RFI Responses on Opportunities to Support Breakthrough Innovations in K-12 Education
Kumar Garg
RFI Responses on Opportunities to Support Breakthrough Innovations in K-12 Education
In July, with support from the Walton Family Foundation, we issued a Request for Information, on the most promising areas where a coordinated research program could drive breakthroughs in education in the United States. We received responses from 350+ scientists, technologists, and innovators, which we summarize below.
The key takeaway: Given recent improvements in the quality, affordability, and usability of technologies like AI, computer vision, and AR/VR, we can reimagine a more personalized, research-driven K-12 experience—one better able to meet diverse learning needs and set students up for success both in school and in life. From chatbots for individual coaching to immersive mixed reality solutions to adaptive technologies supporting culturally responsive pedagogy, we have an opportunity to leverage new technologies to tackle pressing needs across literacy education, STEM instruction, and preparing students for the workforce.
Driving this opportunity will require partnerships between technical visionaries, and those ready to support them. Renaissance Philanthropy is committed to driving such partnerships across philanthropy, government, and markets. Please reach out to levi@renphil.org with your ideas and suggestions on ways we could collaborate.
Unlocking Literacy Potential: Advancing Success in Reading and Writing
The Need
The data is clear and striking: reading and writing skills have declined, with recent National Assessment of Educational Progress scores showing 4th and 8th graders performing on par with students in the 1990s. A third of students assessed in 2022 were unable to read at the “basic” achievement level, which involves reading simple sentences like “the cat sat on the mat.” With limited time to sift through research, teachers need support and data to connect with their students and focus on interventions that work. Learners need frequent, personalized feedback to guide their growth.
Opportunities
AI tools could provide educators with vital insights into the learning process and match students with real-time feedback and support.
Individualized coaching support. Large language models, conversational agents, and intelligent tutoring systems can tailor content to student skills and interests. New tools can also streamline the feedback process, enabling more educators to do data-driven, research-informed teaching. Key challenges will be to make adjustments to prevent hallucinations and reduce bias so that algorithms work effectively and fairly.
Assessment and data collection. Eye-tracking, automated speech recognition, and brain-imaging capabilities can hone our measures of reading comprehension and fluency. These approaches promise to boost screenings of pre-reading skills, language development, and literacy challenges, while providing clearer insights into how reading skills develop. For example, instead of being tested only one or two times a year, every student with a speech disorder might be able to read into a phone and immediately get referred to a speech pathologist. Key challenges will be to safeguard student data and smoothly integrate tools into the classroom.
Empowering Educators: Innovations in Instructional Support
The Need
A thriving education system needs teachers who are fully supported to deliver high-quality instruction. Unfortunately, burn-out rates are on the rise and teacher retention is a major challenge, with 8% of public school teachers exiting the profession from 2020 to 2022. We need solutions for instructional support and development and to help teachers with demanding schedules and administrative workloads.
Opportunities
Advances in AI and audio and video recognition could help educators access high-quality professional development, receive real-time data-driven support, and better manage their administrative workload.
Real-time instructional improvement. New tools, powered by advances in AI and audio and video recognition, can offer just-in-time suggestions and bite-sized research to help educators improve their teaching.These innovations could also help boost the implementation of equitable practices in the classroom.
Automated administrative support. New tools can also automate administrative tasks and data collection, enabling educators to focus on high-quality instructional time and draw on ever-larger pools of information to design classroom interventions. Examples of use cases include streamlining grading, enhancing lesson planning, and facilitating the management of assessment and other student data.
Discover an example of an AI-driven instructional support tool designed to streamline assessment and learning data collection | Sourced from the Tools Competition, one of the initiatives of Renaissance Philanthropy’s AI and Education vertical
Career-Connected Learning
The Need
A growing number of employers are using skills-based hiring, which evaluates individuals’ abilities and competencies rather than their education and direct experience. Unfortunately, today’s students struggle to connect school to the real world, and studies show evidence of increasing academic disengagement.
Opportunities
Innovations are reimagining high school learning, bringing students increased opportunities to build the skills and networks they need for career success.
Personalized skills mapping and career guidance. New AI tools could provide personalized guidance to learners on pathways to develop skills and specific workforce opportunities. Examples of specific use cases include automated skills assessments, digital credentialing tools that document knowledge cultivated outside of the classroom, and tools to match learners with curated learning resources and career choices.
Work-based learning. New developments are enabling schools to bring competency-based learning to students at scale. From multimodal intelligent tutoring tools and AI co-pilots to platforms supporting virtual work-based learning programs, learners are gaining access to individualized, career-focused support.
Advancing STEM Skills for the 21st Century
The Need
In the last decade, we have seen stagnation in assessment scores across STEM subjects such as computer science and data literacy. Large achievement gaps remain across racial and socioeconomic backgrounds.
Opportunities
New tools can transform STEM education, shifting away from static learning approaches to interactive, experiential learning.
Immersive, experiential learning. New tools which combine AI and VR, can provide learners with immersive opportunities to experiment, strengthen their problem-solving abilities, and engage in task-based learning. Key challenges include high costs and barriers to access. Innovators will need to ensure that immersive technologies are developed to reach the learners most in need of these solutions.
