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  4. Application of artificial intelligence to measure attention levels in university students

Application of artificial intelligence to measure attention levels in university students

Author(s)
Roberto Carlos Flores Ramirez
Jhon Marcos Luna Villanueva
Yngue Elizabeth Ramírez Pezo
Date Issued
2 de febrero de 2026
Type
Article
Volume
11
DOI
10.3389/feduc.2026.1753873
Abstract
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.
Subjects

Dynamism

Perception

Class (philosophy)

Control (management)

Cognitive psychology

Psychology

Attentional control

Measure (data warehou...

Computer science

Mathematics education...

Artificial intelligen...

Selective attention

Applied psychology

Dynamics (music)

Significant differenc...

Social psychology

Dynamism

Perception

Class (philosophy)

Control (management)

Attentional control

Measure (data warehou...

Social Sciences Psych...

Physical Sciences Com...

Life Sciences Neurosc...

Metrics
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