Paper Number
ICIS2025-1759
Paper Type
Complete
Abstract
Digital game-based learning (DGBL) is often described as “complex”, given its cognitive, affective, motivational, and socio-cultural dimensions. However, few studies have applied complexity science frameworks to examine these dimensions. This study proposes a theoretical framework grounded in Synergetics, enriched by educational psychology and information systems. Using a longitudinal study design, we investigated critical fluctuations in the usage of Generative AI for instructional support in a five-week business-simulation game to explore how system elements and constraints shape learning processes and outcomes. Findings reveal that students experienced critical fluctuations during a simulated crisis, supporting the view of DGBL as a complex system. PLS-SEM analyses show that Germane Cognitive Load and Enjoyment predicted final exam scores during crisis. Additionally, all four engagement dimensions were significantly influenced by at least one of the following: Intrinsic Cognitive Load, Self-Regulated Learning Strategies, or Game Success - in turn shaped by Extraneous Cognitive Load and Course Affiliation.
Recommended Citation
Wenzel, Anna; Geiger, Jan-Martin; and Liening, Andreas, "Emergent Human-AI Interaction Reveals Critical Fluctuations in Digital Game-Based Learning: A Complexity Science Perspective" (2025). ICIS 2025 Proceedings. 9.
https://aisel.aisnet.org/icis2025/learn_curricula/learn_curricula/9
Emergent Human-AI Interaction Reveals Critical Fluctuations in Digital Game-Based Learning: A Complexity Science Perspective
Digital game-based learning (DGBL) is often described as “complex”, given its cognitive, affective, motivational, and socio-cultural dimensions. However, few studies have applied complexity science frameworks to examine these dimensions. This study proposes a theoretical framework grounded in Synergetics, enriched by educational psychology and information systems. Using a longitudinal study design, we investigated critical fluctuations in the usage of Generative AI for instructional support in a five-week business-simulation game to explore how system elements and constraints shape learning processes and outcomes. Findings reveal that students experienced critical fluctuations during a simulated crisis, supporting the view of DGBL as a complex system. PLS-SEM analyses show that Germane Cognitive Load and Enjoyment predicted final exam scores during crisis. Additionally, all four engagement dimensions were significantly influenced by at least one of the following: Intrinsic Cognitive Load, Self-Regulated Learning Strategies, or Game Success - in turn shaped by Extraneous Cognitive Load and Course Affiliation.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
24-Learning