Background/Context: In the early elementary grades, many students do not achieve literacy proficiency due to inadequate personalized literacy instruction (Taylor et al., 2010). Despite increasing evidence that differentiated instruction informed by assessments of students' reading abilities can improve learning more effectively than one-size-fits-all instruction (Connor et al., 2011a, 2011b), a lack of training and support often makes it difficult for teachers to implement differentiated instruction in classrooms. Intervention/Program/Practice: The Assessment-to-Instruction (A2i) Professional Support System seeks to bridge this gap. It combines data-driven technology with professional development (PD) activities to help teachers use differentiated small-group instruction to improve literacy achievement among K-3 students (Figures 1 and 2). Prior studies have shown compelling evidence of A2i's effectiveness in 28 Florida and Arizona schools since 2005 (Connor et al., 2007; Connor et al., 2011a; Connor et al., 2022). These studies delivered A2i through face-to-face training and ongoing PD. However, the intensive personal attention requires substantial investment in PD, making large-scale implementation difficult and expensive. To identify ways to scale A2i, this study focuses on a mixed-mode PD model that aims to lower PD costs by harnessing the power of technology. In contrast to resource-intensive face-to-face PD, the new model supports implementation of A2i through virtual and in-person coaching, with a significant amount of PD occurring remotely through video conferencing (Table 1). This approach aims to maintain A2i's focus on personalized PD while improving coaches' productivity by reducing travel time. Purpose/Objective/Research Question: This study intends to assess whether the mixed-mode model can be a viable alternative to the face-to-face approach in supporting teachers' use of the A2i system and differentiated small group instruction and improving student reading skills. The research questions are: (1) How well were the models implemented? Did PD implementation differ between the models as expected? (2) Did the models affect teachers' use of the A2i technology differently? (3) Did these models produce differences in teachers' views of A2i and their instructional practices? and (4) Did these models lead to differences in the effect of A2i on students' reading achievement three years after the program started? Research Design and Study Setting: In spring 2018, the study recruited 59 elementary schools from 20 districts around the country and randomly assigned roughly equal numbers of schools to either the mixed-mode or the face-to-face model within districts or district groups. Figure 3 illustrates how the two models were rolled out in these schools over three school years. This school-level Randomized Controlled Trial design determines that any difference between these two groups of otherwise similar schools can be attributed to their exposure to different PD models. If both models were implemented adequately, a finding of no difference in student outcomes would indicate that the mixed-mode model is as effective as the face-to-face model in helping young students read. A separate analysis was planned to assess each model's effectiveness by using a comparative interrupted time series (CITS) design. However, due to COVID-related data issues, the study was not able to carry out this analysis. Population/Participants/Subjects: The 59 study schools predominantly serve high-need students. In Fall 2018, 61% of students in the average study school were Hispanic and 72% were eligible for the free and reduced-price lunch program. There were 27% English learners at the average study school, 13% students with special needs, and 43% of third-graders who could read proficiently (Table 2). For the analysis of student outcomes, the study focuses on students who were at the study schools for all three implementation years by following a cohort of 4,733 first graders enrolled at the start of 2018-19 (Table 3). Data Collection and Analysis: To assess the differential impacts of the two models on A2i implementation, teacher instruction, and student reading achievement, multiple measures were collected for schools, teachers, and students (Table 4). The study uses a multilevel regression model to estimate differences in program experience and outcomes between two groups of schools. The model accounts for data clustering and random assignment blocking. It also controls for relevant student background characteristics to improve statistical precision. Findings/Results: COVID-19 disrupted the implementation of the two models (Figure 4), resulting in the following findings--(1) Before COVID, teachers in mixed-mode and face-to-face schools received PD that differed in amount and delivery mode as intended. However, teachers did not fully utilize A2i technology and had difficulty differentiating instruction based on A2i recommendations; (2) In the second half of the implementation period, in-person PD was not possible due to COVID-related school disruptions, diminishing contrasts between PD received by the two groups. Teachers also reduced their use of A2i components and differentiated small group instruction; and (3) Student achievement in reading across all three years was similar in both groups, and about half of the third graders in the study were reading at or above proficiency level at the end of the evaluation (Figure 5). However, because the full implementation of A2i was not realized, these results do not reflect the actual relative effectiveness of the two PD models. Conclusions: COVID significantly hindered the study's ability to address the key research questions. Due to COVID, A2i usage was lower than expected in both groups, and contrasts between them were diminished. Therefore, the findings did not provide an accurate picture of the two models' actual relative effects if adequately implemented under normal circumstances. Nonetheless, the study learned valuable lessons from school and teacher experiences with A2i. Obtaining buy-in from teachers, understanding local context, tailoring the PD to meet teachers where they are, and building feedback circles between providers, districts, and practitioners are some examples. Future implementation of A2i could benefit from these lessons. A2i is a promising program that bridges the data-to-instruction gap in reading education. It has strong empirical evidence and can be a valuable tool to help students get back on track in the post-COVID era. Therefore, it remains important to expand its evidence base and explore ways to deliver it to more early readers in need.