An Agent-Based Modeling and Simulation Tool as a Learning Aid for Diffusion of Innovations

The diffusion of innovations describes how new technologies spread through a population. Agent-based modeling and simulation (ABMS) cover interactions among autonomous agents and the analysis of emergent outcomes from the behaviors, reactions, and interactions of these agents. Existing studies using ABMS aim to illustrate dynamic agent behavior and interaction with other agents and the environment in the context of diffusion of innovations. However, they do not extend the use of the simulators to teaching and learning. This study describes an ABMS built using NetLogo that allows students to explore the impact of various agent characteristics, behaviors, and interactions on adopting new innovations. Students can manipulate certain parameters involving the characteristics of these agents, such as their level of innovation propensity, social influence, and connectivity, to see how these factors influence the adoption of the innovation. The outcome of each run is logged, analyzed, and presented to the students as meaningful feedback and suggestions for supplementary learning from an LMS in preparation for succeeding simulation iterations. The simulator preserves agent autonomy and adaptability while allowing the students to play with model parameters. As the simulator transitions to more empirical data for rules governing the behaviors of agents, future versions of the simulation may incorporate additional user interface and Al-based simulator elements.