The Technology for Education’s Moonshot is Here
K-12 education is long overdue for its moonshot, that amazing technological breakthrough—like the actual lunar landing or the recent development of the self-driving car—that will take student learning to the next level and close the achievement and opportunity gaps once and for all.
Consider the self-driving car for a moment. Back in 2005, when the Defense Advanced Research Projects Agency (DARPA) offered cash for anyone who could create an autonomous ground vehicle capable of completing a certain course, the automotive industry didn’t take it too seriously. But a few visionary thinkers did, and we’re just a few years away from a major disruption in how human beings get around.
Sebastian Thrun, known by many as the father of self-driving cars, explained the implications of the technology in a wide-ranging interview with the San Francisco Chronicle:
“If transportation becomes a service, we will need many fewer cars and won’t need individual car insurance. Parking garages will be obsolete; trauma surgeons and tort lawyers will have less work. City design will be different; people can live closer together and waste less land. It will be uniformly better for the planet.”
Thrun asserts that self-driving cars are now safer than human-controlled cars, and the reason is data at scale. “When a human driver makes a mistake, he or she learns but nobody else learns,” Thrun says. “When a self-driving car makes a mistake, all the other cars learn from it as well as the unborn cars, future cars. The rate of progress is much faster.
What If We Could Improve Education in a Similar Way?
Imagine if we could harness Big Data to enable machines to learn the way students do. It would radically change the way we educate our children. Just think of the possibilities if we could leverage multiple measures associated with teaching and learning—including learning styles, career and college interests, dispositions, academic skills, and content knowledge—to create truly individualized success paths. And consider the impact it would have on education if all remaining teachers who use lectures as their primary instructional strategy (sage on the stage) could move, thanks to the ubiquity of information on computers and mobile devices, to a new role that facilitates learning and critical thinking.
Here are just some of the things we might see if we put our minds to implementing machine learning technology in education at scale:
THE TRADITIONAL CLASSROOM COULD BECOME A THING OF THE PAST. Information is everywhere, and machine learning programs could potentially support teachers with differentiated tier one instruction for every student through various modalities, both online and in the classroom. Students may not even have to report to a physical building five days a week.
THE WAY TEACHERS AND STUDENTS INTERACT COULD SHIFT DRAMATICALLY. As more students learn core curricula through machine learning platforms, teachers would be empowered to focus on individual students, pinpointing gaps and enrichment areas and creating safe and supportive learning environments. Teachers would become more like coaches and mentors, called upon as needed to proactively support all learners.
THE TERMS “SCHOOL WEEK” AND “SCHOOL YEAR” MIGHT NEVER BE USED. With the possibility of students and teachers becoming less tethered from physical buildings, learning can become more virtualized. Students could choose multiple college and career pathways and take advantage of various locations to support relevant learning. Course completion and graduation dates could become more fluid, and students could take advantage of opportunities to travel or gain work experience in new and exciting ways.
STUDENTS COULD BECOME EVEN STRONGER ADVOCATES FOR THEIR OWN LEARNING. With greater freedom and individualized guidance from teachers they truly respect and admire, students could explore their interests and learn to appreciate subjects they might not have been exposed to previously.
The Time to Experiment with Machine Learning is Now
Technology is changing just about every other industry. Our job as educators is to prepare students for the world they’ll be graduating into, so it’s imperative that we learn from societal trends like the gig economy, data analysis, machine learning, and artificial intelligence to continue empowering teachers and ensuring that no students fall through the cracks.
Machine learning, especially, is proving to be a powerful tool to support educators in the transformation we’re about to undertake. We can see the day when we can use data to help teachers create a technological system that accommodates different learning styles, supports educational deficiencies, and crafts individualized success paths that close the achievement gap.
This article was co-authored with Chris Walker. If you would you like to learn more about machine learning, artificial intelligence, and its impact on education, please download our latest eBook:
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Machine Learning could be a very good tool for students to learn but learners are of different levels, there will still be the need of time for others for a teacher who will be assisting. It’s totally different when learning is just done through machines alone without someone guiding them if confusion comes in. I agree, however, that there is more to be learned by learners when they actually actually learn it through manipulation but I still suggest the need of the teacher on one’s side.