Activity Monitoring

The monitoring of Ph.D. program activities can be divided into three broad categories: a) a detailed analysis of the activities of individual Ph.D. students; b) the evolution over time of various indicators (such as those from ANVUR, but not limited to them); c) the analysis of questionnaires administered to Ph.D. students.

 

Detailed Analysis of Doctoral Students' Activities

This is carried out by the Faculty Board through an analysis of each doctoral student's logbook, which documents all stages of their academic journey (courses taken, seminars, workshops, research periods abroad, conference participation, and scholarly output). At special meetings held at the end of each year, the Faculty decides, for each doctoral student, whether to admit them to the following year (2nd and 3rd years) or to allow them to present their final dissertation.

 

Quality Assurance and Monitoring of Ph.D. Programs

The University of Naples Federico II, in compliance with ANVUR guidelines (AVA3 Model) and current regulations (Ministerial Decree 226/2021), has adopted an integrated Quality Assurance (QA) system for its Ph.D. programs. The system is based on the ongoing analysis of quantitative system indicators and active engagement with doctoral students, with the aim of ensuring the continuous improvement of the educational offerings, research activities, and support services.

Monitoring of ANVUR Indicators

The assessment of the stability, sustainability, and attractiveness of doctoral programs relies on the official indicators developed by the National Agency for the Evaluation of the University and Research System (ANVUR).

Through the University System Dashboard, the University constantly monitors key quantitative data, ensuring transparency in the following areas: These statistical indicators are complemented by the Doctoral Program Self-Assessment Report, prepared by the Faculty Council to monitor the adequacy of research infrastructure, the scientific qualifications of supervisors, and the effectiveness of internal management processes.

  • Attractiveness and Enrollment Trends: Data on enrollment, progression rates to subsequent program levels, geographic origin (domestic and international), and gender distribution of doctoral students.
  • Financial Sustainability: Percentage of scholarship coverage relative to the number of positions advertised and the breakdown of funding sources (ministerial funds, PNRR, corporate and foreign co-funding).
  • Results and Careers: Rates of completion of the Ph.D. degree.

Ph.D. Student Opinion Survey (ROPiD System)

The direct involvement of Ph.D. students is a cornerstone of the University's quality assurance system. To collect structured and anonymous feedback on the educational and research experience, the University uses the official ROPiD system (Ph.D. Student and Doctoral Graduate Opinion Survey).

The monitoring process consists of two main surveys: Completing the ROPiD questionnaires is a fundamental institutional requirement. The data collected are processed in aggregated and anonymous form.

  • SQ-D Form (Current Ph.D. Students): Aimed at Ph.D. students in the middle years of their program, this form is designed to evaluate the organization of instruction, the effectiveness of supervision and tutoring, the adequacy of material resources (laboratories, libraries, workstations), and the impact of the workload.
  • SQ-DR Form (Ph.D. Graduates): Completed at the end of the program or immediately after earning the degree. It provides an overall assessment of the three-year experience, the acquisition of transferable skills, and prospects for employment.

For more information, please refer to the University guidelines for surveying the opinions of doctoral candidates and PhD graduates

Data Analysis and Improvement Cycle

The results of ANVUR monitoring and the findings from the ROPiD questionnaires are periodically incorporated into the analyses conducted by the University Quality Assurance Office (PQA) and the Evaluation Unit.

The evidence gathered enables program coordinators and faculty councils to identify potential issues, design corrective measures, and plan strategies for improvement, thereby closing the self-evaluation cycle and ensuring high standards of quality for research and graduate education.

 

Here in the following the members of the more recent (41st cycle) PhD faculty staff: