Rewordable is a uniquely fragmented word game.
The 120 card deck of one, two, and three letter sequences has been carefully crafted through statistical language analysis techniques to encourage the creation of longer, more common words.
Rewordable is a game for 2-8 players that uses a custom-designed 120-card deck of one-, two- and three-letter sequences. The goal of the game is to have the biggest lexicon of words at the end of the round. Players take turns making words, using at least one card from their hand. Players may also add onto their own already constructed words, or steal words from other players, optionally using cards from a common pool. Sixteen “Rewardable” tokens also rotate into play during the game, giving players a changing set of goals, potential strategies, and bonuses every turn. Each round uses a random subset of 60 cards from the deck, ensuring a fresh linguistic experience from one game to the next.
Most word-building games use individual letters as their game pieces, and assign a value to letters based on how common they are in the English language. Makes sense, right? But there’s a frustrating side effect to this design: the highest-scoring words tend to be the shortest and most obscure. (Think of someone scoring 50 points for playing “XU” in Scrabble.) We think that word games are more fun when you don’t have to memorize a dictionary just to be competitive. So when we made Rewordable, we carefully engineered the cards to facilitate the construction of longer, more common, more satisfying words, leading to an inclusive and engaging experience for players of all skill levels.
Rewordable is the result of a computer-aided game design process, using both computational analysis and extensive in-person playtesting. We made a computer simulation capable of playing thousands of Rewordable rounds in seconds, and then fed it a variety of decks based on the most common and most widely distributed one-, two- and three-letter sequences in English. The simulation told us how often each sequence was used across the simulated rounds – which helped us to reason about which cards worked well with each other and which were less useful.
Using results from these simulations, we created prototype decks with the best combinations of letter sequences and test them out with our (human) playtesters. After incorporating player feedback, we fed the deck back into the simulation, allowing us to quickly understand how the changes affected the overall balance and tempo of the game.
This iterative process helped us build a deck not just of common letter sequences, but of letter sequences that uniquely work together to create balanced gameplay. For example, TIO is a very common letter sequence in English, but because it almost always needs an N card to be useful, it’s very difficult to use in a game of Rewordable. Our playtesters told us that TIO was useless, and the simulation confirmed it – so we dropped it. We brought this same critical process to all 120 cards in the deck.
Finally, Rewordable’s many playtesters were invaluable in this design process. We’ve tested Rewordable on kitchen tables, coffee tables, and carpet, and at bars, cafes, meet-ups, and most regularly at the NYU Game Center’s Playtest Thursdays. We’re extremely greatful to our many fantastic playtesters who have brought incredible insight throughout months of rule changes, new game mechanics, and significant shifts in deck composition.
Rewordable initially was created in a master’s course at New York University’s Interactive Telecommunication Program (ITP). In May 2016, it was selected as the first non-digital game at the NYU Game Center Incubator. The purpose of the NYU Game Center Incubator is to bridge experimental work with the realities of the marketplace, giving promising games time, space, guidance, and resources to maximize opportunities for commercial success. Thanks to the Incubator, the Rewordable team had the opportunity to develop the game further and bring it closer to publication.
On September 21, 2016, a Kickstarter campaign was launched to fund the game’s initial print run. The project was successfully funded in just eights days, and by the end of its campaign, 1232 backers showed their support for Rewordable by pledging $43,342 (288% of the project's funding goal).
In January 2017, Rewordable teamed up with Clarkson Potter, an imprint of Penguin Random House, to publish the game. Wider retail distribution will begin Fall 2017.
NYU Game Center Incubator
First non-digital Incubator game
Revolution Learning Conference
NYC Media Lab Summit
2016 Gallery Selection
The Rewordable Team first met as students at New York University’s Interactive Telecommunications Program (ITP). Since graduating, they each have worked in diverse sectors of media, technology, education, and games, and are reuniting for Rewordable.
Allison Parrish is a computer programmer, poet and game designer whose teaching and practice address the unusual phenomena that blossom when language and computers meet. She has recently given talks on computer-generated poetry at the Electronic Literature Organization conference, !!Con, Alt-AI, SXSW Interactive and Eyeo. From 2014 to 2016, Allison was the Digital Creative Writer-in-Residence at Fordham University, and has recently been a research resident at DBRS Innovation Labs and a Processing Foundation fellow. Allison is currently a member of the full-time faculty at NYU's Interactive Telecommunications Program.
Adam Simon is an innovation-driven entrepreneur, having used technology to build innovative experiences for over fifteen years. His work has included directing live performances and television, designing games and theme park attractions, and creating new platforms for media distribution and consumption. In 2008, he founded Socialbomb to work with clients like HBO, Red Bull, Technicolor, and the BBC to build breakthrough mobile social software. Recently, Adam joined the IPG Media Lab to bring innovation-driven solutions to a new caliber of global client, while he continues to consult on creative technology strategy, design, and development for companies of all sizes. His work has earned him a Clio and several Webbys, and has been featured in The New York Times, The Washington Post, Fast Company, and Gizmodo.
Tim Szetela is a designer, animator, and digital artist. He makes maps, media, and games that visualize language, location, data, and technology. His work has been shown at museums, festivals, and exhibitions around the world. He also collaborates on the production of digital content and consults on technology and design for a wide range of companies, organizations, filmmakers, and artists. He has taught courses and workshops in media production, design, and computing at New York University, the School of Visual Arts, Harvard University, and Mexico's Monterrey Institute of Technology.