Taming Log Files From Game/Simulation‐Based Assessments: Data Models and Data Analysis Tools

Abstract

Extracting information efficiently from game/simulation‐based assessment (G/ SBA ) logs requires two things: a well‐structured log file and a set of analysis methods. In this report, we propose a generic data model specified as an extensible markup language ( XML ) schema for the log files of G/ SBAs . We also propose a set of analysis methods for identifying useful information from the log files and implement the methods in a package in the Python programming language, glassPy . We demonstrate the data model and glassPy with logs from a game‐based assessment, SimCityEDU . Report Number: ETS RR‐16–10