Crystallize: Simulating LanguageImmersion through Gameplay

Gabriel CulbertsonInformation ScienceCornell Universitygrc74@cornell.edu

Permission to make digital or hard copies of part or all of this work forpersonal or classroom use is granted without fee provided that copies are notmade or distributed for profit or commercial advantage and that copies bearthis notice and the full citation on the first page. Copyrights for third-partycomponents of this work must be honored. For all other uses, contact theOwner/Author. Copyright is held by the owner/author(s).CHI’15 Extended Abstracts, April 18–23, 2015, Seoul, Republic of Korea.ACM 978-1-4503-3146-3/15/04.http://dx.doi.org/10.1145/2702613.2728654

AbstractMany people want to learn a foreign language, but find itchallenging to sustain engagement when daily life isdisconnected from the target language environment.Ideally, we would have language learning tools thatprovide the same benefits as being immersed in the targetenvironment. Crystallize takes a first step towards thisgoal by providing a structured immersive experience.Instead of memorizing vocabulary words and grammar,the player solves linguistic puzzles, interacts with theenvironment, and infers word meanings from context.

Author KeywordsGames; Language Learning; Immersion; Spaced repetition

ACM Classification KeywordsK.8.0 [Personal Computing]: General Games.

IntroductionForeign language learning is a critical part of secondaryand tertiary education. However, many learners find itchallenging to sustain motivation. Traditional curriculaoften emphasize rote memorization of vocabulary and verbconjugations and do not provide the learner much controlover how he or she learns. This can be tedious andunrewarding. It also contrasts with how people learn whenimmersed in a foreign language environment, which

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provides opportunities to infer word meanings fromcontext, learn through exploration and experimentation,and receive immediate feedback.

Figure 1: Crystallize gamifieslanguage learning challenges byorganizing them into quests. Theplayer can always see a list of theactive quests to direct the playerand give them a sense ofachievement as he or shecompletes them.

Figure 2: Players collect wordsby overhearing dialog. Wordmeaning is inferred from context.

Ideally, we would have tools for language learning thatcapture the advantages of immersion. According toIsbister, games for learning are most engaging when theyhave mechanics that interface deeply with the targetlearning material and facilitate exploration [7]. Inspired bythese ideas, we designed Crystallize, a Unity game thatfeatures an engaging sequence of puzzles. Each puzzlerequire the player to explore a 3D environment, infer wordmeanings and grammatical rules from context, build aninventory of words by taking them from phrases spoken byother characters, construct target phrases with words fromthe inventory, and reinforce vocabulary meanings overtime.

BackgroundTraditional classroom language learning tends to focus onmetalinguistic information (such as verb conjugations)and rote memorization. This structure has lead to twoshortcomings in classroom learning: (1) lack ofpersonalization and (2) lack of engagement. Classroomexercises such as translation and vocabulary quizzes aredifficult to tailor to the individual needs of each student.Furthermore, students read language scenarios fromtextbooks rather than experiencing them.

Previous research projects and commercial products haveused technology to address these shortcomings. Forexample, Duolingo gives students immediate feedback andoffers uses point systems to motivate users [10]. However,Duolingo focuses on translating sentences and doesprovide deep immersion. Furthermore, the game

mechanics are weakly related to language learning whichmany designers believe is ineffective [7].

Other work has focused on using immersion to engagelanguage learners. The theory of situated cognitionsuggests that context is essential to the content beinglearned [1]. MicroMandarin makes use of the user’s realworld location as a source for vocabulary words [4].Another game, Sanjigenjiten, uses a 3D environment toteach vocabulary words [6]. Both systems make use ofvisual context but are limited to individual words and donot provide a structured set of challenges.

Previous research suggests that language learning toolsthat provide personalized feedback, deep game mechanics,and an immersive experience would be most effective.However, there is a lack of games that combine all ofthese elements. We attempt to bridge this gap inCrystallize by combining rich context with personalizedfeedback in an engaging game.

Gameplay designThe game mechanics are designed to work with anylanguage, but this particular prototype uses Japanese.Japanese grammar is significantly different from Englishgrammar allowing us to test the game mechanics.

Crystallize uses four deeply embedded gameplaymechanics to engage users: (1) a questing system thatmotivates players, (2) computer-controlled characters thatgive contextual clues that facilitate inference of wordmeanings, (3) sentence construction puzzles thatgradually expand the abilities of the player and (4) aspaced repetition system (SRS) that minimizesforgetfulness through personalized reinforcement.