Personalized interventions for inquiry-based learning. AI-driven assessments, large language models, and adaptive tools can deepen student engagement with step-by-step guidance through problem-solving and by creating more opportunities for learners to practice data interpretation.
Assessment Technologies
The Need
High-stakes tests administered at the state level are infrequent, time-consuming, and have persistent challenges of effectiveness and equity. We need tools which can better measure specific underlying competencies and generate actionable, real-time insights. A narrow focus on traditional school subjects may also mean we’re not getting a full picture of student learning.
Opportunities
AI-augmented assessments can offer faster, more precise, and more comprehensive snapshots of student progress and learning challenges.
Broadening measurement, enabling precision. Advancements in AI can allow us to track a wider range of competencies, supporting precise measures of core math and literacy sub-skills and offering reliable insights on skills like critical thinking and collaboration. In particular, multi-modal tools could expand the types of student work that can be assessed. Key challenges include accessing diverse, unbiased training data that is also pedagogically driven to improve learning impact, while ensuring fairness and equity in assessment tools.
Improving efficiency and integration. AI tools have the ability to streamline the assessment process, making it faster and ultimately taking less time away from teaching. With the power to rapidly turn data into implementable recommendations and track student progress in real time, new tools can integrate more seamlessly into the classroom and support measurable, personalized learning improvements.
Explore an example of an AI-powered assessment platform targeted at supporting middle school students | Sourced from the Tools Competition, one of the initiatives of Renaissance Philanthropy’s AI and Education vertical
Strengthening Support for Students with Learning Disabilities and Differences
The Need
Students with disabilities and learning differences have persistent learning gaps and high rates of disengagement. Specific challenges include delayed identification of learning disabilities and implementation of individualized education plans (IEPs), special education shortages, heavy administrative loads, and lack of access to key research and data.
Opportunities
New technologies have the potential to reshape the educational experience for learners with disabilities, creating new possibilities for personalized instruction.
Early assessment and identification. Advanced algorithms and screening tools show promise for more rapid assessment and identification of developmental delays. These innovations have the power to ensure students don’t fall through the cracks and are matched with early support.
Evidence-driven support. Leading-edge innovations integrate features that automatically recommend research-backed practices and monitor data and progress toward IEP goals in real time. From school leaders to parents, interventions can empower stakeholders with access to consolidated data histories for better collaboration. A key challenge is to ensure these innovations evolve with careful attention to student privacy.
Accessible, multimodal learning. Multimodal tools featuring speech-to-text, text-to-speech, and artificial reality capabilities are making content more accessible and engaging for learners. A key challenge is to design these tools to account for varying needs among students with learning disabilities and differences.
Leveraging and Increasing Data Collection
The Need
Data-informed approaches in education are vital in tackling achievement gaps, tracking learning, and addressing engagement challenges like absenteeism and barriers to student motivation. Limitations in time, resources, and capacity make accessing and leveraging data difficult for the majority of schools and districts.
Opportunities
New technologies could enable more efficient and effective data collection and sharing to help schools and districts access and use the information they need to better serve students.
Data-based student engagement. AI tools could help schools track and assess key metrics like attendance, motivation, and performance. Schools and districts can leverage data to deploy targeted interventions like data-informed communications with families.
Data sharing and accessibility. Advanced solutions for aggregating metrics across platforms, classrooms, and learners can enable the creation of centralized dashboards for better insights into student progress. New Privacy-enhancing technologies (PET) can enable pooling of data across multiple schools, school districts, and even government departments. For example, the use of PET enabled researchers to discover an intervention that boosted test scores in grades 3-8, and increased college enrollment by 17%.
Exploring additional opportunity areas
This resource points to some of the most compelling new developments we’ve seen, but it is not comprehensive. To connect with our team around these opportunities or to share others, please reach out to levi@renphil.org.
Sources
2024 Voices of Gen Z Study by the Walton Family Foundation and Gallup | August 2024
Data-Driven Decision-Making in Education: How REL Work Makes a Difference | November, 2023
Diversity and STEM: Women, Minorities, and Persons with Disabilities Report | 2023
Eight Percent of Public School Teachers Left Teaching in 2021, a Rate Unchanged Since Last Measured in 2012 | December, 2023
Elementary absenteeism over time: A latent class growth analysis predicting fifth and eighth-grade outcomes | February, 2020
Fact Sheet: 3 Trends in K-12 Assessments Across the Country | January, 2024
How to Engage High School Students in Learning | XQ Institute
K-12 Workers Have Highest Burnout Rate in U.S. | June, 2022
Racial and Ethnic Disparities in Advanced Science and Mathematics Achievement During Elementary School | April, 2023
Request for Information | August, 2024
School Systems Lack Capacity to Support Data Driven Decision Making, National Survey Finds | February, 2023
Skills-Based Hiring Is Gaining Ground | March, 2024
Solving Chronic Absenteeism Through the Smarter Use of Data | September, 2024
Students Need Better/More Data-Science Skills. Here Are 5 Ways Schools Can Help | September, 2023
Two Decades of Progress, Nearly Gone: National Math, Reading Scores Hit Historic Lows | October, 2022
Understanding the Empty Backpack: The Role of Timing in Disproportionate Special Education Identification | August, 2021
What Does the Research Say About Testing? | October, 2019
Why Special Education Teachers Quit—and What Schools Are Doing About It | May, 2024
