HLP 10

Students, including those with disabilities, who do not make sufficient progress in the general education setting, even with supplemental intervention, may require highly intensified, individualized instruction to meet their learning and/or behavioral needs. Although a schoolwide tiered system of supports can reduce the number of students requiring academic or behavioral intervention, approximately 3-5% of students will still need intensive supports (NCII, 2013). In some cases, these students may require as many as 10 to 30 times as much practice as their peers to learn and retain new information (Gersten et al., 2009). Additionally, students requiring this level of intervention often experience complex, co-occurring academic and behavioral needs that require more intensive instructional strategies (Kuchle & Riley-Tillman, 2019).

A recent systematic review of meta-analyses found that out of all the HLPs, intensive instruction has the greatest quantity of evidence supporting its effectiveness with students with disabilities (Nelson et al., 2022). Furthermore, the review found some level of evidence demonstrating the effectiveness of intensive instruction for students in every disability category and every domain of interest (e.g., reading, mathematics, behavior) with the exception of writing. The robust amount of research supporting intensive instruction as an effective strategy for students with disabilities underlines the importance of providing a full continuum of supports to meet students’ needs (Lemons et al., 2018) and affirms its importance within the HLP framework.

Other recent research syntheses have focused on the processes that support the provision of intensive instruction, such as data-based individualization and data-based decision making. For example, a meta-analysis of studies found that use of data-based individualization with K-12 students with intensive learning needs (including those with disabilities) had statistically significant positive effects on student performance across the domains of reading, mathematics, and spelling/writing (Jung et al., 2018). Further narrative synthesis of the included studies found that educator supports are critically important for effective data-based individualization (Fuchs et al., 2021). Another meta-analysis found that data-based decision making, defined as using data to make decisions about when and how to adjust instruction for individual students, had a positive overall effect on reading intervention outcomes for struggling K-12 readers (Filderman, et al., 2018). These research syntheses and their associated studies offer strong support for using data to drive decisions about intensifying instruction for individual students.

Throughout the DBI process, professionals actively consider how these carefully orchestrated instructional moves and decisions consider a student’s unique cultural, linguistic, familial, and learning background while maintaining high expectations for student success. Table 10.2 provides educators with guiding prompts throughout each step of the DBI Process.