Math-a-manics

As she headed into fifth grade, she assumed she was in for more of the same—lectures, memorization, and busy work. Sergio Juárez Correa was used to teaching that kind of class. For five years, he had stood in front of students and worked his way through the government-mandated curriculum. It was mind-numbingly boring for him and the students, and he’d come to the conclusion that it was a waste of time. Test scores were poor, and even the students who did well weren’t truly engaged.

Juárez Correa didn’t know it yet, but he had happened on an emerging educational philosophy, one that applies the logic of the digital age to the classroom. That logic is inexorable: Access to a world of infinite information has changed how we communicate, process information, and think. Decentralized systems have proven to be more productive and agile than rigid, top-down ones. Innovation, creativity, and independent thinking are increasingly crucial to the global economy. And yet the dominant model of public education is still fundamentally rooted in the industrial revolution that spawned it, when workplaces valued punctuality, regularity, attention, and silence above all else.

knowledge isn’t a commodity that’s delivered from teacher to student but something that emerges from the students’ own curiosity-fueled exploration. Teachers provide prompts, not answers, and then they step aside so students can teach themselves and one another. They are creating ways for children to discover their passion—and uncovering a generation of geniuses in the process.

This approach can even be useful for applications that are not, strictly speaking, compressed sensing problems, such as the Netflix prize.

Given the enormous popularity of Netflix, even an incremental improvement in the predictive algorithm results in a substantial boost to the company’s bottom line. Recht found that he could accurately predict which movies customers might be interested in purchasing, provided he saw enough products per person. Between 25 and 100 products were sufficient to complete the matrix.

It wasn’t the size of the data set that was daunting; by big data standards, the size was quite manageable. It was the sheer complexity and lack of formal structure that posed a problem.

If you had asked them, most of my high school teachers would have called me an unmotivated student or said that I lacked discipline and didn't take learning seriously. And yet, that abandoned storage bin told another story: with the aid of my calculator, I'd crafted narratives, drawn storyboards, visualized foreign and familiar environments and coded them into existence. I'd learned two programming languages and developed an online network of support from experienced programmers. I'd honed heuristics for research and discovered workarounds when I ran into obstacles. I'd found outlets to share my creations and used feedback from others to revise and refine my work. The TI-83 Plus had helped me cultivate many of the overt and discrete habits of mind necessary for autonomous, self-directed learning. And even more, it did this without resorting to grades, rewards, or other extrinsic motivators that schools often use to coerce student engagement.

I've now begun to see Texas Instruments graphing calculators as unique among educational technologies in that they enable learning that is couched in discovery more than formal teaching.

take the notion of "correctness." School typically assumes that answers fall neatly into categories of "right" and "wrong." As a conventional tool for computing "right" answers, calculators often legitimize this idea; the calculator solves problems, gives answers. But once an endorsed, conventional calculator becomes a subversive, programmable computer it destabilizes this polarity. Programming undermines the distinction between "right" and "wrong" by emphasizing the fluidity between the two. In programming, there is no "right" answer. Sure, a program might not compile or run, but making it offers multiple pathways to success, many of which are only discovered through a series of generative failures. Programming does not reify "rightness;" instead, it orients the programmer toward intentional reading, debugging, and refining of language to ensure clarity. This is a form of learning that privileges the process of discovery over the interventions of formal teaching. It can fuel an intrinsic desire to pursue similar learning experiences, but even more, it gradually transforms the outlook of the student

Corrypt, upon proper exploration, revealed itself to be a brilliantly designed puzzle game, unforgiving and unwilling to accommodate players who refuse to give it their full attention. Peel back one layer, and it reveals another more surprising one.

After completing a degree in math and computer science at the University of Auckland, Brough moved to London and began working towards a Ph.D. He landed a decent-paying programming job while continuing his scholastic work, but continued making games, including the beautiful, abstract strategy game Vertex Dispenser, which even Brough admits may have been too esoteric. It combined elements of shooters and real-time strategy games with a complex puzzle system, and many players felt overwhelmed. “I just could not get my head around those concepts at the same time,” said one.

Well-designed games, he believes, can teach people how to do some things better. By simulating challenging situations, games can teach us about “managing unexpected situations… making good decisions, thinking about the costs of our actions and dealing with the consequences,” he says.

non-­scientist gamers developed more-­complex proteins than biochemists did

As harder concepts are introduced, students who need more time on a level get additional problems; those who understand it move on.

93 percent of K–12 students successfully mastered concepts after only 90 minutes of gameplay, and they didn’t want to stop

That’s because the American system of teaching these subjects is broken. For all the reform campaigns over the years, most schools continue to teach math and science in an off-putting way that appeals only to the most fervent students.

The system is alienating and is leaving behind millions of other students, almost all of whom could benefit from real-world problem solving rather than traditional drills.

the most important factor that predicted math success in middle school and upward was an understanding of what numbers are before entering the first grade. Having “number system knowledge” in kindergarten or earlier — grasping that a numeral represents a quantity, and understanding the relationships among numbers — was a more important factor in math success by seventh grade than intelligence, race or income.

used properly, testing as part of an educational routine provides an important tool not just to measure learning, but to promote it.

Various kinds of testing, though, when used appropriately, encourage students to practice the valuable skill of retrieving and using knowledge.

tests serve students best when they’re integrated into the regular business of learning and the stakes are not make-or-break, as in standardized testing.

There are three formal AIMS undertakings: a master’s degree program in Mathematical Sciences, research, and teacher training. The master’s program offers free tuition to accepted students and trains them in both general principles – problem formulation, the scientific method, communication – and cutting-edge math in subjects including computer science, biomathematics, and financial mathematics. Research will allow for international collaborations and advanced student training.

Traditionally, classrooms were led by an authoritative teacher who disseminated information to silent students, but Zomahoun hopes to turn that paradigm on its head. “We train people who can challenge the status quo,” he explains, “not just people who learn from books, listen to lectures, and just repeat it.” Rather, he hopes to instill qualities like “critical thinking, independent thinking, and problem solving” in order to prepare students for real-world problems.

By discovering hidden mathematical patterns and regularities in nature that we call equations of physics, we have gotten progressively better at predicting things — from tomorrow’s weather to tomorrow’s technology. The planet Neptune, the radio wave and the Higgs boson were all predicted mathematically before they were observed.

“I’m interested in seeing what design principles nature uses,” Dr. Lalvani said. “Math, perhaps; maybe physics, whatever. The whole D’Arcy Thompson-type stuff.” The biologist D’Arcy Wentworth Thompson’s book “On Growth and Form,” published in the early 20th century, was a seminal work on the subject of patterns in nature. Thompson, a Scotsman, argued that growth and the structures that resulted were governed by physical principles and could often be described in mathematical terms. He saw examples throughout nature — in the spiral shell of a nautilus, the branching veins on an insect wing and the scales of a pine cone, to name just a few.