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ATD Blog

Deliberate Play for Learning Design

Wednesday, August 11, 2021

“A chef is analyzing the visual presentation of a dish: the color palette, the initial impressions of its components. Next, the chef starts tasting the dish: bite by bite, exploring the texture, the dynamics of ingredients in the mouth over time with their specific flavor profile. The flavor profile is the result of art and science in balancing sweet, salty, sour, bitter, and umami. Top chefs can make sure all elements are perfectly balanced across the meal to make the dining experience unforgettable. Finally, the chef makes mental notes of the ingredients, tools, and processes used to make the dish.”

This unofficial, nonscientific description above is my interpretation of one of the challenges in the gamified cooking show Top Chef. During the game show, participants “deconstruct” a dish. Chefs in the competition taste the dish to break down its complexity into distinct attributes (ingredients) so they can use their creative skills to create a deconstructed version of the meal that may look completely different yet keep the essence of the original meal.

What does deconstructing a dish have to do with learning design?

Watching Top Chef provides you with great examples of game design elements used in a nongame environment. The process of deconstructing a dish to create your own interpretation is similar to “deliberate play” for learning designers who want to apply game design to their work.

Deliberate Play

Deliberate play is playing games to analyze and classify the ingredients, observe dynamics in gameplay over time, and capture the essence of the experience. If you’re a learning designer who wants to use game elements in learning design, you must play games first. Without playing games (or playing only a couple you like), your design will most likely use the same “ingredients” and “flavor profile” for every solution. Playing different types of games is a must.

However, playing games, just like eating out at restaurants to become a top chef, is not enough. You need to play with a purpose. You need to practice using deliberate play to classify and describe elements and their dynamics in the game. Then you can deconstruct the experience and integrate it with your learning design.

How Do You “Deliberate Play”?

Most of us are familiar with food classifications such as produce, dairy, protein, and fruit. It is a well-known taxonomy of ingredients. A taxonomy helps us consistently speak a common language and describe elements and attributes. A taxonomy, therefore, enables us to compare, contrast, and deconstruct.


Does a Game Taxonomy Exist? If so, Is There One Mapped for Learning Effectiveness?

The goal of learning design is effective learning rather than pure entertainment (passive engagement). During my session at the ATD 2021 International Conference & EXPO, we’re going to dive deeper into deliberate play using a proposed game taxonomy sheet for learning.

The deliberate play worksheet I’ve put together for learning designers is based on an empirical study, Toward a Taxonomy Linking Game Attributes to Learning: An Empirical Study, which explains why it is important to have a taxonomy.

Without a clear understanding of what truly constitutes a game, scientific inquiry will continue to reveal inconsistent findings, making it hard to provide practitioners with guidance as to the most important attribute(s) for desired training outcomes. This article presents a game attribute taxonomy derived from a comprehensive literature review and subsequent card sorts performed by subject matter experts (SMEs).

There are two compelling reasons why I recommend this study:

  • The game taxonomy is based on the combination of a comprehensive literature review (theory) and card sorting by experts (practice).
  • It also offers a game matrix, an updated version of the matrix originally proposed by Wilson and colleagues. The game matrix maps attributes to training outcomes.

The attributes of describing any game are organized under nine categories: action language, assessment, conflict/challenge, control, environment, game fiction, human interaction, immersion, and rules/goals. Each of these categories then includes one or more attributes. You can use this taxonomy with the categories and their attributes to analyze, describe, and deconstruct any game.


Category Example: Assessment Category in “Cut the Rope”

The assessment category is composed of two attributes: assessment and progress. The assessment attribute represents the measurement of achievement. You can often see this as the score in games. The progress attribute is about how the player progresses toward the game goal. They both function as actionable feedback to the player, but their purposes are different.

In the mobile game Cut the Rope, for example, players swipe to cut swinging ropes to drop the candy into a monster’s mouth. The goal of each level is to feed the monster and move on to the next level. How well you achieved this goal (assessment) is represented by three stars. You can complete each scene (progress) with a single star, but if you’re competitive, you go for the best move.

How Does the Assessment Category Work for Learning?

In a series of e-learning, we designed a deck of cards to collect. Participants gained these index cards as they progressed through the content. The index cards served as reminders as well as reflections on how they’re going to use the skill on the job. The more participants collected, the closer they got to complete the journey. That is the progress attribute. When all cards were collected, the learning journey was over.

Through a narrative, participants also applied the knowledge and skills they gained through these cards. How well they applied the skills was presented through a morale meter. When they made the right decisions in authentic scenarios, the morale meter went up. When they made the wrong decisions, the morale meter went down. That is the assessment attribute. It provided feedback to the participants on how well they’ve mastered the learning goals.

Assessment is just one of the nine categories. In a full deliberate play, you would go through all nine, but I hope this example demonstrated how a well-defined taxonomy can help to understand, analyze, and deconstruct games to create more engaging and effective learning.

If you can’t make it to my session at the ATD 2021 International Conference & Exposition, you’ll find more guidance on games and gamification for learning professionals in the TD at Work article “Game Thinking: From Content to Actions.”

About the Author

Zsolt Olah works in workforce development as a Manager, Digital Learning & Experience at Amazon Web Service with over 20 years of experience in the learning and development space. His passion, to combine innovative learning and performance technology with human-centered design, goes back to his thesis project, where he built an artificial neural-network using machine learning.

Zsolt is a frequent speaker at learning conferences on the subject of engagement and game thinking for L&D. He is also the author of the book, Engage the WORL&D!, exploring six essential traits of instructional design through adventures in an imaginary WORL&D.

Previously, Zsolt worked as a learning consultant at Kineo, led an instructional design team, and for nine years, he worked as a Sr. Program Manager at Comcast, designing and building learning and performance solutions with business impact.

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