RT info:eu-repo/semantics/article
T1 Multichannel assessment of cognitive load and emotions with pedagogical avatars in higher education
A1 Sáiz Manzanares, María Consuelo
A1 Toribio Casado, Celia
A1 Pérez López de Echazarreta, Gloria
A1 Águeda Miguel, Rocío
A1 González Díez, Irene
A1 Muñoz Arranz, Marina
A1 Carbonero Martín, Miguel Ángel
A1 Martín Antón, Luis Jorge
K1 Physiological measures
K1 Cognitive load
K1 Higher education
K1 Expresión facial
K1 Facial expression
K1 Tecnología educativa
K1 Educational technology
AB Integrating multimodal devices (eye tracking, electroencephalography [EEG], and galvanic skin response [GSR]) enables the objective assessment of cognitive and emotional processes during controlled tasks. In higher education multimedia contexts, such measures can inform the adaptive design of educational interfaces. This study examined the processing of avatar images expressing positive (surprise, joy) and negative (sadness, fear) emotions across different user groups (final-year university students, novice university lecturers, and experienced university lecturers), while also considering gender effects. Forty-eight participants completed a visualisation task while physiological indicators derived from EEG (engagement, memorisation, valence, workload), GSR (impact), and eye tracking (number of visits and dwell time) were recorded for relevant and non-relevant areas of interest. Significant differences emerged for surprise, with students showing more visits to non-relevant areas than lecturers members. For joy, final-year university students exhibited longer dwell times on relevant areas than experienced lecturers. No differences by professional group were found for sadness or fear. Regarding gender, women showed higher valence and workload in the joy condition, as well as higher memorisation and longer dwell times in the sadness condition. Based on these findings, adaptive adjustments to avatar design are proposed to better align with users’ cognitive and emotional profiles.
PB Taylor and Francis
SN 0144-929X
YR 2026
FD 2026-07
LK https://hdl.handle.net/10259/12074
UL https://hdl.handle.net/10259/12074
LA eng
NO This work was supported by the State Investigation Agency. Ministry of Science, Innovation and Universities. Government of Spain [grant numbers PID2020-117111RB-I00. Project SmartLearnUni].
DS Repositorio Institucional de la Universidad de Burgos
RD 30-oct-2026