the next level.

Consideration: How do you support self-paced training with coaching, mentoring and peer support?

With the continued rise in the demand for self-paced learning, companies need to carefully consider how they integrate coaching or mentoring support into the learning experience. This is to help with learning transfer, but also to make sure people don’t pick up ‘bad habits’ through misinterpretation or misunderstanding.

Similarly pairing self-paced learning with some group-based coaching can help amplify the online self-paced learning experience. Firstly it provides a great space for people to discuss the materials they are learning. And secondly, it adds a layer of peer accountability to the process which can be useful to drive completion and application of learning.

Make Your Learners Feel Like Rockstars

I’ve really enjoyed taking my bass guitar ability from nil to beginner. And a large part of that is due to Rocksmith making me feel like I could play and that I wasn’t completely incompetent.

The other beautiful gift Rocksmith has given me is the discovery of tons of new music and genres I ordinary wouldn’t have known about or thought of playing. By playing Rocksmith I have developed a love for Garage Rock and Blues Rock (go The Strokes and Black Keys). This is actually remarkable given my very narrow taste in music pre-Rocksmith!

The post How to Make Your Learners Feel Like Rockstars first appeared on Ludogogy.

It’s been challenging, but it has also resulted in a great deal of innovation, and discovery of new techniques and possibilities on the part of learning designers and facilitators. For example, many have discovered that learning games and playful activities are effective ways to deliver learning if you are required to use ‘online’, rather than a classroom setting. Along with that, many have also found that this brings with it enhanced opportunities for data collection and analysis of learner decisions and actions – which, in turn, effects opportunities for more detailed debriefing.

But, is there a difference between debriefing games and other kinds of learning activities? I would argue, No, and Yes.  While the skillset is largely the same, the richness of the learning which comes from games and play, comes not only from the experience the learners have while playing, but also from the broader, and deeper ways in which the experiences can be mined for insights, by a skilled facilitator.

Questions

The most fundamental tool in a facilitator’s toolkit is the question. Effectively, their job is to ask the killer questions (which they have carefully honed to elicit the most effective insights) and then get out of the way while the learners reflect and learn from their own responses. Games allow for different questions (or rather, for different levels of reflection in the learners’ answers) than other learning activities, because the learners have just ‘lived’ an experience which allows them to explore the learning domain, rather than being told, or reading or hearing about it. They have, probably, solved problems to attempt to ‘win’ at the game, and have undergone a time-compressed version of exercising a particular skill or piece of knowledge.

Compare the two learning scenarios. In one, learners have watched a video where an individual talks about their experience of leadership in a large company. In another, they play a game where each of them has taken a turn at leading their teammates through a set of scenarios, evaluating data, making decisions, being presented with the impact of those decisions.  Instead of asking ‘What did they do?’ or ‘What did you think of that person’s actions?’, we are able to ask ‘What did you do?’, ‘Why?’, ‘What would you do differently next time?’ ‘What factors did you consider?’ … and so on.

What’s the Score?

One prominent feature of games and game-like activities is scoring. This is even more marked in digital games, where the possibilities for data gathering are limitless. ‘Scoring’ can be much more than a final count of points to see who ‘wins’. Measures can be kept throughout a game including player level (and corresponding capabilities), ‘spendable’ points such as units of effort or currency, fluctuating scores of success on different metrics, and quantity of ‘territory’ held (non-exhaustive list)

But these are just data, and it is the facilitators job to draw out the insights from them. This is perhaps the most marked difference between facilitating debriefs of games and other activities. Facilitators must themselves be familiar with what the data signify and plan questions which will allow learners not only to reach conclusions but also to practise skills in data analysis. It is by no means certain that these skills will exist in the learners, so facilitators will often have to adapt their questioning on the fly to work with the learners’ existing level of competency and scaffold their learning to reach higher levels of skill over the duration of the game.

Failures and successes

Failing, in a safe space, is an often quoted benefit of using games for learning. While this can be thought of as being largely about the psychological safety of learners (or physical safety of themselves, and others, if the learning is on a safety topic), it is something which should be a major resource for the facilitator.

Failure is a great teacher. The games-based learning facilitator must become skilled in getting learners excited about failing. One real danger is that learners become disengaged when they ‘lose’, especially if the game is a competitive one. It must be made clear, through facilitation, that winning at the game is not the same as winning at learning.

One way to do this might be to gamify the debriefing, so that there are visible measures of ‘winning’ at the learning too. Peer assessment of the quality of insights shared with the room is a good way of doing this.  The facilitator can also give greater attention to questioning the insights that emerge from failure, to emphasise the value that is derived from it.

Competition and Other Attractors

Competition has to be treated cautiously, for the reasons stated above. One of the benefits of games is that they engage, so we must be extremely cautious of losing that benefit when people fail. Competition is also an aspect of games which appeal more strongly to some player types than others.

