Is being a pro athlete like being an academic?

This academic year is a very busy one for me and I spent most of Christmas working (this isn't unusual at all amongst academics) . This didn't feel strange or 'hard': it was simply what I did.

When one of my brothers in law pointed out that writing code on Christmas morning was a bit 'strange' it reminded me of the fact that Jonny Wilkinson (one the best rugby players of all time) supposedly/famously practices on Christmas day (fact #3 here). 

This post is going to be some thoughts about the similarity between professional athletes and academics...

I watched this great +TEDx talk the other day about a kid who describing his 'hackschooling' and in particular discusses 'what he wants to be when he grows up' (the answer is 'happy'):

As a young kid all I ever wanted to be was a professional rugby player (reality set in at about 13-14) . I more or less always had a ball with me, here's a picture of me (I'm the one with my head down) when I was 12ish (I think):

I went to a rugby boarding school when I was 16 and had the best time of my life there. I was never athletically good enough to ever 'be what I wanted to be' (a pro rugby player). A nasty roller blading accident when I was 18 more or less finished off my rugby 'career' anyway. 

From the age of about 15 though I think I realised that I needed a more realistic plan and when people would ask me what I wanted to be I'd always say: 'I want a PhD in mathematics and to be a mathematics researcher'. I don't think I really knew what that was, but that's what I would say.

15 years later that's what I am and I consider myself very lucky to be what I wanted to be when I was a kid.

1. Passion

I think that's probably the first similarity between athletes and academics, it's such a competitive environment. Kids who play pro anything most probably invested (as did their families) a lot of time and effort in to getting there.

Similarly for academics. You have to work extremely hard, to get in to a good University, to do well, to get a PhD and then to finally get a 'pro contract' in the form of post-doc or similar.

2. Luck

For every good pro athlete (I don't mean great), there are probably a bunch that were never 'discovered' (or who themselves never discovered that they were/could be great).

I think this is similar to academics, with less and less funding available for research positions and the extremely competitive job market, there are probably quite a few talented people who never even think of pursuing a career in academia.

A lot of it is probably about being in the right place at the right time. Playing a game when a scout happens to be watching is quite similar to how I got my first post-doc: there happened to be some funding available when I was coming to the end of my PhD and my current employers where open minded enough to appreciate my ability to change fields.

3. Hard Work

Academia is hard. Ridiculously hard. You have to juggle various things: teaching, research, outreach, admin (I really hate admin...) and you have to be good at all of them.

Being a pro athlete is (probably) hard. You have to juggle various things: athletic ability, injuries, athletic IQ, press/media and you have to be good at all of them.

The thing is you do all these things, whether or not that's why you got in to the field in the first place. That's probably because of the passion or the pay (I'll get back to the pay later...).

As a rugby player I was not a good tackler, I was terrible. It was something I had to work on a lot harder than on my vision and fitness for example. I used to spend more time than most working on tackling. 

In academia it took me quite a while to get 'ok' at writing (my PhD supervisor and +Paul Harper who proof read a lot of my early drafts will no doubt agree with that). This was something that I had to work quite hard at (and still do!).

Ultimately athletes and academics are faced with the same 'problem'/'opportunity'. We can work as hard as we want to. There's always further to go (more weights to lift, another training session to have, more tape to watch, more recovery techniques to try...). Here's a good +PHD Comics that was published today illustrating what I mean:

4. Competitiveness

I love competition. I don't really mind losing, but I love competing (I have a rant that I repeat fairly often about the difference between being a bad loser and being competitive but I'll leave that for another time).

When I was in the running for my permanent post I loved knowing that I was working as hard as I possibly could to get it. If someone was going to get appointed ahead of me it was not going to be because I did not push myself hard enough.

The analogous holds immediately with pro athletes and it's a part of my job that I love.

5.  The pay

Ok this is where my analogy perhaps breaks down as the pay is pretty much incomparable but I think there are some parallels to be drawn.

In the press a lot of athletes apparently 'fall out of love with the game' (recently an England cricketer for example was told to go home and remember why he liked cricket), I guess that they sometimes (understandably given how much money comes their way) play for money and it becomes about contracts etc...

