Model-Master-Transfer: Formally Deconstructing Educational Games to Build a Quantitative Theory

Abstract

We live in an increasingly interconnected, complex world, where our collective decisions can have unanticipated indirect consequences on the world. What is today a hands-on job may soon be a job of managing variables at a computer screen. However, people have tremendous difficulty handling even relatively mild levels of complexity in experiments. Yet, in the context of many modern computer games, people eagerly teach themselves vastly complex systems, all without any external guidance or coercion. Educational video games research is a menagerie of different methodologies and paradigms. Meta analyses have found that mixed results in the literature are difficult to interpret due to the combination of different theoretical approaches, different data reporting conventions, and a general focus on proof-of-concept studies. They recommend a transition to narrower investigations of specific causal relationships between game properties and outcomes of engagement and learning, but this requires a way to incorporate them into the broader picture of educational and serious games research. In this thesis, I focus on educational games and propose the Model-Master-Transfer (MMT) framework to break down educational game usage into a set of formal subprocesses that can be studied in more depth individually, and specify how such narrow studies can then be assembled to build up a causal model of the underlying effects. The framework is illustrated using different educational examples. The conceptual study contributes a comprehensive framework to the ambiguous research on educational learning using games. MMT is then used in empirical experiments to address two sub-problems: 1) Why players sometimes choose to lose the game, completely derailing its intended purpose; 2) The design of inherently learnable systems in terms of how the complexity of a game relates to the player’s ability to master it - searching for forms of complexity that elicit curiosity to learn about that complexity. These experiments demonstrate the value and manner of how to apply MMT to investigate specific psychological phenomena while retaining a logically coherent place in our understanding of how educational and serious games achieve positive outcomes - a logically coherent place provided by the framework ofMMT. This body of work provides practical applications for game developers and educators alike, as well as interesting theoretical implications for cognition, curiosity, and complexity.