571.1
Continuity and Innovation in Higher Education. the Case Study of Sapienza University of Rome "CANCELLED"

Tuesday, July 15, 2014: 5:30 PM
Room: 416
Oral
Alessandra DECATALDO , Sociology and Social research, University of Milan Bicocca, Milan, Italy
Antonio FASANELLA , Communication and Social research, Sapienza University of Rome, Roma, Italy
Guido BENVENUTO , Psychology, Development and Socialization Process, Sapienza University of Rome, Rome, Italy
The paper involves a secondary analysis of longitudinal data of administrative type for a description of the phenomena of student late performance and dropping 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 DM 509/1999 - a didactic reform - (from academic year 2001/2002 to 2006/2007) at Sapienza University of Rome. Each of these batches (about 410,000 student enrolments) was monitored up to 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 another 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.

The assumption behind this research design is that the longitudinal perspective is able to provide an accurate frame of student curricula (that are monitored at intervals of six months) and to reconstruct the potentially relevant events to the outcomes of their university career. Longitudinal panel studies monitor the same generation of students (that is an aggregate of students enrolled during the same year) over several years; consequently these strategies are able to offer quite more accurate results because they reduce the risks related to the utilization of aggregate data.

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.