* 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.

She worked on the “Role of biofilm formation in the pathenogenesis of Salmonella Typhimurium in the gut”. I think she found some interesting results in her project, in particular how spatial structure can favour the evolution of suicidal behaviour in salmonella pathogens in the gut. We still need to work on it more to see if results are robust.

Of course, I knew almost nothing about Salmonella; I still know very little, and whatever I know is because of what Sravya taught me during the course of her project. The main reason for me to get into this project is Dr. Srinadnan Chakravarthy, who is a postdoc with Prof. Dipshikha Chakravorty of MCBL, IISc. He has been talking to me about modelling his empirical work on Salmonella for more than an year, and we finally got an opportunity when Sravya wrote to us requesting for a project. I hope that I will be able to continue to work on this very interesting project.

Back to Sravya, it was great having you in the lab for five months and thanks for teaching me about pathogens! Wish you all the best for your future.

Before going on to providing my advice, let me emphasize why it is important to write good emails (which also serve as an application for that position) even for relatively not so significant positions like summer internships. To give my own example, over the past four to five months I have received at least 30 applications asking for various short-term positions. Given the current strength of my lab, I may at the best take only one or two students for the summer (I would like to write another post on costs and benefits of having  short-term students, what sorts of projects are suitable for them in another post).  Note that number of applications may be significantly higher for other professors, depending on their research work, their accomplishments and the how hot or cool their research is (as perceived by students). How will you make sure that your application catches the attention of the professor?

Your best bet is to write a good email/application (also called cover letter if the position happens to be a more formal one). Based on my experience of last one and a half-years at IISc, most of the emails I receive are of terrible quality, perhaps largely due to the fact that students in India are never taught how to write good cover letters or emails. While I don’t think I can fix that problem, here is my advice to students on writing good cover letters for short-term or summer positions. The broad outline below applies for any position but more formal positions may require additional materials as mentioned in their advertizement.

1) Salutation: Address the professor by “Dear Prof. Lastname”. You can write “Dr.” instead of “Prof.”.

I want to mention an important cultural issue that is relevant to any sort of email you write, not just for summer intern applications: Indian students hesitate to address professors or their teachers by their name. It is considered more polite to say “Dear Sir” or “Dear Madam”. Some senior professors even in elite research institutions of India may expect the same cultural norm. Given this here is my suggestion:

(a) If you are writing to anyone in the West (US/Eurore/Australia, etc), it is strongly preferable to address them by their name (Dear Dr. Lastname). If you write “Dear Sir” or “Dear Madam”, it is considered a a generic email that could be sent to anyone and may not be taken seriously. Of course, double cross-check the spelling of their name. Its easy to get them wrong and I think Indians (including me) are very careless in that aspect.

When they respond to you, they usually sign of the email with some name which is either their first name or nick name. It is usually okay to write back to them by the name they use to sign the email, without Dr. or Prof, especially if the person is from the US. Given cultural and individual differences that you may or may not be aware of, it may be safer to continue “Dr. Lastname” unless they tell you otherwise. However, a lot of the time, they may even explicitly ask you to address them by their first name or nick name. If so, you should feel free to do so, although it might seem awkward at the beginning since you are not used to it. If you are not comfortable, let me them know and continue to address them by “Dr. Lastname”.

(b) If you are writing to a relatively young Indian professor, lets say < 50 years ago [1], I think it is  best to address them by their “Dr. Lastname”.

(c) If you are writing to a senior faculty in India, I think it may be safer to write “Dear Sir” or “Dear Madam”.

Now, lets move beyond salutation!

(2) The first paragraph. Introduce yourself saying your name, where are you studying, which year of which program and your major/minor program, etc. End the paragraph by stating the purpose of your email.

