This is the transcript of what I plan to say during the OEB14 debate... but it will depend on my brain power and time itself (a bit of a long text). Feel free to share ideas and comments on it. Text follows the slides.

For those wanting to co-author on the potential negative effects of data on education, feel free to have a look at what I call 'the big data ramble, a plea for more human indicators' (beware that is a draft, so more chaotic than the text I bring below, but ... I want to use the chaotic draft as the basis of starting up a position paper with any of you who have an idea on the subject as co-author).

Digital divide & towards the norm from Inge Ignatia de Waard

Introduction

I will focus on two topics: how does data risk to add to the digital divide? And why does data replicate existing societal norms?

Digital divide

One of the reasons that data is currently corrupting education, is because big data increases the digital divide. Let me give you some examples.

The have and the have not’s … institutes - Digital divide dividing our educational institutes

As big companies retain more and more data, they are now looking for educational partners to use that data. But which partners are they choosing, and how does this affect the other educational institutes?

The digital divide – or the data divide - trickles down from the big Universities all the way to the vulnerable learners. As big universities might be able to pay for data access and results, and use those data to improve the learning goals of their (cognitive, and data minded) students. The less financially strong universities will have access to less data, less tools, which will affect learning/Teaching (although I do add that this might indeed not result in loss of teaching quality).

Which students will be able to pay for those universities? For if data storage and data mining is so expensive, it seems only logical that the educational fees for the data rich universities will rise.

This means that learners from less financially stable backgrounds, or parents with less financial means will have less opportunities.

(Example: oh but that is not going to happen some of you might think… but let’s look at Viktor, he is associated with a couple of large, financially rich universities: Harvard, Oxford)

The digital data-minded professors

The same is true for teachers, professors, research assistants. Learning analytics might provide insights, but these insights need to be translated back to the learners. Which means that all of us in education will have to become data savvy at some point.

Selecting the learners that fit the profiles provided by algorithms

Administrators facing tough budget decisions will look to the application of learning analytics with a profit oriented mind. In a world were profit rules, students from demographic groups that perform less can be seen as a potential loss.

If a university recognizes that a particular demographic group is more likely to quit school, the university may choose to slash recruiting on that group and exclude them for no personal reason of its own. Traditionally poorer performing demographic groups might be excluded based on economic/statistical data reasons. And this practice is already starting, for one university in Belgium is forcing out low performing students after their first year.

Example: looking back, I can tell you that I was one of those weak learners, I was scared out of my wits in my first year at the university. All of a sudden I had to learn?!!! But by some weird twists of faith, I eventually made it, and I am now part of education).

(example me, addition: Aida Opoku-Mensah : 51 million?)

Education for the purpose of future jobs, which jobs?

In 2013 during the World Innovation Summit for Education (WISE) 84% of leading educators, policy makers and governments claimed that the way learning happens today will not adequately prepare young people for the world of tomorrow. By this they referred to preparing the young for future jobs. Big data would solve this.

This seems like a very valid claim to make. One that made sense to me… until recently. Just a couple of weeks ago a new UK report came out focusing on job expectations. In that report the experts predicted that by 2030 one third of the current jobs will be lost due to automation… If there are less jobs to fill, the goal of education should turn towards multiple goals: not education resulting in professional work only, but education should also be aimed at reaching a better quality of life, becoming a truly fulfilled human being, and enabling a new society.

But with big data entering education and automation increasing, there is a strange selection criteria seeping in. If less jobs are available, not that many students need to be prepared for those jobs. So it might be more profitable to only focus on those students who are at the top of the crop.

The facts versus the actions

Until data became a reality, the teachers and trainers were the corner stone of education. Research proved this time and time again. So did we act upon that data?

At the moment government and the financial markets provide us with to contradictory messages. On the one hand we all need to accept cuts in education and training, for we need to help all of us get out of the crisis. On the other hand bigger budgets and funding than ever before are going straight into big data research and implementation (for education among others), because data will enable an improved education.

Why are bigger budgets provided to replace the proven human teaching with automated training that still needs to come of age? (sordid logic)

the drive towards the Norm

What is data other than the reproduced norm of society? The gatekeepers – those with power - build the quizzes, construct the algorithms that are needed for educational data-mining. And based on what? On the need of the day, not the need of the individual, not the need of a sustainable, qualitative society.

As all technologists and developers know, wo/man-made algorithms reproduce the norm of those who constructed the algorithms. (example hit prediction)

Not moved by the norm, but enchanted by the one

For me I am not moved by the norm, but enchanted by the one. Change does not come from the masses, it is the single mind that finds and touches the truth felt within each one of us. The masses only reproduces existing norms, existing power.

If we think of Mahatma Ghandi, Emmeline Pankhurst, Barack Obama, Rosa Luxemburg, Marcel Proust, Muḥammad ibn Mūsā al-Khwārizmī, Rosa Parks, Steve Jobs, … we know that they are individuals, they were never the norm. What is the algorithm of a great person?

The existing norm will also defend its own existence, in spite of data based proof

One of the fields with the most data gathered overtime, even before big data, even before data itself became a concept, is the weather and geological phenomena. And if we look at the last century, data is gathered that points towards climate change. Everyone agrees that climate change is now a reality.

But does it change anything? No. Having big data, does not change anything as long as the political, social and more importantly the economic systems is not willing to change and drop some of their power, some of their profit, and combine forces for a human, global solution.

With regard to education the same has happened. Unesco has been gathering data on what is needed to ensure education for all (which is by the way in part train-the-trainer, the human element of learning/Teaching), but even though the facts needed for change are known for decades, we cannot seem to meet the ‘education for all’ goals no matter how many millennial goals are stated.

So what is the hidden power behind the data, and where does that hidden power direct us towards?

Let us all think for one moment about who we are, you, me, each single one of us.

The question is simple: how much of me is the norm, how much of me is unique?

My guess is, we all were and are exceptions to a rule at some point. We are innovators, and purely because of that we situate ourselves outside of the norm (bell curve early adopters)

I have a Dream … but does data support it?

Educational data is currently build upon the idea of efficiency. But life is not made out of efficiency only, life is quality, life is creativity, life is – at best – living your dream. And if your dream situates itself in the cognitive fields, data will help you find your way and improve your cognitive abilities. But if your dream situates itself in a creative or vocational field, than data will be less likely to support that goal. For dreams are not profitable in many cases, although dreams do enrich each one of our lives

And by making decisions on what we need, what the norm should be, again the digital divide between those who have and have not will increase. Data risks corrupting education, unless we consciously step away from pure profit goals, and turn towards a global, human society.

Conclusion

As my colleagues have showed data has achieved new insights, new innovations in health, urban planning and such. But for all the good data is said to do, if we do not ensure that each one of us can actually get a job, get paid, then we will not be able to pay for healthcare, we will not be able to drive a car in a well-planned urban area. The success is of data is only as strong as the lives it can help improve and before all sustain in the long term. As long as the digital divide is not turned back, as long as data is not reproducing the norm, but ensuring a more balanced society filled with creativity and quality, educational data will have a corrupting effect.