Developing Optimized Adaptive Interventions in Education

Abstract

Hedges (2018) encourages us to consider asking new scientific questions concerning the optimization of adaptive interventions in education. In this commentary, we have expanded on this (albeit briefly) by providing concrete examples of scientific questions and associated experimental designs to optimize adaptive interventions, and commenting on some of the ways such designs might challenge us to think differently. A great deal of methodological work remains to be done. For example, we have only begun to consider experimental design and analysis methods for developing "cluster-level adaptive interventions" (NeCamp, Kilbourne, & Almirall, 2017), or to extend methods for comparing the marginal mean trajectories between the adaptive interventions embedded in a SMART (Lu et al., 2016) to accommodate random effects. These methodological advances, among others, will propel educational research concerning the construction of more complex, yet meaningful, interventions that are necessary for improving student and teacher outcomes.

Figures

Figure 1

An example of one adaptive intervention for improving language outcomes in children with autism who are minimally verbal. This adaptive intervention is typical of usual care (e.g., business-as-usual) in children with autism. This is an intervention design, not a study design.

Figure 2

An example 2-arm randomized trial comparing two adaptive interventions that differ in terms of their stage 1 intervention but are similar in terms of stage 2 strategy (continue intervention for responders, or intensify intervention for slower responders). The adaptive intervention that begins with DTT is the same one shown in Figure 1.

Figure 3

An example sequential multiple assignment randomized trial (SMART). This SMART includes four embedded adaptive interventions, including the one shown in Figure 1 (cells D and E).