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Philly Student (Photo by Vikki Sloviter, courtesy KIPP Philadelphia Schools)

The truth, as many American teachers know firsthand, is that low-income children can be harder to educate than children from more-comfortable backgrounds. Educators often struggle to motivate them, to calm them down, to connect with them. This doesn’t mean they’re impossible to teach, of course; plenty of kids who grow up in poverty are thriving in the classroom. But two decades of national attention have done little or nothing to close the achievement gap between poor students and their better-off peers.

In recent years, in response to this growing crisis, a new idea (or perhaps a very old one) has arisen in the education world: Character matters. Researchers concerned with academic-achievement gaps have begun to study, with increasing interest and enthusiasm, a set of personal qualities—often referred to as noncognitive skills, or character strengths—that include resilience, conscientiousness, optimism, self-control, and grit. These capacities generally aren’t captured by our ubiquitous standardized tests, but they seem to make a big difference in the academic success of children, especially low-income children.

But here’s the problem: For all our talk about noncognitive skills, nobody has yet found a reliable way to teach kids to be grittier or more resilient. And it has become clear, at the same time, that the educators who are best able to engender noncognitive abilities in their students often do so without really “teaching” these capacities the way one might teach math or reading—indeed, they often do so without ever saying a word about them in the classroom. This paradox has raised a pressing question for a new generation of researchers: Is the teaching paradigm the right one to use when it comes to helping young people develop noncognitive capacities?

The problem is that when disadvantaged children run into trouble in school, either academically or behaviorally, most schools respond by imposing more control on them, not less. This diminishes their fragile sense of autonomy. As these students fall behind their peers academically, they feel less and less competent. And if their relationships with their teachers are wary or even contentious, they are less likely to experience the kind of relatedness that Deci and Ryan, professors at the University of Rochester, describe as being so powerfully motivating for young people in the classroom. Once students reach that point, no collection of material incentives or punishments is going to motivate them, at least not in a deep or sustained way.

All of which brings us back to the question of how to help children develop those mysterious noncognitive capacities. If we want students to act in ways that will maximize their future opportunities—-to persevere through challenges, to delay gratification, to control their impulses—-we need to consider what might motivate them to take those difficult steps. What Deci and Ryan’s research suggests is that students will be more likely to display these positive academic habits when they are in an environment where they feel a sense of belonging, independence, and growth—or, to use Deci and Ryan’s language, where they experience relatedness, autonomy, and competence.

From article by Paul Tough

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Lea's Learning Analytics Blog

Learning analytics, educational data mining, formative assessment - all recent buzz words in educational research. In principle, the idea is to find theoretical frameworks, models, procedures, and smart tools to collect, aggregate, analyze, reason on and visualize large scale educational data. LEA’s BOX is a research and development project funded by the European Commission. The project aims at (a) making educational assessment and appraisal more goal-oriented, proactive, and beneficial for students, and (b) at enabling formative support of teachers and other educational stakeholders on a solid basis of a wide range of information about learners. That means, LEA’s BOX is a learning analytics toolbox that is intended to enable educators to perform competence-centered, multi-source learning analytics. More info at http://www.leas-box.eu!


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