Low-fidelity buyer seller simulations can encourage authentic learning experiences

Abstract

The goal of this study is to introduce and evaluate a novel online simulation method built upon buyer-seller roleplay in a private social network for housing economics education. This is at a time when classroom disruptions due to COVID-19 require new methods to engage with students asynchronously. While methods like game-based learning simulations show potential to engage, they are often high-fidelity and require high setup costs. This is also the case for existing housing simulation games, for which besides being single player mode, costs for technical customization and learning curve reduces adoption in the classroom. In this context, the use of social networks to facilitate a low-fidelity buyer-seller housing roleplay may provide flexible learning goals and peer engagement, but its implementation is unclear. This gap in knowledge has motivated this investigation, for which undergraduate students in Hong Kong participated in property buyer-seller roleplay. Students posted available property and buyers bid for them using comments on a private social media app, Soqqle. Post-course reflective essays suggest that various student needs were met, indicating that the setup supports flexible learning outcomes. Authentic learning outcomes like knowledge transfer, reflection, challenge, and realism were also experienced. Further, although statistically insignificant due to lack of observations, a regression analysis shows that experiencing and overcoming challenges (β = 3.996, p = .082) provides the biggest learning outcome (R² = 0.325). A focus group with other simulation practitioners suggests the benefits of this method could extend to them. The findings of this study can benefit practitioners of game-based learning looking for quick and easy methods to introduce online roleplay for real-life scenarios in their classes.