For a lot of Academics it's probably the same thing. After a while (snowed under by a pile of admin) it just becomes a job. There's nothing wrong with that of course (a lot of people perhaps end up in Academic 'by mistake' also).

Personally, I think I have the coolest (second to being a pro rugby player) job in the world and am just ridiculously grateful to be able to do it.

The bad sides of this are that I am a workaholic and don't see my wife very often (she sometimes +1s my G+ posts so we do interact), but ultimately I get to do what I wanted to do when I was a kid (if I had been bigger, stronger and faster I'd be writing a flipped version of this on Toulouse's website right now...). In particular I have found teaching to perhaps be one of the most rewarding experiences one can have.

I'm sure there is a lot wrong with my analogy and a huge amount of differences between 'us' and pro athletes... Perhaps this comparison is just a young boys way of coping with his workload and believing that it's actually what he wants to do and that he made it as a 'pro athlete'... ;)

What I have in my backpack: my academic toolbox

+Rodolphe D'Inca has started a series of posts on G+ looking at his 'toolbox' as a scientist:

1. Reading Science
2. Building a bibliography

In this post I thought I'd join in and briefly share the kit I carry around in my backpack and the stuff I use on a day to day basis software wise.

Hardware

Here is a picture of the usual contents of my backpack:

In there you see:

- My tablet (a nexus 7). I use this mainly to read papers and books but also for some teaching stuff where I use it to tick student progress on +Google Drive.
- My smartphone (a nexus 4). I'm kind of addicted to my phone. I use it for email, +Google+, Google Keep, and to remember where I have to be and when (if it's not in my calendar I won't be there: the reverse not necessarily being guaranteed either...).
- My 11" macbook air. This I probably care about more than my wife. I'll talk about software below but it's really from a hardware point of view that I love this machine. So portable and just the right size. I've been really tempted by the +Dell XPS 13 Developer edition laptop but the screen size (13") puts me off a bit. I love my big monitors for my desktop but for a laptop I think 11" is perfect (the fact that +Linus Torvalds uses it is also kind of cool).
- The dongle to let me connect my macbook to a projector (kind of annoying that you need this but oh well...).
- An actual paper on paper (every now and then I have a paper in my bag as opposed to reading on my tablet: I happened to have one in there today). I've just done a screencast about the particular paper I'm looking at.
- A 250GB hard drive for backups (I'm pretty paranoid about backups).
- My +Moleskine notebook. For the past 3 or 4 years I've only been using this notebooks and make sure I date them so that I've got a tidy record of all my scribblings on my bookshelf in the office. I got this one autographed by Jorge Cham of +PHD Comics:

- My 4 color Bic pen. I used these throughout highschool but 'lost my way' during University. Just started using them again and remember how awesome they are: always work, nice to have the colours and perfect balance for finger spinning (it might be because I spent most of highschool learning how to finger spin with them).
- A usb stick but I very rarely use it (it was in my backpack when I wrote this).

EDIT: After +Rodolfo Carvajal asked on G+ here's a photo of the backpack itself:

I've had it for about 4 years now and it's an Eastpack (I pretty much try to refuse to use anything else as I learnt to love how durable they were during highschool). It's got a nice padded section for my laptop and straps that I can hook my water bottle too but also that I can use to compress the bag when it's empty (the stuff I carry in it does not take much space). It will be a very sad day when (if?) this bag dies as it's by far my favourite backpack ever (pretty much just being compared against other Eastpacks). There are various other tiny bits of kit that I'm missing here (laser pointer, portable battery) but that's because I've left them somewhere and weren't in the backpack when I got the stuff out to take the photo...

2nd EDIT: They still make the backpack! :) http://goo.gl/Vv4STR

Software

I've posted about software and my preferences of *nix environments before but in general I use the following software:

- Vim for editing pretty much everything (LaTeX, +Python, +Sage Mathematical Software System, md);
- +Sage Mathematical Software System for math calculations;
- +Python for more general programming;
- Git for version control;
- Rstudio for R code editing;
- Zotero for reference management (I blogged about using Zotero with +Dropbox here)
- +Dropbox (big fan)

Anyone got anything I should know of and use?

Social Constructivism in Big Classes

+Theron Hitchman (who is a great guy to follow on G+ and one of the go to guys as far as I am concerned when it comes to Inquiry Based Learning (IBL)) recently posted on G+ wondering how he was going to manage with a course of his having 68 students enrolled.

