Taming Log Files From Game/Simulation‐Based Assessments: Data Models and Data Analysis Tools. Issue 1 (29th March 2016)

• Record Type: Journal Article
• Authors: Hao, Jiangang; Smith, Lawrence; Mislevy, Robert; von Davier, Alina; Bauer, Malcolm
• Is Part Of: ETS research report series. Issue 1(2016:Jun.)
• Page Start: 1
• Page End: 17
• Publication Date: 2016-03-29
• Subjects: data model -- log file -- process data -- game‐ or simulation‐based assessment; Universities and colleges -- Entrance examinations; Universities and colleges -- Graduate work -- Examinations; Universities and colleges -- United States -- Entrance examinations; Universities and colleges -- United States -- Graduate work -- Examinations; Graduate Record Examination; Educational tests and measurements; Social sciences; Education -- Research; Education -- Research; Educational tests and measurements; Graduate Record Examination; Social sciences; Universities and colleges -- Entrance examinations; Universities and colleges -- Graduate work -- Examinations; United States; 378
• DOI: 10.1002/ets2.12096
• Languages: English
• ISSNs: 2330-8516

Abstract

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. Abstract : Report Number: ETS RR‐16–10