Generational patterns and digital learning profiles behind AI adoption: A structural and segmentation approach
Year: 2026
Type: conference-paper
Study design: Observational Study
Abstract: This study examines how the use of artificial intelligence (AI) is associated with social and digital learning patterns in a non-representative Hungarian sample of 1,128 respondents. AI adoption was analysed using a composite AI adoption index and an ordinal indicator of self-reported daily AI use. The results suggest a clear generational pattern within the analysed sample: younger respondents reported more frequent AI use and more active engagement in informal digital learning. Ordinal regression analysis showed that informal skill learning and educational attainment were significantly associated with higher levels of self-reported AI use, whereas following educational content alone was not statistically significant in the model. Segmentation analysis identified two descriptive digital profiles that differed in terms of AI use, informal learning activity, generational composition and human capital characteristics. Overall, the findings indicate that AI use in the analysed sample is related to broader patterns of digital learning and social background, but the results should be interpreted as exploratory and correlational rather than causal.
Institution: Obuda University
Language: English
Subfield: Life-span and Life-course Studies
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7204159397