For Professor Sam Sellar, the future of education significantly depends on understanding and responding to the changes and challenges brought about as big data and digital tech have become embedded in schools and universities.
AI and the risks of students' misuse has dominated the news of late, but Professor Sellar's research points to the longer-term trend of data-powered technologies (ChatGPT's forerunners) that have sometime negative effects on teachers and their professional roles.
It does not have to be that way, he says. The future could (and should) be one that sees more teachers shaping technology; rather than tech shaping the teaching.
Professor Sellar, who is Dean of Research in Education Futures and Professor of Education Policy at the University of South Australia, says that "We must start to tackle the hard questions surrounding how far we are willing to automate teacher’s work."
"Will automation proceed to erode teacher's expertise and professional autonomy, or can it be harnessed to empower teachers and public education? Are teachers and teaching at risk of becoming a mere adjunct to technology, and who will control, shape and profit from education in the future," these are some of the hard questions currently facing us, Professor Sellar said.
In a chapter appearing in Elvesier’s new International Encyclopedia of Education, Professor Sellar and his co-author Matthew Thorpe, of Manchester Metropolitan University in the UK, argue that big data is now the major dynamic shaping our collective vision of education. How we respond to this now may decide whether the future is defined by the Uberisation of education, or by the empowerment of teachers and students.
“We call what is happening 'datafication' because almost every element of teaching is becoming more and more connected to collecting and using data. The power of 'big data' and AI shapes every debate about education - there is an idea that data is the most convincing form of evidence we have, when it comes to decisions about how and what we teach,” Professor Sellar said.
“What has to be remembered is that data, facts, evidence, and truth are all very different things. Conflating data and evidence is something all of us find it very easy to do.”
However, Professor Sellar said data just provides a basis for different interpretations and arguments and there is never one way to understand it.
“Evidence and facts can only emerge through digging into different arguments drawn from the same data. Rather than being seen as a way of presenting facts, data should be understood as opening up many possible ways to interpret and shape the world.”
Professor Sellar warns that currently, the way big data and big tech are currently reshaping the world of education means we are walking blindly into serious challenges.
“At present, the way we use data erodes the social trust we place in teachers as professionals,” Professor Sellar said.
“Teachers often feel conflicted, because their educational values and professional knowledge would see them teaching in different ways but, if the results are not easily translated into data, their views may be discounted.”
Datafication has already reshaped teacher’s work, Professor Sellar and Mr Thorpe argue, with the need to produce reams of data constraining teacher’s decision-making.
"The focus on recording data pushes teachers towards what is easiest to measure, not necessarily what is best,” said Professor Sellar. “For example, even teachers in early years and primary settings are now under significant pressure to record and respond to data regarding children’s development.”
Professor Sellar says that this not only reduces teachers' roles, but can lead to a vision of students that leaves out their individuality and personhood. “Each child ends up with a ‘data double’ that often substitutes, in decision-making and assessment, for the child themselves”.
Professor Sellar is concerned that the apparent ability to make predictions based on big data can actually lead to self-fulfilling prophecies.
“It is always useful to be critical about the accuracy of data and the biases it can conceal,” he said.
"Another concern is that making strong predictions can actually determine outcomes that might otherwise be open. For instance, a student might be predicted to have poorer outcomes, so they are assigned less challenging subject matter - they end up acting out a prescribed role. The data did not just predict the outcome, it created one.”
Other risks that Professor Sellar raises include deepening digital divides, not only due to the problem of access to expensive digital devices, but through the fact that algorithms used to evaluate students can perpetuate stereotypes.
“Algorithms are often trained on biased data sets, which make for biased decisions about students’ current and future performance. This is an opportunity to be mindful that biases are common both to human beings and to artificial intelligence,” Professor Sellar said.
"Students must be given the freedom to be more than their data profiles.”
Professor Sellar and Mr Thorpe warn that automation may further disempower teachers, hemming in their professional judgement, autonomy and creativity.
“The question being raised is whether it is or desirable, or even possible, for the role of the teacher to be replaced by artificial intelligence,” they wrote.
Professor Sellar believes the growth of education technologies is disconnected from teachers’ professional judgment.
“Educators do not generally get to inform how these systems and platforms are designed or implemented. Instead, it is teachers who are often represented as old-fashioned, deficient, and in need of replacement by new, commercially profitable, hi-tech solutions," Professor Sellar said.
Professor Sellar and Mr Thorpe think that the next steps in the data-driven re-moulding of education will involve further forms of automation that could leave more decision-making power in the hands of algorithms.
“While the automation of education is still emerging,” Professor Sellar says, “one common idea is that we can personalise learning to resemble Netflix, Facebook or Amazon - automating content based on an algorithm’s reading of previous activity. This prescriptive ‘personalisation’ can really silo each student into their own, narrowed curriculum, where there is very little shared or collaborative learning.”
Professor Sellar clearly states that, “Of course digital platforms are not, by themselves, the problem! They can and do provide benefits. The issue is how technology gets dropped into classrooms as ‘black boxes’ that influence, or even substitute for, aspects of professional judgement and decision-making – without that judgement, in turn, shaping the technology.”
“Unfortunately,” says Professor Sellar, “this way of introducing new data-driven technologies opens up public education to new private actors, involving them in the design, management and delivery of different aspects of public education. Instead, educators should have more involvement and knowledge around how new technologies shape the future of education.”
This is a form of privatisation, say Professor Sellar and Mr Thorpe, and they write that “it is occurring at the same time as another, new, type of privatisation is emerging: the Uberization of education.
Uberization describes the disruption of an existing industry and its business models through the introduction of digital platforms that enable peer-to-peer transactions. Unlike other forms of privatisation, Uberization does not seek to alter the model of public education; rather, private actors aim to break this model by introducing new ways to sell education. These processes contribute to taking education’s future direction out of the hands of teachers, parents, and the public.”
For Professor Sellar, simply opposing or criticising data-driven technology offers few ways forwards. “What is needed is creative ways to push developments in beneficial directions for educators, students, and societies. Researchers and teachers must explore and promote alternative ways to use data and AI; ways that enhance the work of human educators. This is how we can challenge the tendency to automate teaching just because we can, or because it might be convenient to.”
“The opportunities and the risks presented by new, data-rich, digitalised education models are considerable," Professor Sellars says.
"Many of the biggest risks can be avoided by finding ways, no matter how difficult it may seem at first, to bring teachers’ judgement and experience into the design and development of technologies. We can - we have to - put teachers in the driving seat when it comes to education technology.”
This article originally appeared as a media release from MCERA.