(3) The second (and may be the third too) paragraph(s): This is crucial. You should write a short “story” to convince why you are interested in the sort of research work that the professor is doing. How did you get to know about their work, any previous reference like I attended your talk at so and so conference, I spoke to you briefly on that corridor, or how you found the website of that profesor, read one of his/her paper (that is one of the most convincing ways to demonstrate your interest) and found the work interesting.  Do you have past experience in research? Or do you have your own idea? Do mention and explain it briefly (or may be even attach a short write up).

Of course, the level and quality of the story expected of you will vary depending on  whether you are a first year UG student and a final year student, your background (an ecology student writing to ecologist can be expected to write differently compared to a mathematics student writing to get exposure to ecology). But the main point is, is your story compelling?  You should present a convincing story of how given your background and interest, the lab you are applying is an appropriate one.

(5) Logistics: How long do you want the project to be? Tentative dates (note that lot of faculty travel in summer)? Do you have your own funding (Are you any of the KVPY, INSPIRE, IAS fellows)? If not, are you expecting the professor to fund your stay or are you self-funded?

(5) CV: Attach your updated CV (in pdf, not MS word). And mention that CV has been attached!

End your email thanking the professor for their time, and that you look forward to their reply.

(6) Waiting and Reminders: Once the email goes, the best thing to do is to wait. As this article (at the bottom of the page) says, Indian professors are less likely to respond to your emails compared to Western counterparts. So do you remind them about your email? Yes, you can and you should if that lab is of interest to you – but wait for at least a week. After waiting for a week or so you can gently remind your about previous email and ask if they received it, and that you would greatly appreciate their response.

(7) Strictly avoid the following (see this satirical note to applicants by Jonathan Eisen):

(a) Copy paste key words or phrases or worse, entire paragraphs, from their website or their research papers when you talk about research interests.

(b) Spelling errors of professor’s names when you address them.

(c) It is extremely irritating to refer to the reputation of the research group or the institute and use that as a reason to apply for any position.

(d) Write “Dear Sir” (assuming that all faculty are male) or “Dear Sir/Madam” (let the faculty chose their gender!).

(e) CC’ing your email to multiple faculty at the same time.

Would you as a student or a faculty like to add any other points?

[1] This is an arbitrary cut-off that I came up with. I am pretty sure most faculty at IISc would prefer to be addressed by their name, but if it is a general to any senior faculty in India, I am not so sure.

[2] Related article by Prof. Shubha Tole, TIFR

————

Date: 21st Dec 2012.

During the year 2011-12, I interacted with students of Purnapramati [1] only once or twice, but I really enjoyed my time with them. I wanted to interact children more regularly this year. So, after discussing with Indumathi akka [2], the science teacher of the school, we thought it would be nice to work on a short-term project where students get some hands-on experience of learning science. Exactly six months ago, on 21st of June 2012, I began interacting with students of 5th class of Purnapramati.

As I kept thinking what could be a feasible short-term yet interesting thing that primary kids can do, I was already in the class and I began my interaction by exchanging greetings. But the answer was elusive until our interactions gained some momentum.

I asked students, “Is today any special day?”. The answer came almost immediately when one student said “Today is summer solstice”.

I then asked the student back, “I have never heard of that. What does that mean?”

One other student laughed and said, “Don’t you know, it is the longest day of the year”.

“May be, but how do you know about this fact?”, I asked.

“We learnt in the class. Our teacher told us”, came a response from one corner.

“How did your teacher know about that?”. I continued my questions.

“From her teacher” was one answer while the other student said “From our text book”.

“How did your teacher’s teacher or even the text book writer knew that 21st June is the longest day in the year?”.

Although I immediately heard the answer “From their teachers”, it was already clear to some students that I was going to ask “How did that teacher come to know?”

After teasing their minds for a bit, I got the answer I was waiting to hear when I one student said “someone must have measured length of day all throughout the year and found it out”.

I then told students, what if your teacher had never told you that June 21st is the summer solstice? If our challenge is to find it out yourself, how will you do it?

