A Conceptual Cognitive Approach for Designing Digital Learning Games that Cultivate Higher-Order Cognitive Skills

Abstract

Despite the growing interest in using video games for education, a significant challenge remains in designing learning games to effectively foster deep-level learning and higher-order cognitive skills. This limitation continues to hinder both the design and classroom integration of learning games. One promising direction is to explore how the nature of knowledge influences learning game design choices. In this thesis, I address two key research questions:(1) How does the nature of knowledge affect the development of higher-order cognitive skills? and (2) How does the nature of knowledge affect the design of learning games that cultivate higher-order cognitive skills? To answer these questions, I take a cognitive approach and examine knowledge structures through the lens of six fundamental and complementary theories drawn from cognitive psychology, cognitive science, educational pedagogy, and neuroscience. These include Schema theory, Mental model theory, Parallel Distributed Processing theory, Constructivism, Distributed Hub-and-Spoke theory, and the Sparse Coding and Concept Neurons model. Through a cross-disciplinary synthesis of these theories, conducted using thematic analysis, this research suggests that knowledge structures are crucial for developing a deep understanding of the world, and subsequently, higher-order cognitive skills. This type of understanding requires learners to do more than memorize facts; they must construct robust knowledge structures by organizing individual knowledge units around core concepts and identifying their relationships. Based on this synthesis, I conclude that concept-based learning is critical for developing higher-order cognitive skills such as complex problem-solving and critical thinking. Therefore, when leveraging learning games to foster these skills, their design should also focus on promoting conceptual understanding. To satisfy this design need, I propose a novel learning game design framework: the Conceptual-Input-Processing-Output-Feedback (C-IPOF) framework. This framework systematically integrates the principles for building knowledge structures from the six theories and borrows operational concepts from three established instructional frameworks to translate these principles into actionable design insights. The C-IPOF framework offers practical guidelines for designing learning games that promote the construction of knowledge structures and conceptual understanding. This research reframes the function of learning games in education, positioning them not merely as a tool for digitizing content, but as a powerful medium for building robust knowledge structures. This new perspective provides a solid foundation for future research to investigate the cognitive principles underlying effective learning game design.