update

doc/src/week48/exercisesweek48.do.txt

@@ -1,4 +1,4 @@
-TITLE: Exercise week 48
+TITLE: Exercises week 48
 AUTHOR: November 25-29, 2024
 DATE: Deadline is Friday November 29 at midnight
 
@@ -18,11 +18,11 @@ And do you feel this course added to your programming competences and skills?
 
 === How do you judge your own level of knowledge on machine learning before and after this course? ===
 
-Here you can discuss your level of skill/knowledge at start of course
+Here you can discuss your level of skill/knowledge at the start of course
 and at the end of the course and how these matched the level of
 skill/knowledge needed to complete the projects.
 
-=== Did the projects and the teaching material allow you to deepen your insights about Machine Learning? ===
+=== Did the projects and the teaching material allow you to deepen your insights about Machine Learning methods? ===
 
 Feel free to comment here. 
 
@@ -34,8 +34,7 @@ it as it is since we see very clearly that people who attend this
 course have a very good learning outcome. Project based courses are
 however demanding (and expensive seen from the university admin) when
 it comes to proper feedback and evaluations. Feel free to discuss
-whether you found a project-based and active learning approach
-useful. Feel also free to comment upon things we can improve upon or
+whether you found a project-based useful. Feel also free to comment upon things we can improve upon or
 alternative ways to assess whether the learning outcomes have been
 achieved. Would you for example prefer a standard 4 hours written exam
 be something you would prefer?  Or other alternatives to projects? We
@@ -48,12 +47,10 @@ Did the weekly exercises help in getting started with the projects?
 How relevant where they for solving the projects?  Feel free to
 elaborate
 
-=== Active learning/lab sessions and lectures ===
+=== Lab sessions and lectures ===
 
-Was there a good link between lectures and active learning sessions?
-Would you prefer an active learning environment only with no lectures
-or would you prefer a more lecture based format with lab sessions only
-(that is no discussion at the beginning of the lab sessions)? Feel
+Was there a good link between lectures and lab sessions?
+Feel
 free to comment.
 
 
@@ -76,7 +73,7 @@ here such as how to improve to teaching material and more.
 
 === Which resources and tools did you use? Jupyter-notebooks, GitHub, the various textbooks we have recommended, etc etc ===
 
-=== If you did not attend the lectures or the active learning/lab sessions, which resources did you use? ===
+=== If you did not attend the lectures or the lab sessions, which resources did you use? ===
 
 
 === Any other topics, impressions, ideas etc you would like to share with us? ===