Beyond Differences: A Generational Convergence in Technology Use Among Business Students

The rapid digitalization of higher education has transformed how students learn, collaborate, and engage with emerging technologies such as artificial intelligence (AI). While earlier research emphasized generational or academic-level differences in digital behavior, recent evidence suggests convergence in technology use. This study explores whether undergraduate and postgraduate students at the Faculty of Economics and Business, University of Maribor, display distinct technology engagement patterns across five constructs: excessive technology use, online collaboration, the use of digital learning tools (E-boards), the use of AI in education, and perceived academic success. A survey among 285 students was analyzed using the non-parametric Mann–Whitney U test due to a non-normal data distribution. The findings showed that postgraduate students did not report higher levels of E-Board use, online collaboration, or perceived academic success. Undergraduate students scored higher on one item related to excessive technology use, but not across the full construct. However, significant differences emerged in AI use, where postgraduate students showed greater confidence and willingness to integrate AI tools. The findings suggest that digital competence and the quality of technology integration, rather than study level, shape students’ learning experiences. Higher education institutions should promote balanced and ethical technology use, strengthen AI literacy, and foster self-regulated learning skills.

Institutions

Publication Details

Journal
Systems
Published
2025-12-03
DOI
https://doi.org/10.3390/systems13121095
Primary Topic
Digital literacy in education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Beyond Differences: A Generational Convergence in Technology Use Among Business Students

Systems
Digital literacy in education
article

Beyond Differences: A Generational Convergence in Technology Use Among Business Students

article en

Abstract

The rapid digitalization of higher education has transformed how students learn, collaborate, and engage with emerging technologies such as artificial intelligence (AI). While earlier research emphasized generational or academic-level differences in digital behavior, recent evidence suggests convergence in technology use. This study explores whether undergraduate and postgraduate students at the Faculty of Economics and Business, University of Maribor, display distinct technology engagement patterns across five constructs: excessive technology use, online collaboration, the use of digital learning tools (E-boards), the use of AI in education, and perceived academic success. A survey among 285 students was analyzed using the non-parametric Mann–Whitney U test due to a non-normal data distribution. The findings showed that postgraduate students did not report higher levels of E-Board use, online collaboration, or perceived academic success. Undergraduate students scored higher on one item related to excessive technology use, but not across the full construct. However, significant differences emerged in AI use, where postgraduate students showed greater confidence and willingness to integrate AI tools. The findings suggest that digital competence and the quality of technology integration, rather than study level, shape students’ learning experiences. Higher education institutions should promote balanced and ethical technology use, strengthen AI literacy, and foster self-regulated learning skills.

SystemsVol. 13(12)
University of Maribor (SI)
Quality Education
Openalex Percentile: Top 29%
Digital literacy in education
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.