I got to hear a lot of creative and courageous solutions which ranged from how they will wake up and note down sunrise time and also sunset time every day. When I asked how can they see precise time of sunrise or sunset if there is a huge building next to their home, some volunteered to go to mountains and deserts where one can see horizon to horizon. Some even thought of setting up automatic devices that will record sunrise and sunset times automatically.

Finally, we all agreed to take a short-cut given difficulties of going out of home to a desert or even that of waking every morning without fail. The short-cut, as suggested by students themselves, was to look at the newspaper (or panchanga) everyday and note down sunrise and sunset times.

Once the concept for the project was ready, it was time for implementation and that took nearly three to four months, working on this at a frequency of twice a month (sometimes even less).  For this class of 12, each student was assigned a specific month and was asked to note down sunrise-sunset time from newspaper collection at their home. Based on that they calculated daytime duration (which they learnt in the process of our project). They also learnt how to use graph sheets and produced nice plots of duration of daytime for each day of their month.

When they finally put together all those data mostly on their own with occasional help from Indumathi akka (science teacher) and myself, we were all extremely fascinated to see the oscillating pattern of duration of the day. Students immediately went back to the original motive of our project, and found based on their own analysis that the duration of the day was maximum for about 10 days towards last two weeks of June. So it was not one day when it was maximum, but for 10 days!

It was probably in all students’ mind as to why does everyone say June 21st as the longest day of the year when there are 10 days that are longest. But they had figured the reason discussing among themselves; they had data of sunrise-sunset only up to minutes accuracy. To find which day of among those 10 days were longest, they said they would need data of sunrise-sunset time unto seconds, or even milliseconds.

While it is clear what students learnt from this exercise, it was also extremely interesting to interact with students, answer their amusing and intelligent questions. It was also revealing to me to learn finer details of such simple facts, which we all take for granted.

[1] Important Disclosure: The school is founded by close relatives and friends. You can learn more about it by visiting the website: www.purnapramati.in

 [2] Teachers are affectionately called akka (meaning sister) or anna (meaning brother) in this school.

Views from the bottom of the hill:

Views on the way

Views from the top, including the group that made it to the top!

From left: Ajith, Jaideep, Ashwin, Nitin, Vishu, Amit, Chhavi, Sravya, Sabiha and Sumithra (hiding behind the camera!)

Although teaching evaluations where students get to grade teachers are a norm at most places in the world and also in India (like IITs), here at IISc there is no formal evaluation of our teaching. So many of us informally collect anonymous feedback from students. For the half-a-semester module on Theoretical Ecology that I taught in Jan 2012 semester, one of the students (Karpagam Chelliah) helped me set up a survey online and got responses to questions I had set up. With my full semester course on Theoretical and Mathematical Ecology set to start next week, I thought this is a good time to see those feedback again. Here is what I found:

1) First of all, should the half-semester module on theoretical ecology be converted to a full semester course?

Overwhelming feeling among many of my colleagues was that, yes, it should be. I was not so sure, until I saw results of the survey.

All the students who took the survey (total 13) said we should have a full semester course!

2) Now to some details, as to how students self-rate their understanding and how well were the topics covered.

I was able to cover two basic topics, (a) single species population dynamics and (b) random walks and its application to animal movement. In this survey I  subdivided these two broad topics to overall 6 components: (i) Discrete population models (ii) Continuous population models (iii) Stability analysis (iv) Random walks and animal movement (v) Programming and (vi) Overall course.  Student had to rate their understanding for each of the above components, and how well/detailed each of the topics were covered.

This first chart below shows how students self-evaluated their understanding of various components of the course. Y-axis represents percentage of students who gave that rating.

Here, bars on the left side means I should be concerned, and work harder to improve those aspects. Two components that I did no teach well are stability analysis and programming, the math and the computing parts of the course!

This next chart on the right (where a central peak is the ideal response I would like to see) supports the same view with quite a few students suggesting that I covered less than adequate on both stability analysis and programming.

