ABSTRACT
The Covid-19 pandemic played a relevant role in the diffusion of distance learning alternatives to "traditional" learning based on classroom activities, to allow university students to continue attending lessons during the most severe phases of the pandemic. In such a context, investigating the students' perspective on distance learning provides useful information to stakeholders to improve effective educational strategies, which could be useful also after the end of the emergency to favor the digital transformation in the higher educational setting. Here we focus on the satisfaction in distance learning for Italian university students. We rely on data comprising students enrolled in various Italian universities, which were inquired about several aspects related to learning distance. We explicitly take into account the hierarchical nature of data (i.e., students nested in universities) and the latent nature of the variable of interest (i.e., students' learning satisfaction) through a multilevel Item Response Theory model with students' and universities' covariates. As the main results of our study, we find out that distance learning satisfaction of students: (i) depends on the University where they study; (ii) is affected by some students' socio-demographic characteristics, among which psychological factors related to Covid-19; (iii) is affected by some observable university characteristics.
ABSTRACT
The COVID-19 pandemic manifested around the World since February 2020, leading to disruptive effects on many aspects of people social life. The suspension of face-to-face teaching activities in schools and universities was the first containment measure adopted by the Governments to deal with the spread of the virus. Remote teaching has been the emergency solution implemented by schools and universities to limit the damages of schools and universities closure to students' learning. In this contribution we intend to suggest to policy makers and researchers how to assess the impact of emergency policies on remote learning in academia by analysing students' careers. In particular, we exploit the quasi-experimental setting arising from the sudden implementation of remote teaching in the second semester of academic year 2019/2020: we compare the performance of the cohort 2019/2020, which represents the treatment group, with the performance of the cohort 2018/2019, which represents the control group. We distinguish the impact of remote teaching at two levels: degree program and single courses within a degree program. We suggest to use Difference-In-Differences approach in the former case and multilevel modeling in the latter one. The proposal is illustrated analysing administrative data referred to freshmen of cohorts 2018/2019 and 2019/2020 for a sample of degree programs of the University of Florence (Italy).
ABSTRACT
The COVID-19 pandemic manifested around the World since February 2020, leading to disruptive effects on many aspects of people social life. The suspension of face-to-face teaching activities in schools and universities was the first containment measure adopted by the Governments to deal with the spread of the virus. Remote teaching has been the emergency solution implemented by schools and universities to limit the damages of schools and universities closure to students' learning. In this contribution we intend to suggest to policy makers and researchers how to assess the impact of emergency policies on remote learning in academia by analysing students' careers. In particular, we exploit the quasi-experimental setting arising from the sudden implementation of remote teaching in the second semester of academic year 2019/2020: we compare the performance of the cohort 2019/2020, which represents the treatment group, with the performance of the cohort 2018/2019, which represents the control group. We distinguish the impact of remote teaching at two levels: degree program and single courses within a degree program. We suggest to use Difference-In-Differences approach in the former case and multilevel modeling in the latter one. The proposal is illustrated analysing administrative data referred to freshmen of cohorts 2018/2019 and 2019/2020 for a sample of degree programs of the University of Florence (Italy).