diff --git a/exercises/exercise-model/README.md b/exercises/exercise-model/README.md
index 8892a84b3a0d0454e0d7aec3468a6bb585988ed0..cc50a4434272090394b7e7f222deb12e8af708ee 100644
--- a/exercises/exercise-model/README.md
+++ b/exercises/exercise-model/README.md
@@ -1,6 +1,6 @@
 # Exercise Model (DuMuX course)
 The aim of this exercise is it to learn how to set up a new model (new system of equations).
-As an example, we implement a nonlinear diffusion equation mode and apply it for image denoising.
+As an example, we implement a nonlinear diffusion equation model and apply it for image denoising.
 In this exercise, we will only consider the bare minimum of classes to successfully assemble
 and solve such a problem with DuMux. We also implement the model for a specific discretization method
 (the Box method: a vertex-centered finite volume method also known as control-volume finite element method with piece-wise linear basis functions).
@@ -38,17 +38,17 @@ The diffusion example also derives the discrete equations using the Box method a
 
 :arrow_right: Copy the `model.hh` file from the diffusion example into `dumux-course/exercises/exercise-model` and choose appropriate class names.
 
-In the local residual, you can start with a hard-coded diffusion coefficient of `1.0` (linear diffusion coefficient function).
-(Replace `problem.diffusionCoefficient()` by `1.0` because our problem class in `main.cc` does not have a `diffusionCoefficient()`  interface.)
-The goal is to get the simulation running first and then add improvements. For this, it is important to have a
-compiling test such that new changes can continuously be tested.
-
 Do also not forget to change the [include guards](https://en.wikipedia.org/wiki/Include_guard)
 at the beginning of header files (`DUMUX_EXAMPLES_DIFFUSION_MODEL_HH`).
 Include guards have to be unique in the entire application that you compile. (Otherwise some
 code will not be included.) An alternative is using [`#pragma once`](https://en.wikipedia.org/wiki/Pragma_once)
 which is widely supported but not specified by the C++ standard.
 
+First, the goal is to get the simulation running and then add improvements. For this, it is important to have a
+compiling test such that new changes can continuously be tested.
+Thus, in the `computeFlux(...)` function of the local residual, you can start with a hard-coded diffusion coefficient of `1.0` (linear diffusion coefficient function).
+(Replace `problem.diffusionCoefficient()` by `1.0` because our problem class in `main.cc` does not have a `diffusionCoefficient()`  interface.)
+
 Each model also needs to define a model type tag for setting model-specific properties.
 
 :arrow_right: Rename the one of the diffusion model (`struct DiffusionModel {};`) to `NonlinearDiffusionModel`.