Paper Info
Title
Learning Analytics In Serious Gaming: Uncovering The Hidden Treasury Of Game Log Files
Abstract
This paper presents an exploratory analysis of existing log files of the VIBOA environmental policy games at Utrecht University. For reasons of statistical power we have combined student cohorts 2008, 2009, 2010, and 2011, which led to a sample size of 118 students. The VIBOA games are inquiry-based games, which offer a lot of freedom of movement. Our premise is that this freedom of movement is accompanied by behavioural variability across individuals, which may influence the efficiency of learning. Descriptive statistics of our sample revealed such variability of diverse game parameters. We have identified "switching behaviour", defined as the number of game objects (videos, resources, locations) accessed per unit time, as a relevant behavioural pattern. Multiple regression analysis showed that switching rates of videos and locations explain 54 % of the variance of learning efficiency (defined as final score per unit time). Both the model and the model coefficients were significant beyond the 0.001 level. The same switching variables also account for 45 % of the variance of total time spent. Predictive models of final score weren't found. We conclude the paper by critically evaluating our findings, making explicit the limitations of our study and making suggestions for future research that links learning analytics and serious gaming.
Year
DOI
Venue
2013
10.1007/978-3-319-12157-4_4
GAMES AND LEARNING ALLIANCE
Keywords
DocType
Volume
patterns,mining,regression,behaviour,logging
Conference
8605
ISSN
Citations 
PageRank 
0302-9743
3
0.42
References 
Authors
5
3
Name
Order
Citations
PageRank
Wim Westera117419.80
Rob Nadolski224522.09
Hans Hummel345836.21