SL Tool #1: Toulmin Method
The Toulmin Method (aka Model) was a six-part model developed by Stephen Toulmin.
Jun 10th, 2020 | 1 min read

The Toulmin Model is a method of thinking. It shows the components needed to sustain a better argument. Toulmin found there are six components of an argument: Claim, Data/Grounds, Warrant, Backing, Qualifier, and Rebuttal. The first three are fundamental parts of an argument (Claim, Data/Grounds, Warrant); while the last three are not fundamental, yet help us make stronger arguments (Backing, Qualifier, Rebuttal). A good discussion of the Toulmin Method can be found at the Purdue Online Writing Lab.

The six components are:

Image created by Dr. Schwandt via Plectica

Claim: the assertion you are making and want to prove. This is the argument you want to make.

Data/Grounds: the evidence and facts supporting your Claim.

Warrant: the assumption linking the Data/Grounds to your Claim.

Backing: provides specific support for your Warrant.

Qualifier: tells the reader that your claim is not or might not be true in every situation. You will typically see words such as: many, some, chances are, presumably, etc.

Rebuttal: acknowledges other valid perspectives of the situation.

Let's look at an example.

Image created by Dr. Schwandt via Plectica

In this example, my Claim is that student feedback improves a course. The evidence I have to support my Claim (my Data/Grounds) is that my class is centered on feedback provided by students. The assumption (Warrant) linking the two (my Claim and Data/Grounds) is that students care about what they are learning.

The specific support (Backing) for my warrant is that students have provided feedback in my class. What I assume to be true (yet it might not be) is that student feedback helps improve a class (Qualifier). Finally, a possible Rebuttal to my argument is that students do not provide candid feedback, nor do they care about what they learn. I would rebut the Rebuttal (easily); however, this provides a simple example to a powerful method.

This article was written by Jamie Schwandt.
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