Experiment centered design in a massively multiplayer online educational game

Abstract

With the United States of America suffering from a lack of scientifically literate grade and secondary school students, educational games offer an opportunity to engage and inspire students to take interest in science, technology, engineering, and mathematical (STEM) subjects. Learning assessment techniques coupled with machine learning algorithms can be utilized to record student's in-game actions and formulate a model of the student's knowledge. This paper describes "Experiment Centered Assessment Design" (XCD), a framework for structuring a learning assessment feedback loop. XCD builds on the "Evidence Centered Assessment Design" (ECD) approach, which uses tasks to elicit evidence about a student and his learning. XCD defines every task as an experiment in the scientific method, where an experiment maps a test of factors to observable outcomes. This XCD framework was applied to prototype quests in a massively multiplayer online (MMO) educational game. Future work would apply machine learning techniques to the information captured from XCD to provide feedback to students, teachers, and researchers.