Abstract

Reasoning about analogical arguments is known to be subject to a variety of cognitive biases, and a lack of clarity about which factors can be considered strengths or weaknesses of an analogical argument. This can make it difficult both to design empirical experiments to study how people reason about analogical arguments, and to develop scalable tutoring tools for teaching how to reason and analyze analogical arguments. To address these concerns, we describe WG-A (Warrant Game — Analogy), a framework for people to analyze analogical arguments based on Bartha’s (2010) Articulation Model of analogical argumentation. We carry out two experiments designed to probe WG-A’s effectiveness in improving participants’ ability to reason about analogical arguments and argumentation in general, and argue that WG-A is a promising approach, though it is in need of further development.