About

Dr. Nathan Jones is an Associate Professor of Special Education at Boston University, affiliated with the Faculty of Computing & Data Sciences. His research focuses on teacher quality, teacher development, and school improvement, with a specific emphasis on conceptualizing and measuring teaching effectiveness.

Research topics

• Mathematics education
• Computer Science
• Psychology
• Pedagogy
• Developmental psychology
• Medicine
• Medical education

Selected publications

• Service Delivery Models: Impacts for Students With and Without Disabilities

  Educational Researcher · 2025-02-21 · 3 citations

  article1st author

  Students with and without disabilities may be educated across various service delivery models (SDMs): general education, cotaught, pull-out, and self-contained. Still, evidence for their relative effectiveness at scale remains limited. Using longitudinal administrative data from Indiana, we measured the effect of different SDMs on test scores, attendance, and disciplinary incidents. We leveraged within-student variation in SDM assignments and differences across students, applying student fixed effects and lagged outcomes models, which bound the causal effect within a narrow, policy-relevant range. Students with disabilities performed better in less restrictive environments, although the magnitude was often modest and varied across SDMs. Coteaching had a positive impact on students without disabilities. This work contributes to our understanding of inclusive practices’ effectiveness as experienced statewide.

  PublisherDOI

• The Missing Middle? General and Special Educators’ Views of Effective Mathematics Instruction

  AERA Open · 2025-06-05 · 3 citations

  articleOpen access

  General educators rarely receive adequate training for supporting students with disabilities (SWDs). We suggest a key contributing factor is the longstanding gap between special and general education researchers, which is especially pronounced in mathematics. Researchers from these fields work in isolation from one another, the result of what sociologists term “epistemic bunkers.” These cross-field divisions have pragmatic consequences. Well-established teaching strategies known to support SWDs are untouched in general teacher education. At the same time, prospective special educators lack exposure to many key instructional principles from mathematics education. In this interview study, 22 general and special education researchers describe their goals for mathematics education. Our data suggest considerable within-group heterogeneity, but also clear within-group themes and between-group distinctions. There were numerous points of intersection between special and general educators’ perspectives on mathematics teaching and learning, providing clear opportunities for bridge building. We conclude with implications for research and practice.

  PublisherDOI

• Using an observational measure of elementary teachers’ emotional expressions during mathematics and English language arts to explore associations with students’ content area emotions and engagement

  Contemporary Educational Psychology · 2025-02-11 · 1 citations

  articleSenior author
  PublisherDOI

• The Impact of a $10,000 Bonus on Special Education Teacher Shortages in Hawai‘i

  Educational Evaluation and Policy Analysis · 2025-01-28 · 11 citations

  articleSenior author

  We study the impact of a bonus policy in Hawai‘i Public Schools that raised the salaries of all special education teachers by $10,000. We estimate that this policy reduced the proportion of vacant special education teaching positions relative to general education positions by 32% and the proportion of special education positions that were vacant or filled by an unlicensed teacher by 35%. These impacts were largest in historically hard-to-staff schools in which all teachers received additional bonuses. The policy did not have significant effects on special education teacher retention; instead, the impacts of the policy were driven almost entirely by an increase in the number of general education teachers in the state who moved into open special education teaching positions.

  PublisherDOI

• Service Delivery Models and Outcomes for Students With Disabilities

  Remedial and Special Education · 2024-08-28 · 8 citations

  articleSenior author

  In this systematic literature review, we examine the corpus of empirical studies in education that use administrative data (i.e., population-level data) to describe and estimate the impacts of service delivery models for specially designed instruction on outcomes for students identified with special education needs. We focus on studies that use quantitative data analysis—either descriptive or causal—to answer questions about the relationship between special education service delivery models and student outcomes. We analyze seven studies, each of which finds a positive relationship between more time spent in general education classrooms and outcomes for students with disabilities (SWDs). In our analysis, we discuss the affordances and limitations of this type of analysis and opportunities for the field to expand data collection and analysis of population-level data in a way that better illuminates the state of special education services, both in the present and longitudinally, for SWDs.

  PublisherDOI

• A Descriptive Portrait of the Paraeducator Workforce in Washington State

  Exceptional Children · 2024-12-16 · 9 citations

  articleSenior author

  Paraeducators are critically important members of school communities, but there is little statewide research on the characteristics of paraeducators. We therefore use over 25 years of longitudinal data from Washington state to provide a descriptive portrait of the paraeducator workforce. Paraeducators are more racially and ethnically diverse than special education teachers, particularly in the last decade, and tend to be less experienced. Their full-time salaries are about half of the average for special education teachers. Finally, and perhaps most importantly, paraeducator attrition rates from the state's workforce have increased dramatically over time; for example, the paraeducator attrition rate after the 2021–2022 school year (23%) was over twice as high as the that in the 2008–2009 school year (8%). These findings have implications for how policymakers and school leaders should approach decision-making related to the paraeducator workforce, as well as how researchers might approach further research with this group of educators.

