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Updated: Sep 11, 2026

Artificial Intelligence-Based System for Detecting Attention Levels in Students
Published on: December 15, 2023
Assessing differences in emotional intelligence among lifestyle and AI usage profiles generated via Self-Organizing
Lucía Alonso-Larza1, Rocío Fernández-Piqueras2, Adoración-Reyes Moliner Albero3
1Department of Psychology, Inclusive Education and Social and Community Development, Catholic University of Valencia "San Vicente Mártir", Valencia, Spain.
Background:
The transition to higher education exposes first-year students to significant lifestyle changes and the challenges of a hyperconnected ecosystem, including the rapid integration of Artificial Intelligence (AI). While physical activity and digital flourishing are recognized as protective factors, their interaction with students' emotional competencies remains underexplored through non-linear, multidimensional approaches.
Objective:
This study aimed to identify topological profiles among incoming university students based on lifestyle, digital flourishing, and AI usage, and to analyze differences in intrapersonal emotional intelligence across these distinct profiles.
Methods:
A cross-sectional study was conducted with 385 first-year students. Data on physical activity, digital flourishing, AI perceptions and usage, and emotional intelligence were collected using validated self-reported instruments. A person-centered topological approach using Self-Organizing Maps (SOM) and k-means clustering was employed to identify student profiles, followed by one-way ANOVA to evaluate differences in emotional attention, clarity, and repair.
Results:
The SOM analysis successfully identified six distinct behavioral and psychosocial profiles. A clear divergence emerged between an adaptive profile (Cluster 6, characterized by active lifestyles, high digital flourishing, and instrumental AI use) and a vulnerable profile (Cluster 1, marked by relative physical inactivity and lower scores across digital dimensions). Crucially, the inferential analysis revealed that the profiles exhibited significant differences in their emotional competencies, with the adaptive profile showing significantly higher levels of emotional clarity and repair compared to the vulnerable group.
Conclusion:
Successful adaptation to the university and technological environment transcends the mere acquisition of isolated skills. Intrapersonal emotional intelligence acts as a key psychological factor differentiating adaptive from vulnerable student profiles, underscoring the potential benefit of holistic institutional interventions that simultaneously integrate the promotion of physical activity, digital wellbeing, and emotional competence.