As data are interpreted and teachers make decisions, they implement tiered instruction (e.g., Tier 1 Core Instruction, Tier 2 Intervention, Tier 3 Intensive Intervention) using evidence-based practices. Data from different assessments (e.g., universal screeners, diagnostic assessments, progress monitoring measures) are associated with specific instructional decisions so as to provide teachers with guidance for interpreting student performance. These frameworks provide systematic approaches to link assessment results with classroom-level decisions to better align instruction with students’ needs ( Choi et al., 2017). Multi-tiered systems of support (MTSS) and data-based individualization (DBI) represent systems-level frameworks in which instruction and assessment are integrated into one coherent system with the goal of supporting positive outcomes for all students. We also propose future studies to empirically evaluate the assertion of parallel form difficulty. An example from an operational progress monitoring system for mathematics in Kindergarten through Grade 6 is used to illustrate the process. This approach adapts the principles of Automated Item Generation (AIG) and includes carefully designing test specifications, isolating specific components of the content that will be assessed, creating item models to serve as templates, duplicating the templates to create parallel item clones, and verifying that the duplicated item clones align with the original item model. In this manuscript, we describe an approach to designing items that controls item-level variability by constraining the item features that may elicit different cognitive processing. The sets of items administered over time should be parallel in difficulty so that differences in performance can be attributed to differences in the student’s understanding as opposed to variability in item difficulty across sets. Progress monitoring involves administering parallel sets of items to the same student on a regular basis (at least monthly) that are sensitive to changes in the student’s understanding based on instruction. Progress monitoring is a process of collecting ongoing samples of student work and tracking performance of individual students over time. 3Research in Mathematics Education, Southern Methodist University, Dallas, TX, United States.2American Medical Technologists, Chicago, IL, United States.1Education Policy and Leadership, Southern Methodist University, Dallas, TX, United States.Ketterlin-Geller 1* Anthony Sparks 2 Jennifer McMurrer 3
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