Perspective: Defined by Data
There is little denying that we live in a world defined by data. When historians view this era, the explosion of data and the ways in which it shapes our lives may turn out to be one of its most distinctive characteristics. The growth is staggering: the amount of worldwide data doubles every two years.
This data revolution is inexorably entering all aspects of our modern lives. New approaches to gathering and analyzing data define winning political candidates, generate new techniques for tracking criminals and drive decisions about responding to disease outbreaks. Data produced by our everyday actions inform everything from television programming to product development. Data and its proliferation touch our lives in countless ways, from viewing an online ad or considering the privacy implications of Internet traffic monitoring.
This data revolution has immense ramifications for education. The students we are preparing today will enter a world very different from the one in which we were educated. They will be thrust into a small world filled with big data, and will need to be able to succeed at careers whose titles don’t even exist today. They will need the knowledge to comprehend the math and science that drive these data and the skills to navigate oceans of information fluently. As this future becomes clearer, we are beginning to understand how we might prepare students for this new, data-rich age.
In many ways, however, the most important revolutions spurred by big data are already present. Today’s rapidly evolving technology and recent advances in research on teaching and learning usher in a new, deeply digital realm of education. While any use of data must also address concerns about protection and careful application, when taken in total, the entrance of data offers a wealth of opportunities within education: redefining the places where education occurs, the ways we understand student performance and the nature of the underlying pedagogy.
Places of learning
As technology continues to break down barriers, new opportunities for learning open up across time and space. With ubiquitous access to technology—from desktop computers to smartphones—learning can happen in places that were scarcely imaginable before. Divisions between formal and informal education fade away as we access learning on the go, providing new opportunities to understand how learning evolves in this fluid world.
Our Learning Everywhere initiative is beginning to examine this question by offering connected learning opportunities that complement and extend museum experiences into after school or at-home settings. Students can design an energy-efficient building in an after school program, then modify and test it at a museum-based design competition. Or they can begin an investigation in a museum and continue the experimentation with models and simulations they can access from home. By gathering in-depth data on the use of these materials, we will be able to see precisely how learning takes place across these environments.
Process of learning and design
Through the use of data and its applications via technology, we are able to gain new insight into processes and concepts. Understanding how students learn engineering and design skills is vital to knowing how to increase student interest in engineering. But these skills are difficult to characterize and even harder to quantify and measure. New technologies offer the opportunity to gather huge data sets, however, and bring forth a new dimension of understanding.
Our Energy3D software, developed by Charles Xie and Saeid Nourian, is a computer-aided design environment with powerful data-driven features. The software offers students a simple and engaging way to create and test energy-efficient house designs. At the same time, it generates detailed logs of the design process that unfolds with every mouse click. These logs are gold mines of unprecedented detail about how students undertake and learn the process of design. They have already uncovered many novel insights about student design patterns and gender-specific design processes. In a new project, we are building next-generation analysis tools to characterize the data from these design processes and extend the experiments to thousands of students at a time, a potential transformation of engineering education propelled by the data revolution.
The potential that data offer for understanding student learning is by no means limited to the process of engineering and design. Data hold great potential for assessing student learning, both assessment of content understanding and more complex assessment of the practices of science and engineering. By bolstering tools such as models and simulations with logging capabilities and carefully designing opportunities for learning and assessment, we can gain new views into student learning that can be much more informative than current, traditional assessments. With technology, we can peer over a student’s shoulder virtually and observe as she undertakes the process of scientific inquiry.
These capabilities offer the potential for designing performance assessments that truly capture the essence of these scientific practices. We are now working with some of the country’s leaders in content learning and assessment design to create the next generation of performance assessments, aligned with the Next Generation Science Standards. Big data is setting the stage for an entirely new paradigm of assessment. The multiple-choice test may one day join the overhead projector and mimeograph machine as a relic of a former era.
Teachers make implicit use of data all the time. They watch students, grade papers and ask questions that inform them about student thinking and understanding. These pedagogical methods are tried and true, but incomplete: student learning happens through many actions that are invisible, allowing many “teachable moments” to slip by unnoticed in the hidden fabric of daily learning. As we move toward new forms of learning made possible by digital technology, data offer increasing opportunities to identify and make use of these moments.
By capturing data about nascent student learning and providing those data to teachers as they make decisions about how to usher learning forward, the teaching experience evolves from a series of educated guesses to a process of informed decisions. Already, our software is collecting and providing near real-time data on student performance, carefully honing data sources to increase insight for teachers. Through judicious application of technology, we can suggest promising pedagogical paths for teachers—from helping them understand the thinking of their students mid-class to providing a detailed picture of the misconceptions their students harbor.
Possibilities for the future
With the rush of new data come huge and unforeseen opportunities. Many of these can be anticipated, but not yet fully envisioned. Mobile devices generate huge data sets that could be tapped to understand how learning evolves. Apple’s new iPhone contains an entire chip devoted to using motion data in unexpected ways, from sending information about your activity levels to health apps to remembering your location when it senses you parking your car. Other smartphones contain up to a dozen sensors, from gyroscopes to barometers to radio and magnetic field sensors.
With these devices, students worldwide now carry mature mobile laboratories in their pockets, generating data whose promise for learning remains almost entirely unrealized. Similarly, data about learning will evolve in new and unexpected ways as technology continues to proliferate in the classroom and beyond.
Chad Dorsey (email@example.com) is President of the Concord Consortium.