Skip to content

Evaluation

Statistics

question mean_pre mean_post p_value different
I feel comfortable with the book 'R for Data Science' 0.7692308 4.000000 0.0002311 TRUE
I can recommend the swirl package to the right person 0.6153846 3.222222 0.0018848 TRUE
I can use ggplot2 to create a simple plot 1.8461538 3.666667 0.0635871 FALSE
I can save a plot created by ggplot2 2.0000000 3.555556 0.0759172 FALSE
I can tell what ggplot2 aesthetics are 1.0000000 3.666667 0.0010547 TRUE
I can tell what ggplot2 geometrical objects are 0.6923077 3.666667 0.0011247 TRUE
I can assign a value to a variable 1.6153846 4.000000 0.0043364 TRUE
I can use snake case when naming a variable 0.5384615 3.888889 0.0001414 TRUE
I can write a comment 1.9230769 3.666667 0.0520753 FALSE
I can correct typos in simple code 1.9230769 3.777778 0.0283757 TRUE
I can read a comma-separated file 1.9230769 3.875000 0.0457190 TRUE

f

Confidence

All confidences

Confidences per question

Feedback

  • This was a little fast-paced, even for a user with some experience with R. Very helpful though! Plenty to take with me and go from here.
  • I think the course was a bit too packed - although I have experience in coding (in Python) using a ""new"" language takes some time so it was difficult to get through all the exercises
  • Thanks so much for a fun and informative lecture. As a self-learner I really appreciated all the resources you have shared with us! Also, I loved your positive attitude and high energy :)
  • Maybe it would be better to explain how to read the code before actually using the program, but overall it was a formative and fun experience
  • It has been fun learning about R although, I feel I still need to make time to learn and understand it since I am a complete beginner. Otherwise, I thoroughly enjoyed the session.

KTH course evaluation

16. Were there any parts of the course that were excellent?

If so, please specify which parts and in what way. Were there any parts of the course that were excellent? If so, please specify which parts and in what way

  • the course content overall, Meike was a very informative and helpful teacher
  • The course was brilliant — very well put together and thoughtfully structured. I especially appreciated the software practicals that were especially helpful in familiarising us with the tools. The lectures were easy to follow, and all concepts were clearly explained. They provided a comprehensive and well-structured overview of the most important aspects of data visualisation and scientific illustration. The constant encouragement from Meike and the opportunity to receive iterative feedback made a big difference. It felt like a supportive learning environment rather than just lectures. I now feel inspired and confident to develop visuals and graphical abstracts for my research data. Thank you so much!
  • Meike's lectures, tutorials and self-study documents in AI/Inkscape.
  • Overall the design of the course. You learn a lot from both the teacher, your peers, and yourself, which is unique! Meike is probably one of the best teachers I’ve ever had. She really helps you to look at design as both artist and scientist.
  • It was great Meike was open to discussing and having exercises for the three major vector illustration programs. I valued that flexibility. Happy to see the design elements and theory in how to build figures.
  • Yes. The most exciting part for me was the projects we had to do. They were challenging in a way that pushed me to go out my way to finish the text. They weren't so easy for me but I loved that I got to see the level of my growth through them.
  • Excellent course format and lectures by Meike. It's clear she knows how to structure and convey information well. The notion page was also very clear, nice to hold onto. The frequent breaks and active participation really boosted my concentration spans (during pandemic I was always exhausted after half a day, here not at all).
  • The content of the lessons was in general really good. The practice exercises were well designed and allowed to easily get hands-on experience. The mid-course and final feedback sessions were excellent to get feedback as well as practice to critically evaluate scientific visualizations.
  • The entire course was excellent. The course was very well structured and each section's learning goals were clear. The balance between "passive" learning and working on our projects was great. I particularly liked that we could work with our data and topics. Moreover, the instructor was extremely knowledgeable and very open to students' questions and feedback.
  • The Adobe classes were extremely nice! The setup of the document to learn the most important tools was super helpful and intuitive. The submission deadlines and feedback provided were also very nice.
  • Maike was a great teacher - very knowledgeable and motivated! I think her balance of theoretical input and practical exercises was great. The size of the group was also good - and that we worked a lot in smaller groups/break out sessions. Especially the sketching sessions helped me develop a better feeling on how to start a visualisation process.
  • Meike is an amazing professionist and teacher, always punctual and understanding of everyone's needs.

17. Do you have any recommendations as to how the course could be improved?

If so, please specify which parts and how. Do you have any recommendations as to how the course could be improved? If so, please specify which parts and how

  • I think the way that the course is structured in the data viz part is a bit messy, meaning that we were required to start working on the code but with only few functions explained and how the language actually works. This led to some confusion and to rely on other tools to make the code work. It could be better to first give more background on how R functions and then make the students work on the coding.
  • I am not from Karolinska Institute but from a different uni and I was a bit surprised when I got the schedule the week before the course. Of course I knew it was a 2-week course but at least for me it was a lot because I still had to do my normal lab work next too it. Some more information already during the application process would have helped. The sections on R were not so well organized in my opinion. It seemed that the two different teachers for R did not talk to each other so some things were redundant - and some things that were explained later really should've come first. Especially regarding R there was a huge range of experiences within the group and I feel like most people were left out; either because it was too easy or because it was too complicated. The talk from Lonni Bresancon while interesting was not relevant to the learning objectives at all - maybe this could have been skipped or made more clear that it was not mandatory.
  • I would suggest adjusting the order of the R lectures. It felt like some of the more advanced material came before the basics were properly introduced, which made it a bit hard to follow for some people. I think starting with the foundational concepts earlier would make the progression smoother and more accessible for everyone.
  • I didn’t enjoy group work in R. I think that when it comes to coding, individual work is the way to go. When it’s such diverse group there is always someone knowing a lot and someone knowing nothing and it ends up with one person coding and the rest not knowing what to do. I had similar sessions several times and it always ends like that, which means that most people learn nothing during it. But it was just one exercise, so no biggie.
  • Maybe the course could be divided in two: one for complete beginners, and one for users with some experience. Beginners could benefit from having more dedicated time to learn to use the software, and experienced users could focus on more advanced exercises and tools.
  • I found that the mermaid toolbox was not that useful and the time allocated to it was not needed.
  • The course is well structured and touches on so many aspects of learning. However, the one major thing that can be improved is to find a way to help complete beginners in more active way to avoid them having the anxiety out not understanding something and feeling the pressure because others are ahead with the task. Otherwise, they end up feeling left behind.
  • Sessions regarding the use of R could be more wisely organized. Now the exercise with Martin was a bit out of place and hard to follow. Also during Richel's sessions there was quite limited time to work through the exercises if you had not worked with R before. Maybe a similar tutorial session with self-study component that was now done with Illustrator could work better also with R.
  • Martin Jonsson had a accessible presentation about R, but fluency and structure could be improved (seemed confused with some examples). How do we use ggplot in concert with vector software to make a clear figure?
  • I can recommend some clarity in the syllabus, there is no mention there about R, however it still was a dominant part of the course. Based on the syllabus my expectations were a course predominant on the usage illustration software and not an introduction to using R and plotting with R.
  • I think the r coding parts were the weakest part of the course. I luckily had prior knowledge of R, so for me it was good to follow. However, the coding that was shown was usually very fast without explaining every step. I can imagine this is not optimal for new learners.