Skip to content

Reflection

Before teaching

After teaching on the first day, I reflected. Today, due to that, I added the 'Why is R important?' and 'Why is ggplot2 important?', as well as a demo to the schedule. It felt like fixing my own teaching. I think it is interesting that have missed this important part of a lesson. That I missed this is easy to explain: my private life feels rushed and too-little-time too.

During teaching

I did the two better-late-than-never sections at the start, then I let the people that want to work in their breakout rooms, while others would see the demo. The majority stayed. Then I did the demo. This went smoothly, except for copy-pasting into the Zoom chat: it sometimes took ten seconds to load. I used the Slack as a backup for pasting quickly.

I asked some learners if the demo was useful and if I should do that demo on day 1. One stated that the demo was useful, but day 1 would be too early. Another stated that the demo was useful and that it should have been on day 1.

  • [x] do the demo on day 1

I think I should do the demo on day 1, so I added this to the schedule to remind me.

Such opposite opinions reflect the diversity of the group well: it had everything from complete beginners to not-really-needing-to-be-there experts.

After the demo, I went through all the rooms. I noticed I had created too few rooms, so some learners cramped together in a room first, and later moved to fill up a vacant room.

At around 10:30 around three fourth of the learners were already asking questions about how to communicate clearly with a plot. At around 11:30, I understood from the last learner that he/she had a plot, so my mission has been successful.

After teaching

I never felt connected to my teaching these two days, in the way that I usually do. Sleep will fix this.

It was an interesting experience, with a mix of

  • A diverse group
  • Problems due to a mismatch between the bigger and my course
  • An unexpected second learning outcome
  • all (?) learners achieving the goal

I will evaluate in a bit more detail with the course coordinator on Friday.

Evaluation results

A lot of ""I am cool and enthusiastic and flexible and do what you want"" show and a little too little orientation over the course contents / the plan / the to dos -> I found the freedom not engaging but confusing. Please record lectures in the future for 2x option (even though I do understand that the way it is structured now, it does not really make sense to record it, because there is no content to record, but then the label ""lecture"" in the schedule is maybe not the best description of what it is)"

I agree that there is a lot of freedom. I think what would help improve this is to first offer a structure in general, then offer flexibility in breakout rooms for those that need it, like I do in all (?) other courses I teach. I love the quote 'I found the freedom not engaging but confusing' and I will use it as a reminder to myself.

I also agree that the start was not done well and I have already improved that.

I agree that 'lecture' would be a misnomer. Taking a look at the schedule, there is no mention of the word 'lecture'. Maybe this learner would also agree with me that 'course' is a misnomer and that it should be called a 'workshop' instead. Aha, now I get it: my workshop is put in the bigger course's schedule as a lecture!

  • [ ] Ask the course coordinator to refer to my sessions as a workshop

It was a good repetition of R theoretical part, I could work on my own pace. Help was available if needed.

Great!

I had no previous experience in using R and I feel that in just two morning i managed to learn the very basics with plotting a graph. I feel that there should have been at least a small lecture where the teacher was going throught the very basics (how your data should look like on excel, or how to save your R script for example). I found these two hours fun and this increased my interest in learning how to use R better

I agree with this learner and I think he/she missed the lecture on day 2 (that should have been given on day 1), where I did most of these suggestions. I enjoy the tip about reading Excel: I've seen more people using it. As this is a very diverse group of people, it would help those that need it.

  • [ ] Add how to read Excel data

I think It would be good at the beginning of the course to make a more clear distinction between the experience people have with Rstudio, to make it less frustrating for the people who have not tried it before and also make better groupings ind the zoom-rooms. This would make it easier for people to get what they need out of the course and also have better discussions with people on the sample level - to generalte ideas for how to display data.

I agree that it should have been more clear that the course provides for learners of all levels. I have already updated this in the course material, but maybe I should make this even more explicit, for example, by grouping people on experience level.

  • [ ] Consider grouping on experience level.

I have created some kind of plot, but I had to figure most of it out on my own, with the help of AI... It had been very helpful for a beginner like me to have the introduction to R Monday morning (not Tuesday). It had saved me some anxiety at least.

I am happy we agree that I should have done that presentation on day 1. It would indeed make life less stressful.

Richel is a friendly teacher to interact with, which makes the learning much more fun and easy!

Great to hear.

After going through these evaluation results

I am happy to see how these results point in the same direction as I did myself. I had already done most of these suggestions, and I will add to my to-do list the items below. A thank-you to the learners!

