PM-KIMEN 24A: A dataset for analyzing EEG-based concentration and performance in gamified learning environments

This dataset was collected during the EEG-Gamified Simulator Pilot experiment, which explores the relationship between concentration, socio-emotional skills, and executive functions in educational simulation environments. The dataset combines neurocognitive, biometric, and task performance data to evaluate how concentration impacts skill acquisition. Participants engaged in gamified simulation tasks while their cognitive and emotional states were monitored using EEG devices and advanced educational tools. The study involved undergraduate students from diverse academic disciplines interacting with a gamified simulator designed to foster decision-making. Data were collected over two sessions (S2, S3), integrating EEG metrics and performance indicators. This dataset is valuable for understanding the dynamic interplay between cognitive engagement and task performance in simulated learning environments. It supports interdisciplinary research in neuroeducation, gamification, and educational technology. The database includes the following variables: General Identifiers: ● User: Unique numerical identifier for each participant, ranging from 1 to 14. ● Session: Unique text identifier for each session in the format "SN" (e.g., S1, S2, S3). ● Timestamp: Date and time of data collection in the format "yyyy/mm/dd HH:MM". ● Time: Elapsed time during each task, recorded in "HH:MM:SS". EEG and Brainwave Data: ● RAW_TP9, RAW_AF7, RAW_AF8, RAW_TP10: Raw EEG data in microvolts recorded at specific sensor locations (TP9, AF7, AF8, TP10). ● RazonTP9(B/T), RazonAF7(B/T), RazonAF8(B/T), RazonTP10(B/T): Ratios of beta to theta brainwave bands for each sensor location, reflecting concentration levels. ● X_Delta, X_Theta, X_Alpha, X_Beta, X_Gamma, X_Razon(B/T): Mean values of delta, theta, alpha, beta, gamma bands, and beta-to-theta ratio for each session. ● S_Delta, S_Theta, S_Alpha, S_Beta, S_Gamma, S_Razon(B/T): Standard deviations for the respective brainwave bands and ratios, providing variability measures. Concentration Analysis: ● Peaks_Concentration: Detected outliers where concentration values exceed two standard deviations, indicating significant concentration spikes. ● Total_Peaks: Count of concentration peaks identified during the session. ● Predicts_Concentration: Concentration levels calculated using the predictive model developed by Pérez-Gómez et al. (2025), which estimates concentration through a low-cost EEG device. ● Total_Predicts: Count of predicted concentration peaks using the authors' model. Simulator Performance Metrics (KPIs): ● KPI Plazo: Measures time management efficiency within tasks. ● KPI Costo: Evaluates resource management during simulations. ● KPI Satisfacción: Represents satisfaction levels of stakeholders involved in the simulation. ● KPI Total: Aggregates all performance metrics to provide an overall performance score.