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The Hechinger Report
Reframing ed tech to save teachers time and reduce workloads
McKinsey report estimates that existing artificial intelligence applications can save teachers 13 hours a week
By Jill Barshay
January 27, 2020
For much of the previous decade, advocates of education technology
imagined a classroom where computer algorithms would differentiate
instruction for each student, delivering just the right lessons at the
right time, like a personal tutor. The evidence that students learn
better this way has not been strong and, instead, we’re reading reports
that technology use at school sometimes hurts student achievement.
So it was interesting to see McKinsey & Co., an elite consulting
firm, reframe the argument for buying education technology away from
computerized instruction to something more pedestrian: saving teachers
time. A January 2020 report by the firm estimated that between 20
and 40 percent of the 50 hours that a typical teacher currently works a
week could be saved through existing automation technology, often
enabled by artificial intelligence (AI). That adds up to 13 saved
hours a week, hours of freedom that could help relieve teacher burnout.
Those hours could also be reallocated so that teachers can do more of
what teachers do best: interact with students.
“Many of the attributes that make good teachers great are the very
things that AI or other technology fails to emulate: inspiring
students, building positive school and class climates, resolving
conflicts, creating connection and belonging, seeing the world from the
perspective of individual students, and mentoring and coaching
students,” the McKinsey authors wrote. “These things represent the
heart of a teacher’s work and cannot — and should not — be automated.”
The McKinsey authors suggest that existing technology can be used to
help teachers in several areas: planning lessons, assessing students,
grading homework, giving feedback and administrative paperwork. The
consultants aren’t suggesting that computers can replace any of these
tasks entirely but rather reduce the amount of time teachers have to
spend on them. For example, they estimate that lesson preparation could
be cut from almost 11 to six hours. They calculate that weekly grading
could be cut in half from six to three hours. And they say that two
hours a week of administrative paperwork could be trimmed.
The report is provocatively titled, “How artificial intelligence will
impact K-12 teachers,” though many of the recommendations are for
categories of software applications that don’t necessarily use
sophisticated AI algorithms at all, such as sites where teachers can
find curriculum materials posted by other teachers. I was curious to
learn what scientists who are involved in studying and developing AI in
education thought of McKinsey’s analysis and heard a range of praise,
skepticism and outright criticism.
A lot of automatic grading technology isn’t very good yet, AI experts
told me. “There’s stuff out there than you can use tomorrow but I also
think there’s still a lot to be done,” said Ryan Baker, a professor at
the University of Pennsylvania who studies how students learn from
educational software. Computers can easily grade math computations, he
said, but automated writing feedback or feedback for more complicated
math or science problems still needs to get better.
Another shortcoming with a lot of existing technology, Baker said, is
using the data that computerized systems generate for lesson planning.
If computers are grading homework or assessing what students know, the
systems need to convey results for each student in a way that’s useful
for teachers. “It’s a hard challenge,” he said. “There’s a lot to be
done in taking sophisticated AI models that I work with and translate
them into something that’s understandable to teachers and that they
trust.”
Often developers of educational software create dashboards for teachers
to decipher that sometimes add to their workloads instead of saving
them time. Or the feedback for teachers is very simplistic, such as, 56
percent of the class got a particular homework problem wrong. But
there’s no insight into how to help each student.
Stefania Druga, a doctoral student at the University of Washington, who
studies AI in education and who founded a coding project to teach
students how AI models work, argues that automated grading can have the
unintended consequence of breaking the feedback loop between teacher
and student. Often a student can trick a robograder and get the problem
right without understanding the underlying concept, she explained. Or
the student learns what metrics the automatic grader looks at and
“optimizes” for them. For example, a writing feedback program might
emphasize the use of the word “evidence” and other synonyms and give
high marks to incomprehensible essays that sprinkle those keywords
throughout. Though time consuming, having teachers actually read
student work directly, she says, is important for the learning process.
Some of the biggest time savings, according to McKinsey, could be in
using existing technology for lesson planning. But curriculum experts
who reviewed popular online curriculum resources found them to be
mediocre. McKinsey acknowledges that quality in ed tech is a problem.
Schools and teachers are pitched a “myriad of competing solutions,”
some of which “promise great things but deliver little,” the report
explains. McKinsey called for “neutral arbiters” to evaluate the
quality of software with “objective and rigorous performance data.”
The cynic in me was wondering if McKinsey is merely offering ed tech
companies new talking points to sell their existing wares. Instead of
boasting about how much they boost student performance, ed tech
marketers can tout how many teacher hours they save. But I was
intrigued with McKinsey’s suggestion to use AI more for the back
office. The consultants suggest that automation software could fill out
forms or suggest potential responses, maintain inventories of
materials, equipment, and products, and automatically order
replacements.
Andrew Berning, the president of the Renaissance Institute, a company
that sells back-office tech services to schools, told me that
McKinsey’s reframing is “spot on.” “The market has been too focused on
developing AI ‘teaching machines’ and not enough in the area where we
can really have an impact, such as facilitation, automation and
teachers support,” he said, via e-mail. His big growth area: tools for
schools to monitor their internet traffic to detect cyber threats, such
as phishing, fraud and ransomware.
That’s what schools need: more technology to protect them from the harm that the technology they’ve already bought is causing.
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