1 resultado para predictor-corrector methods

em Digital Commons at Florida International University


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Accurately predicting the success of graduate students is an important aspect of determining which students should be admitted into graduate programs. The GRE is a pivotal factor to examine since it is one of the most widely used criteria for graduate school admission. Even though the GRE is advertised as an accurate tool for predicting first year graduate GPA, there is a lack of research on long term success factors such as time to degree and graduate rate (Luthy, 1996; Powers, 2004). Furthermore, since most studies have low minority sample sizes, the validity of the GRE may not be the same across all groups (ETS, 2008b; Kuncel, Hezlett, & Ones, 2001). Another gap in GRE studies is that few researchers analyze student characteristics, which may alter or moderate the prediction validity of the GRE. Thus, student characteristics such as degree of academic involvement, mentorship interactions, and other academic and social experiences have not been widely examined in this context. These gaps in the analysis of GRE validity are especially relevant given the high attrition rates within of some graduate programs (e.g., an estimated 68% of doctoral student never complete their programs in urban universities; Lovitts, 2001). A sequential mixed methods design was used to answer the research questions in two phases. The quantitative phase used student data files to analyze the relationship of two success variables (graduation rate and graduate GPA) to the GRE scores as well as other academic and demographic graduate student characteristics. The qualitative phase served to complement the first phase by describing a wider range of characteristics from the 11 graduate students who were interviewed. Both proximal and distal moderators influence student behaviors and success in graduate school. In the first phase of the study, the GRE was the distal facilitator under analysis. Findings suggested that both the GRE Quantitative and the GRE Verbal were predictors of success for master’s students, but the GRE Quantitative was not predictive of success for doctoral students. Other student characteristics such as demographic variables and disciplinary area were also predictors of success for the population of students studied. In the second phase of the study, it was inconclusive whether the GRE was predictive of graduate student success; though it did influence access to graduate programs. Furthermore, proximal moderators such as student involvement, faculty/peer interactions, motivational factors, and program structure were perceived to be facilitators and/or detractors for success.