Abstract
In this chapter we describe Analysis of Patterns in Time (APT) and how it can be used to analyze gameplay choices to provide evidence of a play-learner’s understanding of concepts modeled in a game. APT is an empirical approach to observing and coding phenomena as mutually exclusive and exhaustive categories within classifications. These data form a temporal map of joint and sequential patterns. We examine the case of the online Diffusion Simulation Game. An algorithm calculates scores for gameplay data patterns and compares them with scores for patterns based on optimal strategies derived from the game’s conceptual model. We discuss the results of using APT for analysis of game sessions for three play-learners. We describe how APT can be included as part of a serious game to conduct formative assessment and determine appropriate hints, coaching, or other forms of scaffolding during gameplay. We conclude by discussing APT methods for summative assessment.
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Myers, R.D., Frick, T.W. (2015). Using Pattern Matching to Assess Gameplay. In: Loh, C., Sheng, Y., Ifenthaler, D. (eds) Serious Games Analytics. Advances in Game-Based Learning. Springer, Cham. https://doi.org/10.1007/978-3-319-05834-4_19
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