IES Blog

Institute of Education Sciences

Spotlight on FY 2023 Early Career Development Grant Awardees: Supporting Latine Transborder Caregivers and Their Young Children with or at Risk for Autism

NCSER continues its series spotlighting the recently funded Early Career Development and Mentoring Grants Program principal investigators with an interview with Ana Dueñas, assistant professor in special education at San Diego State University. Dr. Dueñas is conducting research aimed at improving outcomes for Latine transborder caregivers and their young children with or at risk for autism. We are pleased that this blog also honors Hispanic Heritage Month

How did you become interested in studying early intervention for Latine children on the autism spectrum?

Headshot of Ana Dueñas

As a first-generation Mexican cis-gender woman who was raised in a bicultural transborder community alongside the San Diego/Tijuana border, I learned to navigate a shifting identity—speaking English and Spanish fluently to feel accepted by both communities and managing schooling and housing across borders. Like many other children of Mexican immigrants, I served as a translator, social worker, and advocate for my parents. These experiences, along with my sensitivity to the unique needs of this population, inform how I approach community-engaged research. I am also very aware of how the biases that my education and training in special education and applied behavior analysis influence my approach to intervention research, particularly in light of the history of deficit-driven rhetoric and a medical model of disability in these fields. I aim to be mindful of the power differential that is often associated with higher education, social class, and researcher institutions in my interactions with the families I support.

My interest in building partnerships with Latine caregivers of children with autism began 10 years ago. Earlier in my career, I was a social worker for the California Regional Centers, a non-profit organization that provides services, advocacy, and support to individuals with developmental disabilities and their families. There I gained firsthand awareness of the behavioral health disparities faced by historically minoritized families (delayed diagnosis and access to culturally relevant services). Now, as a junior faculty member and researcher, I bring these experiences to my work and hope to form genuine relationships with the Latine community to better inform autism intervention research.

What are some of the unique challenges and needs of your study population?

I hope to understand these issues in depth more throughout this project. What we know from the literature about the Latine community more broadly is that they face significant disparities in access to timely diagnosis and treatment for their autistic children. This racial disparity is exacerbated in rural communities, or “service deserts” like the Imperial Valley of California, where this project is situated. The transborder community as a subgroup of the larger Latine community has very specific needs that may create a mismatch in evidence-based practices. Some points of mismatch are logistical and environmental—living and working across borders—which may lead to limited compliance, attendance, or engagement in intervention. Other points of mismatch may occur because Latine families may have a history of working with staff that lack cultural competence and therefore have few positive experiences receiving early intervention services. Further, though my project doesn’t focus on families who are undocumented, transborder families may be dealing with unique issues related to immigration status—threats of deportation, housing insecurity, and limited access to physical and mental healthcare. 

What broader impact are you hoping to achieve with your research?

Through my research, I hope to address the behavioral education disparities among marginalized populations, as they undermine the quality of life and opportunities for autistic children and their families, particularly among families exposed to vulnerable circumstances. My study addresses one small component of the many disparities that occur across a continuum from identification to treatment to improve the match between evidence-based interventions and the specific needs of marginalized individuals. Many interventions were developed with minimal input from ethnic and/or racially marginalized communities. Though there continues to be an implementation fidelity versus cultural adaptation debate, without sensitivity and responsiveness to the unique needs of communities, interventions may fail to be adopted. In my work, I begin with an assessment to ensure that the intervention is relevant to community needs and desires.

What advice do you have for other early career researchers?

Don’t give up. Understand and harness your value. Follow your instinct. Seek mentorship.

Ana Dueñas demonstrates passion and meaningful personal connection to her research. We are excited to follow her work and see what lies ahead in her academic career trajectory in special education.

This blog was produced by Emilia Wenzel, NCSER intern and graduate student at University of Chicago. Katherine Taylor (Katherine.Taylor@ed.gov) is the program officer for NCSER’s Early Career Development and Mentoring program.