  • [x] Ask the course coordinator to refer to my sessions as a workshop
  • [->] Add how to read Excel data
  • [->] Consider grouping on experience level

Reflection with the course leader

  • She agreed to call these sessions a workshop

Course evaluation results

Verbatim Student Submissions

  • I really like the part that there's an the time slot to freely work on our own project and get feedback from it. Also the part where examples of good illustrations were used to explain the concept and process of design.
  • Great course and competent teachers.
  • Having a journal was very useful to follow up the progress one has made during the course.
  • The possibility to receive feedback, make improvements, and receive feedback again was also very appreciated.
  • Hands-on training on the design softwares was very high quality and easy to follow. In general the first week of classes was all top notch. Overall the best course I took during my whole PhD!
  • I think having the journal to stay accountable and on top of assignments was good. All of Meike's lectures were super informative and useful.
  • Friendly environment and very interesting lectures.
  • Learning how to make graphic abstract using affinity
  • Meike Latz's parts were well thought through, utilized great methodological diversity matching the each topic, very well strctured. Engaging. Flexible. One of the best online courses I had in a long time.
  • Overall i really enjoyed this course! I loved the freedom to do figures and the time to also work on it by my self by still be able to seek help if needed. And really beneficial to get feedback from other people not in my field, to see where the figures might have been to complicated or to confusing.
  • This was among the best courses that I have participated in. Very clear structure, great teacher, very interactive and I learned a lot. The lectures were well structured and provided a lot of opportunity to be implemented in my later career (even if its not academia). I would recommend this as a mandatory course for every PhD Student.

Verbatim Student Submissions

There are some responses that are quite negative against me. I am fine with that: I am happy that the learners speak their thoughts. Within the course, the R sessions is a bit of an outlier: (1) it is a minor part of the course (2) the main audience (i.e. people that are attracted to do graphical visualisations) may not be attracted to programming, (3) the learners are expected to work (unlike the other minor parts in the course, where they are only expected to listen). Due to this, me and the course leader expect most negative feedback to go to this part of the course.

  • Not really, keep it as it is. This was the first KI course I recommend to other PhD students.
  • I think it would be great if during week to the students were devided into groups of who have experience with Rstudio and who do not have.

Great idea! Me and the course leader already agreed to do so too :-)

  • Because as somebody with experience I used a lot of time on helping with the basics and I think that because I was not prepared for this I did not know how to do it properly - to lessen the students in my groups frustation of learning a completly new program. So I could have used my time better by talking and developing ideas for my data visulization if I had been in a group where people have experience and the one i 'helped' could have learned it better if they had gotten a structred teaching on Rstudio.

I wish I understood better what happened here. I never ask my learners to take over teaching. I do ask them to help each other. I do see (and saw here too) that some learners start teaching. And I feel this is a good thing: the learners have some freedom on how to engage with each other and I should be generous on how they should do so. However, what happened here is not what I wanted; that a learner started taking over teaching.

What I do know, is that the plan to differentiate between learners has already been accepted. I hope that that will resolve this issue.

  • The R session was very confusing and disorienting. Working with a book does not need to happen in breakout rooms. Very irritating teaching style in terms of the way we were spoken to, in my opinion.

These are different ideas. I think working with a book should happen in breakout rooms. My teaching style is annoying for passive learners and I will accept any criticism from that.

I do agree that I could have done a better job and have already decided to do so before these evaluation results came in. I hope that that will fix this.

  • I personally find that the homework needs more than the planned time, especially to get use to a new software. It could have been a bit more credit hours.
  • Richel Bilderbeek was not the perfect teacher for a total beginner in R! I would have wanted some introduction and some tips and tricks how to at least get started. (He did not teach med R, AI did.)

Yes, I agree that a demo should have been on the first day. This has already been updated in the course schedule.

  • The description could be a little bit more clear. I misinterpreted it somewhat. Quite overwhelming for someone who has never worked with vector programs or R before.
  • It might be better to have the possibility to have education IRL during the practical sessions. Difficult to get help online.
  • They should allow the use of elements from Biolender
  • The DataVis practice on the Wednesday of the 2nd week felt very repetitive, especially the group parts in breakout rooms, after we had talked a lot about data visualisation. Maybe it should be earlier in the course. I also didn't find the lectures on Thursday very useful, there wasn't much tangible information in there, more like 'hey be aware those things exist and look into them'.
  • I also would suggest making people plot the same data for the 2 data visualisations, it makes it more interesting to compare how to communicate in scientific publications and to a general audience.
  • Even though graphical design skill were not required, it would be good to mention it in the syllabus. It was a bit stressful in the beginning.
  • Maybe the R software part could be a bit more redesigned / flexible to include multiple softwares for those who are not using R frequently.

Yes, we will divide the beginners into groups.

  • Would be nice to add a section on which graphs / visuals can work better to convey the message and impacts for different types of data.

Reflection

  • [ ] Add how to read Excel data
  • [ ] Group the learners on experience level, e.g.
Level Description
A I can write R code comfortably
B I can get (mostly copy-pasted) R code to work
C I have never gotten R code to run