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Crystallize uses a questing system to provide guidance aswell as freedom. Quests are completed by successfullyconversing with non-player characters (NPCs). This isaccomplished in two stages: (1) the words necessary tocomplete the conversation must be found in context and(2) the words must be used to construct the phrasesneeded for completing the conversation. Figure 1 showsthe panel used to track the state of each quest andprovides positive feedback by checking off completedquests.

Figure 3: Sentences areconstructed by dragging wordsfrom the inventory.

Figure 4: Words are practicedafter increasing intervals

NPCs provide clues to find the meaning of words withoutgiving direct translations. Schneider et al. suggests thatlearning words through challenges rather than being giventhe meaning increases long term retention [9]. Two typesof NPCs exist in Crystallize: interactive actors and passiveactors. When a player approaches an interactive actor,that actor will initiate a conversation with a Japanesephrase. The words necessary to complete the conversationare indicated as empty slots in the player’s inventory. Theplayer must then find those words by either finding thewords in the prompt, or approaching other characters. Themeaning of words must be determined by context such asenvironmental clues. For example, one character may say“What are you [unknown word]?” and another characterresponds with “I am [unknown word] sushi.” The playermight guess from the exchange that the missing word is“eating”. Use of environmental context can be seen inFigure 2. The meaning of “sayounara” can be inferred tomean “goodbye” because the word is said as one of thecharacters walks away. To provide another example, if acharacter says “This is an [unknown word].” whilepointing to a cow, the unknown word is probably “cow”.

Completing conversations requires the player to constructincreasingly complex sentences. The theory of the Zone of

Proximal Development (ZDP) states that each learner hasa set of concepts that can be learned if provided guidanceand that learning materials should continually target thisset [8]. This balance of challenge with skill is not onlygood for learning, but also enables the player to reach aflow state [3]. In Crystallize, some words are given to theplayer and verbs are already conjugated in order to buildchallenges at rate which is challenging without beingoverwhelming. As shown in Figure 3, when learning thephrase, “am a student”, the player is first asked to fill inthe word “am”, then the word “a student” and finally theentire phrase “am a student”. If the player fills in thesentence incorrectly, the player receives immediatefeedback and must fix the sentence before continuing theconversation. Drag and drop sentence construction allowsfor quick experimentation. By minimizing the effort ofrearranging words, emphasis is placed on grammaticalstructures, allowing players to see patterns that may haveotherwise been unclear.

To ensure the player is reviewing words enough tominimize forgetfulness, we designed Crystallize with aleveling mechanic. Increasing the speaker level opensaccess to more interactive actor conversations. This isaccomplished by by translating words in the inventoryafter an appropriate interval has passed as is shown inFigure 4. The text is entered above the Japanese word,and flashing indicators show when a word needs to beranked up. These reviews are scheduled using a SRS.SRSes use exponential back-off to facilitate memorizationand have been found to be useful for language learning[5]. For example, if a base time of twelve hours waschosen, the word would be reviewed after 12 hours, thenone day, then two days and so on. Answering incorrectlyresets the word.

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Conclusion and Future WorkIn conclusion, Crystallize combines structured,personalized learning with immersion. The questingsystem provides the player achievable goals. InteractiveNPCs enable the inference of word meanings using actionsand the environment. Sentence building puzzles teachgrammar. A SRS gamifies the tedious process of review.Although Crystallize shows the potential of gamifiedimmersion, more work is needed to measure itseffectiveness and explore new ways to motivate and teach.

We will deploy Crystallize to classrooms and gamewebsites. Data will be collected both automaticallythrough numerical usage statistics such as progress, timeplayed and return rate as well as through interventionsincluding surveys, interviews and pre/post-tests. Thesetests will allow us to continue to improve the game byadjusting variables such as the rate of increase ofdifficulty, the order of concepts and the review interval.

Other work will focus on content generation. New toolswill be created to allow players to and instructors toproduce quests tailored to specific interests and prioritiesof each learner. For example, if a student is especiallyinterested in food, the game will prioritize vocabulary andgrammar associated with this topic.

AcknowledgmentsI would like to express my gratitude to Prof. ErikAndersen and Prof. Walker White for their tremendouslyhelpful advice and feedback throughout the design ofCrystallize.

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