This article was originally published on SCMR.com.
Learning a new skill can be difficult, especially when it’s relatively complex. It’s often hard to keep definitions, concepts, and descriptions straight when you’re trying to make inroads into an area you don’t fully understand.
This is why so many learners flock to gamified learning experiences. Recontextualizing a complex concept into a puzzle or set of goals and providing regular feedback to player decisions can make the learning process more interesting, approachable, and accessible. Just look at platforms like Duolingo, Kahoot, or even throwbacks like your elementary school’s copy of Mavis Beacon Teaches Typing—each of these games helps players approach the multifaceted learning experience through a framework they can understand and, ideally, start to enjoy.
It was in the hopes of making the complex more accessible that my team at Gurobi Optimization decided to collaborate with top educators to develop our own web-based learning tool: the Burrito Optimization Game.
At Gurobi, we specialize in an area of applied mathematics that remains somewhat inaccessible to many of today’s learners: mathematical optimization. With roots in the 1940s, optimization is not necessarily new or flashy. Even so, there are still barriers to entry for new learners who are ready to dive into making optimal decisions with models, because not all programs teach optimization. Even when they do, it’s often introduced with a theoretical and mathematics-first approach.
Because of this, we understand that optimization has not always been the most approachable subject for all problem solvers. Even those who have completed college-level courses in data science, computer science, or engineering often only encounter this concept in passing. And due to its complexity, most end up thinking of it more as hard mathematical formulations for extremely difficult problems and less as an accessible means of improving decision-making capabilities.
This is the perception that we wanted to change with our game. We needed to take the power of optimization—and its relevance to an abundance of practical problem-solving applications—and make it appealing to a broad audience of potential learners, from data scientists and researchers, to professionals, and even younger students.
The obvious way to do this? Burritos.
The Burrito Optimization Game is a free and publicly available educational tool developed by Gurobi and Dr. Larry Snyder, deputy provost for faculty affairs and professor of industrial and systems engineering at Lehigh University.
The objective of the game is relatively straightforward: players are tasked with strategically dragging and dropping burrito trucks on a map of “Burritoville” in order to serve hungry customers throughout the city with the goal of maximizing total profit. You might recognize this as a facility location problem, a standard challenge in modern supply chain planning. While today’s practitioners might be placing warehouses instead of burrito trucks, the structure and parameters of this scenario are largely familiar.
During each “day” of gameplay, players need to factor in ingredient cost, total potential revenue, customer demand (and forecasted demand in round two), allowable locations, and more as they decide on the best possible placement(s) of their burrito trucks. As the days progress, the game introduces new complexities that reflect real-world business scenarios—for example, one day involves a supply chain disruption that increases the price of cheese, impacting costs and the resulting trade-offs. At the end of the day, the game leverages Gurobi’s solver to present the mathematically optimal solution and score to the player based on how far their solution was from optimal.
Gamification in Burritoville sets up a scenario in which students can learn by experimenting in relatable and realistic contexts that they recognize. They are encouraged to try multiple approaches to problem-solving (including mental math, enumeration, trial and error, using logic and heuristics, etc.) in order to try to manually achieve an optimal solution. As the game progresses, players ultimately learn that there’s a better and faster way to plan for variety, scaling, and complexity—if you haven’t guessed it by now, it’s leveraging mathematical optimization.
To make this game both educational and accessible, we knew we couldn’t work in a vacuum. We needed to create something that was fun and engaging for learners, but also useful for educators who might use it to teach optimization concepts. Our core intention was to provide a reliable and free resource that could help introduce mathematical optimization to problem solvers.
We collaborated closely with Dr. Snyder and a group of brilliant technical experts and developers at Gurobi throughout the entire game development process to ensure a balance of professional optimization expertise and academic experience. Dr. Snyder served as the lead story developer, education consultant, and game producer, working with Gurobi to plan, build, and test the Burrito Optimization Game throughout each of its iterations.
This academic-professional partnership was influenced greatly by previous experiences with gamifying complex topics. I had the opportunity to collaborate with Dr. Snyder in the past to develop puzzle books that helped learners use their operations research knowledge, computer science concepts, probability, and logic to solve super challenging (and fun!) puzzles that Dr. Snyder authored. Understanding the benefits of academic input—as well as a professor’s perspective on how to apply this game in the classroom—and meet the needs of top faculty—made our development efforts more informed and intentional.
