Each school year, roughly a thousand students drop out of Montgomery County Public Schools (MCPS). However, unlike other large, urban school districts where students who drop out skip school and are suspended often (Balfanz & Byrnes, 2010), students who drop out of MCPS are present in school; they just are not doing well academically. According to the end-of-year MCPS attendance files provided to the Maryland State Department of Education (MSDE) each year, students who drop out of MCPS are generally coded as dropping out of school due to: 1) a lack of personal motivation or interest to continue their education, or 2) a lack of academic success, including low grades and/or retention. These are both signs of a lack of student engagement (i.e., investment and motivation towards school). Fortunately, students who drop out of school exhibit a pattern of behaviors that are generally identifiable in advance. These behaviors are referred to as Early Warning Indicators (EWIs).

EWIs use student-level data including attendance, behavior, and course performance (the ABCs) to identify cutpoints that are related to an increased likelihood of students dropping out of school. With longitudinal data systems, these patterns have generally been identified by Grade 6 (Balfanz & Byrnes, 2010), but can be identified as early as Grade 3 (Rethinam & West, 2012). By applying the EWIs approach to MCPS student data, this report illustrates how a continuous EWI approach can use attendance, behavior, and course performance patterns to identify high school dropouts well in advance of them dropping out. Specifically, this report focuses on the first marking periods of Grades 3, 6, and 9. Additionally, for the first time in EWI research, this report identifies EWIs for Grade 1.

The following research questions are addressed in this study:

1. What are the attendance, behavior, and coursework patterns at the end of marking period three for Grade 1 students, and at the end of marking period one for Grades 3, 6, and 9 students who eventually drop out of high school?
2. For each of the time points, what is the likelihood of students dropping out by each EWI?
3. Are the EWIs for identifying the MCPS high school Class of 2011 dropouts reliable at identifying the Class of 2012 dropouts?

To analyze these questions, a series of cross tabulations and logistic regressions are examined to analyze the relationship between various attendance, behavior, and coursework cutpoints and dropout status.

Download the full report, available here in pdf. Published by the Office of Shared Accountability for Montgomery County Public Schools in Rockville, Maryland.

Download the full presentation, From Start to Finish Presentation NCES STATS-DC 2013.

See Education Week’s coverage of this report, available at Education Week’s website here.

See Time Magazine’s evaluation of the impact of this report and the conversation around it, available at the Time Magazine website, here.

Read a UK perspective on the US study here.

See the Washington Post coverage, available at the Washington Post website here.