One in a series of posts about an aeronautical engineering course I created this year.
This first lecture focuses on the notions of lift and lift coefficient as they apply to ordinary flight. The project’s aims were to explore the very peculiar way in which drag constrains flight, as well as the notions of energy and power, through the exploration of the flight domain of an aircraft.
The lecture approaches the main notions in a practical, exploratory way: we make many small thought experiments in class to come up with the main physical trends (which results in the numerous graph curves shown in the hand-outs). This makes for a rather intense, and I hope, productive time in class; however as a result the notes are less effective at guiding the reader through.
The project looks somewhat like a puzzle at first sight, but once “cracked”, provides a great platform for the student to play with the data (for example, “what happens if the wing surface is shrunk?”).
Only one hour into the lecture it became clear that there was a significant gap between my pace and the students’, and subsequently a lot of effort went into bridging it. The English language was not, I believe, preventing understanding, but it made the lecture so much more demanding for the students that little energy was left for participation.
It was also the students’ first encounter with the unusual format of the lecture and hand-outs, so the lecture took longer than it should have. I still think it went well.
The project, too, took too long. My hope was for the first sketches of the flight domain to come up within the second hour of in-class work, so that the rest of the time could be dedicated to exploring the many interesting implications of the results. Unfortunately, by the end of the day many teams were barely on track, and most students obtained their results very late in the project cycle.
Next time I will spend much more time and energy explaining that the project shouldn’t be handled as a puzzle, and that most of the complexities of the models, data, and available tools are just distractions from the analysis that makes the core of the project.
I will also be much more active in making sure the students work effectively — there were great mis-uses of everyone’s time in class, that I thought would solve themselves progressively but in fact never did.
All in all, I think, a good project. It will not take much to make it great.