I am still understanding IBL but it is one of many teaching methodologies that use a constructivist model (here's a post by +Dana Ernst about an article that claims that these approaches aren't that great). I have spoken about constructivism before when reviewing a great education book. The basic concept of constructivism is that students need/should learn through a personal 'construction of the concepts'. IBL does this by giving students the reigns to the direction and also the discovery of the content of a course (I am sure +Dana Ernst, +Theron Hitchman  and others could either forgive me or correct my brief summary).

This is often done (although not exclusively, take a look at +Bret Benesh's post) done through the use of student presentations and generally needs a non-lecture based approach: which is difficult with a large number of students!.

Theron's post on G+ got a lot of comments with people offering advice and +Bret Benesh wrote a nice blog post suggesting a peer learning approach.

I thought I would throw in my two cents as I have recently designed a new course that made use of peer learning.

The course is a statistical programming course on our MSc programme here at +Cardiff University.

You can see all the resources for the course here.

To deal with large teaching numbers in that class (this was the first year of running and it had 27 students but I certainly believe that my approach is scalable and I designed it thinking that I'd have 40+ students at times). I used a peer learning approach based on flipped classrooms, problems and with a hint of IBL thrown in.

• First of all it took a lot of preparation. I flipped the class completely putting together a full set of notes as well as a full set of videos (you can see them on the site).
• I made groups of 3/4 out of all the students.
• For every topic, I put together a set of problems that all the groups where told they had to complete. I called these 'challenges' (it seemed a bit snappier) and you can see them on the course website.
• Every class (this course was taught in 8 sessions over a 4 week period) started with the me asking who would like to present a solution to the challenge.

The students were aware that their final mark for the course would take in to account participation in these presentations but I made it clear that the corresponding contribution would be mainly based on the fact that they tried and not necessarily how good a job they did. In essence I did not really care whether or not they managed to do the challenges, I just wanted them to work on it!

By the beginning of the 5th session, students were happy to present and needed no gentle nudging from me. In fact some of the students who presented started off by saying "I didn't manage to do this but this is what I tried". Seeing that students got that it was ok to not succeed at something was really great to see. Whenever that happened the students would start discussing amongst themselves how to do a particular problem: and would teach each other!

Throughout all of this, I would sit at the back of the room and vary rarely say anything at all. At times I would perhaps nudge a bit with a "does anyone know a different way to do that?".

One of my favourite memories of the course was towards the end when at the beginning of one session I did not prompt the students to start the class. All of them were just chatting amongst themselves (not about the course) and I was sat at the back observing. After a while one of the students turned around and looked at me questionably. I just smiled. She got up, told everyone that they should get started and the class started teaching itself. That day I didn't actually say anything.

I think this happened to work well because the challenges were designed in such a way so that students were lead through the curriculum but given the nature of the course I also made sure that they had plenty of resources with which they could practice things further.

I encouraged the students to find other resources then the ones I put together and also encouraged them to share their solutions with each other after each session (I believe they used a dropbox folder but I emphasised that I would stay out of the way).

The whole course culminated with one of the assessments being a presentation where the students (still in their group) had to teach me something that was not in the resources made available to them. I wrote about this here and one of the things a group put together was this cool gif of the Mandlebrot set:

I'm currently going through a teaching certification process and have blogged about it many times. You can see my various portfolios [here](http://www.vincent-knight.com/home/teaching/pcutl) but if I am to take only one sentence from everything I've done so far it would be this pretty cool definition of teaching:

"To create learning opportunities."

I believe that teaching in a constructivist framework does exactly that and I really hope that large classrooms do not dissuade educators from using it :)

Anyway, what I hoped would be a perhaps helpful post for +Theron Hitchman ended up just being another page or two of me rambling on...

Why and how: open education resources.

This is the fourth post in a series of posts reflecting on the teaching and learning in a recent course I've taught on SAS and R. This post will be quite different in nature to the previous posts which looked at students choices between SAS and/or R in their assessment:

• Individual course work
• Teaching presentations
• Class test

Here I would like to talk about how I deliver teaching materials (notes, exercises, videos etc) to my students.

