IES Blog

The Department of Education’s Small Business Innovation Research Program (SBIR), administered by IES, provides awards for the research and development of new, commercially viable education technology products. Known as ED/IES SBIR, the program’s goal is to grow a portfolio of scalable, research-based products that address pressing needs across topic areas in education and special education.

From an education technology perspective, 2021 will surely be remembered as the “year after” the onset of the global pandemic—where demand for effective education tools and platforms skyrocketed and developers pivoted to meet the needs of the return to in-person and hybrid learning environments. Dozens of ED/IES SBIR-developers contributed to these efforts, with millions of students and educators using their products to support remote and in-person learning in 2021. This blog shares some highlights from the ED/IES SBIR program in 2021 and provides a preview of its recently released 2022 solicitations.

The ED Games Expo

IES hosted the 8^th annual ED Games Expo virtually in June 2021 to provide resources to the public in response to pandemic-related challenges. As part of the virtual Expo, 170 IES- and government-supported education technology products were available at no cost to educators and students around the country. The Expo also presented 35 virtual events for the public that have been viewed more than 10,000 times on YouTube, highlighted by a Kick Off Show introduced by Secretary of Education Miguel Cardona and including master classes for educators and behind-the-sciences “how to” events for students. Dates for the next ED Games Expo will be announced soon.

New ED/IES SBIR Awards

ED/IES SBIR announced 29 new 2021 awards, including 18 for prototype development and 11 for full-scale education technology product development. The awards continue trends from recent years.

One exciting trend is the employment of advanced technologies such as artificial intelligence, machine learning, natural language processing, or algorithms to personalize student learning. Examples include projects by Myriad Sensors (Pocket Lab) to develop an AI engine to assess and provide feedback to students while doing physical science experiments, Analytic Measures Inc. (AMI) to create an natural language processing engine to recommend personalized practice activities based on a student’s level of oral reading fluency, and by KooApps and Kings Peak Technology to use machine learning to provide immediate vocabulary support to English learners.

Another trend in 2021 is the development of new products to scale existing IES-funded research. Projects that build on prior IES research include: Nimble Hiring to develop a platform to improve school district hiring and educator retention, xSEL Labs to create a platform for social and behavioral learning innovations, and Emberex to create a user interface with reporting and recommendation features to meet modern standards for a reading assessment.

ED/IES SBIR also continues to support projects in new areas. For example, three new projects are developing music-based technologies to support learning (Muzology, Edify, and Lyrics to Learn).

Highlights From Individual Projects in the Portfolio

Many ED/IES SBIR-supported companies enjoyed newsworthy successes in 2021.

• Through its ED/IES SBIR-developed platform, Future Engineers administered the TechRise Student Challenge and Lunabotics Junior Challenge for NASA, and an AEOP We Heart Veterans Pin Design Challenge for the Army through which more than 15,000 students participated around the country. 
• Myriad Sensors (PocketLab) hosted a series of “Science is Cool Unconferences” in 2020 and 2021 to present innovative approaches for sciences educators which were attended by more than 65,000 science educators.
• Codespark was acquired by BEGIN to support wide-scale distribution of its coding apps, including ED/IES SBIR-developed Story Mode.
• Cognitive Toybox and research partners received an award from the Gates Foundation to continue development of their early childhood assessment; they also received an investment from Morgan Stanley to grow their business.
• Muzology was recognized as a Top 10 Finisher in the 2021 Elite 200 by GSU-ASV as a top pre-seed start-up in the field of education technology.
• The Education Development Center received an IES research grant to evaluate the efficacy of Electric Funstuff’s Mission US Games, which were developed in part through ED/IES SBIR.
• ECO by Strange Loop Games reached more than 500,000 units sold in 2021.
• Inq-ITS reached the one million mark for its completed virtual labs.

ED/IES SBIR Releases Two 2022 Program Solicitations

On December 1, 2021, ED/IES SBIR released two new solicitations. Phase I solicitation #91990022R0001 is a request for proposals for $250,000 awards for 8 months for the research, development, and evaluation of new prototypes of education and special education technology products. Direct to Phase II solicitation #91990022R0002 is a request for proposals for $1,000,000 for 2 years for R&D and evaluation to develop new technology to prepare existing researcher-developed evidence-based innovations (products, interventions, practices) for use at scale, and to plan for commercialization. The goal is to support the successful transfer of research to practice at scale in education and special education. Proposals for both solicitations are due February 1, 2022.