Spotlight on FY 2023 Early Career Grant Awardees: Word-Level Reading Disabilities

NCSER is excited to share the work of our three new Early Career Development and Mentoring Grants Program principal investigators (PI). The aim of this grant program is to support early career scholars in their academic career trajectories as they pursue research in special education. Through a series of interview blogs, each PI will share their research interests, advice for other early career scholars, and desired impact within the field of special education.

The first scholar we are spotlighting is Kelly Williams, assistant professor in communication sciences and special education at the University of Georgia (formerly at Indiana University). Dr. Williams received a grant to develop an intervention to support reading and spelling outcomes for adolescents with word-level reading disabilities (WLRD).

How did you become interested in this area of research?         

Headshot of Dr. Kelly Williams

I originally became interested in research on WLRD through my experience as a high school special education teacher in rural Georgia where I taught English literature and composition to students with mild to moderate disabilities. Most of my students had difficulty reading and spelling words accurately and automatically, which significantly impacted their performance both in and out of school. In school, my students struggled to complete grade-level coursework, which, in turn, affected their ability to graduate with a regular high school diploma. Outside of school, my students had difficulty with tasks such as completing job applications that required extensive amounts of reading. Although I was well prepared to provide classroom accommodations and modifications for my students, I found that I lacked the knowledge and skills to provide intensive interventions that would help improve basic reading and spelling skills. These experiences ultimately led me to pursue my doctorate in special education with an emphasis on learning disabilities.

What advice do you have for other early career researchers?

I think it is important for early career researchers to collaborate with various stakeholders throughout the entire research process. Although many of my ideas stem from my own experiences as a teacher, I have found that listening to various perspectives has helped me identify problems, brainstorm potential solutions, and design practical interventions that will improve outcomes for students with disabilities. Sustaining effective interventions requires us to think about how we can involve students, teachers, administrators, parents/caregivers, schools, and other community members in research.

What broader impact are you hoping to achieve with your research?

We know low reading achievement is associated with numerous negative outcomes across domains (social, emotional, behavioral, academic, economic). My hope is that this project will provide secondary teachers with a feasible and practical intervention to improve reading outcomes for older students with WLRD, which, in turn, may help prevent or ameliorate the effects of these negative consequences. Ultimately, I envision that this intervention could be used independently or as part of a multi-component reading intervention for secondary students with WLRD.

How will this intervention be distinct from other reading and spelling interventions?

There are two ways that this intervention is distinct from other word reading and spelling interventions. First, this intervention will embed spelling instruction within word reading, which is not currently happening in research or practice for secondary students with WLRD. Many existing programs teach spelling in isolation or through rote memorization, despite a large body of research demonstrating a connection between spelling and word reading. Second, the proposed intervention will emphasize a flexible approach to multisyllabic word reading instead of teaching formal syllable division rules. The goal of this approach is to reduce cognitive load, thereby improving the ability to accurately and automatically read and spell words.

Thank you, Kelly Williams, for your thoughtful insights and commitment to improving reading and spelling among students with word-level reading disabilities. NCSER looks forward to following your work as you progress in developing this intervention.

This blog was produced by Emilia Wenzel, NCSER intern and graduate student at University of Chicago. Katie Taylor (Katherine.Taylor@ed.gov) is the program officer for NCSER’s Early Career Development and Mentoring program.

What We are Learning from Research Using NAEP Mathematics Response Process Data

Three students (two using tablets, one using a laptop) sitting at a library table

The National Assessment of Educational Progress (NAEP) is the largest nationally representative and ongoing assessment of subject knowledge among students in public and private schools in the United States. On the 2017 eighth grade mathematics assessment, 38% of students without disabilities scored at the NAEP Proficient level or above while 25% scored below the NAEP Basic level. However, for students with disabilities, math achievement levels were much worse. Only about 9% of students with disabilities scored at the NAEP Proficient level or above whereas 69% scored below the NAEP Basic level. In response to this gap, in 2021, the National Center for Special Education Research (NCSER) released a funding opportunity to coincide with the release of the 2017 Grade 8 NAEP Mathematics response process data. NCSER intended to support research that explores how learners with disabilities interact with the NAEP digital assessment to better support these learners in test-taking environments and determine whether and how that information could be used to inform instructional practices. There is much to learn from research on NAEP process data for understanding test-taking behaviors and achievement of learners with disabilities. Below we showcase the latest findings from currently funded research and encourage more investigators to conduct research with newly released process data.

