Animated Visual Encoding and Layer Blending for Identification of Educational Game Strategies

TL;DR

This paper introduces an animated visualization tool that uses kinetic encoding and layer blending to help researchers interpret complex, noisy game strategy data in educational game analysis.

Contribution

The paper presents a novel animated visualization method with layered blending for better understanding of player strategies in educational games.

Findings

Enhanced interpretation of noisy game data

Effective visualization of long-term strategies

Demonstrated usefulness with domain expert collaboration

Abstract

Game-Based Learning has proven to be an effective method for enhancing engagement with educational material. However, gaining a deeper understanding of player strategies remains challenging. Sequential game-state and action-based tracking tools often gather extensive data that can be difficult to interpret as long-term strategy. This data presents unique problems to visualization, as it can be fairly natural, noisy data but is constrained within synthetic, controlled environments, leading to issues such as overplotting which can make interpretation complicated. We propose an animated visual encoding tool that utilizes kinetic visualization to address these issues. This tool enables researchers to construct animated data narratives through the configuration of parameter interpolation curves and blending layers. Finally, we demonstrate the usefulness of the tool while addressing specific interests as outlined by a domain expert collaborator.