The Design of Disciplinarily-Integrated Games as Multirepresentational Systems

Introduction

Clark et al. (2015) propose an approach for leveraging digital games as a medium to support the development of scientific modeling in K-12 classrooms based on the Science as Practice perspective (Pickering, 1995; Lehrer & Schauble, 2006). Clark et al. (2015) refer to this approach as disciplinary integration. Disciplinarily-integrated games (DIGs) represent a generalizable genre and template for designing games to support science learning in order to bridge across formal and phenomenological representations of core science relationships. Therefore, by definition, DIGs are multirepresentational systems with the affordances and challenges associated with that medium.

Ainsworth (2014) highlights the importance of articulating broader theoretical frameworks to investigate how multiple representations improve learning and under what conditions. She also highlights the importance of explicitness in articulating the design and function of representations in multirepresentational systems so that research across the field can move beyond simplistic comparisons to instead drill deeper into how specific design decisions affect learning processes in light of specific intended functions of the multirepresentational system.

More specifically, this paper seeks to analyze the DIG genre and template through the focal parameters framed by the DeFT framework (Ainsworth, 2006) to synthesize effective design considerations for DIGs in terms of the specific design and intended functions of the representations themselves as well as the overarching environment and activity structures. We leverage the literatures on embodied cognition, adaptive scaffolding, representations in science education, and learning from dynamic visualizations to address the challenges, tradeoffs, and questions that the framework highlights. We apply these research-derived design considerations to an existing DIG (SURGE Symbolic) and to hypothetical examples of DIGs in other domains to investigate the generalizability of the design considerations and the genre.

Disciplinary Integration

As we have asserted in our earlier papers (Clark et al., 2015; Sengupta & Clark, 2016), modeling is generally recognized as the core disciplinary practice in science (Lehrer & Schauble, 2002; Nercessian, 2008; Pickering, 1995). Science and math education research shows that engaging learners in modeling and progressively refining representations can contribute to a deeper understanding of mathematical and scientific knowledge and practices (Gravemeijer, Cobb, Bowers, & Whitenack, 2000; Hall & Stevens, 1995; Lehrer & Schauble, 2009). Clark et al. (2015) and Sengupta and Clark (2016) suggest that DIGs are a generalizable genre and template for supporting players in interpreting, manipulating, and translating across phenomenological and formal representations in support of a Science as Practice perspective.