Since 2017, administrations of NAEP have captured a variety of response process data, including keystrokes as learners progress through the assessment, how learners use the available tools (such as the calculator), and how accommodations (for example, text-to-speech or more time to complete the assessment) affect performance. Besides score data, NAEP datasets also include survey data from learners, teachers, and schools, and information on test item characteristics and student demographics (including disability). Together, these data provide a unique opportunity for researchers to conduct an in-depth investigation of the test-taking behavior and the mathematics competencies of learners with disabilities compared to their peers without disabilities.  

In July 2021, IES awarded two grants to conduct research using NAEP process data. The results of these projects are expected to improve the future development and administration of digital learning assessments, identify needed enhancements to mathematics instruction, and highlight areas where further research is needed.  Although these projects are ongoing, we would like to highlight findings from one of the funded projects awarded to SRI International and led by principal investigator Xin Wei  entitled Analysis of NAEP Mathematics Process, Outcome, and Survey Data to Understand Test-Taking Behavior and Mathematics Performance of Learners with Disabilities.

The findings from this study, recently published in Autism, is an example of the power of process data to shed new light on learners with disabilities. Focusing on autistic students, Xin Wei and her team analyzed data from 15 items on the NAEP math assessment, their response time in seconds, their score on the items (including partially correct scoring), and survey data related to their enjoyment, interest, and persistence in math. They also analyzed the content of each item using Flesch Reading Ease scores to measure the reading difficulty level of the item. Finally, they rated each item based on the complexity of any social context of the item, as prior research has shown that these contexts can be more challenging for autistic students. They conducted statistical analyses to compare the performance of autistic students with extended time accommodations, autistic students without accommodations, and general education peers. The researchers were not only looking for any areas of weakness, but also areas of strength. Previous studies have demonstrated that autistic people frequently excel in abstract spatial reasoning and calculation tasks, relying more on visual-mental representations than verbal ones.

The findings showed that in comparison to their general education peers, unaccommodated autistic students scored higher and solved math problems involving the identification of figures more quickly. Unaccommodated autistic students were also faster than their general education peers at solving the following types of math items: comparing measures using unit conversions, mentally rotating a triangle, interpreting linear equations, and constructing data analysis plots. Although autistic students who used the extended-time accommodation were lower performing than the other two groups, they had a higher accuracy rate on items involving identifying figures and calculating the diameter of a circle. Both groups of autistic students seem to perform poorer on word problems. Researchers concluded that the linguistic complexity could be one of the reasons that autistic students struggle with math word problems; however, there were two word problems with which they seemed to struggle despite the fact that they were not linguistically complex. It turns out that the items were rated as having substantial social context complexity. The researchers also looked at the student survey data on what types of math they enjoyed more and found they had more enjoyment working with shapes and figures and less enjoyment for solving equations.

The researchers recommend incorporating meta-cognitive and explicit schema instruction during mathematics instruction to aid autistic students in understanding real-life math word problems. They also recommend that assessment developers consider simplifying the language and social context of math word problems to make the assessment more equitable, fair, and accessible for autistic students. Because the autistic student population is particularly heterogenous, more research is required to better understand how to improve instructional strategies for them.

IES plans to release the same type of process data from the 2017 Grade 4 NAEP Mathematics at the end of this summer. We encourage researchers to request these process data to conduct research to understand test-taking behavior and performance of students with disabilities at the elementary school level. For a source of funding for the work, consider applying to the current Special Education Research Grants competition. Here are some important resources to support your proposal writing:

This blog was authored by Sarah Brasiel (Sarah.Brasiel@ed.gov), program officer at NCSER, and Juliette Gudknecht, summer data science intern at IES and graduate student at Teachers College, Columbia University. IES encourages special education researchers to use NAEP response process data for research under the Exploration project type within our standard Special Education Research Grants Program funding opportunity.   