Stay tuned for updates in 2022 on Twitter and Facebook as IES continues to support innovative forms of technology.

Edward Metz is a research scientist and the program manager for the Small Business Innovation Research Program at the US Department of Education’s Institute of Education Sciences. Please contact Edward.Metz@ed.gov with questions or for more information.

In honor of American Education Week, IES recognizes the many school-based educators and staff who work together to support student learning and growth. This is particularly true for teams working to improve outcomes for students with disabilities. Providing special education requires a team approach with collaboration among a variety of professionals. To this end, school-based teams—teachers, administrators, special education and behavior specialists, and other support professionals—at the elementary level are in a constant process of problem solving. Student needs, ever evolving, are best met using targeted data and evidence-based practices. But how do school teams ensure that they are defining student needs accurately and applying the most effective interventions? In the busy school environment, how can team members best use their meeting time to serve students?

NCSER-funded researchers have been working to measure and support school team efforts through the development of decision-making models and observation tools refined and expanded over the course of more than 15 years. One approach dedicated to training team members and facilitating successful problem-solving meetings has been demonstrated to improve the decisions made by school teams and is now being integrated with student data systems and supported by online tools for staff.

Dr. Rob Horner (University of Oregon) and his team recognized the need for school problem-solving teams to access to student academic and behavioral data and to have a protocol for the effective use of these data. Based on an observational tool, Decision Observation Recording and Analysis (DORA), and a decision-making process developed with a previous NCSER grant, they evaluated the efficacy of Team-Initiated Problem Solving (TIPS). Focused on the school-based team meeting procedures, TIPS helps train school staff to use data to define student problems and develop targeted solutions that draw from existing research but are specific to each student’s unique circumstances and needs. This randomized controlled trial tested the TIPS model with school teams trained in schoolwide Positive Behavioral Interventions and Supports (PBIS), a systems-level framework that involves implementing multi-tiered, evidence-based practices to improve student social/behavioral and academic outcomes. Results indicated that the teams already had fairly strong foundational meeting procedures (such as use of agenda, minutes, and assigned roles) following the general PBIS training, but after exposure to TIPS training and coaching, school teams were better able to identify precise academic and behavioral problems in the students they observed. The solutions they generated were more targeted and, notably, researchers saw a shift from solutions that focused on changing the student to those that aimed to alter the student’s environment. In addition, teams that participated in TIPS were more likely to implement solutions they developed and their schools had fewer out-of-school suspensions than the schools that had teams in the control group.

Although there were positive effects of the TIPS model, it is important to note that drawing together a team of school staff with diverse specialties and relationships with the student remains a challenge. Together with Dr. Horner, Dr. Erin Chaparro (University of Oregon) is leading an IES-funded project to develop a set of technology tools to facilitate the use of TIPS with problem-solving teams. The project includes both online professional development modules tailored to team members’ needs and an app to assist with meeting protocols and easy access to meeting history and student data. These programs, collectively called the TIPS EdTech tools, are intended to improve team functioning and, by extension, student outcomes. The researchers are currently completing a pilot study to help determine the fidelity of implementing these tools and the promise for positive impacts on team functioning and student outcomes.  

TIPS is now being used in additional research. Dr. Wayne Sailor (University of Kansas) and his research team are focused on school teams’ ability to effectively leverage data to integrate student behavioral and academic supports. This NCSER-funded grant aims to improve school teams’ use of an integrated multi-tiered systems of support, which works to combine behavior and academic services, through the development of a decision support system (DSS). The DSS consists of two parts, one of which is an adaptation of the TIPS model for problem-solving team meetings termed “the meeting engine.” The second component consists of an existing digital system called DataWall, an integrated data system to link education databases, chart data, and build summary reports at various levels (such as school, grade, or student). This research team is currently enhancing DataWall while integrating with TIPS procedures.

