Web based methodologies and techniques to monitor electronic resources use in university libraries

The aim of this paper is to measure user satisfaction and the quality of the electronic resources consultation services offered by the Milano Bicocca University Library

Emotion recognition in Italian political language to predict positionings and crises government.

The paper aims to analyze the political language adopted on Twitter by the main Italian parties’ leaders during the first two waves of Covid-19 pandemic. A two-step model based on sentiment emotion recognition (ER) and Correspondence analysis detected which emotions characterized the political language and which changes happened between the two waves. The results showed the use of a language with a strong emotional weight for some political actors as opposed to others who used a neutral register of political language in both waves. The comparison between two waves denoted a shift from anger to sadness and fear for Meloni and a moving away Salvini by predicting through ER the rift of the right-wing

Evaluation of human capital in education-based perspective

This paper considers one of the intangible aspect of human capital: the university knowledge accumulation. It is relevant both for academic management and for recruitment world. In the former case it can be an useful guide to identify the characteristics of clever students, while in the latter case it can be applied to worker selection. Because of the velocity of credit acquisition is not sign of cleverness, it becomes important to analyze different aspects of university human capital accumulation. We will investigate it through latent growth modeling on administrative data come from an Italian university

Web based methodologies and techniques to monitor electronic resources use in university libraries

The aim of this paper is to measure user satisfaction and the quality of the electronic resources consultation services offered by the Milano Bicocca University Library

Chapter Emergency remote teaching: an explorative tool

The worldwide rapid spread and severity of the infectious disease caused by Coronavirus forced the WHO to declare a global state of pandemic emergency during March 2020, by leading the governments around the world to adopt policies that created the widest rift of education systems in human history. Italy have temporarily closed each educational institution, by causing the disruption of tertiary education for 16.89% of the Italian learner’s population. To ensure the “pedagogic continuity”, universities adopted the transitioning from traditional face-to-face to online learning. This paradigm shift to fully remote teaching solutions represents the so-called emergency remote teaching (ERT) in contrast to the traditional teaching inspired by Bologna process principles such as teaching quality and student satisfaction. In a landscape of emerging difficulties connected to ERT contexts, the quality assurance of higher education recalled by the Bologna Process may be not appropriate. We propose an evaluation model for the quality and ERT success across two dimensions used as proxy variables: students’ engagement (SE) and success performance (SP). Within the faculties, we analysed the performance and hence the knowledge, skills and/or attitudes acquired by learners, within the students, the focus was the engagement as interest, motivation and involvement. Under this perspective our research question has an explorative nature: we are interested in detecting empirical evidence about the learning assessment and engagement in higher education with focus on students’ engagement and their success performance during ERT. The investigation carried out on Iulm University’s student population (N=775). We integrated textual data related to the students evaluation of ERT and their career data such as credits, marks before and post disease. The results show the relations between the two dimensions taken into account, with a multidimensional approach we created a factorial plan useful to create an agile tool of analysis in the ERT context

Can elearning platform use augment the statistical learning? Some evidence from Italy

The study of statistics, in degree programs not specifically designed, is one of the most difficult obstacles to overcome in the students’ perspective. Italian students have a superficial knowledge of mathematics and they tend to assimilate the statistics to the mathematics so they develop prejudices towards statistics too. In the last time the PISA-OCSE surveys indicate a slight improvement in the understanding of mathematics at the level of high school, however, we are still far from the European average. The statistical literacy can be considered as latent construct measured through observed repeated variables linked to the passed exams. In detail, the analysis uses the scores generated from e-learning tool (MathXL) in 10 repeated occasions for each student conjointly to demographic and social aspects. The analysis of the statistical literacy growth carries on three cohortes of students in an Italian humanistic university for the academic years 2012-2013, 2013-2014 and 2014-2015 in students perspective. The statistical learning growth is investigated both through nonlinear latent growth modeling and latent state trait analysis. This choice comes from the rejection of linear trajectories previously tested and confirmed in the literature. The results for former two academic years highlight a nonlinear growth with an effect of voto di diploma. The same results have been confirmed by latent state trait analysis. For the last academic year, the results can be avaible after ending of the course on April 2015

David and Goliath: small banks in an era of consolidation. Evidence from Italy

Consolidation in the banking industry has caused concern about the survival of small banks. However, empirical evidence shows that often small banks are performing better than larger banks in terms of loan growth and profitability. This paper addresses the main question of “how David can be successful in a Goliath’s world” analysing two broad sets of issues, tested on a sample of Italian small banks. We first address the question of whether peculiarities of small banks, e.g their ability to lever on relationship lending, are good explanatory variables of their loan growth. Second, we investigate the relationship between loan growth and profitability and credit risk to point out which small banks can continue to be a viable competitor of larger bank

David and Goliath: small banks in an era of consolidation. Evidence from Italy

Consolidation in the banking industry has caused concern about the survival of small banks. However, empirical evidence shows that often small banks are performing better than larger banks in terms of loan growth and profitability. This paper addresses the main question of “how David can be successful in a Goliath’s world” analysing two broad sets of issues, tested on a sample of Italian small banks. We first address the question of whether peculiarities of small banks, e.g their ability to lever on relationship lending, are good explanatory variables of their loan growth. Second, we investigate the relationship between loan growth and profitability and credit risk to point out which small banks can continue to be a viable competitor of larger bank

Latent class models for childhood obesity

Using data about students from 6 to 10 years old, we want to identify the main causes of childhood obesity using some latent classes. We will try to see if the decisions, about the consumption of meat, eggs, pasta, cheese, salami, sweets, fruit, vegetable, fi sh and rice, allow to identify some life stiles that we can model as latent variables and that we can compare with some familiar behaviors such as daily consumption of sweets and snacks