“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 […]
Controversies Standard Error of Measurement and Borderline Regression Method in an OSCE Management System
The Standard Error of Measurement (SEM) indicates the amount of error around the observed score. The observed score, the score we retrieve, store and analyse from an OSCE, is in fact the result of the true score and error around this true score. If we want a reliable decision around passing or failing a station […]
Borderline Regression Analysis in Assessment
Borderline regression analysis (BRA) is an absolute, examinee-centered standard setting method widely used to standard set OSCE exams, Yousuf, Violato, and Zuberi (2015). Candidates are awarded a “global score” for a station in a circuit, based on the examiner’s professional judgment of their ability. Borderline Regression Method is illustrated above using item score on the […]