Benevolent friction—the concept of being soft on people but hard on ideas—is an approach to constructive engagement and innovation that I’ve long embraced and brought to DreamBox Learning over seven years ago. We find that benevolent friction is a catalyst for thoughtful and candid dialogue that leads to creative ideation. It’s in our DNA and has made us stronger as individual contributors, team members, and devoted shepherds of our customers’ experiences.
In the spirit of benevolent friction, I’d like to share a few thoughts with our colleagues working at the intersection of education and technology as I reflect on 2017 and look ahead to the new year.
Surprises from 2017
As 2017 dawned, I held hope that more instructional technology solution providers would take up the mantle and publish third-party efficacy studies. I have to admit some disappointment that as this year comes to a close, most edtech companies have not produced independent efficacy studies, thus further perpetuating the lack of research on learning technologies.
One bright spot was when Johns Hopkins University launched EvidenceForESSA.org to identify programs that meet the evidence standards in the Every Student Succeeds Act. Yet it was sobering to find only two elementary math software programs with randomized, controlled trial studies from the past six years. With all the math programs and apps on the market, how is it possible there aren’t more?
Perhaps what we need is for education leaders to demand proof that the technologies and digital tools they’re using are positively impacting student achievement.
But this brings me to another revelation from 2017: Many districts aren’t screening for efficacy when adopting learning technology resources.
Earlier this year, 10 extensive reports were published for the EdTech Efficacy Research Academic Symposium, facilitated by the Jefferson Education Accelerator. The reports found that prior to adopting edtech products, K-12 school leaders usually don’t require independent research showing positive impact on student learning. In fact, the most common metric used to determine if an edtech product is “working” is simply how often it is used. School leaders assume that teacher usage equates to efficacy and student learning.
If we are going to design schools and curricula that ensure success for all students, school leaders and teachers must demand that instructional technology tools demonstrate third-party proof of efficacy. Unfortunately, until educators require it as a non-negotiable part of the adoption process, companies will have few incentives to produce such research.
Looking to 2018
We have long known that we need to improve student achievement in math. Students who possess competency in mathematics do better in school and in life. They emerge as more confident learners, family members, professionals, and community leaders. Yet far too many students are not reaching their potential in this subject that is critical to learning, citizenship, innovation, and our shared future.
This year, a major challenge we heard from district administrators is that K-8 teachers, especially at the elementary level, lack sufficient mathematical content knowledge for teaching. Because of this, I expect to see increased emphasis on mathematics-related professional development in 2018. Through a research grant from the Bill & Melinda Gates Foundation, we found that when teachers accessed on-demand support to learn more about math content, their students saw much higher math growth than their peers.
We also heard that learning guardians of all types—coaches, teachers, tutors, and parents—need more actionable insights about how children learn. If we hope to positively and sustainably impact student growth and success, we need to move beyond merely providing more data to delivering meaningful and timely information about how each student is progressing. We need to move away from a DRIP approach—data rich and information poor—to an environment where teachers are empowered to adapt their instructional approaches.
Next year, I also expect further irrational exuberance about the benefits of artificial intelligence, machine learning, and automation in education. While these developments may hold longer-term promise for learning, it’s important to find the right applications of these powerful and potentially transformational technologies as they relate to the science of learning.
Artificial intelligence is not going to be education’s “silver bullet” any more than radio, TV, the internet or the iPad have been. We care more about what each student is thinking than about what we are training artificial intelligence to think. Kids have incredible ideas, and any intelligent education technology needs to be informed by classroom teachers who know how to cultivate deep student thinking at every stage of learning.
Those of us working at the intersection of education and technology must hold ourselves to the highest standards, which sometimes requires engaging in benevolent friction that challenges our ideas and assumptions. To innovate is to question; to question is to learn.
Let’s continue to test—and challenge—new hypotheses about how learning happens optimally so that we may intentionally reshape outcomes for all students, regardless of where they live and who they are.