Teaching can be driven by data

Using data to guide the way children with learning disabilities are taught can be effective in mainstream schools, argue Douglas Fuchs and Lynn Fuchs

FOR MANY PEOPLE, RESPONSE TO INTERVENTION (or RTI) represents a fundamental rethinking and reshaping of general education into a multilevel system that focuses on early intervention and prevention. RTI is a three-level (or three-tier) teaching system, with each of the levels being distinguished by the distinctiveness of the instruction that is being delivered and the skills they require of the teachers.

What we know
● Special education can be the most intensive instructional level in an RTI framework.
● Special education teachers must learn to intensify teaching using data-based, hypothesis-testing approaches.
● Increasing teaching time or reducing group size is not the answer.

RTI has moved to the forefront of discussions about education reform in the US. There is disagreement about whether special education should have a role in RTI frameworks. Some wish it would become the most intensive instructional level in RTI frameworks. Others say that special education should exist outside RTI or become an RTI component only after it has been redefined and “blurred” with general education. We are in the first of these two camps.

In this article we give an overview of the three levels of RTI, and describe a promising RTI approach called Data-Based Instruction (DBI).

Level one: Primary prevention

Primary prevention refers to the general teaching all children receive in mainstream classrooms. This includes the core program; classroom routines meant to provide the opportunity for differentiation, permitting virtually all students access to the primary prevention program; and problem-solving strategies for addressing motivation and behavior.

Screening in primary prevention identifies children at risk of not responding to the general program. These students can then receive more intensive secondary prevention in a timely manner. Screening is typically done through brief tests given to all children, with a cut-off point established by prior research (reflecting students’ likely performance in high-stakes tests, and teacher assessments).

Level two: Secondary prevention

Secondary prevention differs from primary prevention in several ways. Probably the most important difference is that while primary prevention programs are designed using instructional principles derived from research, they have typically not been proven by empirical research studies. Secondary prevention, by contrast, often involves small-group teaching using a research-proven tutoring program (proven by experimental or quasi-experimental studies).

The tutoring program specifies teaching procedures, duration (typically 10 to 20 weeks of 20- to 45-min sessions), and frequency (three or four times per week). It is often led by an adult with special training. Schools can design their RTI prevention systems so children receive one or more tutoring programs in the same academic area or in different areas. Assessment during secondary prevention determines how well children respond. This assessment is usually based on progress monitoring during tutoring, an assessment following tutoring, or a combination of the two. Schools use these data to decide whether students should return to primary prevention, or whether more intensive intervention is necessary.

Level three: Tertiary prevention

A combination of strong primary and secondary prevention will still fail to meet the academic needs of between 5% and 10% of school students. These students require additional intensive and expert tertiary prevention.

We believe that this tertiary prevention should include special education. Special educators should be charged with delivering specialized, expert, tertiary prevention to students who are not helped by prior levels of teaching. We take this controversial position because, once upon a time, there were many special educators in the US who were trained to deliver a most intensive and scientifically validated form of academic instruction. This most intensive version of academic instruction is Data-based Instruction.

Data-based Instruction (DBI)

DBI is a way of individualizing and intensifying teaching. It is based on the assumption that, despite evidence supporting explicit, skills-based teaching for struggling readers, we cannot know a priori whether a specific teaching approach will work for each child. Rather, instructional decisions should be treated as hypotheses that can be tested empirically. DBI involves the following steps:

  1. Establish the current levels of pupil performance and set long-range goals;
  2. Implement high-quality interventions designed to address individuals’ needs, and monitor progress toward those goals;
  3. Check if a pupil is on track toward his or her goals; and
  4. Make changes to teaching if progress is insufficient.

Researchers have conducted systematic investigations of DBI with different groups of children in various academic areas. These have shown there are three key elements that determine whether DBI will have a positive effect on outcomes:

1. Use data effectively For DBI to exert a positive effect on outcomes, teachers must not only use data to determine when to change their instruction, but also use the data to determine what instructional change(s) should be made and how to implement the change. In other words, teachers must be capable of determining how to effectively intensify teaching for individuals.

2. Qualitative not quantitative Students who have responded inadequately to strong primary and secondary efforts are not likely to respond to quantitative approaches to intensifying instruction (such as increasing the frequency or duration of teaching or reducing group size). Rather, they are more likely to benefit from an approach that is qualitatively different from what they have already received. This could include relatively minor changes, such as modifications to who is doing the teaching (eg, a peer rather than a teacher), to delivery (eg, more explicit levels of modeling and guided practice), to opportunities to respond to and receive corrective feedback (eg, using errorless learning approaches), or to motivational enhancements (eg, using goal setting and incentives). Qualitatively different approaches could also involve more significant changes, such as using a different curriculum or teaching approach (eg, from a skills-based approach to one that embeds cognitive training).

3. Instructional experts Despite its strong research base, DBI is not widely implemented. Why is this so? An important explanation is that it requires expert clinician–researchers who are well trained to use time-series analyses to make teaching decisions; who are knowledgeable about a broad array of curricula and programs to test instructional hypotheses; and who have the self-discipline and drive to sustain high-quality, ongoing intensive instruction. Colleges and universities in the US are simply not preparing such professionals, and the implications for service delivery are profound.


Based on our work in US schools, our impression is that when children do not benefit from secondary prevention in an RTI framework, they often face one of two troubling scenarios. They either remain indefinitely in secondary prevention, despite their long-running unresponsiveness, or move to special education, which ends their involvement in RTI frameworks. This special education often comprises in-class accommodations that are less intensive than secondary prevention. We have to wonder whether it signals that schools have given up on teaching their most educationally needy children. Equally troubling is the possibility that these children and the specialized expert teaching they require – which may occur outside the classroom – are being sacrificed because of an inclusion policy that lacks necessary nuance.

Special educators should reorient toward providing intensive support to students for whom primary and secondary levels of prevention are insufficient. We are under no illusions – this reorientation represents a major change in the practice of special education, and will require changes in teacher training and professional development. Furthermore, special education teachers must learn to intensify teaching using data-based, hypothesis-testing approaches for the children who are persistently unresponsive to research-based standard treatments. DBI represents one such promising approach.

About the authors

Doug Fuchs is Professor and Nicholas Hobbs Chair of Special Education and Human Development at Vanderbilt University in Nashville. His research areas include instruction of children at risk for school failure because of disability or poverty, and special education policy. Previously, he taught in a special school in Baltimore and was staff psychologist for the Minneapolis public schools’ special education preschool program.

Lynn Fuchs is Professor and Nicholas Hobbs Chair of Special Education and Human Development at Vanderbilt University. She has conducted research on assessment methods for enhancing instructional planning and on instructional methods for improving reading and mathematics outcomes for students with learning disabilities.

Further reading

Deno SL and Mirkin PK (1977), Data-based Program Modification: A Manual. Reston, VA: Council for Exceptional Children.

Fuchs D, Fuchs LS, and Stecker PM (2010), The “Blurring” of Special Education in a New Continuum of General Education Placements and Services. Exceptional Children, 76, 301–22.

Stecker PM, Fuchs LS, and Fuchs D (2005), Using Curriculum-based Measurement to Improve Student Achievement: Review of Research. Psychology in the Schools, 42, 795–820.

Wanzek J and Vaughn S (2007), Researchbased Implications from Extensive Early Reading Interventions. School Psychology Review, 36, 541–61.


October 2013