Open AccessTaming Log Files From Game/Simulation‐Based Assessments: Data Models and Data Analysis Tools
Author(s) -
Hao Jiangang,
Smith Lawrence,
Mislevy Robert,
Davier Alina,
Bauer Malcolm
Publication year - 2016
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/ets2.12096
Subject(s) - computer science , xml , python (programming language) , markup language , file format , schema (genetic algorithms) , data mining , programming language , data file , information retrieval , database , world wide web
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 .