Irony as complexity scaffold for deep learning

Abstract

In Feller (2008) I have argued that irony can be used to motivate people to take a specific course of action. Based on my findings, this paper looks into the effects irony can have on someone’s mental actions. More precisely, I argue here that ironic expressions can be used in learning interactions to promote deep learning. Under certain circumstances, it can serve as a complexity scaffold in the sense that the learner is prompted into thinking along more complex schemas. Following Chi and Ohlsson’s (2005) psychological framework for deep learning, I illustrate how irony facilitates the learner’s arriving at new insights by re-representing her knowledge in certain ways. I will demonstrate on the back of selected examples of quasi-authentic learning interactions from the US television show House, M.D. how this works.