If we are going to use play and games, we should be aware of player types and the particular aspects of play they find attractive, not only while designing and delivering the play experience, but while debriefing it. Using a player type model such as Marczewki’s Hexad and a model which evaluates gamified experience, such as Yu-kai Chou’s Octalysis framework, will allow you to plan your debrief with different player types in mind.

If the play experience itself favours particular player types, you can use the debrief as an opportunity to cater to the needs of the other player types. For example,  players who value the social aspects of the experience could be drawn out with questions which focus on the value of social interaction or utilising people skills in how they approached their play strategy. Those who are rewarded by the exercise of creativity would enjoy the opportunity to share how they worked to find creative solutions.

All learners will benefit from a debrief that gives space for the strength of all player types to be expressed and analysed.

Storytelling

Many games include a narrative element, and all games, I would argue, allow players to construct their own narratives of how they interact with the game. Even really simple games will allow learners to answer the question ‘What was your strategy to play this?’ with a story about their thought processes, or if the game itself has an embedded narrative, to continue the story of the game with their own point of view and ‘plot twists’.

Storytelling holds a special place in our repertoire of learning activities because of the specific cognitive impacts that it has. Among these are greater emotional impact than other types of communication and an enhanced likelihood of persuading the listener. Not only that, but research show that the brain waves of those listening to a story can start to synchronise with those of the person telling it. Stories can enhance empathy, help us to see things from another person’s perspective and result in shifts of core values which persist even after the story is over.

Facilitators should think carefully about how to couch their questioning so that they maximise the potential of learners responding in a narrative way.

Moving Forward and Hypothesising

Along with the ‘safe space’, games are excellent for providing opportunities for ‘do-overs’. In conjunction with failure, being able to try again with a different strategy, or being able to play the same scenario with slightly different parameters, gives us a chance to learn that rarely happens outside of a game setting.

Inviting learners to hypothesise about future results and then to evaluate how well those results match their hypothesis is an effective way to get learners to be active in their learning and to think seriously and deeply about how they are going to play, rather than just ‘winging it’

Games without a Facilitator

While this article has focused on the (cautiously optimistic) idea that we will be moving back into physical learning spaces with our learners, we should also consider that this may not be the case.  The pandemic is far from over, and also, as we know, cost-saving has always been something that clients of learning providers have always been particularly keen on. Having realised that learning can be done remotely, they may wish to stay there.

Many of the things discussed above could, of course, be facilitated via Zoom or similar – and many of us have discovered that platforms such as Zoom, Miro and so on give us things to play with that face-to-face doesn’t – building escape rooms in Zoom, for example, can be done by creatively using the settings of the software itself.

But another and very different proposition is the asynchronous learning experience.  How do we debrief learning (games) which we have implemented as lessons on Mighty Networks or Teachable. Is ‘debriefing’, possible in this case.

While this situation obviously does not allow the spontaneity of a debrief where a facilitator is adapting questions and conversations on the fly, a good compromise is to use all the facilities available in the platform to encourage conversation between learners, and a facilitator can do this by using carefully crafted questions, and by ‘dropping in’ from time to time to prompt. Set ‘assignments’ which incorporate sharing as much as possible, and if possible, ‘gamify’ this participation to reward those who start and maintain peer interaction.

Featuring insightful contribution from learners within platforms, and adjusting subsequent learning activities (and facilitative questions) to indicate that learner input is noticed and valued is a good way of doing this, and some platforms actually have gamification features (allocating points etc.) built into them.

Last thoughts

Although facilitating games-based learning(GBL) does not require different skills than facilitating other kinds of learning, it does present different opportunities for a facilitator. If you have not facilitated GBL before, it is worth spending just that little time more to prepare so that you can ensure that you have taken advantage of that. It is also worth spending sometime becoming familiar with the theoretical basis of games and gamification, because through that you will find much inspiration for the angles you can take in your facilitative questioning.

The post What’s in a Game? – Debriefing Learning Games first appeared on Ludogogy.

Feedback is an important part of the learning process. Feedback is also really important for games to be engaging and fun.

Feedback in education is based on providing the student with tangible information that they can use to improve their learning, knowledge grasp, or retention.

Feedback in a game is provided to the player in order to viscerally show them the impact of their actions.

The two can be combined in order to both meet learners’ outcomes as well as provide some interesting and engaging feedback in a games-based learning environment.

Type of Feedback

There are two main types of feedback: positive feedback loops and negative feedback loops. Each one can be used to elicit a certain response from our students and players. Both can be used in balance to shape their experience and steer them towards the learning outcomes and experiences we’ve designed for them.

Positive Feedback

You can think of positive feedback as a reinforcing relationship. In this relationship, we’ve given the student or player something of value.  That item of value can change based on the venue where the feedback is provided.

