Inside IES Research

Notes from NCER & NCSER

Introducing NCER’s Federation of American Scientists Fellows

We are excited to have Katherine McEldoon and Alexandra Resch, two Federation of American Scientists (FAS) Impact Fellows, who joined the center in December 2023 to support the Accelerate, Transform, Scale (ATS) Initiative. The ATS Initiative supports advanced education research and development (R&D) to create scalable solutions to improve education outcomes for all learners and eliminate persistent achievement and attainment gaps.

Both of our FAS Fellows have experiences that reinforce the need to start with the science and to use the right methods at the right time to build solutions. They’ve observed that while researchers are great at producing insights about education and learning, and developers are great at building education solutions and technologies, the broader field isn’t yet great at is doing the two together. Through their careers, they’ve come to see rigorous research and development happening together as the path forward to build effective, evidence-based solutions.

In this blog, Alex and Katherine share about their career paths and how their unique experiences and perspectives are suited to help grow the ATS Initiative.

Alexandra Resch

I’ve always been driven by an urge to try to improve our education systems. I often felt bored in school and could see huge gaps in resources and opportunities among classrooms in my school and between my district and others nearby. I studied economics because the quantitative and analytic tools came naturally to me and because I could see the importance that incentives and resource constraints play in understanding how our systems work and how to improve them. I love the lens that economics provides to make sense of the world.

When I finished my PhD in 2008, I got my dream job as a researcher at Mathematica. Among other things, I worked on the What Works Clearinghouse, interesting methods papers, and national studies. I enjoyed these projects, but I started to worry that while I was doing great research, it wasn’t answering the questions practitioners had and wasn’t timely enough to inform their decisions. I gradually started shifting my work to be closer to decisions and decision makers, eventually building out a portfolio of work on rapid cycle evaluation and ways to be opportunistic about generating strong evidence. I also started thinking about how we talk about evidence and whether we’re framing questions and findings to privilege the status quo. I’ve come to believe the questions we ask, the methods we use, and how we describe our results all need to be different if we want to affect how the education system works and make a difference for student learning.

Over the last decade, I’ve developed expertise in R&D, learning about and applying tools and processes for human centered design, continuous improvement, product development, and product management. I haven’t put aside the tools I had from economics, but I have a bigger toolbox and am better able to use the right tool at the right time. I’ve seen progress in recent years in bringing more rigor to product development and more speed and agility to education research. I’m excited to support the work that the ATS initiative is doing to bring researchers and developers closer together into productive partnerships in the service of solving genuine problems for educators and students. 

Katherine McEldoon

Early in my career, I set connecting scientific insights and education practice as my north star, and I haven’t looked back since. I was intrigued with what cognitive sciences could unlock: clear explanatory mechanisms of certain behaviors and beliefs—empirically validated, no less! There were so many insights ripe for the classroom, but why weren’t they being used?

Through my doctoral work at Vanderbilt University and the IES-funded Experimental Education Research Training (ExpERT) program, I grounded myself in cognitive theories of learning and designed instruction using those insights while measuring impact. This cross-training equipped me with the skillset I’d need to conduct a range of efficacy studies and honed my ability to speak multiple academic dialects—a skill that became more important as I grew in my career.

Next, I set my sights on scale-up: first at Arizona State University, where we incorporated a theory of active learning into teacher practice; then by running a state-level evaluation study for an EdTech start-up company; and finally by supporting a networked improvement community with the Tennessee Department of Education. I learned firsthand how many layers we had to work through to bring the "active ingredients” into the learner experience. I also developed an appreciation for the multifaceted collaborations it takes to bring these efforts together.

In 2019, I joined Pearson’s Efficacy and Learning division, where we collaborated with product development teams, providing research-based insights to inform learning design and outcome measurement. We started with insights from the learning sciences and conducted iterative R&D with end-users from ideation, to prototypes and designs, to mature product evaluations. The research perspective kept our eye on conducting development work in a careful, measured, and learning outcomes-focused way. The development perspective kept us centered on researching applied and immediate problems and keeping practical significance at the fore. When done well, the balance of research and development hummed into harmony, and resulted in effective, enjoyable experiences that really worked.

