robot teacher

In the 1960s TV show “The Jetsons,” youngest son Elroy heads off to school with a robot teacher. While other parts of the futuristic Jetson world have come to bear — like video conferencing — robot teachers still seem like something out of a sci-fi novel.

In recent years, they’ve crept onto the education scene, popping up in American classrooms as toy-like teaching assistants and in Japan as remote-controlled novelties.

Robots aren’t yet ready to teach our children alone, but they’re getting closer. Here’s the thing: Big data has arrived in the classroom, and it’s inching into the teachers’ role. Analytics programs can study how students are performing and tailor instruction for them in a personal way that they can’t get in a classroom of 30 or a lecture hall of 500.

One edtech company, Desire2Learn, has cottoned onto this trend. It launched in 1999 as an platform for schools to hold classes online, like its competitor Blackboard. But after raising its first ever funding round in 2012 — a whopping $80 million Series A — it started gobbling up smaller data analytics and communication companies like a shark.

In January, it acquired Degree Compass, which is a software that helps students pick classes by using their transcript data to predict how well they will do. A few months later it bought Wiggio, which is Yammer for schools, giving a space for student organizations to collaborate on documents, chat, and share calendars.

Desire2Learn’s acquisitions hint at the company’s larger strategy: to become a triple threat. By owning the communication, learning, and data analytics platforms, the company can be a one-stop shop for online learning. Basically, Desire2Learn is trekking down the path towards ed-tech Beyoncedom.

Now, a few months later Desire2Learn has announced its latest grab: Knowillage Systems, Inc. Knowillage makes LeaP, an artificial intelligence that can sit on top of a learning management system. LeaP tracks individual K-12 grade student’s performance through online assignments and quizzes, and grows smarter with everything it sees. It then tailors the student’s lessons to them, offering different types of readings or practice problems if the student is struggling.

Basically, it’s a robot teacher, albeit one that operates through a computer.

“When I went to school I didn’t get any attention from the teacher,” Desire2Learn’s VP of Marketing Jeff McDowell says. “The teacher helped the top three best students and the bottom three students. I was a solid B student and I never got any attention from the teacher because I was right in the middle.” Desire2Learn believes that LeaP solves this problem.

Teachers still teach the lessons during class, but students do all their assignments and projects through the online management system. Everyone gets a personalized homework path, courtesy of Artificial Intelligence. “Adaptive learning allows every teacher to teach every student in the class…because they have this tool and don’t have to analyze the habits of every student,” McDowell says.

It’s a little sad that our educational system is so strapped that we need machines to give students individualized care.

But wishing we had more teachers doesn’t make it so, and in theory LeaP would help mitigate the problem of the overcrowded classroom. In theory, it would help every student progress at their own pace, teaching different aspects of the concepts they struggle with and moving quickly through the ones they don’t. In theory.

In reality I wonder how this would actually play out. Perhaps the students that struggle the most would wind up with really long homework sessions because the program would make them go through a bunch of different lessons till they understood it. Said students may or may not bother sitting through the LMS lessons.

At what point does the teacher step in to give tailored instruction to the student? If the LeaP system truly does what Desire2Learn claims it does, then teachers aren’t needed. The program will pull different ways of explaining the concept — drawing on videos, different textbooks, a variety of problem sets — till the student understands.

Kinesthetic learners are still screwed, as always. It’s the forgotten bastard child of the learning styles. Even if LeaP recognizes that a student is a kinesthetic learner, the Artificial Intelligence is still bound to a computer. It can’t send the child out into the world to use their hands to learn a concept. There’s a bias for auditory and visual learners.

Despite potential problems, data analytics programs like LeaP have gotten a hell of a lot closer to the Jetson’s robot teacher idea than the actual robots currently on the market. Machine learning systems may be the ones to rival the teacher’s touch.

[Image via Smithsonian Magazine]