Serving students with disabilities requires the skills and collaboration of many different education professionals, such as teachers and special education teachers, administrators, service providers, and paraeducators. The challenge of coordinating the efforts of school-based teams calls for ongoing innovation by both researchers and practitioners. TIPS and its iterations are one evidence-based way of helping to facilitate school staff supports for diverse student needs.

Written by Julianne Kasper, Virtual Student Federal Service Intern at IES and graduate student in Education Policy & Leadership at American University.

This March, IES Director Mark Schneider released a blog in which he discussed exploring a partnership with the National Science Foundation (NSF) to encourage scientists with expertise in AI and related fields to address the important post-pandemic need for accelerating learning. IES is now excited to announce our resulting participation in NSF’s National Artificial Intelligence (AI) Research Institutes—Accelerating Research, Transforming Society, and Growing the American Workforce solicitation. In this blog, we describe this new funding opportunity, provide examples of existing NCSER-funded research in this area, and highlight the potential for such research to further improve outcomes for learners with disabilities.

 Artificial Intelligence Research Funding Opportunity

With funding from the American Rescue Plan, NCSER plans to support research under Theme 6, Track B: AI-Augmented Learning for Individuals with Disabilities. Proposals must discuss how the work will respond to the needs of learners with or at risk for a disability in an area where the COVID-19 pandemic has further widened existing gaps and/or resulted in decreased access and opportunities for students with disabilities to learn and receive support services. Please review the solicitation, the webinar (November 16), and the frequently asked questions for more information. Interested applicants should note the primary focus of this institute:

“The primary focus of an institute in AI-Augmented Learning includes research and development of AI-driven innovations to radically improve human learning and education. Achievement and opportunity gaps, particularly for learners from disadvantaged or underserved communities, have always been present, but COVID-19 has exacerbated them. Institute plans for this theme should address and measure outcomes with direct education impact, in both the short- and long- term, that have practical significance to educators, parents, or other decision-makers. Plans must also directly address algorithmic bias, model transparency, security and data privacy in the support of learning.”

Current NCSER-Funded Grants Applying Artificial Intelligence and Machine Learning

Prior to the new collaboration between IES and NSF, NCSER funded several grants that apply artificial intelligence and machine learning approaches, including those described below.

With a 2018 NCSER grant, Dr. Maithilee Kunda and her team at Vanderbilt University are building on a technology-based intervention known as Betty’s Brain. This computer-based instructional program for middle school science, designed with the support of a 2006 NCER grant, allows students to teach a computer agent to understand certain concepts, increasing their own knowledge and understanding. Dr. Kunda and her team are developing a new game called Film Detective, which is designed to improve theory of mind (ToM) reasoning in adolescents with autism spectrum disorder (ASD). More information about this project can be found in this IES blog.

With a 2021 NCSER grant, Dr. Patrick Kennedy and his team at University of Oregon are using machine learning to validate a well-known assessment, Dynamic Indicators of Basic Early Literacy Skills, 8^th Edition® (DIBELS 8) as a screener for dyslexia. As of 2020, 47 states require that students be screened for dyslexia in early elementary school and many states use DIBELS for this screening. However, it remains to be validated for this purpose. To address the validity of the DIBELS for screening, this research team is using machine learning approaches to predict and classify scores in relation to a pre-defined target. This will allow the research team to draw conclusions about the validity of the DIBELS 8 for dyslexia screening. These conclusions will be disseminated widely to state and local education agencies and other stakeholders.

The Potential of AI for Improving Outcomes for Learners with Disabilities

In addition to the work that IES is funding, AI has already demonstrated potential for improving outcomes for learners with disabilities in many other ways:

• AI has been used to support children with ASD who have difficulties understanding people’s emotions, with AI-driven apps and robots helping students practice emotion recognition and other social skills.
• AI has informed the development of algorithms that can help those involved in assessment identify disabilities in students, such as ASD, specific learning disabilities (dyslexia, dysgraphia, and dyscalculia), and attention-deficit/hyperactivity disorder (ADHD).
• AI-embedded interventions have included error analysis to inform instruction and personalized feedback in spelling and math for students with disabilities.

