Today, the Chan Zuckerberg Initiative (CZI) announced the expansion of its work in artificial intelligence to help ensure education tools that leverage AI are grounded in research and best practices for teaching and learning. CZI launched two new AI developer tools for education designed to empower developers to integrate high-quality education content seamlessly into their platforms. Knowledge Graph helps developers enhance AI system inputs by aligning them with learning science research, state academic standards, and curricula, while Evaluators help developers assess AI system outputs to ensure they meet the accuracy, rigor, and quality essential for teaching and learning.
Alongside these new private beta tools, CZI also announced the appointment of a new advisory board that includes experts in schools, data privacy, artificial intelligence, education technology, and learning science.
“With the rapid growth of artificial intelligence, improving the quality of outputs from large language models is increasingly important–especially where student learning and outcomes are involved,” said CZI’s Head of Education, Sandra Liu Huang. “CZI is partnering with education, research, and technology experts to help ensure artificial intelligence tools are high quality and support educator efforts to unlock the full potential of every student.”
“In a nutshell, we’re really focused on both enhancing the AI system inputs and assessing those system outputs by being really intentional in our work with edtech developers.”
–CZI spokesperson
These new tools are part of CZI’s efforts to help schools address everyday challenges by co-building tools with educators and empowering technology developers with resources to build high-quality, research-backed AI solutions for education.
Core AI Resources for Education Developers
Through Knowledge Graph and Evaluators, CZI is using its learning science expertise and technical strengths to enable edtech developers to incorporate rigorous, high-quality educational content into their platforms and improve the overall infrastructure of AI-driven education products.
To help developers improve the quality of their inputs, Knowledge Graph will launch with two key interconnected datasets: a high-quality, openly licensed core math curriculum in partnership with Illustrative Math, and academic standards from all 50 states in partnership with 1EdTech.
For Evaluators, CZI also worked with academic experts to help edtech developers support teachers in closing the gap in student reading skills. They leveraged a Rubric for Literature from Student Achievement Partners to evaluate the complexity of AI-generated text outputs. They also worked with English Language Arts experts from The Achievement Network and Gradient Learning to assess the dataset.
“One of the challenges right now is that AI outputs might look right but there could be inaccuracies with them. And so we think one of the 1st steps in making Gen. AI more pedagogically aligned–more useful in the classroom–is to actually measure the quality that it’s returning.”
–CZI spokesperson
The private beta phase includes initial collaboration with Playlab and Diffit, who are piloting the tools to improve their AI-based educational offerings.
Education Advisory Board
CZI is also announcing its Education Advisory Board, bringing together a diverse group of experts to help guide efforts in advancing the use of AI to transform learning and improve educational outcomes.
The Advisory Board members are:
Dan Carroll
Former Chief Product Officer and co-founder of Clever
Richard Culatta
CEO of ISTE+ASCD
Alina von Davier
Chief of Assessment at Duolingo, CEO and Founder of EdAstra Tech, and VC Partner at the LearnLaunch Accelerator
Louis Gomez
Professor of Education at UCLA and a member of the National Academy of Education
Babak Mostaghimi
Founding Partner of LearnerStudio
Amelia Vance
Amelia Vance, Founder and President of the Public Interest Privacy Center (PIPC)
“We know more than ever about how kids actually learn. And so that’s sort of the whole point–to bridge the learning science and to get it into this new technology.”
“One of the challenges right now is that AI outputs might look right but there could be inaccuracies with them. And so we think one of the 1st steps in making Gen. AI more pedagogically aligned–more useful in the classroom–is to actually measure the quality that it’s returning.”
“In a nutshell, we’re really focused on both enhancing the AI system inputs and assessing those system outputs by being really intentional in our work with edtech developers.”
This post is exclusively published on eduexpertisehub.com
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