All of the teaching materials for the course can be found here: drvinceknight.github.io/MAT013/.

How they got there and why I think it's a great place for them to be will be what I hope to discuss...

A Virtual Learning Environment that was not as good as alternatives.

At +Cardiff University we have a VLE provided that is automatically available to all our students that all lecturers are encouraged to use. So when I started teaching I diligently started using the service but it had various aspects that did not fit well with my workflow (having to upload files on every change, clunky interface that actually seemed optimised for IE and various other things). It was also awkward (at the time, I believe that this has been addressed now) for students to use the environment on smart phones etc...

As an alternative, I setup a very simple website using google sites and would use +Dropbox's public links to link pdfs and other resources for my students. An example of such a delivery is these basic Game Theoretical materials. This gave me great control, I no longer had to mess around with uploading versions of files, every change I made was immediately online and also as the site was pretty simple (links and pdfs) it was easily accessible to students on all platforms (I could also include some YouTube videos).

An immediate consequence of this approach is that my materials are all publicly available online.

To anyone, our students or not. The first thing I did was check with +Paul Harper: the director of the MSc course that I was only teaching on at the time that this was ok. We chatted about it a bit and were both happy to carry on. My main train of thought was that there are far better resources already available online so mine might as well be. (I've subsequently checked with our School's director of learning and teaching and there's no internal regulations against it which is nice to know about +Cardiff University)

There is a huge amount of talk about open access in research (I won't go in to that here) but less so to some extent in teaching. I did find this interesting newspaper article that ponders as to "Why don't more academics use open educational resources?". This offers a good general discussion about open education resources.

I would feel very very humbled if anyone chose to actually use my resources. I'm at the early part of my career and am still learning so I don't think that will happen anytime soon but there is another more important benefit to having my teaching stuff online for everyone.

I always post about any new courses I'm working on, on G+ and am grateful to get a fair bit of feedback from other academics around the world. This in itself gives me a certain level of confidence in front of my students who know that what I'm teaching them is verifiable by anyone in the world. I've often changed a couple of things based on feedback by other academics and I think that's brilliant.

To some extent my teaching resources are not just reviewed by a couple of peers in my university but also by anyone online who might be interested in them.

(It would be great if research worked this way too)

Through G+ (I've posted about how awesome a tool G+ is as an academic personal development tool) I learnt about git and github. If you don't know about git watch this video by +Zoë Blade is very helpful:

After a while I jumped in and starting using it. After a little longer while I found out that you can use github to host a website:

Using this I it is really easy to put together a very basic website that has all the teaching materials. The added benefit is that the materials are now all in a github repo which opens them up even more (using dbox, only the pdf files were in general in view) whereas now everything is (md, tex source files etc...) and theoretically if anyone wanted to they could pull etc...

I'm certainly not the first person to put teaching stuff up on github, (watching people like +Dana Ernst, +Theron Hitchman and various others do it is what made me jump in).

The github repo for my R and SAS course can be found here and here are some other teaching things I have up on github (with the corresponding webpage if I've gotten around to setting it up):

• A game theory course (still a work in progress): site
• A one day intro to OOP workshop: site
• A LaTeX course
• A outreach workshop introducing game theory to high school kids

To finish off here are the various reasons I have for putting my teaching stuff up on github:

• Openness:
  • my students know that this is viewable by everyone which hopefully gives the resources a level of confidence;
  • people on G+ and elsewhere are able to point out improvements and fixes (if and when they have time);
• Access: the sites are really simple (basic html with links) so they can be viewed on more or less anything;
• Ease of use: I don't have to struggle to use whatever system is being used. If it's an option I kind of refuse to use stuff that makes me less efficient (an example of this is our email system: I use gmail). At the moment the system I like is github + git.

I wrote a blog post (which is the most read thing I've ever written - online or offline - I think) showing how to combine various things like tikz, makefiles, +Sage Mathematical Software System etc to automate the process of creating a course site so I'll put a link to that here.

An online list of mathematics books

A couple of days ago +James Noble posted a link on G+ to a spreadsheet on G+ that is editable publicly inviting people to contribute mathematics books.

The link to the sheet it here and so far it has 65 books on it (there is also a meta list of lists that has 8 lists of books; to which I've added these 2 previous posts: about mathed and about game theory) and a website I've put together that uses it as an underlying database (which I'll talk about below) can be found here.

