Why Education Needs a “Precise” Approach

Picture a dozen students gathered around a piano for a lesson. One sits at the keys, receiving instruction from the teacher. For the rest who stand and watch, it’s mostly irrelevant—a waste of their time and highly demotivating. That’s why you never see group piano lessons.

For too long and for too many, however, K-12 education has resembled a group piano lesson. Information that’s delivered in a group setting isn’t meaningful and, come test time, students cram as much as they can memorize into short-term memory. The amount they retain long term is often minimal, creating knowledge deficits and leaving holes that can lead to incompetence.

A better approach, perfected through 20 years of research and development, is applying personalized, adaptive learning techniques that resemble many of the characteristics of a one-on-one tutorial. New, advanced learning technologies, if combined with teacher-student interactions that focus more on what each learner needs, can fundamentally improve how precisely we can deliver individualized instruction.


What Will You Learn in the Next Five Minutes?

Humans live one-dimensionally, as time moves forward. Minute to minute, we can only do a limited number of things. When students are trying to learn something new, the more precise instruction is in the next five minutes, the more effective it is. That doesn’t mean memorizing by rote; rather, it means making the most of those five minutes with individualized instruction and providing meaningful practice in solving problems. It’s all about precision.

Precision education is highly individualized, with adaptive systems that draw on our knowledge of how the brain functions. The system adapts to the learner—not the other way around. Merely having a computer model that uses statistics to predict how students will perform—where they will likely struggle, what they will probably need to review to improve retention—does not meet the needs of most students. Years ago, as an anatomy instructor at the University of Copenhagen, I thought I could predict where the students would be challenged. Quickly, I discovered such assumptions were bound to be incorrect: learning needs are as diverse as the students themselves.

Another lesson learned from medical school was that students struggle to learn everything they needed to know. From K-12 onward, there is never enough time to learn things fast enough. Given our human nature, we tend to practice what we already know, getting a feel-good experience of a right answer, but spend too little time on what we don’t know. Add to that the crammed information that doesn’t stick long term, and there can be serious gaps in what we need to know to perform competently. These gaps can become glaringly evident when we’re under pressure.

Research into medical errors found that even skilled doctors and nurses had gaps in their knowledge that put patients in danger. In the US, medical errors are the third leading cause of death after heart disease and cancer. According to the Institute of Medicine, medical errors result in costs (including for additional care necessitated by the errors) that have been estimated at between $17 billion and $29 billion per year. When medical situations were recreated using simulators, doctors were shocked to encounter that, when under pressure in critical situations, they often lacked the knowledge of what to do. These findings were not meant to criticize clinicians who had practiced competently for years; rather, the results shed light on the time-starved medical students who were forced to cram for exams and didn’t retain knowledge that’s infrequently used. To prevent errors, these medical professionals need precision education models to relearn and retain not just knowledge, but also skills and attitudes.

The Humility of a Precision Approach

Developing learning models requires a great deal of humility. Educators cannot assume they know how to address each learner’s needs—that “most” or “average” is a proxy for “all.” Worse, as Todd Rose pointed out in The End of Average, the basic idea of an “average” student is fatally flawed. The biggest challenge for many educators is acknowledging the vast diversity in the way people learn. Precision education starts with the premise of meeting an individual’s needs. It brings together research, technology, and education policies to ensure that all students benefit from a more effective approach.

Importantly, precision education does not seek to replace teachers. Rather, it augments their efforts, particularly in what they do best—engaging and motivating students. No machine can (yet) replicate the emotional intelligence of the teacher-student dynamic. But computer-based, adaptive learning technology can amplify teachers’ efforts to make the learning experience more meaningful and productive.

Much can be learned from an analogous approach, precision medicine, which brings together research, technology, and public policy to empower patients, researchers, and medical providers to develop individualized care. As a recent White House report states, precision medicine has led to new discoveries and treatments tailored to a person’s genetic makeup or, in the case of certain cancers, the genetic profile of an individual’s tumor. Precision medicine moves beyond medical treatments that are designed for the “average patient,” which may be very effective for some, but not for others. Precision, not statistical averages, now leads to greater effectiveness in medicine.

In the same way, precision education moves beyond what the “average student” may require, to focus on each learner and his or her diverse needs. The latest generations of technology-augmented education bring great potential to this area.

An Educational Journey

Adopting a precision education approach involves an educational journey for teachers, students, and policymakers. While precision education is still in its infancy, these professionals face the tough decision of choosing which models to use. During this initial phase, there will be models and technologies of varying quality and effectiveness—some of them little more than decoys that divert attention away from what works. Some may even be dangerous, doing more to derail learning than to enhance it (as I will address in a later post).

To understand the potential of precision education, educators and policymakers must commit to becoming more informed about these models as they take baby steps towards systematic implementation. At the same time, they must recognize that precision education is a scientific approach, grounded in hard data about what works and what doesn’t. As powerful as precision education is, we can’t expect it to solve all problems or be effective if it is applied in the wrong way.

Precision education exists within the broader ecosystem of education. In addition to the models themselves, precision education should use analytics to track other factors that impede student learning; for example, why students don’t show up for class or commit to learning. More than flagging these absences, analytics can help identify what’s needed to get these students to class and keep them engaged and motivated. Even more important, advanced analytics can help focus teachers’ attention with greater precision on those learners who need the teachers the most. Professor John Hattie has performed great research into 138 factors, synthesized from more than 800 meta-studies, that affect student achievement.

By identifying behavior patterns and the diverse needs of learners, precision education will become a symbiosis of teacher and technology. The result will be a revolution in education.