Integrating Intervention Systems to Address Student Mental Health and Social-Emotional-Behavioral Functioning

In honor of Mental Health Awareness Month, NCSER is featuring an IES-funded study on student behavioral supports and interventions that best address the mental health needs of students. Positive Behavioral Interventions and Supports (PBIS) and school mental health (SMH) are both evidence-based interventions that provide student mental health support independent of one another. For this blog, we interviewed Dr. Brandon Schultz, principal investigator of a current study investigating the integration of both PBIS and SMH into a comprehensive school intervention. In the interview below, he discusses the differences between PBIS and SMH, how this research contributes to equity and inclusion in the classroom, and his research journey.

Your study is comparing schools that integrate PBIS and SMH into the enhanced version of the Interconnected Systems Framework (ISF) to schools that implement these as separate, parallel systems. Can you describe PBIS and SMH, and explain the key differences between the integrated framework and parallel systems?

Headshot of Dr. Brandon Schultz

PBIS is a tiered prevention system that addresses student behavioral needs. It provides universal support (Tier 1) to all students, including clear schoolwide behavioral expectations and a rewards system for desired behaviors. For students who do not respond to these efforts, Tier 2 provides targeted help through classroom-level or small group interventions, such as teacher consultation or student mentoring/counseling. For students who need intensive support, Tier 3 provides specialized one-to-one behavioral services. SMH, in contrast, focuses specifically on mental illnesses (for example, anxiety, trauma, depression) and, in some cases, involves community-based therapists working contractually with schools. Typically, PBIS and SMH function separately as co-located services, but there is a growing recognition that student needs are best met when these efforts are meaningfully integrated. Integration, however, is challenging because it requires educators to rethink their teaming and progress monitoring practices and include different stakeholders in critical decision-making processes. This study tests innovations to the ISF model, designed by my co-PI, Dr. Mark Weist (University of South Carolina), to meet the challenges of integrating these systems in two diverse school districts.

How did you become interested in this area of research?

My previous research was mostly focused on school-based interventions for students with ADHD, but it became clear that without systems-level change, interventions meant to help students with ADHD are unlikely to be implemented or sustained effectively, no matter how well they are designed. So, I became interested in understanding school systems and identifying the elements, processes, and resources that are critical for student support services of all kinds. 

How does your research contribute to equity and inclusion in education?

Part of my current study is focused the degree to which innovations to the ISF model can reduce racial inequities in school disciplinary actions. Research shows that Black students receive higher rates of exclusionary punishments (for example, suspensions and expulsions) than their White counterparts, even after controlling for the type of infraction. The modified ISF model aims to reduce the overall need for exclusionary punishments, especially among students of color. By improving team functioning, ISF allows educators to identify systemic problems that lead to racial inequities in disciplinary referrals and to generate new strategies to address student needs in a fair and equitable manner. With this model, we anticipate increased support for students of color that obviates disciplinary referrals. We are working with school districts now to examine disciplinary data before, during, and after the implementation of the enhanced ISF. Our hope is to identify strategies that close race-related gaps and share the lessons learned broadly.

Have you encountered any challenges in studying this integrated framework in elementary schools?

Yes, absolutely. Systems-level change in general is difficult, as it requires change agents to overcome structural inertia rooted in local norms, routines, and expectations. Those challenges have been exacerbated by the COVID-19 pandemic and preexisting trends in childhood mental illnesses. 

During the pandemic, student progress in mathematics and reading have dramatically declined. Meeting these academic needs, a priority for teachers, can divert attention away from student mental health needs. For example, all teachers in one of our states are required to take a year-long online course in reading instruction, partly to address student learning loss. Although commendable, this requirement creates a significant burden for teachers that can leave little room for other concerns. 

