Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…

Since 2012, the Wisconsin Department of Public Instruction (DPI) has maintained a statewide predictive analytics system providing schools with an early warning in middle grades of students at risk for not completing high school. DPI is considering extending and enhancing this system, known as the Dropout Early Warning System (DEWS). The proposed…

The Texas Projection Measure (TPM) has grown out of the state's need to meet the requirements of No Child Left Behind (NCLB). An examination of the state's method of predicting 8th grade mathematics scores reveals that several factors have been ignored in the process of developing the model, including assumptions in its underlying statistical…

EXPERIMENTS WERE PERFORMED TO DETERMINED HOW MENTALLY RETARDED AND NORMAL SUBJECTS SYNTHESIZE STIMULI WITH RESPONSES. ALSO, RELATIONSHIPS AMONG THE STIMULUS SYNTHESIS PROCESS, INTELLIGENCE, AND RATE OF LEARNING WERE STUDIED. DISCRIMINATION TASKS WERE USED WHICH REQUIRED SUBJECTS, NORMAL (COLLEGE, HIGH SCHOOL, AND GRADE SCHOOL ENROLLEES) AND…