Transformational Funding Fuels Cutting-Edge Research to Personalize Learning
PITTSBURGH–(BUSINESS WIRE)–#nationalsciencefoundation—Carnegie Learning, a leader in artificial intelligence for K-12 education and formative assessment, announced today that it received a transformational grant from the National Science Foundation (NSF) to design educational research infrastructure to fast-track student outcomes. The $400,000 grant funds a five-year project to develop new approaches to automatically personalize instruction to students. It’s one of six NSF grants Carnegie Learning has received since 2004.
The research advances the science of learning and instruction, methods for analyzing complex educational data, and machine learning algorithms that use data to improve educational experiences. Now more than ever, using effective materials to help students whose learning progress was stymied during the pandemic is paramount. The nation’s report card clearly demonstrates a sense of urgency to close the learning gap in reading and math with curriculum that delivers results.
“What we know from doing this work for over 30 years is that when students feel a personal connection to the instructional material, they are significantly more likely to engage and learn,” said Carnegie Learning Chief Scientist Steve Ritter. “By personalizing the context of the problems, students tend to perform better academically, and their feelings about the subject matter, particularly in STEM topics, improves. The aim is to provide the conditions that optimize a student’s connection to the material, thereby igniting their interest and desire to learn.”
This project develops the Experiments as a Service Infrastructure (EASI), which lowers the barriers to conducting randomized experiments that compare alternative ways of designing digital learning experiences, as well as analyzing the data derived from the systems to rapidly change what future people receive. It does this by bringing together multidisciplinary researchers around the shared problem of testing ideas for improving and personalizing educational resources.
A collaborative effort with higher education partners Carnegie Mellon University, the University of Toronto and the University of Alabama, the work aligns diverse educational communities around the shared problem of enhancing and personalizing education. Through experimentation, the multidisciplinary research provides extensive support for collaboration and sharing of designs, data, analysis scripts and algorithms while fostering an online community to promote high-quality, innovative, impactful results.
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Contacts
Eden Bloss
Carnegie Learning
336-706-1372
ebloss@carnegielearning.com