Despite these advancements, there appear to be persistent gaps in AI research for students with disabilities, such as AI for students with intellectual and developmental disabilities. This is an especially important area of work because many of these learners have multiple disabilities and/or serious health conditions. For example, children with intellectual and developmental disabilities who also have hearing loss or visual impairment have compounded challenges. Some students with Down syndrome also have hearing loss and other health complications, such as cardiac issues. AI affords an opportunity to integrate health information across different applications to improve the quality of life for these students. These technological solutions can assist in managing information about the students and communicating health information between teachers, physicians, and caregivers.

AI has the potential to transform special education. We hope that this NCSER-NSF partnership will encourage researchers to be creative in planning projects that move the field of AI forward as well as provide innovative solutions to support learners with disabilities.

This blog was co-authored by Sarah Brasiel (Sarah.Brasiel@ed.gov), program officer at NCSER and Bennett Lunn (Bennett.lunn@ed.gov), Truman-Albright Fellow for NCSER and the National Center for Education Research (NCER). IES encourages special education researchers to partners with experts in Artificial Intelligence to submit to this NSF AI Institute solicitation 22-502 to increase the evidence base on use of AI for this population.

Artificial intelligence (AI) is poised to revolutionize the way humans live, even in ways yet unseen, and education is no exception. IES funds research at the cutting edge of technology and education science, and, as Director Mark Schneider has recently pointed out, AI may eventually serve to help educators identify, assess, and support students with disabilities. In 2018, NCSER awarded funding to Dr. Maithilee Kunda of Vanderbilt University to do just that.

Dr. Kunda and her team are developing a new game called Film Detective to improve theory of mind (ToM) reasoning in adolescents with autism spectrum disorder (ASD). ToM reasoning is the ability to infer the mental state of others, allowing us to understand and predict behavior based on our perception of their beliefs, intentions, and desires. The game builds on a technology-based intervention known as Betty’s Brain. Developed with support from a NCER grant, Betty’s Brain is a computer-based instructional program for middle school science that allows students to teach a computer agent to understand certain concepts. By teaching the agent, students grew their own knowledge and understanding. Dr. Kunda and her team are building on this software by adapting the learning-by-teaching model to improve ToM reasoning in neurodiverse students. (For more on Dr. Kunda’s perspective on the importance of neurodiversity, see this blog.)

The Film Detective game takes students through an interactive storyline in which they must help a scientist from the year 3021 “decode” the way people in today’s world behave in a series of films. The stakes are high as students help a scientist unlock a time machine by retrieving codes hidden in films by an evil scientist—aptly named Von Klepto—who has stolen items from the Museum of Human History. By teaching the computer agent—the player’s robot sidekick (named T.O.M.)—how to identify modern behaviors, the student develops their own ToM reasoning. The Film Detective storyline is a product of the creative talents of several Vanderbilt creative writing students, and the game mechanics were designed with insights of college students with ASD themselves. With the help of post-doctoral student and project lead, Roxanne Rashedi, the project team has used participatory design and qualitative methods to better tailor the game to the community for which it is intended. By working closely with students with ASD and their families, the project team was able to refine the original Betty’s Brain structure with new reward structures and storylines that balance the challenge of the game with the frustration that students can feel playing the game.

Film Detective’s Theatre and Time Machine Room (illustration by Kayla Stark)

Every part of the project draws on the diverse expertise of the team, and the inclusion of a variety of perspectives has been crucial to informing the project’s development. The team includes experts from Vanderbilt’s School of Engineering and the Vanderbilt Medical Center’s Treatment and Research Institute for Autism Spectrum Disorders (TRIAD), with Dr. Kunda and students in computer science and psychology providing insights in cognitive science and artificial intelligence. The joining of expertise in artificial intelligence, clinical psychology, and educational psychology has allowed the team to merge theoretical perspectives on ToM development with conceptions of knowledge representation and modeling in computational systems. This approach offers the team a unique framework for understanding the development of social reasoning skills in students with ASD. Beyond the theoretical, the team has also leveraged artificial intelligence to evaluate how students progress through the game, using advanced data mining techniques and eye-tracking-enabled user studies to better understand how students with ASD can develop greater ToM reasoning through learning-by-teaching.

