#cssia17 Connecting and Sharing

I have been following up on some leads shared by Mara Averick. Two recent suggestions caught my attention as I try to improve the ways I share and connect.

The first was a post by Joris Muller about reproducible computational research for R users. In it he explores ideas shared in a 2013 paper written by Geir Sandve and colleagues. In that paper, Geir proposes ten rules for reproducible computational research. These are very pertinent to those seeking to share and explore performance in sport using analytics insights.

The ten rules are:

  1. Keep track of how every result was produced.
  2. Avoid manual data manipulation steps
  3. Archive the exact versions of all external programs used
  4. Version control all custom scripts
  5. Record all intermediate results in standardised formats when possible
  6. For analyses that include randomness note underlying random seeds
  7. Always store raw data behind plots
  8. Generate hierarchical nalysis output allowing layers of increasing detail to be inspected
  9. Connect textual statements to underlying results
  10. Provide public access to scripts, runs and results

Joris concludes his post:

All the 10 rules proposed in the Sandve paper are reachable for a R user. Just by using R itself, the rmarkdown workflow and some organisational rules cover most of these rules. My basic reproductible workflow meet almost all the criterias with the notable exceptions of the software archive (but it’s work in progress with packrat) and the lack of public access (but I can’t share everything).

For an introduction to Joris’s workflow, you might find this post of interest.

The second lead from Mara focussed on reproducible behaviour too.  Jenny Bryan shared her ideas back in 2015 about Naming Things. This is one of the many resources Jenny has shared. I have found her GitHub repositories immensely helpful. In her 2015 paper, Jenny notes three principles for file names: machine readable, human readable and ‘plays well with default ordering’.

The two leads sent me off thinking about how I might improve my practice. I am fascinated by Joris’s transparency with his workflow and I see this approach as essential for sport analytics as we start to extend cumulative rather than ‘ab initio‘ research. I admire Jenny’s work immensely. I have tried to use some robust file naming conventions for the past fifteen years as I have sought to use cloud based storage for all my resources. I realise I am a long way from meeting Jenny’s three principles at the moment but this will be a work in progress.

Mara Averick’s Twitter recommendations are becoming a very important way for me to connect with a community of practice. These two leads discussed here are a way for me to make this process explicit … and to initiate a conversation about reproducible behaviours in sport analytics research and practice.

Photo Credits

Tree on campus (Keith Lyons, CC BY 4.0)

Memes as evaluation opportunities (#UCTL16)

I am still smiling about this tweet

It is the first time I have looked closely at a # meme. (The origin of the meme is here.)

Perhaps it is because I have been reading around perfomativity that I was drawn to the wonderful humour and insight on display within the meme.

The two connect for me through this quote from John Austin:

The words which are used to express ourselves are also means by which we enact ourselves.

All of which encouraged me to think about how teachers and learners might evaluate their shared learning experience through a variation of the meme.

These are my thoughts as an example of an imagined unit at the University of Canberra.

I imagine a rich conversation emerging from this parsimonious observation. This approach resonates, I think, with Mary Ryan’s (2012) contemplation of teaching discursive and performative reflection in higher education:

Teachers need to provide opportunities for students to develop meta-discursive skills, whereby they not only engage in the different discourse communities of the different disciplines, but they also know how and why they are engaging and what those engagements mean for them and others in terms of social positioning and power relations.

If students are to enact particular identities within the discipline, they should be provided with opportunities and pedagogic scaffolding to represent their reflective learning in different modes.

As I conclude this post, Scott‘s tweet has received 7,000+ likes and 4,000 retweets. Imagine what this level of engagement might do for personal learning conversations.

Prosocial connections


On most weekdays, I start my online day by reading Stephen Downes’ OLDaily.

I admire Stephen’s willingness to share openly.

I feel profoundly grateful that he does share.

Some time ago (2006), Jo-Ann Tsang defined gratitude as:

A positive emotional reaction to the receipt of a benefit that is perceived to have resulted from the good intentions of another.

Stephen’s open sharing has encouraged me to share openly too, nourished by what I hope are “good intentions” (Attila Szolnoki and Matjaz Perc, 2013).

I understand that many people are reluctant to engage in open sharing. I spend a lot of time advocating for and discussing the use of open educational resources with those who are nervous about so doing.

A paper by Patricia Lockwood and her colleagues (Matthew Apps, Vincent Valton, Essi Viding and Jonathan Roiser) published online before print (15 August, 2016) has helped me think about my arguments in favour of prosocial behaviour. They have introduced me to the subgenual anterior cingulate cortex/basal forebrain (sgACC).

Patricia and her colleagues observe that the sgACC “drives learning only when we are acting in a prosocial context”. They add:

However, there is also substantial variability in the neural and behavioral efficiency of prosocial learning, which is predicted by trait empathy. More empathic people learn more quickly when benefitting others, and their sgACC response is the most selective for prosocial learning.

Their paper explores this prosocial behaviour and considers how their findings might help us understand the behaviour of those people with “disorders of social cognition”.

In their study of altruism, Frans de Waal, Kristin Leimgruber and Amanda Greenberg (2008) reported that prosocial behaviour with a partner was a favoured option “provided their partner was a) familiar, b) visible, and c) receiving rewards of equal value”.  They added:

Prosocial tendencies increased with social closeness, being lowest toward strangers and highest toward kin.

Perhaps it is because I perceive receiving Stephen’s OLDaily as a letter from a friend that I am encouraged to share too. The literature on primates suggests that I should work much harder at understanding differences and traits … and hopefully become familiar and trusted.

Photo Credit

Mercedes Bends and Altruism Rules (Newtown Grafitti, CC BY 2.0)