Part of an academical job is to lecture. Myself am very lucky that this duty is part of my obligations as I really like to do it. In the past I have mainly assisted teaching or did tutoring in various lectures, but next term I will get my own lecture to plan and give in full. I will get important assistance on one or two lectures as my schedule require me to be away for some dates, but apart from that it I will have to fill the four hours a week. The topic will be in a statistical area and so more in my core expertise as my lecturing I did up to now, which was mainly in the physical areas of climate science.
In the upcoming months I will write some posts about this topic, my experience of preparing the lectures and my thoughts about concepts. Of cause I will omit talking about the actual lectures, as students should never fear that they are put on the spot. As the topic of the lecture will be the basis of statistics, it will be not so much about the actual topics, but on how to present them and how to make it an interesting learning experience for the students.
As there are another two month to go I have started to prepare the first lectures. All in all there will be roughly 15 weeks to fill, partly with predefined content and with practicals. The german system sets a fixed numbers of hours the student should work on any lecture and in my case this number can be worked out as 12 hours per week. That is a lot, because even with taking the four hours of presence study not into account, there are eight hours left. So it will be a balance to get enough stuff into the lectures and explaining it in a way that a general unloved topic can be understood. Statistics is for many students like maths and that is in applied physics courses like meteorology/oceanography/geophysics usually not very popular for them. Usually one to two years of mathematical studies, mostly not very connected to the rest of the curriculum, are the beginning of every students life and so the next step with a mostly quite dry topic like statistics is thought to be the same. And unfortunately, therein lies a problem. When you get into statistics too much on the applied side, then you do not give context to the maths lectures given before and it will get harder for the students in the future to get into statistics properly (so not only as an auxiliary subject, but a real tool which is comfortable to handle). On the other side when you do it too mathematically, it is just another hated maths subject. Balancing in the middle of it is certainly an aim, but not really realistic to achieve.
I am looking forward to this experience, but am also aware that all my planning and thoughts might not work out as planned and it ends up it a struggle for the students and myself. That is a challenge and I like challenges.