Three posts about analysis and analytics

I have had some time to think about meta issues in performance analysis and analytics. I think this is an exciting and transformational time for this epistemological and ontological domain.

My three posts, written today flowed from a friend’s email in which my friend employed in an institute of sport observed that “the biggest challenge is how we develop and mentor these data people”.

The first post (link) discussed the concept of a sticky campus as a “a digitally-enabled space” and “a learning environment designed to give students everything they need for collaborative and solitary study, and to promote active learning”.

The second post looked at the verbs we use to describe what we do (link). This was prompted by a conjunction of my friend’s email and news of the IBM’s AI Ladder (link). The artificial intelligence ladder has four characteristics: collect; organise; analyse; and infuse.

A third post uses a lens of a critical friend to explore pedagogies and practices in performance analysis and analytics. It uses a seminal paper by Arthur Costa and Bena Kallick (1993) (link) to explore the trusted relationships that grow between friend and analyst. I am particularly interested in the role of a friend is an advocate for success (link). A key point in this post is the investment required by leaders in these learning opportunities “funds should be focused on providing high-quality professional learning experiences”.

Photo Credits

Vintage Sheep Hiking (Lenny K Photography, CC BY 2.0)

Markus Spiske on Unsplash

RLadies London (Twitter)

James Baldwin on Unsplash

Describing what we do

In conversations about people involved in data analysis, one of my colleagues in an institute of sport observed that “the biggest challenge is how we develop and mentor these people”.

I see this as a critical issue as sport expands its data science portfolios. It has encouraged me to think about the verbs we use to describe our work in data.

When I first started in performance analysis in pre-digital days, we aspired to:

  • Observe
  • Record
  • Analyse
  • Model

Guillermo Martinez Arastey (2018), amongst others, has described how this role has changed in a digital era (link). It has meant for me that performance analysts are connected and I saw this at first hand when I met Darrell and Adam in Cardiff (link).

Darrell’s Vocational Performance Analysis post and Adam’s What has changed in Performance Analysis over the last 5 years? exemplified their reflection in and on action that define connected, sensitive educators.

I was thinking about these connections and changes when I came across IBM’s AI Ladder (link). This ladder used a fourfold taxonomy of verbs:

  • Collect accessible data
  • Organise a business-ready foundation
  • Analyse with trust and transparency at scale
  • Infuse throughout the business

I would add to this feedforward (link). With artificial intelligence I think it is vital to consider where we will be and involves us in mental time travel.

In a 2012 paper, Peter Dowrick observes:

The most rapid learning by humans can be achieved by mental simulations of future events, based on reconfigured preexisting component skills. These reconsiderations of learning from the future, emphasizing learning from oneself, have coincided with developments in neurocognitive theories of mirror neurons and mental time travel.

It is these “mental simulations of future events” that strike me as very important as we consider the verbs that guide us through a dynamic domain opening up before us.

Photo Credit

Markus Spiske on Unsplash

Networks

My son, Sam, has just written a post about systems and networks (link). I found the post really interesting in a paternal sense and an epistemological sense.

The paternal part of me is delighted to read a blog post by Sam and to learn about his observations and reflections as a member of the #INF537 (link) Masters of Education (Knowledge Networks and Digital Innovation) online at Charles Sturt University.

The epistemological delight is in my commitment to self organising networks hinted at in Sam’s post. I have written a lot about networks (link) and have been thinking about these issues a great deal since the distributed, open course CCK08 (link), and becoming an accidental connectivist (link).

I am keen to persuade Sam privately and publicly to explore self organising networks (link) and to read more about Stephen Downes’ (link) and Alan Levine’s (link) work. I appreciate Sam’s particular working environment constraints (systemic) but am determined to explore the action possibilities he can address as a community driver and facilitate network flourishing within those constraints (link).

I sense that with energy anything is possible even in constrained contexts.

Photo Credit

The Maze (Keith Lyons, CC BY 4.0)