IES Blog

April is National Bilingual/Multilingual Learner Advocacy Month and Mathematics and Statistics Awareness Month. We asked Drs. Haiwen Chu and Leslie Hamburger, secondary mathematics researchers at the IES-funded National Research & Development Center to Improve Education for Secondary English Learners (EL R&D Center), to share how classroom observations are critical to analyzing and improving learning opportunities for English learners.

Could you tell us about your IES-funded project?

Haiwen: As part of the EL R&D Center portfolio of work, we developed RAMPUP, or Reimagining and Amplifying Mathematics Participation, Understanding, and Practices. RAMPUP is a summer bridge course for rising ninth graders. The three-week course is designed to challenge and support English learners to learn ambitious mathematics and generative language simultaneously. We will conduct a pilot study during summer 2024, with preliminary findings in fall 2024.

What motivated you to do this work?

Haiwen: English learners are frequently denied opportunities to engage in conceptually rich mathematics learning. We want to transform these patterns of low challenge and low support by offering a summer enrichment course that focuses on cross-cutting concepts uniting algebra, geometry, and statistics. We also designed active and engaged participation to be central to the development of ideas and practices in mathematics. English learners learn by talking and interacting with one another in ways that are both sustained and reciprocal.

Leslie: In addition, we wanted to offer broader approaches to developing language with English learners. As we have refined the summer program, we have explicitly built in meaningful opportunities for English learners to grow in their ability to describe, argue, and explain critical mathematics concepts in English This language development happens simultaneously with the development of conceptual understanding.

What have you observed among English learners so far in RAMPUP study classrooms?

Leslie: Over the past two summers, I have observed RAMPUP in two districts for two weeks total. The classrooms reflect America’s wide diversity, including refugee newcomers and students who were entirely educated in the United States. I was able to see both teachers facilitating and students learning. I observed how students developed diverse approaches to solving problems.

Through talk, students built upon each other’s ideas, offered details, and expanded descriptions of data distributions. Over time, their descriptions of data became more precise, as they attended to similarities and differences and developed labels. I also observed how teachers assisted students by giving hints without telling them what to do.

Haiwen: As we observed, we wanted to understand how English learners engaged in the activities we had designed, as well as how their conceptual understandings and language developed simultaneously. I have spent two summers immersed in three districts over seven weeks with diverse students as they developed relationships, deep understandings, and language practices.

I was honestly surprised by the complex relationships between how students wrote and the development of their ideas and language. Sometimes, students wrote to collect their thoughts, which they then shared orally with others, to collectively compose a common way to describe a pattern. Other times, writing was a way to reflect and give each other feedback on what was working well and how peers could improve their work. Writing was also multi-representational as students incorporated diagrams, tables, and other representations as they wrote.

From closely observing students as they wrote, I also gained valuable insight into how they think. For example, they often looked back at their past work and then went on to write, stretching their understanding.

Why are your observations important to your project?

Haiwen: RAMPUP is an iterative design and development project: our observations were driven by descriptive questions (how students learned) and improvement questions (how to refine activities and materials). By observing each summer what worked well for students, and what fell flat, we have been able to iteratively improve the flow and sequencing of activities.

We have learned that observations matter most when they directly inform broader, ongoing efforts at quality learning.

Now, in our final phase, we are working to incorporate educative examples of what quality interactions looked and sounded like to enhance the teacher materials. Beyond the shorter episodes confined within a class period, we are also describing patterns of growth over time, including vignettes and portfolios of sample student work.

Leslie: Indeed, I think that wisdom comes both in practice and learning by looking back on practice. Our observations will enable teachers to better anticipate what approaches their students might take. Our educative materials will offer teachers a variety of real-life approaches that actual students similar to their own may take. This deep pedagogical knowledge includes knowing when, if, and how to intervene to give the just-right hints.

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This blog was produced by Helyn Kim (Helyn.Kim@ed.gov), program officer for the Policies, Practices, and Programs to Support English Learners portfolio at NCER.

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.

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).

For students with learning disabilities, many of whom may take more time to read and process information than non-disabled peers, an extended time accommodation (ETA) is often used on standardized assessments. In 2021, IES awarded a grant for researchers to explore the test-taking behavior, including use of accommodations such as ETA, of students with disabilities in middle school using response process data from the NAEP mathematics assessment. In this blog, we interview Dr. Xin Wei from Digital Promise to see what she and Dr. Susu Zhang from University of Illinois at Urbana-Champaign are learning from their study.