If it’s a game then we can provide an award for earning a high score. That reward can be some sort of power up that allows the player to achieve an even higher score on the next level. That new high score would allow them to earn a new item etc… This feedback loop continues to reinforce itself.

This is particularly important for learners when it comes to scaffolding. We teach students to create knowledge or master a specific skill or ability. Ideally, we then have them use that knowledge, skill, or ability to tackle an appropriate challenge. That challenge can then be used as a new opportunity to introduce the next skill or ability they will need to know in order to keep progressing.

Whether it’s a class or a game, the properties of positive feedback loops are the same:

Positive feedback loops:

• Destabilize the game by providing players with an “edge”
• This edge allows players to get ahead
• When players get ahead, they cause the game to cycle faster

In a competitive game, this is often what you want. Though, in a classroom it can be difficult to mitigate.  Teachers can often recall that some students will get ahead of the average pace of the class and others students will lag behind. These positive feedback loops are reinforcing of behavior but also promote inequity in a group learning process.

This inequity is demonstrated in competitive real time strategy games like Starcraft where players follow the “4x” style feedback loop of explore, expand, exploit, and exterminate. Here, players explore the map with their starting resources; they expand to attain more resources; they exploit their competitive position against their opponents; and then they move to exterminate them with more powerful units gained from more resources.

The inequity we see embraced in this real-time strategy game can be mitigated through learning. One key to addressing this is to treat learning as a cooperative game: where multiple students can achieve the “win state” simultaneously.

This can be reinforced through feedback when the instructor provides some minimally meaningful information at an assessment stage in the process. I’ve done this before when I taught public speaking by presenting speakers with a visual reminder of where they are on time and pacing. This small, but significant form of feedback, gave those students real time insight on the speed of their speech. They learned to control how fast they were speaking and time their content accordingly.  Other students cooperated by providing them visual feedback on when they’ve made appropriate eye contact with members of the audience.

Negative Feedback

Understandably, negative feedback loops are the opposite of positive loops.  Though in games, we see them as balancing the relationship between the players and the game state.

That balance comes from the game ensuring that the action that a player took to trigger that negative feedback makes it harder for that action to occur again.

That’s just a long way of explaining something that has been included in many popular games: the catch up mechanic.

The catch up mechanic is a negative feedback loop that makes it easier for players who are not in the lead to catch up to the leader. That can be via points, position, or resources.

We’ve seen this in games like Mario Kart where that infamous Blue Shell gets rocketed towards the lead player to unseat them.  When growing up, I learned to race near the middle of the pack where you weren’t such a big target.

This negative feedback loop brought equilibrium to the game by incentivizing players to avoid the extremes of the pack: not in the very front and not at the very end.

We see negative feedback loops like this in the classroom with practices like grading on a curve. When grading on a curve, you’re looking for a normalized distribution of grades. So the majority of grades will be the average number for the class with a few grades as outliers: from exemplary to failing.  Because of this system, students aren’t necessarily working to master the material or the information.  Instead, they are incentivized to pursue a relatively better position than their peers to earn a passing grade.

Whether it’s a class or a game, the properties of negative feedback loops are the same:

Negative feedback loops:

• Stabilize the environment
• Cause players and students to move towards the “average”

Using feedback in your practice

Consider how your use of feedback will impact your players or students before using it in your practice.

Scaffolded feedback is important for the classroom.  Highly technical feedback about forms and concepts not yet covered by a student would just confuse and hinder them. By targeting feedback that addresses your current learning outcomes, you can better setup your students for success.

Be aware of the kind of perception built on your feedback loop. Ask yourself: “Would this feel “good” or “bad” by my players / students?”  Are they being rewarded for exploring the game in the way you designed? Are they meeting their learning outcomes? How can you structure your feedback loop in order to prioritize those player experiences?

How observable is your feedback by others players and students? Can others adjust their actions based on the performance of their peers? Is the feedback public? Or is it highly specific to individual players and students?

What is the volume of the feedback that you are providing? Too much feedback can be counterproductive. Instead, focusing on just one or two key elements can be more successful than focusing on the student’s entire performance at once.

This is similar to board games called “point salads” where players earn points for all sorts of different actions. Well balanced games allow players to pursue different, asymmetric strategies, in order for them to compete fairly against one another.

Closing thoughts

As with all games and instructional material: it’s best to test them with your demographic of choice before pursuing a full roll out.

Remember to think about the experience from the users’ perspective by sitting in their seat. What is it like to receive this type of feedback? What can they do now that is actionable? How can they improve their performance? What can they do to play the game better?

This article covered the feedback loops in games-based learning. To learn more about feedback loops in gamification, check out the free course on Gamification Explained.

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The post Focus on… Feedback Loops in Games Based Learning first appeared on Ludogogy.