Next-generation SATA (Select-All-That-Apply) question formats - from classic selection to meta-cognitive reasoning
How SATA formats are grounded in psychometric theory, assessment science, and measurement validity frameworks
SATA formats leverage polytomous IRT models (Partial Credit, Graded Response) for precise ability estimation. Unlike binary scoring, partial credit captures nuanced competency levels, reducing measurement error by 30-40% (Embretson & Reise, 2000).
Multiple correct options increase content coverage per item (Messick, 1995). Evidence-based and meta-cognitive formats add construct-relevant variance, better aligning assessment with underlying cognitive processes and reducing guessing.
Response patterns reveal misconceptions and partial knowledge states. Weighted, confidence-rated, and elimination formats provide richer diagnostic data than traditional MCQs, supporting formative assessment and adaptive remediation.
SATA items provide more information per question, enabling shorter adaptive tests with equivalent reliability (α = 0.85+ achievable with 30% fewer items). Matrix and progressive formats optimize information functions across ability continuum.
UALS SATA formats combine psychometric science with adaptive testing innovation, supporting Item Response Theory, Computerized Adaptive Testing, and next-generation assessment validity
"Select one correct answer"
"Select all that apply"
"Psychometrically-validated adaptive assessment"
Psychometrically-validated assessment formats with IRT foundations
Choose the format backed by psychometric science and IRT theory