Through my career I’ve learned that instead of asking how do we connect research to practice, the better question is how do we intertwine the research and development process? Not only should we be starting with research-based insights, but we should also be integrating research methods and development processes to build a high quality and useful solution from the start. That’s precisely what we’re working to achieve with the ATS Initiative.


This blog was written by Alex Resch and Katherine McEldoon, Accelerate, Transform, Scale Initiative, NCER.

How IES-Funded Research Infrastructure is Supporting Math Education Research

Every April, we observe Mathematics and Statistics Awareness month to increase public understanding of math and stats and to celebrate the unique role that math and stats play in solving critical real-world problems. In that spirit, we want to share some exciting progress that SEERNet has made in supporting math education research over the past three years.

In 2021, IES established SEERNet, a network of platform developers, researchers, and education stakeholders, to create and expand the capacity of digital learning platforms (DLPs) to enable equity-focused and rigorous education research at scale. Since then, SEERNet has made significant progress, and we are starting to see examples of how researchers can use this new research infrastructure.

Recently, IES held two rounds of a competition to identify research teams to join SEERNet to conduct a study or series of studies using one of the five DLPs within the SEERNet network. Two research teams joined the network from the first round, and the second round of applications are now under review. We want to highlight the two research teams that joined SEERNet and the important questions about math education that they are addressing.

  • Now I See It: Supporting Flexible Problem Solving in Mathematics through Perceptual Scaffolding in ASSISTments – Dr. Avery Closser and her team are working with the E-Trials/ASSISTments team. ASSISTments is a free tool to support math learning, which has been used by over 1 million students and 30,000 teachers across the nation. IES has supported its development and efficacy since 2003. E-Trials is the tool that researchers can use to develop studies to be implemented within ASSISTments. The research team’s studies are designed to test whether perceptual scaffolding in mathematics notation (for example, using color to highlight key terms such as the inverse operators in an expression) leads learners to pause and notice structural patterns and ultimately practice more flexible and efficient problem solving. This project will yield evidence on how, when, and for whom perceptual scaffolding works to inform classroom practice, which has implications for the development of materials for digital learning platforms.
  • Investigating the Impact of Metacognitive Supports on Students' Mathematics Knowledge and Motivation in MATHia – Dr. Cristina Zepeda and her team are working with the Upgrade/MATHia team. MATHia is an adaptive software program used in middle and high schools across the country. UpGrade is an open-source A/B testing platform that facilitates randomized experiments within educational software, including MATHia. The research team will conduct a series of studies focused on supporting students’ metacognitive skills, which are essential for learning in mathematics but not typically integrated into instruction. The studies will seek to identify supports that can be implemented during mathematics learning in MATHia that improve metacognition, mathematics knowledge, and motivation in middle school.

Both research teams are conducting studies that will have clear implications for curriculum design within DLPs focused on math instruction for K-12 students. The value of conducting these studies through existing DLPs rather than through individual researcher-designed tools and methods includes—

  1. Time and cost savings – Without the need to create materials from scratch, the research teams can immediately get to work on the specific instructional features they intend to test. Additionally, since the intervention and pre/post assessments can be administered through the online tool, the need to travel to study sites is reduced.
  2. Access to large sample sizes – Studies like the ones described above are frequently administered in laboratory settings or in a handful of schools. Since over 100k students use these DLPs, there is the potential to recruit a larger and more diverse sample of students for studies. This provides more opportunities to study what works for whom under what conditions.
  3. Tighter feedback loops between developers and researchers – Because the research teams need to work directly with the platform developers to administer their studies, the studies need to be designed in ways that will work within the platform and with the platform content. This ensures their relevance to the platform and means that the platform developers will be knowledgeable about what is being tested. They will be interested to hear the study’s findings and likely to use that information to inform future design decisions.

We look forward to seeing how other education researchers take advantage of this new research infrastructure. For math education researchers in particular, we hope these two example projects inspire you to consider how you might use a DLP in the future to address critical questions for math education.


