diff --git a/docs/R-IOC/07_IOC_R_week_06.md b/docs/R-IOC/07_IOC_R_week_06.md
index 57ec726f6..46b61c8b9 100644
--- a/docs/R-IOC/07_IOC_R_week_06.md
+++ b/docs/R-IOC/07_IOC_R_week_06.md
@@ -6,28 +6,29 @@ and sometimes even more intuitive. On your marks, get set, go to the section [ti
 
 ## Let's Practice
 
-For each week, you'll have a set of exercises that you must render in an R script. 
+For each week, you'll have a set of exercises that you must render in an automatic rapport. 
 After that you need to complete the following google form to answer some MCQ (Multiple
-Choice Questions) where the final question is to deposit your R script.
-Please note that an Rscript has the extension `.R` but it's not supported by Google Form.
-To avoid this inconvenience, you need to add the `.txt` extension to make your file named as: `NAME_week6_script.R.txt`. 
+Choice Questions) where the final question is to deposit your RMD/QMD.
+Please note that an Rscript has the extension `.Rmd`/`.qmd` but it's not supported by Google Form.
+To avoid this inconvenience, you need to add the `.txt` extension to make your file named as: `NAME_week6_script.Rmd.txt`. 
 
 ![](images/toolbox-do-it-yourself.png){: style="width:75px"} **Do it yourself!**
 
 - [x] 1. Create a tibble `my_phones` from the available data.frame `WorldPhones`. Beware of the rownames ! We don't want to lose them
 - [x] 2. Make it tidy and write it in `my_phones`
-- [x] 3. Filter the tibble to retrieve only the European (don't write it in `myphones`).
-- [x] 4. Select the tibble to retrieve only the region (don't write it in `myphones`).
-- [x] 5. Replace "." by underscore in region name
-- [x] 6. Replace truncated region names (`Amer`) by the full continent name using stringr's pattern matching functions.
+- [x] 3. Filter the tibble to retrieve only the European (don't write it in `my_phones`).
+- [x] 4. Select the tibble to retrieve only the column that contains region names (don't write it in `my_phones`).
+- [x] 5. Replace "." by an underscore in region name 
+- [x] 6. Replace truncated region names (like `Amer`) by the full continent name using stringr's pattern matching functions.
 - [x] 7. Group the data based on the region
 - [x] 8. Compute the mean of number of telephones per region
 - [x] 9. Add a column with a normalized number of telephone per region (Reminder : `norm_val = val - mean(val) / sd(val)`)
 - [x] 10. Resume the information to check if the mean equal 0 and the sd equal 1. What do you get ?
-- [x] 11. Do the same for the last 4 questions but by grouping on the year you can change the created column names
+- [x] 11. Do the same for the last 4 questions (from Q7 to 10) but by grouping on the year you can change the created column names
 - [x] 12. Resume the information to retrieve the Year with the most phones for each region
 
-Please be aware of the best practices for your Rscript, we will be attentive to them!
+Please be aware of the best practices for your Rmarkdown or quarto document, we will be 
+attentive to them!
 
 Now you can fill the following quiz: [Quiz of week 6](https://forms.gle/aNvCqoyqZbajxtZQ9).