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IES Grant

Title: The Consequences for High School Students of Failing State Exit Exams: Evidence from Massachussetts
Center: NCER Year: 2008
Principal Investigator: Murnane, Richard Awardee: Harvard University
Program: Improving Education Systems      [Program Details]
Award Period: 2 years Award Amount: $193,369
Type: Exploration Award Number: R305A080127

Purpose: Over the past two decades, a growing number of states have implemented high-stakes exit examinations that students must pass to graduate from high school. Exit exams are often justified as a means to verify that high school graduates have mastered important knowledge and skills. However, concerns have been raised that exit exams may cause students, particularly those from low income and urban backgrounds who are already struggling in the educational system, to drop out of high school or decide against postsecondary education. This project will develop evidence regarding whether the concern over the adverse impacts of exit exams, primarily for struggling students, is valid or not.

Project Activities: The project will use two longitudinal datasets from the Massachusetts Department of Education: one that tracks students through their high school career (including their 10th grade exit exam results and their scores on an 8th grade low stakes exam) and the other that links student data to their records in the state's higher education system. Using a regression discontinuity design, the project will examine whether failing one or both of the 10th grade exit exams causes students near the border of passing to be more likely to drop out of high school or to be less likely to enroll in or graduate from college. In addition, the project will examine whether failing the low stakes 8th grade exam causes students who are near passing to drop out before taking the 10th grade exams.

Products: The products from this project will be evidence regarding the impact of failing high school exit exams on later school dropout and college entry and persistence that will be provided in published reports.

Structured Abstract

Setting: The research team will be examining data on students in the Massachusetts secondary school system and higher education system.

Population: The population includes graduation cohorts of Massachusetts students from 2006, 2007, and 2008 for almost 200,000 student records.

Intervention: The Massachusetts Comprehensive Assessment System is the intervention being studied, specifically its assessments in two grades. The primary intervention is the high-stakes, 10th grade, exit examinations in English and Math. A secondary intervention is the low stakes 8th grade exam.

Research Designs and Methods: A regression discontinuity design is used to compare students who fall just short of the state-set cut-off score for passing the exams (and so fail) with students who just pass. The design is based on two assumptions: (1) that the relationship between score and graduation is smooth around the cut-off score, and (2) that students have no influence over whether they pass or fail other than their performance on the test. These two assumptions allow a determination as to whether the relationship between graduation and test score is discontinuous at the cut-off score. If so, the discontinuous disruption in the graduation outcome provides an unbiased estimate of the causal impact of failing the exam.

Control Condition: Students who score just above the cut-off point for passing the exams are used as the control group under the assumption that they should be similar in motivation and skills to students who score just under the cut-off point.

Key Measures: The key outcome measures are whether a student graduates or drops out of high school, whether a student enrolls in college, whether the student requires remediation courses in college (based on a standardized placement exam score), and whether the student graduates from college (two year or four year). Covariates include student race, gender, and limited English proficiency status, and fixed effects for school district (or an indicator of urban district).

Data Analytic Strategy: Logistic regression analysis is used to model the relationship between the dichotomous outcome variables and exam score (both raw score and whether the student passed or failed), controlling for the covariates. The models will be estimated for failure on the English exit exam, the math exit exam, and then both exams. Additional analyses will examine whether differences in student success on specific subgroups of the test items (e.g., open-ended or writing prompts) leads to different outcomes for students with the same total score. Supplementary analyses will examine the impact of failing the exams for subgroups such as urban students and also examine whether subgroups have different rates of retaking the test and score differently on retests. A similar analysis will be done using the 8th grade exam using high school dropout before the 10th grade exam as the outcome measure.

Related IES Projects: Intended and Unintended Consequences of State High-Stakes Testing: Evidence from Standards-Based Reform in Massachusetts (R305E100013)


Journal article, monograph, or newsletter

Papay, J., Murnane, R.J., and Willett, J.B. (2010). The Consequences of High School Exit Examinations for Low-Performing Urban Students: Evidence From Massachusetts. Education Evaluation and Policy Analysis, 32 (1): 5–23.

Working paper

Papay, J.P., Murnane, R.J., and Willett, J.B. (2008). The Consequences of High School Exit Examinations for Struggling Low-Income Urban Students: Evidence From Massachusetts, Working Paper 14186 (NBER 14186). Cambridge, MA: National Bureau of Economic Research Working Paper.

** This project was submitted to and funded under Middle and High School Reform in FY 2008.