This blog was written by Erin Higgins (Erin.Higgins@ed.gov), Program Officer, Accelerate, Transform, Scale Initiative.

 

Research and Development Partnerships Using AI to Support Students with Disabilities

A speach therapist uses a laptop to work with a student

It is undeniable that artificial intelligence (AI) is, sooner rather than later, going to impact the work of teaching and learning in special education. Given formal adoption of AI technologies by schools and districts and informal uses of ChatGPT and similar platforms by educators and students, the field of special education research needs to take seriously how advancements in AI can complement and potentially improve our work. But there are also ways that these advancements can go astray. With these technologies advancing so quickly, and with AI models being trained on populations that may not include individuals with disabilities, there is a real risk that AI will fail to improve—or worse, harm—learning experiences for students with disabilities. Therefore, there is a pressing need to ensure that voices from within the special education community are included in the development of these new technologies.

At NCSER, we are committed to investing in research on AI technologies in a way that privileges the expertise of the special education community, including researchers, educators, and students with disabilities and their families. Below, we highlight two NCSER-funded projects that demonstrate this commitment.

Using AI to support speech-language pathologists

In 2023, NCSER partnered with the National Science foundation to fund AI4ExceptionalEd, a new AI Institute that focuses on transforming education for children with speech and language disorders. Currently, there is a drastic shortage of speech-language pathologists (SLPs) to identify and instruct students with speech and language needs. AI4ExceptionalEd brings together researchers from multiple disciplines including special education, communication disorders, learning sciences, linguistics, computer science, and AI from nine different universities across the United States to tackle pressing educational issues around the identification of students and the creation of specially designed, individualized instruction for students with speech and language disorders.

By bringing together AI researchers and education researchers, this interdisciplinary research partnership is setting the foundation for cutting-edge AI technologies to be created that solve real-world problems in our schools. A recent example of this is in the creation of flash cards for targeted intervention. It is common practice for an SLP to use flash cards that depict a noun or a verb in their interventions, but finding or creating the exact set of flash cards to target a specific learning objective for each child is very time consuming. Here is where AI comes into play. The Institute’s team of researchers is leveraging the power of AI to help SLPs identify optimal sets of flash cards to target the learning objectives of each learner while also creating the flash cards in real time. To do this effectively, the AI researchers are working hand-in-hand with speech and language researchers and SLPs in the iterative development process, ensuring that the final product is aligned with sound educational practices. This one AI solution can help SLPs optimize their practice and reduce time wasted in creating materials.

Adapting a popular math curriculum to support students with reading disabilities

Another example of how partnerships can strengthen cutting-edge research using AI to improve outcomes for students with disabilities is a 2021 grant to CAST to partner with Carnegie Learning to improve their widely used digital math curriculum, MATHia. The goal of this project is to develop and evaluate reading supports that can be embedded into the adaptive program to improve the math performance, particularly with word problems, of students with reading disabilities. CAST is known for its research and development in the area of universal design for learning (UDL) and technology supports for students with disabilities. Carnegie Learning is well known for their suite of curriculum products that apply cognitive science to instruction and learning. The researchers in this partnership also rely on a diverse team of special education researchers who have expertise in math and reading disabilities and an educator advisory council of teachers, special educators, and math/reading specialists.

It has taken this kind of partnership—and the inclusion of relevant stakeholders and experts—to conduct complex research applying generative AI (ChatGPT) and humans to revise word problems within MATHia to decrease reading challenges and support students in understanding the semantic and conceptual structure of a word problem. Rapid randomized control trials are being used to test these revised versions with over 116,000 students participating in the study. In 2022-2023 the research team demonstrated that humans can successfully revise word problems in ways that lead to improvements in student performance, including students with disabilities. The challenge is in trying to train generative AI to reproduce the kinds of revisions humans make. While generative AI has so far been unevenly successful in making revisions that similarly lead to improvements in student outcomes, the researchers are not ruling out the use of generative AI in revising word problems in MATHia.

The research team is now working with their expert consultants on a systematic reading and problem-solving approach as an alternative to revising word problems. Instead of text simplification, they will be testing the effect of adding instructional support within MATHia for some word problems.

