“Current data-based methods of analysis and predictive models are insufficient – big data is able to remedy this. ”
– Dr. Alexander Lenk
Pass/fail decisions by faculty are mostly based on the ability of students to pass or fail prior to (Angoff) or post standard setting (Borderline Regression Analysis) criteria developed by faculty. Standard setting is a critical part of educational, licensing and certification testing. But outside of the cadre of practitioners, this aspect of test development is not well understood. Standard setting is the methodology used to define levels of achievement or proficiency and the cut-scores corresponding to those levels. A cut-score is simply the score that serves to classify the students whose score is below the cut-score into one level and the students whose score is at or above the cut-score into the next and higher level.