Preexisting mental health trends demonstrate that mental illness was increasing sharply among school-age children; by 2018, nearly 15% of all K-12 students experienced a psychiatric condition each year. Then, with the onset of the pandemic, indicators of childhood mental illness (for example, emergency room visits for suicidal behavior) spiked. Childhood anxiety and depression doubled worldwide from pre-pandemic estimates, and it is unclear whether those rates will return to baseline.

Together, these events have created real challenges, not just for our research, but for student support services in general.

What is currently the greatest area of need in studying school-based systems that support student mental health, particularly for those students with or at risk for emotional and behavioral disorders?

Perhaps the greatest area of need for supporting students with emotional and behavioral disorders is understaffing in critical school mental health positions. There is a significant shortage of school psychologists, counselors, social workers, and nurses nationwide. In North Carolina, the current ratio of school psychologists to students is 1:2,527, five times higher than recommended. This understaffing hinders schools’ ability to provide high-quality services and complicates efforts to test and refine innovative practices because field-based practitioners are unable to collaborate on research efforts. Researchers have had to hire individuals to fulfill critical roles, such as behavioral consultants, that might otherwise have been assigned to district-employed staff. Trained personnel then exit the school district when the research project ends and that skillset is lost. We hope that states prioritize the hiring of school mental health practitioners in the coming years to ensure optimal student support services and that university-school research collaborations can reliably lead to sustainable innovations.

NCSER looks forward to seeing the results of this efficacy trial and will continue to fund research aimed at supporting the mental health and social-emotional-behavioral needs of students with or at risk for disabilities.

This blog was authored by Isabelle Saillard, student volunteer for NCSER and undergraduate at the University of Virginia.

Exploring the Intersection of Special Education, Learning Analytics, and Psychometrics: A Journey in Education Research

This year, Inside IES Research is publishing a series of blogs showcasing a diverse group of IES-funded education researchers and fellows that are making significant contributions to education research, policy, and practice. In recognition of Asian American and Pacific Islander Heritage Month, in this interview blog we asked Dr. Xin Wei, a senior quantitative researcher at Digital Promise to discuss her career journey. Dr. Wei’s current IES-funded study uses statistical and machine-learning techniques to understand the test-taking behavior of National Assessment of Educational Progress (NAEP) grade 8 learners with and without disabilities.

How did you become interested in a career in education research?

As a child, I aspired to become a teacher, and in college I decided to pursue a degree in child development. During my senior year of college, I worked as a research assistant on a project studying statistical and psychometric methods used to analyze learning differences among children. This experience sparked my interest in education research and revealed the potential for statistical analysis to inform and enhance teaching practices.

Graduate studies at the University of Wisconsin-Madison and Stanford University helped me gain a deeper understanding of quantitative methods in education research. Through applying and improving quantitative methods, I discovered how national and state longitudinal datasets can help us understand the learning, social, and emotional needs of students with disabilities and which policy interventions can help us achieve better outcomes. This opportunity helped me understand the challenges students with disabilities face in the education system and deepened my appreciation for secondary data analysis and its power to inform intervention research.

Currently, my research focuses on analyzing log/process data to understand how digital learning and assessments can facilitate student learning, accurately measure progress, and improve outcomes for students with disabilities. Through this work, I am committed to advancing the education research field at the intersection of special education, learning analytics, and psychometrics.

What has been the biggest challenge you have encountered, and how did you overcome the challenge?

When I came to the United States to pursue a graduate degree at the age of 23, I faced a host of challenges that forced me out of my comfort zone. Navigating a new culture and adapting to academic expectations and research demands was overwhelming. Additionally, understanding U.S. K-12 education policies and practices was no easy feat. However, I was fortunate enough to have incredible mentors, professors, peers, and colleagues who provided me with guidance, support, and patience when I needed it most. These individuals played a crucial role in helping me grow as a researcher.

The most important lesson I learned from the challenges I faced was the value of continuous learning and growth in my career. These experiences have strengthened my commitment to making a positive impact in education and helping others who may be facing similar obstacles.

How can the broader education research community better support the careers and scholarship of researchers from underrepresented groups?