The promise of AI

AI technologies may provide an opportunity to optimize education for all learners. With educators spending large amounts of their day planning and doing paperwork, AI technologies can be leveraged to drastically decrease the amount of time teachers need to spend on this administrative work, allowing more time for them to do what only they can—teach children. Developers and data scientists are invariably going to continue developing AI technologies, many with a specific focus on solutions to support students with disabilities. We would like to encourage special education researchers to exert their expertise in this development work, to partner with developers and interdisciplinary teams to apply AI to create innovative and novel solutions to improve outcomes for students with disabilities. For AI to lead to lasting advances in education spaces, it will be imperative that this development is inclusive of the special education field.

This blog was written by NCSER Commissioner, Nate Jones (Nathan.Jones@ed.gov) and NCSER program officers Britta Bresina (Britta.Bresina@ed.gov) and Sarah Brasiel (Sarah.Brasiel@ed.gov).

IES Makes Three New Awards to Accelerate Breakthroughs in the Education Field

Through the Transformative Research in the Education Sciences Grants program (ALN 84.305T), IES  invests in innovative research that has the potential to make dramatic advances towards solving seemingly intractable problems and challenges in the education field, as well as to accelerate the pace of conducting education research to facilitate major breakthroughs. In the most recent FY 2024 competition for this program, IES invited applications from partnerships between researchers, product developers, and education agencies to propose transformative solutions to major education problems that leverage advances in technology combined with research insights from the learning sciences.

IES is thrilled to announce that three grants have been awarded in the FY 2024 competition. Building on 20 years of IES research funding to lay the groundwork for advances, these three projects focus on exploring potentially transformative uses of generative artificial intelligence (AI) to deliver solutions that can scale in the education marketplace if they demonstrate positive impacts on education outcomes. The three grants are:

Active Learning at Scale (Active L@S): Transforming Teaching and Learning via Large-Scale Learning Science and Generative AI

Awardee: Arizona State University (ASU; PI: Danielle McNamara)

The project team aims to solve the challenge that postsecondary learners need access to course materials and high-quality just-in-time generative learning activities flexibly and on-the-go.  The solution will be a mobile technology that uses interactive, research-informed, and engaging learning activities created on the fly, customized to any course content with large language models (LLMs). The project team will leverage two digital learning platforms from the SEERNet networkTerracotta and ASU Learning@Scale – to conduct research and will include over 100,000 diverse students at ASU, with replication studies taking place at Indiana University (IU). IES funding has supported a large portion of the research used to identify the generative learning activities the team will integrate into the system—note-taking, self-explanation, summarization, and question answering (also known as retrieval practice). The ASU team includes in-house technology developers and researchers, and they are partnering with researchers at IU and developers at INFLO and Clevent AI Technology LLC. The ASU and IU teams will have the educator perspective represented on their teams, as these universities provide postsecondary education to large and diverse student populations.

Talking Math: Improving Math Performance and Engagement Through AI-Enabled Conversational Tutoring

Awardee: Worcester Polytechnic Institute (PI: Neil Heffernan)

The project team aims to provide a comprehensive strategy to address persistent achievement gaps in math by supporting students during their out-of-school time. The team will combine an evidence-based learning system with advances in generative AI to develop a conversational AI tutor (CAIT– pronounced as “Kate”) to support independent math practice for middle school students who struggle with math, and otherwise, may not have access to after-school tutoring. CAIT will be integrated into ASSISTments, a freely available, evidence-based online math platform with widely used homework assignments from open education resources (OER). This solution aims to dramatically improve engagement and math learning during independent math problem-solving time. The team will conduct research throughout the product development process to ensure that CAIT is effective in supporting math problem solving and is engaging and supportive for all students. ASSISTments has been used by over 1 million students and 30,000 teachers, and IES has supported its development and efficacy since 2003. The project team includes researchers and developers at Worcester Polytechnic Institute and the ASSISTments Foundation, researchers from WestEd, educator representation from Greater Commonwealth Virtual School, and a teacher design team.

