The Covid-19 pandemic has changed the characteristics of universityteaching-learning practices marking the transition from face to face to on-line activities by means of digital platforms. This digitization process has produced several effects on students’ habits and learning ability. Within this scenario, aim of the contributionis to assess the student perception of the distance learning experience by adopting a network analysis approach. A network of adjectives is obtained from Semantic Differential scales and links are defined as a function of the most frequent polarized items co-occurences. The network core allows to identify the most importantadjectives describing the students’ e-learning perception.

Assessing undergraduate students’ perceptions of distance learning during the COVID-19 pandemic

Ilaria Primerano;
2022

Abstract

The Covid-19 pandemic has changed the characteristics of universityteaching-learning practices marking the transition from face to face to on-line activities by means of digital platforms. This digitization process has produced several effects on students’ habits and learning ability. Within this scenario, aim of the contributionis to assess the student perception of the distance learning experience by adopting a network analysis approach. A network of adjectives is obtained from Semantic Differential scales and links are defined as a function of the most frequent polarized items co-occurences. The network core allows to identify the most importantadjectives describing the students’ e-learning perception.
2022
Istituto di Ricerche sulla Popolazione e le Politiche Sociali - IRPPS - Sede Secondaria Fisciano (SA)
9788894593358
Higher Education
Network Analysis
Semantic Differential
Textual Network
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/525036
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