Distance learning university students: who are they?

Despite the growing relevance of distance education, evidence on the characteristics of students who choose this mode of provision remains limited and fragmented. This paper addresses this gap by examining the characteristics and changing profiles of distance-learning students using population-level administrative data covering the Italian higher education system from 2012 to 2023. The study combines supervised modelling and clustering techniques to examine the determinants of enrolment in distance-learning versus in-person universities, as well as the internal differentiation of the distance-learning population and its evolution over time. Results indicate that age is the strongest factor associated with distance-learning enrolment, while educational background, territorial origin, field of study and prior academic experience contribute further differentiation. The clustering analysis reveals a gradual diversification of the distance-learning population, with profiles traditionally associated with this mode of provision remaining prominent but increasingly coexisting with younger and first-career entrants. Overall, the findings contribute to understanding how the expansion of distance education is accompanied by changes in student composition, connecting these developments to broader processes of expansion and diversification in higher education participation.

Authors

Publication Details

Journal
Figshare
Published
2026-11-04
DOI
https://doi.org/10.6084/m9.figshare.34917901
Primary Topic
Online and Blended Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distance learning university students: who are they?

Rebecca Ghio, Silvia Salini, Stefano Trancossi, Matteo Turri et al.
Figshare
Online and Blended Learning
article

Distance learning university students: who are they?

Rebecca Ghio, Silvia Salini, Stefano Trancossi, Matteo Turri, Marta Magnani, Sophia Chiara Fiora, Marta Campagnoli
article en

Abstract

Despite the growing relevance of distance education, evidence on the characteristics of students who choose this mode of provision remains limited and fragmented. This paper addresses this gap by examining the characteristics and changing profiles of distance-learning students using population-level administrative data covering the Italian higher education system from 2012 to 2023. The study combines supervised modelling and clustering techniques to examine the determinants of enrolment in distance-learning versus in-person universities, as well as the internal differentiation of the distance-learning population and its evolution over time. Results indicate that age is the strongest factor associated with distance-learning enrolment, while educational background, territorial origin, field of study and prior academic experience contribute further differentiation. The clustering analysis reveals a gradual diversification of the distance-learning population, with profiles traditionally associated with this mode of provision remaining prominent but increasingly coexisting with younger and first-career entrants. Overall, the findings contribute to understanding how the expansion of distance education is accompanied by changes in student composition, connecting these developments to broader processes of expansion and diversification in higher education participation.

Figshare
Openalex Percentile: Top 8%
Online and Blended Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon