Reducing Student Absenteeism
Category: Student Learning
This study investigates how absenteeism can be more rigorously measured as an early warning indicator of future academic risk. Using administrative data from 8,891 Boston Public Schools students followed from Pre-K through eighth grade, we (1) describe patterns in excused, unexcused, and total absences, measured as both days and rates, across grades; (2) apply Signal Detection Theory and Receiver Operating Characteristic (ROC) curve analyses to compare the diagnostic accuracy of different absenteeism measures for predicting standardized test scores; (3) use Youden’s J to identify optimal thresholds for defining chronic absenteeism; and (4) examine how the diagnostic accuracy of different absence measures varies with temporal proximity to academic outcomes. We find that total absence rate provides the most consistent diagnostic signal across grades and that diagnostic accuracy increases with temporal proximity, with same-year or immediately preceding-year absences generally providing the strongest signal. Notably, empirically derived thresholds for identifying students at risk using Youden’s J consistently fall below the widely used 10% chronic absenteeism benchmark, generally around 7-8% in Pre-K and kindergarten and 3-6% throughout the elementary and middle school grades.
Keywords
chronic absenteeism, student attendance, receiver operating characteristic (ROC) curves, signal detection theory, Youden’s J, early warning indicator
Education level
Topics
Document Object Identifier (DOI)
10.26300/1zvw-qw93
