The race is on to provide students with personalized learning experiences based on their individual emotions, cognitive processes, 鈥渕indsets,鈥� and character and personality traits.
Academic researchers, for example, are busy developing computerized tutoring systems that gather information on students鈥� facial expressions, heart rate, posture, pupil dilation, and more. Those data are then analyzed for signs of student engagement, boredom, or confusion, leading a computer avatar to respond with encouragement, empathy, or maybe a helpful hint.
鈥淭he idea is that emotions have a powerful influence on cognition,鈥� said Sidney D鈥橫ello, an assistant professor of computer science and psychology at the University of Notre Dame, in Indiana. The increasing power and affordability of eye-tracking, speech-recognition, and other technologies have made it possible for researchers to investigate those connections more widely and deeply, he said.
鈥淭en years ago, there were things you could do in a lab that you couldn鈥檛 do in the messiness of the real world,鈥� D鈥橫ello said. 鈥淣ow, you can get a reasonable proxy of a student鈥檚 heart rate from a webcam.鈥�
Still, widely available classroom applications of such work might be a decade or more away.
More prevalent now are digital resources that seek to measure and support the development and self-identification of such 鈥渘oncognitive competencies鈥� as self-management, perseverance, and a 鈥済rowth mindset鈥� that recognizes skills can improve with effort. The U.S. Department of Education鈥檚 new National Education Technology Plan, for example, officially calls for more work to develop such tools.
Organizations such as the MIND Research Institute are at the forefront of those initiatives. The group鈥檚 widely used educational math software, called ST Math, provides students with learning exercises that aim to build not only math skills, but also curiosity, perseverance, and a mindset that mistakes are powerful learning opportunities.
Ideally, the software would be able to recognize each student鈥檚 strengths and weaknesses across each of those domains, then provide a steady stream of customized problems based in part on such factors as a student鈥檚 capacity to keep trying to solve new challenges, said Matthew Peterson, the group鈥檚 co-founder and CEO.
For now, though, the MIND Research Institute gauges mindset and character traits primarily at the aggregate level, based on laboratory research and analysis of user data about the 鈥渢ypical鈥� 2nd grader.
Other vendors, meanwhile, are wrestling with the opposite challenge. Princeton, N.J.-based startup Mindprint Learning, for example, uses a battery of online cognitive assessments to provide highly customized profiles of how individual students learn, including everything from verbal reasoning to spatial perception. But the company, like others in the field, is still trying to find user-friendly ways for schools and parents to turn the resulting information into compelling learning experiences that are customized for each individual student鈥檚 cognitive strengths and weaknesses.
Privacy concerns and continuing debate about the appropriate use of such technologies for schools in addressing character, mindset, and affect will help shape what happens next.
But district leaders such as Brien Hodges, the executive director of K-12 schools for the 28,000-student Colorado Springs School District 11 are eager for new resources to help personalize student learning, based on more than just academic ability.
鈥淎 digital tool that understands what it is the teacher wants all students to know, and knows how each student thinks and learns, and gives the teacher ideas on how to present the material differently would be gigantic,鈥� Hodges said.