The student population in the United States is diverse, and it is essential that the education research community reflects that diversity by including scholars who bring unique perspectives and experiences.

One way to do this is by actively seeking out and valuing diverse voices in research, teaching, and leadership positions. This includes promoting diversity in conference panels, as well as actively recruiting and hiring researchers from underrepresented groups. By creating a culture of inclusivity, the education research community can better support the careers and scholarship of researchers from underrepresented groups.

Another way to better support the careers and scholarship of researchers from underrepresented groups is through mentoring programs, summer internships, and postdoc positions. These opportunities can provide valuable professional development and collaboration opportunities. In addition, research grants specifically targeted toward underrepresented groups can also help support their work and advance their careers. It is essential to widely advertise these opportunities and make them accessible to ensure that all researchers have an equal chance to participate.

In your area of research, what do you see as the greatest research needs or recommendations to address diversity, equity, and inclusion and to improve the relevance of education research for diverse communities of students and families?

To address diversity, equity, and inclusion in education research, it is crucial to adopt an asset-based approach when working with neurodiverse students. By shifting the focus from deficits to strengths, we can recognize and leverage their unique abilities, promoting more equitable educational practices. Additionally, targeted support should be provided to address the specific challenges underserved students face, ensuring inclusive learning environments. For instance, my research findings indicate that students with autism exhibit strengths in visuospatial reasoning and are drawn to STEM fields. However, autistic students may benefit from extra support to develop perseverance and improve their weaker areas (such as word problems) in math.

Furthermore, there is a need for more research focusing on understanding how students with disabilities or other underserved groups engage with and benefit from digital learning and assessment systems. This entails investigating their cognitive processes, level of engagement, needs, and barriers within these contexts.

To address this gap, I am currently analyzing the NAEP process/log, performance, and survey data to study the impact of digital tools (such as text-to-speech) on student performance. This line of research is crucial and should be expanded to gather new insights on inclusive and accessible learning possibilities as technologies continue to develop.

In addition, research efforts should extend beyond traditional methods and incorporate the analysis of multimodal data. By considering a range of data sources, including behavior log/process data, speech, facial expressions, and eye-tracking data, we can gain deeper insights into how students interact with digital learning and assessments. This comprehensive approach enables us to capture nuanced aspects of their experiences and informs the design and implementation of effective educational interventions and digital learning platforms.

What advice would you give to emerging scholars from underrepresented, minoritized groups that are pursuing a career in education research?

First and foremost, seek out a great mentor and research team. Having someone to guide and support you in the field can be tremendously beneficial to your career. Look for someone who shares your research interests, is supportive of your goals, and is committed to helping you succeed. Learning from others in your team is a great way to improve your skills and knowledge.

Second, don’t be afraid of change. The greatest opportunities often require stepping out of your comfort zone and exploring new research areas or methodologies. Be open to feedback and new perspectives that can help you grow as a researcher.

Third, be brave! It is important to recognize that your unique experiences and perspectives are valuable assets to the research community. Do not be afraid to share your ideas and contributions with others. Being proactive about your work can be a great way to build your network and collaborate with other researchers in the field.

Lastly, know that you have the potential to lead a research team yourself. Keep working hard, stay focused on your goals, and do not be afraid to take on leadership roles when the opportunities arise. Pursuing this career as an emerging scholar from an underrepresented or minoritized group can be challenging but also incredibly rewarding, and you can make a meaningful impact in the field and inspire others to follow in your footsteps.


Dr. Xin Wei is currently a senior quantitative researcher at Digital Promise. Prior to joining Digital Promise, she held the position of principal research scientist at SRI International for a duration of 15 years. She specializes in using applied experimental design, statistical and machine-learning techniques to evaluate and improve instruction, interventions, assessments, and policies. In addition to her current IES study, Dr. Wei has designed and directed statistical analysis of more than 26 grants funded by federal agencies.

Produced by NCER program officer Wai Chow (Wai-Ying.Chow@ed.gov) and Virtual Student Federal Service intern Audrey Im.