Development of a practical model for school leaders using elementary student data to predict high school dropout risk

Abstract

Many researchers have identified the myriad of concerns that frequently affect people who drop out of school prior to high school graduation. These include increased risks of lower income, need for welfare support, unemployment, and criminal activity (Alexander, Entwisle, & Horsey, 1997; Christenson & Thurlow, 2004; Gleason & Dynarski, 2002; Suh, Suh, & Houston, 2007). School leaders have a keen interest in helping all students successfully complete school, thereby reducing the risk of these issues occurring later in life. In an effort to help students avoid these potential risks, school leaders have tried to identify students at risk of dropping out of school so they can intervene and help the students persist to graduation. Researchers have documented the ineffectiveness of high school intervention efforts (Bowers, 2010) as well as the greater effectiveness of earlier interventions (Entwisle & Alexander, 1993; Suh et al., 2007). As a result, there has been more emphasis placed on identifying potential dropouts earlier in their educational careers. This study has attempted to develop a practical dropout prediction model based on elementary data. The study examined 222 students who entered high school together, then collected data from when those same students were in elementary school. The resulting models did not have high levels of predictive accuracy, but they did provide some useful results for identifying the students most severely at risk of dropping out. In addition, the study has provided some useful knowledge to aid in further research on identification and intervention efforts.