  PublisherDOI

• The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education

  arXiv (Cornell University) · 2024-04-03

  preprintOpen access

  Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and heavily dependent on observers' expertise and idiosyncratic factors, preventing teachers from getting timely and frequent feedback. Different from prior research that mostly focuses on low-inference instructional practices on a singular basis, this paper presents the first study that leverages Natural Language Processing (NLP) techniques to assess multiple high-inference instructional practices in two distinct educational settings: in-person K-12 classrooms and simulated performance tasks for pre-service teachers. This is also the first study that applies NLP to measure a teaching practice that is widely acknowledged to be particularly effective for students with special needs. We confront two challenges inherent in NLP-based instructional analysis, including noisy and long input data and highly skewed distributions of human ratings. Our results suggest that pretrained Language Models (PLMs) demonstrate performances comparable to the agreement level of human raters for variables that are more discrete and require lower inference, but their efficacy diminishes with more complex teaching practices. Interestingly, using only teachers' utterances as input yields strong results for student-centered variables, alleviating common concerns over the difficulty of collecting and transcribing high-quality student speech data in in-person teaching settings. Our findings highlight both the potential and the limitations of current NLP techniques in the education domain, opening avenues for further exploration.

  PublisherOA PDFDOI

• The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education

  2024-01-01 · 4 citations

  articleOpen access

  Paiheng Xu, Jing Liu, Nathan Jones, Julie Cohen, Wei Ai. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2024.

  PublisherOA PDFDOI

• Expanding Education Researchers’ Access to Classroom Observation Data With a Remote and Cost-Effective Video Data Collection Protocol

  Prevention Science · 2024-03-22 · 6 citations

  articleOpen access

  The onset of the COVID-19 pandemic and associated long-term shifts to virtual instruction among most US schools presented notable challenges among education researchers. Ongoing projects conducted in school settings experienced sudden losses of access to teacher and student participants, in many cases leading to severe interruptions to data collection efforts. Perhaps most notably, upon returns to in-person instruction in the 2021/22 academic year most schools instigated strict policies limiting the number of non-school personnel who could enter school buildings, including researchers conducting in-person data collections. As such, many researchers had to find alternative means to gather data. In this paper, we offer a new protocol that we created in response to these challenges that allows for the secure and fully remote collection of video data in school settings. This new protocol not only addressed the immediate needs of the focal study but also addresses some of the most notable barriers to collecting classroom video data in the field of education research at large. In this paper, we describe the initial development and application of this protocol among a local study of elementary teachers, as well as the scaling of this protocol in a study of elementary teachers in multiple states. It is our hope that this protocol can expand education researchers', practitioners', and policymakers' access to classroom video data.

  PublisherOA PDFDOI

• Are Effective Teachers for Students With Disabilities Effective Teachers for All?

  Educational Evaluation and Policy Analysis · 2023-12-25 · 4 citations

  article

  The success of students with disabilities (SWDs) depends on access to high-quality general education teachers. Yet, teacher value-added measures (VAMs) generally fail to distinguish between effectiveness in educating students with or without disabilities. Using data from the Los Angeles Unified School District, we create two VAMs: one focusing on teachers’ effectiveness for SWDs and one for non-SWDs. We find that many top-performing teachers for non-SWDs have relatively lower VAMs for SWDs and vice versa, and that on average SWDs have teachers with lower scores in both VAMs than non-SWDs. Overall, SWD-specific VAMs may be more suitable for identifying which teachers have a history of effectiveness with SWDs and could play a role in informing student assignment to teachers.

  PublisherDOI

Frequent coauthors

• Courtney A. Bell

  University of Wisconsin–Madison

  13 shared

• Mary T. Brownell

  University of Florida

  11 shared

• Jennifer M. Lewis

  Swiss HIV Cohort Study

  10 shared

• Kristabel Stark

  University of Vermont

  7 shared

• Yi Qi

  University of Nebraska–Lincoln

  7 shared

• Shuangshuang Liu

  nLIGHT (United States)

  7 shared

• Geoffrey Phelps

  Educational Testing Service

  6 shared

• Elizabeth Bettini

  Children's National

  6 shared