Film Detective’s Hallway to Concessions (illustration by Kayla Stark)

The work that has gone into Film Detective exemplifies the ways that novel research that combines technological advancement and diverse perspectives can lead to important innovations in the education sciences. While Film Detective is still under development (it is currently being user tested, and readers are encouraged to sign up to take part here), IES is eager to see what will come out of this exciting collaboration.

Dr. Maithilee Kunda is the director of the Laboratory for Artificial Intelligence and Visual Analogical Systems and a faculty investigator for the Frist Center for Autism and Innovation at Vanderbilt University. This blog was written and edited by Bennett Lunn, Truman-Albright Fellow for the National Center for Education Research and the National Center for Special Education Research.

Nearly 10% of all children in the United States have at one time been diagnosed with attention-deficit/hyperactivity disorder (ADHD)—over 6 million children, according to the Centers for Disease Control and Prevention. As the name implies, ADHD can lead children to have primary problems with attention, hyperactive behavior, or both. Over the past two years, NCER and NCSER have awarded more than $12 million to four projects focusing on children and youth with ADHD through their primary grant competitions, from preschool to high school.

Comparing Virtual and In-Person Sessions for Parents of Young Children

Developed with NCSER funding, the Promoting Engagement with ADHD Pre-Kindergartners (PEAK) program has preliminary evidence of positive impacts on parent and child outcomes. Building on these findings, Principal Investigators (PIs) George DuPaul and Lee Kern are now testing the efficacy of the intervention with both face-to-face and online delivery methods. PEAK gives parents information on ADHD and a host of strategies, including behavioral management and response, reading and math skill development, and communication with school personnel to aid in the transition to kindergarten. The research team is comparing the face-to-face version, online version, and a control group without PEAK to determine the efficacy of the intervention and comparative efficacy between each method of delivery. They will also determine whether effects are maintained for up to 24 months after the end of the parent sessions.

English Language Learners (ELLs) in Early Elementary Grades

PI Nicole Schatz and her team are addressing a gap in existing research: very few interventions for the development of language and reading skills in ELL students are tailored to those who also have disabilities, particularly for ELL students with behavior disorders such as ADHD. Their 2021 NCSER-funded study will examine whether language and behavioral interventions, delivered independently or combined, improve learning outcomes for kindergarten and first grade ELLs with or at risk for ADHD. The research team will examine the impact of one of these three interventions: 1) an educational language intervention involving small-group, interactive reading; 2) a behavioral classroom intervention; and 3) a combined intervention in which students receive both the language intervention and the behavioral classroom intervention.

Academic and Social Effects of Sluggish Cognitive Tempo (SCT) in Elementary and Middle School

SCT is an attention disorder associated with symptoms similar to ADHD, such as excessive daydreaming, mental confusion, seeming to be "in a fog,” and slowed behavior/thinking. In this recent extension of PI Stephen Becker’s initial NCER grant, he explores how SCT is associated with academic and social impairments over development. The research team will collect measures of student engagement and organization, withdrawal and social awareness, and contextual factors like student-teacher relationship and school climate. The yearly observations will follow cohorts of 2^nd-5^th graders through their 5^th-8^th grade years, half with and half without SCT.

Peer Support from Upperclassmen for 9^th Graders with ADHD

Sometime in adolescence, there tends to be a shift from the influence of parents and teachers to the influence of peers. With their recent grant from NCER, researchers Margaret Sibley and Joseph Raiker will be testing Sibley’s peer-intervention program, Students Taking Responsibility and Initiative through Peer-Enhanced Support (STRIPES). Developed with IES funding, STRIPES was designed to support students with ADHD by leveraging successful peer influence to address organization, time management, and planning. Supervised by a campus staff member, 11^th and 12^th grade students who have demonstrated academic and social competencies mentor 9^th grade students with ADHD. These older peers are trained to help with goal setting, strategies for completing homework and organization, and maintenance of skills once the program is finished.

Stay tuned for findings and lessons learned from these newly funded studies.

Written by Julianne Kasper, Virtual Student Federal Service Intern at IES and graduate student in Education Policy & Leadership at American University.