The problem with “the Chinese student”

The Reddit discussion that followed the article was fascinating because it quickly became a battle of anecdotes. One lecturer says Chinese students are among the hardest-working students they have ever taught. Another says they barely speak English. Someone else blames cultural differences. Another blames universities recruiting students for their fees. Another blames AI. Someone else points out that British students can be spectacularly disengaged too.

Everyone has a story.

This is where Geoffrey Bowker and Susan Leigh Star’s Sorting Things Out (1999) becomes useful. Their central insight is simple: classification is about describing the world; classifications also help organise and produce the world. Categories determine what becomes visible, what disappears and how people are subsequently treated.

“The Chinese student” is one such category.

It can become a convenient informational shortcut. A student who does not speak in seminars becomes “passive”. A group that speaks Mandarin becomes “unintegrated”. Poor English becomes “low ability”. Translation software becomes evidence of disengagement. AI-generated writing becomes evidence that the student is cheating.

Sometimes those interpretations will be completely justified. But sometimes they won’t.

The danger is that once the category becomes established it begins doing explanatory work before we have actually investigated the individual.

Yet I don’t think the answer is to throw the category away and insist that every criticism is simply racism. That would be equally lazy.

There are real differences in educational experience, language proficiency, expectations of teachers and classroom participation. Pretending otherwise does not help Chinese students, their classmates or their lecturers.

The trick is distinguishing a real pattern from a lazy explanation of that pattern.

Passive students are…still students?

There is another uncomfortable point here.

A cultural explanation can become an excuse.

Yes, some Chinese students come from educational environments where questioning teachers publicly is less common. Yes, moving to a British university can involve enormous linguistic and cultural adjustment.

But at some point, you still have to participate!

If you have paid £25,000 or £30,000 for a master’s degree, nobody should need to mime the entire seminar at you.

And this is where I think some of the Reddit responses become overly defensive. We can acknowledge racism and stereotyping without pretending that every criticism of student behaviour is illegitimate.

International students are adults. They are not merely passive victims of British university structures. They make choices too.

Choosing to spend an entire year communicating almost exclusively in Mandarin, translating everything and not developing English competence, contributing the bare minimum to group work, outsourcing thinking to AI and treating the degree as a certificate in lieu of an education has consequences.

It can be unfair to classmates and it can be exhausting for lecturers.

And perhaps most importantly, it can be a spectacular waste of the opportunity the student has paid for.

But maybe universities are pretending too

Now comes the other half of the problem.

The Spectator article is right to point towards university finances. UK higher education has developed powerful incentives to recruit international students, particularly on expensive one-year master’s programmes.

The student is therefore simultaneously a learner, customer, income stream, visa holder, statistic and retention figure.

This is where Michel Foucault’s Discipline and Punish (1975) remains relevant. Foucault showed how modern institutions govern people through observation, documentation, assessment and classification. Schools, hospitals, prisons and other institutions do not simply exercise power by telling people what to do. They produce records about people.

The contemporary university takes this to another level.

Students generate data everywhere:

attendance records, grades, engagement statistics, satisfaction surveys, progression rates, admissions profiles, misconduct cases, learning analytics and now AI-detection reports.

The university accordingly doesn’t actually see learning. It sees traces of learning. And that distinction matters.

A student can attend every lecture without learning anything. Another can sit silently and understand everything. Someone can produce beautifully written prose with considerable intellectual depth. Someone else can produce beautifully written prose with ChatGPT doing most of the intellectual heavy lifting.

The information system has to turn all of this messy reality into categories….Present. Absent. Engaged. Disengaged. Pass. Fail. Authentic. AI-generated. Satisfactory. Unsatisfactory.

The messier the reality becomes the more attractive these clean categories become.

And then there is AI

The irony in all this is that the original complaint about students “pretending to learn” arrives at exactly the moment when AI makes the performance of learning easier than ever.

A student can ask Claude to translate an article, explain a theory, generate an essay plan, rewrite an email, produce a discussion post and even formulate a supposedly spontaneous seminar contribution. But maybe universities are hardly innocent bystanders here. They use AI too: AI detection, automated feedback, analytics, dashboards and algorithmic monitoring.

We are thus entering an educational environment in which students use machines to simulate learning while institutions use machines to measure it.

Everyone gets their information. Everyone gets their dashboard. Everyone gets their grade. And somewhere in the middle, actual learning is expected to have happened.

So who is pretending?

This is why I find the original headline compelling.

“We pretend to teach, they pretend to learn”.

Perhaps the uncomfortable answer is both sides.

Some students really are pretending. Some are disengaged, underprepared or simply looking for the quickest route to a British qualification. That deserves criticism. Being an international student should not place someone beyond criticism and cultural difference should not become an all-purpose excuse for poor academic engagement.

But maybe universities are pretending too.

They pretend that recruitment and education are always perfectly aligned.

They pretend that a £30,000 international master’s degree necessarily represents £30,000 worth of intellectual transformation.

They pretend that grades accurately measure learning.

They pretend that attendance measures engagement.

They pretend that AI detection can tell us who genuinely wrote something.

And they pretend that institutional financial pressures have nothing to do with academic standards.

It is an information ecosystem in which students, academics and institutions have incentives to produce convincing traces of success and not the thing itself.

Bowker and Star (1999) remind us that classifications shape the worlds they describe. Foucault (1975) again reminds us that documentation and assessment are forms of power. And today’s AI systems add another twist: they make it easy to manufacture the informational appearance of competence.

So perhaps we should ask an awkward question:

What happens to a university when everyone becomes very good at producing the information that says learning has taken place?

That is a much harder problem to solve. And considerably less comfortable than blaming anyone!