Students' Careers and AI: a decision-making support system for Academia

In the peculiar realm of higher education, some of the challenges of Public Administration, in terms of quality assurance and data intelligence, can be addressed thanks to the complex ecosystem based on the careers of students and their engagement with the host academia. University governance, ranging from the university Rector and Quality Assurance committee to single heads of degree courses, needs to rely on quantitative and unbiased measures when designing and planning actions. This paper reports on an ongoing project started at Parma University in 2019, that has multiple goals: (1) to collect various sources of students' career-related raw data and to and provide simple access to aggregated analyses through a web portal; (2) to offer an AI based synthesis, in form of automatically generated reports in natural language; (3) to analyze data to detect and predict potential issues (e.g., students drop-out, classes attendance, graduation time estimations, blockages in the career) that can be promptly highlighted, for immediate intervention. As opposed to the majority of academic analytics implementations, particular care is devoted to minimizing ethics and privacy issues and adhering to explainable AI principles in the generation of synthetic explanations of charts and reports. The results of lines of research (2) and (3) will be integrated in the portal (1) that is currently deployed at Parma University.