Center co-leads discuss their research in automated scoring and performance assessment in this video series.
Dr. Peter Foltz discusses some of the research goals for the Center for Next Generation Learning & Assessment; how automated scoring, immediate feedback, and reading complexity measures can help personalize instruction and learning for students. Or view a shorter Center overview.
Steve Ferrara describes one topic the Center for Next Generation Learning & Assessment is currently focused on; performance assessment. He discusses the influence performance assessment can have on student achievement, the challenges this type of assessment brings to students and educators, and the benefits performance assessment can bring to instruction. Or view a shorter Center overview.
The Reading Maturity Metric (RMM) uses latent semantic analysis to measure the complexity of a passage and assign it a reading level/score. RMM is more accurate than standard measures and how this tool can help align curriculum to new college readiness standards and personalize learning for each student.