An ENA research for an alternate reality game
Task: Data coding; Data analytics
Role: Assistant Researcher
Evaluate the efficacy of an alternate reality game in fostering scientific inquiry skills among teens.
Funded by National Science Foundation; Research paper was published on Connected Learning Summit 2018.
DUST is an Alternate Reality Gaming experience that centers on the mysterious collapse of adults worldwide who fall into a coma-like state following a cataclysmic meteor shower. Following the story through a series of interactive motion comics, real-life players “hack” into NASA research databases and engage in collaborative play and inquiry across multiple media platforms to save the world. Sponsored by the National Science Foundation, DUST gives teens the opportunity to learn and apply STEM (science, technology, engineering, and mathematics) principles in formal and informal settings. Over 2,000 players participated during its first launching session and generated a huge game behavior dataset.
In this paper we employ a method of analyzing gameplay called Epistemic Network Analysis (ENA), which creates relational network graphs between actions within a game-space. We found that key players exhibited behavior like proxy players, but also diverged from them in meaningful ways. We present case studies of one active player and one proxy player that demonstrate the power of ENA to model ARG play. We describe ways in which ENA reinforced the design insights that guided our original creation of proxy players while also allowing us to analyze the implications of those design choices in practice. We conclude by enumerating some research and design benefits of employing ENA in other learning contexts.
As the research assistant, my main responsibilities include: 1）Dataset cleaning; 2）Players’ discourses coding, based on Next Generation Science Standards (NGSS); 3）Game data analytics and visualization on player behaviors and levels of scientific thinking.