I think this is a great idea!

It's completely open and anyone can add to it and also benefit from it. I've used various keywords to search and have found 1 or 2 books that I didn't know about.

Some initial analysis of the list

I decided I'd throw some python at this spreadsheet and first of took a look at the contributors. In particular how many books are individuals contributing (a link to all the python code is available here).

As you can see about 50% of people contribute more than 1 book (including yours truly).

I was also curious as to how many authors were listed:

Here however it seems rare for an author to have more than 1 book in the list. The most prolific author is J. SCOTT CARTER with 5 books.

Some very basic natural language analysis

Two fields in the data set that I have not yet mentioned are the 'Overview' field and the 'Target' field. These two allow for some free text describing what the book is about and who it is aimed at. I used the nltk python library (python really is crazy, anything and everything has a library) to take a look at the frequency of "uncommon" words in these two fields.

First of all the description of the books:

Nothing too surprising here (I should perhaps remove certain words from this frequency analysis) but it's cool to see that "History" is pretty high up, as well as "Teaching" and "Philosophy".

The final piece of analysis is the frequency of the words in the description of who the book is for:

An initial glance at this seems to indicate that the books on the list are mainly aimed at students and or/teachers. It would be nice I suppose to see more books for research...

A very basic static website

The other thing that the code I've put together does is write a website that is hosted using (github pages) and lists the various books (as well as gives up an up to date analysis of what you see above). The website can be found here: 

http://drvinceknight.github.io/An_online_list_of_math_books/

The website is very very basic and all static but I've scripted everything (including the download of the spreadsheet although I haven't included that on github yet) so if it's helpful and anyone wants me to update the site just let me know (give me a nudge on G+ and I even check twitter sometimes).

The github repo for all this is here. If you have any ideas for further stuff that could be done to this data set then please improve my analysis or just let me know :) It would be nice to do something slightly smarter with the nltk and also do some analysis of the links between the books (although it would probably need a bunch more books... for that to be insightful)...

A really great job by +James Noble 

I think stuff like this is really great and it's been nice chatting to James about it.

If you know of any books that aren't on the list yet please do add to the list. 

It was cool to watch the list grow (I saw James's post pretty early so go to watch people make a bunch of contributions) and it'd be nice to see it grow even more.

Probability of saying 'yes' to academic responsibilities

I've just read a great post by +Adriana Salerno: Learning to say no.

In that post Adriana discusses how in mathematics (and I'm sure a bunch of other/most fields) one needs a long period of uninterrupted time to work on Research she links to this Big Bang Theory clip:



She also however talks about how as an early career researcher it's important to take opportunities for responsibilities as and when they come. This is something that rings very true to me. Growing up I played a lot of rugby and basically had a "Say yes to coach" attitude ("Vince, you're slow, run sprints" - "Yes coach", "Vince, you're going to sit on the bench this week" - "Yes coach" etc... - Although I actually said "Oui Monsieur" as all my rugby was played in France, but I digress...).

I've kind of taken that attitude in to the early days of my career (I'm still a 'young pup' academia wise) but I also am very grateful of every opportunity that gets sent my way (I'm very lucky to be sitting on various committees, the editorial boards for a couple of journals and am in the middle of preparing not 1 but 2 brand new courses which is a great opportunity as opposed to being given others people's courses!).

Having said that, as Adriana points out in her blog it's important to find a balance so that I can also do some research.

The point of this post is not to say that I've figured out how to do that but to post this xkcd style graph that I made using this package on github: XKCDify.

I'm about at the point where the solid line meets the dashed line (ie the "unkown" for me). I suspect that I'm still being quite optimistic as to how low the probability of saying yes will go for me as I still generally do as I'm told and appreciate the opportunities greatly :)

In Adriana's post she talks about a "research day", I might try to be strict on that...

PS Here's another similar kind of graph that +Paul Harper (my head of research group) put together when he was actually looking back a bit on his 10 years in Academia.

(If anyone's interested here's the repo with the code I used to get that plot, I actually used +Sage Mathematical Software System 's find_fit command to fit a quintic to the few points I wanted to have on there... There might be a better way to do that though...)