The Use of Robotic Players in Online Games


  • Jon Guest Aston Business School, UK
  • Matthew Olczak Aston Business School, UK
  • Robert Riegler Aston Business School, UK


Short in-class games have become an increasingly common way to teach a range of key concepts and theories in economics. These allow students to gain first-hand experience of incentives and the impact on decision making. This makes it easier for tutors to convey underlying economic theory and the implications of the resulting predictions. Furthermore, there is increasing evidence that these can have a positive impact on student learning (e.g., Emerson and Taylor, 2004; Dickie, 2006; and Emerson and English, 2016). The move to an online teaching environment due to Covid-19 presents challenges for using this method of interactive teaching. Online versions of economics games have become increasingly common, and Carter and Emerson (2012) find no significant difference in students learning between paper and online experiments. However, these online games typically require human-human interaction. Consequently, the widespread adoption of asynchronous activities means that students cannot play such interactive games against one another. An alternative is to run games in which students play against robotic players that make decisions according to some pre-programmed rules. This greatly increase the possibility of using online games asynchronously. However, as it stands very little is known about how this affects student learning. The aim of our study was to investigate how student perceptions and in-game behaviour change when robotic players are used. Our study relates to a wider literature on framing and anonymity in games (e.g., Ross and Ward, 1996 and List et al., 2004). In addition, we also contribute to a wider literature on human-robot interactions (e.g., Wu et al., 2006).






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