As a corrective measure, I plan to have one week exclusively dedicated to programming. I should also have more discussion, worked examples and assignment questions on stability analysis which is an extremely fundamental and useful tool for ecologists.

3) I had asked for general critical comments on the course. As you can imagine they are very helpful and here is a summary:

What was good:

It seems students liked discussions we used to have in the class. One student said  ”The course encapsulated modelling really well and helped banish some fears of the same.” That was precisely the goal of this course, so it was glad to see that the course achieved that goal to some extent (although its only one data point!).

Some particularly liked how I used to recap ideas from previous classes before going onto what next (I learnt this from some of my teachers because those were the only classes I could understand well). Some thought there was enough scope for thinking independently in the course and that assignments were “thought provoking“. But as you see below, there is lot to improve as well.

What needs improvement:

Assignments and Workload: Four students (that’s 25% of the class) commented that workload was too much for half-a-sem course. On the other hand, one student thought many calculations done in class could be moved to assignments so that we can discuss more in the class.  One student said “please give adequate reading material. Even though I understood what was being done in class, I forgot everything upon coming back home”!

Clearly, balancing these contrasting needs of reducing workload while increasing reading/assignments is not going to be easy! One student had a suggestion that short and frequent assignments could be more useful – I think this may satisfy both sort of students and this is what I am planning in the coming semester.

Other suggestions were to include empirical data with models, how to validate models and how models can be helpful with conservation. This is not easy given time constraints, but I can try with one or two examples from my own research work. One student said course should be better structured, and I entirely agree with that because I know how haphazard my preparation was especially with respect to assignment and reading materials.

One other important point was that some math and programming background can enormously help this course. Our biological sciences division does offer a basic course on Math and Stat but it is offered in the same semester as this course. It would be ideal if students come prepared with math and programming in Aug semester for two quantitative ecology courses in Jan (the other one being highly sought course taught by my colleague Kavita Isvaran on Quantitative Ecology: Research Design and Statistical Inference).

4) What other topics should be covered if its a full semester course?

Almost all respondents said “Evolution” (more specifically, evolutionary dynamics, ESS and Game theory, population genetics, etc). There were also suggestions on predator-prey dynamics, host-pathogen dynamics, more on chaos and animal movement, etc. Clearly, evolution is the winner and I plan to teach this for 4-5 weeks. I also plan to teach structured models and spatially explicit models in ecology. This may come at the cost of studying more classic models like competition and predation, but I feel that with the kind of background that this course offers, students should be able to pick up a text book and read it on their own.

What do you think? What topics should a basic theoretical ecology course cover given that students basically come with no math/programming background?

Watch this space for more updates.  Tentatively, we will have our first class on one of the days on Jan 2-4.

We are looking for one (but possibly two) project assistant(s) to work in one of the following general research areas.  (i) Animal movement and collective behavior OR (ii) Spatial vegetation patterns (especially semi-arid regions). The work could involve collaborations with researchers both within and/or outside IISc.

In each of the above themes, you may be interested either in theoretical/computational work, or experimental/field work.

Eligibility: B.Tech/BE/MSc in any discipline. Applicants from mathematics, physics and engineering disciplines with interest in ecological sciences are strongly encouraged to apply. BSc students can be considered for a project trainee position.

Preferred background for theoretical/computational work: applicants should have one or more of the following quantitive skills with deep interest in ecology and animal behavior. Quantitative skills include programming (C/C++/matlab/R/ArcGIS), ideas of random walks and diffusion theory, nonlinear dynamics, image processing, statistics, etc.

For the experimental/field work: you should have relevant experience.

Please see our research pages and publication page for more details on the nature of our work. Also see Join Us page.

Email me (guttal (at) ces.iisc.ernet.in or vishwesha.guttal (at) gmail.com) with your CV highlighting how your interests and skill are relevant to our lab. Salary of the position will be as per the institute norms and usually varies from 14,000 to 18,000.

UPDATE:  The advertised position has been filled up.

