Like last year, I took students’ opinion/evaluation of my course. Unlike last year, this year the course was taught for the complete semester, allowing us to cover more topics and do better on projects. Before I go onto summarizing the course evaluation, here was the composition of the class:

*** Undergraduate students: 10** (Nine of them from IISc and in their 4th semester; they were taking electives for the first time. Of the 9, six were from Math major, 2 from Biology major and 1 from Physics major. One UG student was an international visitor – from France – with computer science major).

*** PG Students: 7** (4 CES PhD Students; 2 NCBS PhD Students and 1 M.E student from Chemical engineering).

*** [UPDATE]: Auditing Students: **I entirely forgot to add that there were roughly 6-10 students who audited the course; most of them fron non-math background. They were equally active in the class, in doing (most of) class assignments, etc.

Clearly, having 10 UG students was a major surprise but the overall mixture added lot of value to the class by allowing a diversity of perspectives and skills. Writing more about this requires a separate post! So, let me move onto the summary of course evaluation by students.

*1) How do students self-evaluate their understanding of various components of the course? *Clearly, on an average the distribution peaks at “Good” and “Very Good”, which is great! Compared to last year, the distribution has moved towards “Very good”. More specifically, topics that were mostly rated as “Good” (Discrete population dynamics, continuous population dynamics and stability analysis) have now moved towards “Very good”.

However, the topics where I need to improve (so that students self-evaluate with higher scores!) are the topics I added this year, so I was teaching them for the first time. The reasons seem quite obvious! These are evolutionary dynamics and two-species interactions.

*2) How good was the coverage of topics? *A very nice distribution that peaks at around “Adequate”. But with a clear right-skewed distribution, suggesting that most students wanted me to cover more of pretty much most of the topics – which is not possible given the time constraints. Here is what one of the students commented about this question:

the options given r not good, like a little more detail is always Helpful!! Adequate with respect to what?? w.r.t exams or w.r.t interest in the topic?? 😛 ( dnt mind!! 🙂 )

I thought that was a very good point, and that is clearly reflected in the average response of students. The response is exactly same as the previous years where the average response was that more details are needed on many topics! The best I could take away from the above plot is that more on two-species interactions and evolutionary dynamics would be appreciated. Anyway, the same student also said:

Coverage and depth both wer (sic) nice, as most of the times it went according to the students! It was good!

How should I rephrase the question next time, or should I entirely skip this altogether?

3) In general, the ratings on *lecture notes and quality of teaching* were pretty good (both above 4.25 on a scale of 5). Compared to last year, both have improved. In particular, I had hardly given any lecture notes last year. This year, we recorded all classes and they were available on the course website – typically within a week of the class. Lecture notes were prepared based on transcribing the videos and also posted on the website. I had employed two TA’s specifically for these purposes and they did a splendid job, I think. Although I don’t know if anyone really used these resources, we had made our effort.

*Work load* was rated at 3.58 – but I dont know what that means. Again poor phrasing of question (the options ranged from “Very poor” to “Very good”). I can make sense of “Very good” but what does average workload mean? Did students want more workload, or less workload? Last year, they explicitly said less workload would be better. Although it’s hard to imagine students asking for more work load, I think I can expect something counterintuitive from this class ;-).

*4) What other topics would you have liked to learn?*

Most commenters perhaps realized that it is difficult to cover more topics in the semester. But two suggestions that one student had was to include meta-population dynamics and island biogeography models. Great suggestions, even if I can not cover them in a class, I should consider doing a workshop at ces.

A very useful suggestion is to talk about interesting history behind mathematical models and concepts. I will try this next year, after learning myself more about them.

*5) General comments to improve the class further: *

A common point that came in 4 of five comments was that

Mathematics is clearly very important for this course.

and since ecology students come with not much math background (some may have taken their last math course in their 10th class),

some fundamental Mathematics [and programming] classes would be useful for non-math students.

