Application of artificial intelligence to measure attention levels in university students

Objective To evaluate the effect of an AI-assisted attentional monitoring system on the perception of class dynamism and the self-assessment of attention among university students. Methods A quasi-experimental design was employed with 160 students divided into an experimental group, which attended classes with attentional monitoring and real-time feedback provided to the teacher, and a control group, which received traditional instruction. Perception of attention and dynamism was assessed pre- and post-intervention using the AIDA questionnaire. Results The experimental group exhibited significant increases in perceived class dynamism and attentional self-regulation compared to the control group ( p < 0.05), demonstrating improved engagement during the session. Conclusion AI-assisted immediate feedback was associated with enhanced attention and student participation, highlighting the potential of such tools to support and strengthen teaching dynamics in in-person educational settings.