For this game to have a significant impact on both learners and teachers, we couldn’t just release it into the world as-is. Informed by Dr. Snyder’s insights, we knew that we needed to develop supplementary educational resources to help make the Burrito Optimization Game more than just a fun exercise.
This is why we created resources like the Burrito Optimization Game Teaching Guide, an in-depth Game Guide, a sample lesson plan, and even an entire slide deck that provides a deeper dive into the mathematical concepts behind optimization and various jumping off points for teaching both optimization and Gurobi to new learners.
We also developed a “Championship Mode” of the game, making it easy for teachers to turn this exercise into a competition for their students. This only enhances the gamified nature of this learning experience, empowering students to refine their skills and try and beat their peers with the closest-to-optimal solution and see their name at the top of the leaderboard.
While we joked earlier that the obvious way to approach gamifying optimization was through burritos, this has been much closer to the truth than we could’ve imagined. The reach and impact of the Burrito Optimization Game has completely exceeded our initial expectations. Since its release just a couple of years ago, the game has been played over 50,000 times by learners and instructors all around the world. This included both individual and hosted Championship Games at academic institutions like the Massachusetts Institute of Technology, RWTH Aachen University, Columbia University, Georgia Tech, and Rice University, to name a few.
We’ve also heard directly from professors like Northwestern University’s Dr. Michael Watson, who have used the game to introduce students to optimization. Anecdotally, I’ve also been regularly approached at industry conferences by professors who tell me they’ve fully incorporated the game into their lesson plans and syllabi. Some have even asked if we’d consider working with them to develop additional games.
What this experience has ultimately shown us is that teaching and learning about complex concepts like optimization does not need to be, well, overly complex. Wherever there is an appetite for problem-solving, gamification can act as a gateway to deeper and more comprehensive learning experiences. And by demonstrating the power of optimization in a decision-making context, we hope to demystify the concept and empower a new generation of problem solvers with an important and applicable new skill.
Curious to try the game out (either on your own or in a classroom or training setting)? It’s totally free and only takes a couple of minutes to set up and dive in at www.BurritoOptimizationGame.com. Interested in learning more about optimization? Check out our full site of open educational resources at www.gurobi.com/learn.
Senior Director of Academic Programs
Senior Director of Academic Programs
Lindsay brings over 13 years of experience working at the intersection of technology and education. Prior to Gurobi, Lindsay worked as an Operations leader at Opex Analytics, a product and services firm dedicated to solving complex business problems using the power of Artificial Intelligence. While there, she focused on growth and business development, product launch, and marketing. Lindsay spent 10 years working in various leadership capacities at Universities including Columbia University, Northwestern University, and the University of Chicago. From 2013 to 2017, she worked to establish and grow the Master of Science in Analytics degree at Northwestern University’s School of Engineering, the program was one of the earliest MS degrees focused on an applied data science curriculum. During her time with Northwestern, she managed external relations and corporate relations, helped hire and onboard new faculty and subject-matter experts in various disciplines of analytics, directed recruiting efforts/admissions/student advising, and managed a team of administrative professionals. Prior to Northwestern, she spent over 5 years working in Advancement at Columbia University’s School of Engineering and Applied Science. She completed her Bachelor’s Degree in English and Fine Art at Sewanee: The University of the South and her Master’s Degree in Nonprofit Management at Columbia University.
Lindsay brings over 13 years of experience working at the intersection of technology and education. Prior to Gurobi, Lindsay worked as an Operations leader at Opex Analytics, a product and services firm dedicated to solving complex business problems using the power of Artificial Intelligence. While there, she focused on growth and business development, product launch, and marketing. Lindsay spent 10 years working in various leadership capacities at Universities including Columbia University, Northwestern University, and the University of Chicago. From 2013 to 2017, she worked to establish and grow the Master of Science in Analytics degree at Northwestern University’s School of Engineering, the program was one of the earliest MS degrees focused on an applied data science curriculum. During her time with Northwestern, she managed external relations and corporate relations, helped hire and onboard new faculty and subject-matter experts in various disciplines of analytics, directed recruiting efforts/admissions/student advising, and managed a team of administrative professionals. Prior to Northwestern, she spent over 5 years working in Advancement at Columbia University’s School of Engineering and Applied Science. She completed her Bachelor’s Degree in English and Fine Art at Sewanee: The University of the South and her Master’s Degree in Nonprofit Management at Columbia University.
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