We did have TAs teach basic pre-requisite math in the course. But I suspect a full fledged course on math and programming prior to this course would make a difference to many ecology students. Unfortunately, there is no bandwidth in the CES, as of now, to add a new course.

Class room programming sessions cannot be called a success as not all students were well versed with the R language. … Atleast 2 classes of basic R is mandatory to be freely usable even during exams.

I don’t know how to resolve the above problem on programming language. I thought that TAs did do tutorials on R – at least in some rudimentary way and were usually available during programming sessions to help students. And many students as far as I can tell did well in those sessions. No doubt it needs to be better done. I Another related point was that

But probably due to a skewed structure of the class where majority of students have a strong mathematical background, the purpose of the course for ecology students ( who usually don’t have a strong mathematics foundation) tends to get lost.

I really hope that was not the case! If this course were really to be taught only to those with strong math skills, it would take a very different trajectory (and not necessarily a good one). I think having this extreme set of students added a great value to the course.

One possibility that some faculty at CES have been thinking is to make an online basic math and an R programming course (such as those from udacity or corsera taken in the Aug-Dec semester) a pre-requisite for my course (in Jan-April sem). Going through online classes can get boring, so we should assign some TAs and mentors so that there will also be some discussion sessions to clarify doubts and to ensure there is no attrition. One thing that we have decided in our department now is that my colleague Kavita Isvaran’s course on Quantitative Ecology 1 will be offerred in the Aug semester from 2014. This course covers some stats and programming could also help students when they take my course.

maths and ecology students should be assessed separately.

I have thought a bit about this since the beginning of the course but am unable to justify separate grading schemes. One way to think about this was that if a math student were to go and take a hard core biology course, would he/she be graded differently? Most likely not. Even within this course, standards of ecology were maintained same for both math and non-math students. Anyway, something worth thinking again but for the next year. Despite all these issues, I found non-math students who had very little math and programming experience did exceptionally well in the course.

Here is one other critical and very useful comment:

Projects, I feel were not graded very satisfactorily. At the least the student should know the categories upon which the project was graded upon so that in the bare minimum, even if he/she gets a not so good grade he/she will at the least know how to do/present a project in futureby correcting appropriately.

Good point about project grading. I am usually very careful in mentioning something like how grading is done, but as the course progressed, it slipped out of my mind to remind students about how things are graded in ase of projects. But point taken.

Its always good to end with a positive light-hearted comment:

Prof, TA’s, AC in the room, and cookies in the break..everything is Very nice!! 🙂 really liked and enjoyed the course!! 🙂 and I really appreciate the way the class was handled by prof, I mean extreme Bio n extreme maths people at same time!!! :O 😀

Thanks to all students for being part of the course! Special thanks to TAs Sabiha, Jaideep, Sumithra and Nitin for fantastic help that you all offerred throughout the course.

I audited the course, and despite the fact that I missed a lot of classes, I found the course excellent. Understanding the maths behind the ecology really changes ones understanding of a model. I wish we could have covered more, though the existing course load was not trivial! I agree with the comments that a few classes devoted to maths and R early on will make a difference. While TAs did cover some topics in extra classes, maybe the material covered here could be streamlined and taught better to enable students to learn faster. Some attention to making the extra classes really count might help to sort out some problems. One more suggestion might be to read a few papers that use models and maths, and have a discussion at/ towards the end of each topic.

Nandini, Thanks for your comments and I am really glad that you found the course useful.

re: few classes on math and R – yes, I agree that we need to streamline the materials covered by TAs on math and programming. I did think quite a bit on this but clearly it is still insufficient. Of course, this would mean that in the first month or so, the course load would be heavier because the regular pace of the course has to continue. Actually, I should have had a question on getting feedback on the work of TAs and how we can improve that further. I totally forgot!

re: reading papers and discussion on them, I love the idea but I just did not get enough time to prepare for those. There are two challenges. First is to identify a good readable paper for all and two is to find modes of discussing them. I find that most good papers tend to be too mathematical and not useful for the diverse class we have. I guess I would have more time to dig out such papers in next year since I am mostly ready with materials now.