#UCSIA15 Connecting and Sharing Macro and Micro Perspectives

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Introduction

We are three weeks away from the start of #UCSIA15, a free, open, online course that will share experiences of sport informatics and analytics.

The course aspires to be a connectivist course. Stephen Downes (2012) notes that in  a connectivist course “the content does not define the course”. He adds:

By navigating the content environment, and selecting content that is relevant to your own personal preferences and context, you are creating an individual view or perspective. So you are first creating connections between contents with each other and with your own background and experience. And working with content in a connectivist course does not involve learning or remembering the content. Rather, it is to engage in a process of creation and sharing. Each person in the course, speaking from his or her unique perspective, participates in a conversation that brings these perspectives together.

In an earlier post, Stephen (2007) points out that:

At its heart, connectivism is the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks.

I like Gordon Lockhart’s (2013) description of his experience of a connectivist open course (cMOOC):

it dawned on me that, contrary to what was on the tin, a cMOOC wasn’t a ‘course’ at all. Instead, a heady amalgam of ‘massive’, ‘open’ and ‘online’ was leading to a quite extraordinary place where the normal rules of learning engagement just didn’t apply. There were a couple of facilitators but no teachers. Participants were encouraged to create and maintain their own blogs. Social media was used for discussion and sharing resources. Topics were explored together, connections made and groups were formed and maintained long after the MOOC was over. cMOOCs never die …

Self-organising networks of shared interest

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Self-organising networks flourish in connectivist courses. Participants follow their interests and meet others on their learning journeys.

I am hopeful that participants in #UCSIA15 do pursue shared interests to extend their understanding of sport informatics and analytics.

I think one area of activity could be the discussion of football performance. There is a vibrant community of analysts who write about their work.

I wondered if this might be an example of a topic that would engage a community of practice …

I have been looking at the characteristics of teams that win European League competitions. I started with five competition winners: Manchester City, Paris St Germain, Bayern Munich, Juventus, and Atletico Madrid.

I used secondary data from worldfootball.net to look at all games played by the teams in the 2013-2014 season. Atletico played 61 games, Manchester City 57, Bayern 56, Juventus 55, and Paris St Germain (PSG) 52. I gathered data manually from these games.

My primary question about the teams is: do they score first in each game and do not lose?

The data I collected enabled me to produce this matrix:

ELC Matrix

This is how I visualised the success curves of the five teams:

ELC 2013-2014

Macro perspectives and phenomenographic detail

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I have compiled my data in this Google Sheet.

These days I start all my analyses with a macro indicator, particularly as I use secondary data to identify performance characteristics (other examples here).

This macro approach leads me to much more detailed phenomenographic interest.

I think the community of practice of football analysis and analytics provides this granular (phenomenographic) detail.

In the case of Bayern Munich, for example, they lost just one of their fifty-six games after scoring first (against Manchester City in the Champions’ League). Ironically, this game was played at home and Bayern were 2v0 ahead after 12 minutes.

It is interesting to note that the other four teams lost very few games after scoring first: PSG 2, Manchester City 2, Juventus 1 and Atletico 1.

One of my hopes for #UCSIA15 is that we might be able, as diverse self-organising networks, to wikify our understanding of performance.

Neural tapestry

When I am asked what kind of course #UCSIA15 will be, I return to Stephen Downes for guidance.

Last year, Stephen (2014) wrote that a learner is “a self-managed and autonomous seeker of opportunities to create, interact and have new experiences”. He added that learning is not “the accumulation of more and more facts or memories, but the ongoing development of a richer and richer neural tapestry”.

I like the idea of neural tapestry for participants themselves and for self-organising networks of interest.

I understand that participants in the course might expect some formal structure to the four weeks of sharing. I hope to do this each day with my friends from Cardiff Met in Wales. Together we will share the day’s activities as a twenty-four hour open course.

I hope we might provide the heady amalgam of opportunities Gordon wrote about. If we do not I trust that the transparency of our approach will make it possible to address issues raised by participants’ personal learning journeys.

Football performance might be one of the catalysts for these conversations.

Photo Credits

Munchen 11-2014 (Armin Rodler, CC BY-NC 2.0)

Internet Splat Map (Steve Jurvetson, CC BY 2.0)

Crowd in Railway Station (Matthias Ripp, CC BY 2.0)

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