The researchers have delved into the performance, process, and survey data of the eighth graders who took the digital NAEP mathematics test in 2017. Their recent article presents a quasi-experimental study examining the differences in these data across three distinct profiles of students with learning disabilities (LDs)—students with LD who received and utilized ETAs, students with LD who were granted ETAs but did not use them, and students with LD who did not receive ETAs.

The key findings from their study are as follows:

• Students with LDs who used their ETAs performed statistically significantly better than their peers with LDs who were not granted ETA and those who received ETA but did not use it. They also engaged more with the test, as demonstrated by more frequent actions, revisits to items, and greater use of universal design features like drawing tool and text-to-speech functionalities on most of the math items compared to students who were not granted extended time.
• Students with LDs who had ETAs but chose not to use them performed significantly worse than their peers with LDs who were not granted extended time.
• Students with LDs who were granted ETAs saw the best performance with an additional 50% time (45 minutes compared to the usual 30 minutes provided to students without ETA).
• Students who were given extra time, regardless of whether they used it, reported feeling less time pressure, higher math interest, and enjoying math more.
• There were certain item types for which students who used ETAs performed more favorably.

We recently discussed the results of the study with Dr. Wei to learn more.

Which types of items on the test favored students who used extended time and why do you think they benefited?

The assessment items that particularly benefited from ETAs were not only complex but also inherently time-consuming. For example, students need to complete four sub-questions for item 5, drag six numbers to the correct places for item 6, type answers into four places to complete an equation for item 9, type in a constructive response answer for item 11, and complete a multiple-choice question and type answers in eight places to complete item 13.

For students with LDs, who often have slower processing speeds, these tasks become even more time-intensive. The additional time allows students to engage with each element of the question thoroughly, ensuring they have the opportunity to fully understand and respond to each part. This extended time is not just about accommodating different processing speeds; it's about providing the necessary space for these students to engage with and complete tasks that are intricate and time-consuming by design.

Why did you decide to look at the additional survey data NAEP collects on math interest and enjoyment in your study of extended time?

These affective factors are pivotal to academic success, particularly in STEM fields. Students who enjoy the subject matter tend to perform better, pursue related fields, and continue learning throughout their lives. This is especially relevant for students with LDs, who often face heightened test anxiety and lower interest in math, which can be exacerbated by the pressure of timed assessments. Our study's focus on these affective components revealed that students granted extra time reported a higher level of math interest and enjoyment even if they did not use the extra time. ETAs appear to alleviate the stress tied to time limits, offering dual advantages by not only aiding in academic achievement but also by improving attitudes toward math. ETAs could be a low-cost, high-impact accommodation that not only addresses academic needs but also contributes to emotional health.

What recommendations do you have based on your findings for classroom instruction?

First, it is crucial to prioritize extra time for students with LDs to enhance their academic performance and engagement. This involves offering flexible timing for assignments and assessments to reduce anxiety and foster a greater interest in learning. Teachers should be encouraged to integrate Universal Design for Learning principles into their instructional methods, emphasizing the effective use of technology, such as text-to-speech tools and embedded digital highlighters and pencils for doing scratchwork. Professional development for educators is essential to deepen their proficiency in using digital learning tools. Additionally, teachers should motivate students to use the extra time for thorough problem-solving and to revisit math tasks for accuracy. Regularly adjusting accommodations to meet the evolving needs of students with LDs is vital in creating an inclusive learning environment where every student can achieve success.

What is the implication of the study findings on education equity? 

Our study demonstrates that ETAs offer more than just a performance boost: they provide psychological benefits, reducing stress and enhancing interest and enjoyment with the subject matter. This is vital for students with LDs, who often face heightened anxiety and performance pressure. To make the system more equitable, we need a standardized policy for accommodations that ensures all students who require ETAs receive them. We must consider the variable needs of all students and question the current practices and policies that create inconsistencies in granting accommodations. If the true aim of assessments is to gauge student abilities, time is a factor that should not become a barrier.

U.S. Department of Education Resources

Learn more about the Department’s resources to support schools, educators, and families in making curriculum, instruction, and assessment accessible for students with disabilities.

• The Center on Inclusive Technology and Education Systems (CITES) funded by the Office of Special Education Programs (OSEP)
• The National Center on Accessible Educational Materials (AEM) funded by OSEP
• Myths and Facts Surrounding Assistive Technology Devices and Services from OSEP
• National Education Technology Plan from the Office of Education Technology

Learn more about conducting research using response process data from the 2017 NAEP Mathematics Assessment.

This  interview blog was produced by Sarah Brasiel (Sarah.Brasiel@ed.gov), a program officer in the National Center for Special Education Research.

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.