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

Hao Jiangang | Zendy; Smith Lawrence | Zendy; Mislevy Robert | Zendy; Davier Alina | Zendy; Bauer Malcolm | Zendy

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Taming 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 .

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