180309 Finds

During this week I came across some excellent resources. This post is an aide memoir for me but I hope it might be of interest.

Open Badge Template

This design your own open badge template appeared in the Wapisasa sandbox.

Data Culture

Rahul Bhargava, Catherine D’Ignazio and the Stanford Center on Philanthropy and Civil Society, have worked together with 25 organizations to create the Data Culture Project.

Data Science Text

Pablo Casas (2018) has published a data science live book. The introduction to Why this book?

The book will facilitate the understanding of common issues when data analysis and machine learning are done.

Building a predictive model is as difficult as one line of R code:

my_fancy_model=randomForest(target ~ var_1 + var_2, my_complicated_data)

That’s it.

But, data has its dirtiness in practice. We need to sculpt it, just like an artist does, to expose its information in order to find answers (and new questions).

Michael Clark’s Documents

Michael notes of his online resource shared on GitHub:

Here you’ll find documents of varying technical degree covering things of interest to me or which I think will be interesting to those I engage with. Most are demonstration of statistical concepts or programming, and may be geared towards beginners or more advanced. I group them based on whether they are more focused on statistical concepts, programming or tools, or miscellaneous.

Michael is the Statistician Lead for the Advanced Research Computing consulting group, CSCAR, at the University of Michigan. He provides analytical, visualization, code, concept, and other support to the larger research community.

March Madness

A tweet from Mara Averick led me to Sam Firke’s discussion of March Madness college basketball.

Sam shares his guide for March Madness predictions (an estimate how likely it is that Team A beats Team B, for each of the 2,278 possible matchups in the tournament).

Sam shares a link to Gregory Matthews and Michael Lopez’s (2014) paper Building an NCAA mens basketball predictive model and quantifying its success. Gregory and Michael were winners of the 2014 Kaggle competition to predict the outcome of the tournament.

Photo Credits

…so… you’re saying the round one would please her more? (Pim Geerts, CC BY-NC-ND 2.0)

sweet16wide (Andy Thrasher, public domain)

Thinking about course design

I have been thinking about designing University courses in an age of open educational resources.

My particular interest at the moment is the combination of data science and sport analytics.

I keep returning to the idea of a ‘pedagogical technologist‘ able to offer ‘structured exposure’ to learners who might not otherwise choose to attend university. I see structured exposure as the key here if we are to offer a service to students in an institutional setting.

My inspiration is Alan Levine.

In 2014, Howard Rheingold described Alan as a pedagogical technologist “an architect of open, connected learning systems that enable students to take power over and responsibility for (and joy in!) their own learning”.

Howard added “Many people have something to say about what to do with the educational opportunities afforded by digital media. Fewer can persuasively articulate a case for specific pedagogies that digital media enable”.

I think Alan does this profoundly well.

Howard observed “while schools no longer have a monopoly on learning because free digital media can be used to learn anything, knowing what to learn, how to learn, what questions to ask, isn’t a given, even with the savvy online self-learner. The role of the instructor has not gone away, but it has shifted …”

This shift came to mind this morning when I read Bharath Raj’s How to play Quidditch using the TensorFlow Object Detection API.

I wondered how I might engage students like Bharath should he want to extend his domain knowledge to sports other than Quidditch as he guided his readers “through creating your own custom object detection program, using a fun example of Quidditch from the Harry Potter universe! (For all you Star Wars fans, here’s a similar blog post that you might like)”.

In his post he noted:

My motive was pretty straightforward. I wanted to build a Quidditch Seeker using TensorFlow. Specifically, I wanted to write a program to locate the snitch at every frame.

But then, I decided to up the stakes. How about trying to identify all the moving pieces of equipment used in Quidditch?

I though any design for learning I might propose would need to be profoundly personal. In this case, I wondered how prospective students might be introduced to object detection in sport using Bharat’s blog post as a problem finding start to a learning journey that encompassed first principles and granular detail.

I thought I might extract some provocations from the post and suggest students go back to some early work by Janez Pers and his colleagues (2002) and on to some of the more recent ‘ghosting’ studies of basketball and football.

This could become a spontaneous hackathon. At the University of Canberra, for example, I imagine this being facilitated by Roland Goecke in ways that underscored the power of structured exposure.

I hope students and teachers would have personal and shared learning journals that make transparent the emerging understanding about big things and small things. In doing so, we would all be moving toward a world that will be rather than a world that was.

I sense that pedagogical technologists are at home in this world of emerging performances of understanding. It is a fallible environment that demands institutions themselves become much more agile and much more imaginative in ways that courses are designed and assessed.

Photo Credits

Music abducted me (Carlos Romo, CC BY-NC-ND 2.0)

Alan Levine on/of the web (Kristina Hoeppner, CC BY-SA 2.0)

A model Fenway Day (Brian Talbot, CC BY-NC 2.0)

We are many. Can we be as one?

My Price and Value post earlier this week seems to have struck chords with some performance analysts.

The post has become one of the most read posts on Clyde Street and there were some important exchanges on Twitter. I have been reflecting on these responses and this is a follow up post.

The title of this post comes from the lyrics of an Australian song

We are one, but we are many
And from all the lands on earth we come …
I am, you are, we are …

I am sorry about my naivety in using these but they do resonate with me about the next phase in performance analysis.

We have to address these kinds of issues:

Lucy Rushton

Couldn’t agree more As we have to make a stand. We cannot continue to devalue ourselves in this way Its too easy to say ‘thats football {insert sport name}’. It’s not. Its what we have created & accepted. We cant let our passion for our job continue to be exploited

Amber Luzar

And it doesn’t take long for the novelty to wear off and the 60+ hours a week you work feeling extremely undervalued…for the love and growth of sport, this must change, to keep world class analysts continuing to be world class!

Jason Lear

The same issues seem to raise its head every couple of months and its sad that no collective exists to adopt the broader industry arguments. We remain or seem fragmented and easy to deflect by employers.

Lance Du’Lac

Time seems right to come together and change that then.

I am mindful that in starting this part of an occupational culture discussion, I do have responsibilities in an actionable conversation.

My commitment is to go away and do some comprehensive research about practice that I can share with the community.

In asking if we can be one, I am not asserting an homogeneous view of performance analysis and analytics. I want to celebrate diversity and different epistemic cultures.

A starting point for me is to engage with cultures whose first language is not English. I am critical of my own anglo-centric emphasis.

A second point is to discuss gendered identity in performance analysis and the languages we use to describe performance analysis practice.

Thirdly, I want to continue to advocate for our community to share practice openly so that we can have transparent conversations about our culture. (And support those who give their time and energy to connect our community.)

Fourthly, I think this is a conversation we must have with professional organisations, institutes of sport, and sport organisations.

This is where we can become one … through mutual recognition. It is my fight but it could be our shared fight if it is right for you.

I hope you do not mind me ending with music. When I think about what we can do together, I have this kind of performance in mind, at the end of a long day concert.

I will be back, possibly on drums.

Photo Credit

Baby’s hand (Fruity monkey, CC BY 2.0)