Before I get to my story, let me say that I couldn’t agree more on the basic point McGill is making that ecologists tend to overuse (perhaps, largely in response to demanding referees) statistics when simple methods would yield equally good results. If you dont have fancy named stats in your publication, referees and editors, especially those of high impact factor journals, may object and ask for more, and likely even reject your paper. Your peers may criticize that you haven’t been rigorous enough. Despite recent debates, fancy and complicated statistics continue to flourish in the ecology literature.

What is the role of statistics in theoretical ecology? Being a theoretical ecologist, at least in principle, I don’t need to use any statistics for my publications. Our aim is to show general ecological principles or develop predictive tools using simple mathematical models. We do this either through analytical calculations where we derive relationships between two ecological quantities, or when we can not derive analytical results, we do numerical simulations to find those relationships. For the former case, statistics is not needed at all. For the latter, since we can do as many simulations as we like, we can obtain relationships where the error bars could be smaller than the thickness of the dots or lines on the plot. In other words, we can live without statistics (but see last paragraph).

Here is my unusual story of referee’s comment on stats during a manuscript review.  As a physics graduate student, I submitted a paper to an ecology journal developing a quantitative method to ‘assess’ ecosystem dynamics, commenting on how it may offer an useful tool for ecologists. In this largely theoretical paper, we showed our claim by analytical calculations and numerical simulations but we had not done any statistics (and I could not have done anything either). Referees in general liked the idea, and here is a comment by one of the referees that you may find interesting: “Authors are physicists, not ecologists; it would be unfair to ask them to do detailed statistical analyses, and that will make paper too long” [1, 2]. I dont know what I thought of that at the comment at that time, but now I find it amusing at first sight but also very reasonable. I will leave it to you for your own interpretation.

Why would a theoretical paper need statistics when I argued above that we can avoid it entirely. Statistics can be very useful, and perhaps essential, to test whether our principles or tools derived from mathematical models work (i.e., provide significant results) even within typical limitations of real ecological data sets.  For example, the ecological data are typically short and not finely resolved. It will have observational errors and we usually lack a full understanding of underlying processes. It was in this context that the referee was talking about statistical analyses in our manuscript. Eventually, after our work and several other related papers suggesting new such tools came out, many papers that exclusively develop and discuss statistical methods for these types of analyses got (and continue to get) published. Clearly, it would have been an overkill to demand statistics for our paper and I am glad referees were with us.

[1] I have made a slight modification to the actual referee comment to shorten an otherwise long sentence.

[2] I am not entirely sure if its okay to quote an anonymous referee’s comments. Any ideas?

I was lucky to be interviewed by G. S. Mudur who writes really well, perhaps one of the best in India, on science. Here is article: ”Fish spill group secret on video game”

http://www.telegraphindia.com/1120817/jsp/nation/story_15863790.jsp#.UT9rnNEY3kY

Here is video:

Here is a non-exhaustive list of media coverage (from here):

Ed Yong, Discover Magazine “To work out why fish swim together, tempt a predator with virtual prey”

Nell Greenfieldboyce, NPR “Swarming up a storm: why animals school and flock”

Akshat Rathi, The Economist “The benefits of schooling”

G.S. Mudur, The Telegraph, India “Fish spill group secret on video game”

Zoe Kleinman, BBC News “Fish play video game in new behavior study”

Jeffrey Matulef, Eurogamer.net “Princeton University develops videogames for fish”

Lee Rannals, RedOrbit “Simulations help scientists understand predator prey relationship”

Mark Brown, Wired “Predatory fish play video game to answer evolutionary quandry”

Children’s BBC (CBBC) Newsround “Video gaming fish help science”

Futurity “Video game for fish shows how prey survive”

Richard Chirgwin, The Register “Angry sunfish in piscine boss battles”

LiveScience “Fish video game reveals benefits of sticking together”

Phys.org “Video gaming fish play out the advantages of groups”