Student attrition, although some to be expected, comes at a high cost. Failure to complete studies is recognized as a personal loss for the individual, an economic loss for the universities, and an intellectual loss for society. While extensive research efforts have been used to develop and improve theoretical models of student retention or persistence, a concern of many administrators remains the ability to predict as early as possible the likelihood of a student dropping out of school. Following these recommendations, this present study employed the analysis of secondary and program specific data to examine the predictive impact of student characteristics on persistence in an online doctoral leadership program. This research examined individual differences that exist in the leadership development of doctoral students that would contribute to and predict success and persistence in leadership development programs. The study has used a logistic regression to test whether critical thinking, leadership effective behavior, Master's GPA, gender, application summary score, and psychological type are positively related with academic retention/completion amongst doctoral students enrolled in an asynchronous-distance program in leadership studies. Findings emphasize the importance of behavioral characteristics, such as effective leadership and psychological type, in regard to persistence. LPI-Modeling the Way emerged as a significant predictor for retention and persistence in the online doctoral leadership studies program, a finding that - to this date - did not surface in any other research pertaining to retention or persistence. As such, this article focuses on the impact of effective leadership behavior in general and Modeling the Way in particular and why it is, indeed, a significant factor in student success and retention
Student attrition, although some to be expected, comes at a high cost. Failure to complete studies is recognized as a personal loss for the individual, an economic loss for universities, and an intellectual loss for society. While extensive research efforts have been used to develop and improve theoretical models of student retention or persistence, a concern of many administrators remains the ability to predict as early as possible the likelihood of students dropping out of school.
Research findings suggest that the strongest predictor of graduation is a student's conformity with the characteristics of those who have graduated from the same institution or program previously (Ash, 2004; Mansour, 1994). Institutions routinely collect a broad array of information on their students' backgrounds, socioeconomic status, past academic achievement, social involvement, and even personal characteristics. All factors that align well with the major theoretical models of student retention (Ash, 2004; Astin, 1984; Bean, 1985; Mansour, 1994; Tinto 1987, 1993). Several researchers therefore contend to make institution- specific predictions about retention and attrition based upon the increasing amount of student assessment data that are being collected by institutions of higher education (Seidman, 1995; Johnson, 1997; Murtaugh, Burns & Schuster, 1999). Their research indicates that analysis of readily available student data specific to a particular university and program can, indeed, be a valid predictor for student persistence and retention. Johnson (1997) suggested that each institution create its own predictor equations based on the characteristics of students who have succeeded in the past. Knowledge of students who are most likely to succeed and who are at risk to drop out may provide administrators and educators with the information necessary to develop strategies that encourage, guide, and motivate students through to degree completion. Once specific characteristics or tendencies are recognized, effort can be directed toward the development of programs and practices to help students overcome weaknesses and encourage a greater level of persistence. …