Scenario-Based Assessment in the age of generative AI: Making space in the education market for alternative assessment paradigm

Awardee: University of Memphis (PI: John Sabatini)

Educators face many challenges building high-quality assessments aligned to course content, and traditional assessment practices often lack applicability to real world scenarios. To transform postsecondary education, there needs to be a shift in how knowledge and skills are assessed to better emphasize critical thinking, complex reasoning, and problem solving in practical contexts. Supported in large part by numerous IES-funded projects, including as part of the Reading for Understanding Initiative, the project team has developed a framework for scenario-based assessments (SBAs). SBAs place knowledge and skills into a practical context and provide students with the opportunity to apply their content knowledge and critical thinking skills. The project team will leverage generative AI along with their framework for SBAs to create a system for postsecondary educators to design and administer discipline-specific SBAs with personalized feedback to students, high levels of adaptivity, and rich diagnostic information with little additional instructor effort. The project team includes researchers, developers, and educators at University of Memphis and Georgia State University, researchers and developers at Educational Testing Service (ETS), and developers from multiple small businesses including Capti/Charmtech, MindTrust, Caimber/AMI, and Workbay who will participate as part of a technical advisory group.

We are excited by the transformative potential of these projects and look forward to seeing what these interdisciplinary teams can accomplish together. While we are hopeful the solutions they create will make a big impact on learners across the nation, we will also share lessons learned with the field about how to build interdisciplinary partnerships to conduct transformative research and development.


For questions or to learn more about the Transformative Research in the Education Sciences grant program, please contact Erin Higgins (Erin.Higgins@ed.gov), Program Lead for the Accelerate, Transform, Scale Initiative.

ED/IES SBIR Special Education Technology is Showcased at the White House Demo Day

On Tuesday, November 7, 2023, the White House’s Office of Science and Technology Policy hosted a Demo Day of American Possibilities at the Showroom in Washington, DC.  The event featured 45 emerging technologies created by innovators through federal research and development programs across areas such as health, national security, AI, robotics, climate, microelectronics, and education. President Biden attended the event and met with several developers to learn about and see demonstrations of the innovations.

An IES-supported project by a Michigan-based Alchemie, the KASI Learning System (KASI), was invited to represent the U.S. Department of Education and its Small Business Innovation Research program, which IES administers.

KASI is an inclusive assistive technology that employs computer vision and multi-sensory augmented reality to support blind and low vision learners in using hand-held physical manipulatives to practice chemistry. A machine learning engine in KASI generates audio feedback and prompts to personalize the experience as learners progress. At the event, the project’s principal investigator and former high school chemistry educator, Julia Winter, demonstrated KASI to leaders in government and to attendees from the assistive technology field.

ED/IES SBIR supported the initial development for KASI through three awards. Based on these awards, Alchemie received funding from angel investors in Michigan, won a commercialization grant from the Michigan Emerging Technology Fund, and is establishing partnerships with publishers in K-12 and higher education. To extend KASI to more topics, Alchemie has won additional SBIR awards from the National Science Foundation, the National Institutes of Health, and the National Institute of Disability, Independent Living, and Rehabilitation Research, and is currently a finalist in the 2024 Vital Prize Challenge competition. KASI has also recently been highlighted in Forbes and Crain’s Detroit Business.

 

 

Stay tuned for updates on KASI and other education technology projects through the ED/IES SBIR program on Twitter, Facebook, and LinkedIn.


About ED/IES SBIR: The Department of Education’s (ED) Small Business Innovation Research (SBIR) program, administered by the Institute of Education Sciences (IES), funds entrepreneurial developers to create the next generation of technology products for learners, educators, and administrators. The program, known as ED/IES SBIR, emphasizes an iterative design and development process and pilot research to test the feasibility, usability, and promise of new products to improve outcomes. The program also focuses on planning for commercialization so that the products can reach schools and end-users and be sustained over time. Millions of students in thousands of schools around the country use technologies developed through ED/IES SBIR.

Edward Metz (Edward.Metz@ed.gov) is the Program Manager of the ED/IES SBIR program.

Laurie Hobbs (Laurie.Hobbs@ed.gov) is the Program Analyst of the ED/IES SBIR program.