Evaluation of student performance data to determine when to intensify, fade, or change instructional interventions. Supports teachers in documenting progress and justifying evidence-based modifications for individual learners.
A multi-day progress-monitoring system designed to assess and track IEP goals for following multi-step functional reading instructions. It includes 10-trial combined-measure data sheets, realistic vocational and project task cards, and assessment administration protocols.
This sequence teaches undergraduate students how to use systematic data collection to identify behavioral escalation patterns. Students transition from subjective descriptions to objective operational definitions, analyze antecedents, track behavior metrics, and use scatterplots to predict future incidents, culminating in the creation of data-driven Behavior Intervention Plans.
This sequence explores the implementation and monitoring of IEPs for 11th-grade students, focusing on data collection, progress reporting, secondary transition planning (ITP), and the ethical balance between legal compliance and educational quality. Students transition from being passive participants to active designers and evaluators of the IEP process.
A comprehensive graduate-level sequence on the visual analysis of behavioral data, covering graph construction, interpretive dimensions (level, trend, variability), statistical aids, and experimental design logic. Students learn to make evidence-based clinical decisions through rigorous data interpretation.
This graduate-level sequence focuses on the technical proficiencies required for high-quality Functional Behavior Assessments (FBAs). Students will master indirect assessment methods and direct observation techniques, critiquing the validity and reliability of various data systems to ensure accurate behavioral triangulation.
This advanced sequence explores the integration of measurement and analysis into behavioral intervention decision-making. Students learn to establish stable baselines, monitor treatment fidelity, and use quantitative data to determine when to modify, fade, or maintain supports.
