Evaluation of the Italian University reform policies. A case study

Studies on university productivity show that little has changed though of the enforcement of DDMM 509/1999 and 270/2004: the long-standing ills that had afflicted the Italian university under the previous system still continue to affect it even after the adoption of the “3+2” reform. These considerations on productivity of the university system are alarming especially in terms of the objectives that the DM 509/1999 intended to achieve and the expectations of what was invested. These expectations concern the control on productivity (more regular graduates) and an approach to academic and working life, maintaining high standards of quality training. It seems that has not worked out in the process of change from the old to the new university system. Italian university has answered to external pressures absorbing change content in pre-existing organizational structures and cultural background. We are conducting a research that allows for an in-depth examination of the phenomenon of poor productivity of the university system, and also sheds light on some of the factors that combine to determine this result. The Sapienza University of Rome was identified as an ideal context for this analysis, due to its dimensions and complexity, and because of its variety of scientific and educational areas of academic training. The research involves conducting a secondary analysis of longitudinal data of administrative type for a description of the phenomena of late performance and student drop out. It focuses on the batches of students enrolled in specific key moments before (from academic year 1991/1992 to 2000/2001) and after the reform (from academic year 2001/2002 to 2006/2007). Each of these batches (about 410,000 student enrolments) was monitored up to April 2008 (the official closing date of academic year 2006/2007). The analysis take into account ex novo enrolments, excluding both the re-registrations and students who have already obtained more than one degree. Longitudinal analyses (the generational approach) allow us to individually monitor students in a single generation for a number of years, reduce the risks associated with aggregate data. This data - required statistical office of Sapienza - were treated to obtain variables in line with the present research and then be reorganized into a diachronic database. From a practical point of view, we analyzed how the DM 509/1999 was introduced and implemented within and by the university organization (analyzing a wide variety of phenomena such as dropping out, delayed and decreasing graduations). From a methodological point of view, we came to the creation of longitudinal multidimensional models of the students’ careers, aiming at identifying the “mechanisms” through which from an initial state t0, a subsequent state t1 is generated.