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Archive for January 11th, 2012

Learning Is Performance; Performance Can, And Will, Be Analysed

Posted by Brian Kelly (UK Web Focus) on 11 January 2012

Learning is Performance

Learning is performance” Steve Wheeler tells us in his opening sentence in his first blog post of the year. Steve goes on to describe how:

Some of our earliest performances, particularly in formal learning contexts (school, college, university), are under the scrutiny of subject experts who award grades, and ultimately, some form of accreditation. This kind of performance is commonly referred to as formal assessment. Sadly, it is often the case that the measure of performance is not fit for purpose, as we have all witnessed recently in the universal failure of standardised testing, or the exam paper fiascos that continually assail our senses via the media.

The implication may to be that since sometimes (is there evidence that the term ‘often’ should be used in this context?) a “measure of performance is not fit for purpose” we should avoid assessment. However as Steve goes on to point out:

[Assessment] is important for the community, because the community needs skilled and knowledgeable members, and some form of check is required to ensure that the skill or knowledge is up to date, safe to use, and is relevant for the needs of society. If we get assessment wrong, we fail the student, and ultimately we fail society.

The JISC CETIS service has had a long-standing involvement in exploring issues related to assessment. But Steve Wheeler’s comment that “Learning is performance” has reminded me that it may be beneficial to explore approaches to assessment beyond the tools, projects and resources which CETIS have documented on their web site.

Sporting Performance

One lunch time a few months ago I met Doctor Ken Bray, a Senior Visiting Fellow in the Mechanical Engineering Department at the University of Bath.

Ken’s work has been featured in a couple of press releases published by the University of Bath. In January 2009 the focus was on work related to the physics of darts:

As the British Darts Organisation’s (BDO) Lakeside World Professional Darts Championships gets into full swing this week, new research from the University of Bath shows that the secret of true darts skills is all in the maths.

Visiting fellow Dr Ken Bray’s calculations for the Get On campaign shows how darts stars taking to the oche this week will have to master geometry, physics and algebra to win their place in the sport’s hall of fame.

However Ken’s main interest is in the science of football. Ken is author of How to Score: Science and the Beautiful Game which was published in 2006. His interests in this area have continued and were featured on the This Is Bath Web site in March 2011:

​They may not realise it, but the best footballers are actually skilled mathematicians, according to an expert from Bath.

University of Bath sports scientist Dr Ken Bray has analysed hours of football footage to conclude that as much as 30 per cent of a player’s technique is down to an intuitive understanding of maths and science.

A criticism of which could be made of a scientific study of sports is that “We all use mathematical principles – we’d fall over when walking if we didn’t!” And it would clearly be wrong to suggest that David Beckam’s success in taking free kicks is due to a conscious analysis of the variables (the distance, the weather conditions, the angles, …) and the implementation of the appropriate formula which will ensure that the ball succeeds in bending around the defensive wall and out of the reach of the goalkeeper to ensure that England reach the final stages of the World Cup, as Beckham famously did with his 30-yard free kick, three minutes into injury-time of the game against Greece in 2006.

However although footballers and other sports stars may have an “intuitive understanding of maths and science” those involved in coaching nowadays do have an understanding of the maths and physics associates with sports success and are developing measurement techniques which can provide ways of helping to ensure success.

Some approaches will be related to the individual sportsman, for example their diet and general fitness. However others will relate directly to their sporting performance and the performance of the opposition. This is now a major industry with companies such as Prozone analysing sporting performance and selling their methodologies, tools and data to interested parties, including sporting clubs, sportsmen and women, coaches, agents, newspapers and TV companies and sports fans.

As described on the Prozone web site the company provides:

Post match analysis: Analyse every aspect of team and player performance via a range of interactive platforms.

Opposition Analysis: Prozone can provide pre-match performance information on your forthcoming opponents. Commonly known as ‘technical scouting’ this allows you to identify the strengths and weaknesses of upcoming teams and individual players.

Through interactive coaching tools, users are able to gain a unique insight into the performance of upcoming opposition teams. These can help to supplement the knowledge of your scouts and enable you to better prepare for upcoming matches. Scouting analysis can be delivered using a range of video clips, in-depth data and multi-layered graphics and can be accessed online or sent direct to the training ground.

Live Performance Analysis: By offering ‘real time’ information about the game, our Live Analysis service gives management and coaching staff an immediate insight into the performance of players on the pitch.

Enhanced Player Trading: An advanced online solution allowing clubs to make objective and better informed decisions on player trading through the use of accurate performance data.

I wonder to what extend these approaches may have some relevance to the higher education sector? Back in October in a post on  Learning Analytics and New Scholarship: Now on the Technology Horizon I summarised Dave Pattern’s talk at the ILI 2011 conference which described how “The project looked at the final degree classification of over 33,000 undergraduates, in particular the honours degree result they achieved and the library usage of each student” and explored the hypothesis “There is a statistically significant correlation across a number of universities between library activity data and student attainment‘.  Hmm, does this have parallels with analyses of Arsenal’s defensive frailties and strategies for playing against them.  And should we be looking to provide services similar to Prozone’s:

Live Performance Analysis: By offering ‘real time’ information about students’ learning experiences, our Live Analysis service gives management and academic staff an immediate insight into the performance of students in their learning.

Steve Wheeler concluding his blog post by suggesting that:

Knowledge performance is at the centre of community as curriculum. From the sharing of knowledge comes the discourse that adds to everyone’s collective knowledge within the community of practice, and extends its boundaries. It is this sharing of experience, new ideas, contention and support that advances the community of practice exponentially. The tools are here to achieve it. Performance of knowledge through social media will be one of the vital components of education and training in the coming years.

I agree with that final sentence: “Performance of knowledge through social media will be one of the vital components of education and training in the coming years“. But this will not be restricted to learning and teaching. I would slightly modify this conclusion by saying: “Performance of knowledge through social media will be one of the vital components of research, education and training in the coming years“. And being able to analyse the performance will be a major growth area. Or at least that is what the  NMC Horizon Report > 2012 Higher Education Edition seems to be suggesting with the NMC Horizon’s 2012 Preview Report (PDF format) suggesting that Learning Analytics has a time-to-adoption horizon of 2-3 years.

The report defines Learning analytics as

the interpretation of a wide range of data produced by and gathered on behalf of students in order to assess academic progress, predict future performance, and spot potential issues. Data are collected from explicit student actions, such as completing assignments and taking exams, and from tacit actions, including online social interactions, extracurricular activities, posts on discussion forums, and other activities that are not directly assessed as part of the student’s educational progress.

Or if we, this time, apply this to a sporting context with the changes highlighted:

the interpretation of a wide range of data produced by and gathered on behalf of footballers in order to assess football progress, predict future performance, and spot potential issues. Data are collected from explicit sporting actions, such as completing passes and taking penalties, and from non-sporting actions, including online social interactions, extracurricular activities such as not been caught for drunken driving, posts on the footballer’s Twitter account, and other activities that are not directly assessed as part of the footballer’s sporting and non-sporting progress.

The major difference is that football is a game of two halves but an undergraduate course is a game of three years :-)

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