Physiological Model to Classify Physical and Cognitive Workload During Gaming Activities

This study aimed to investigate the impact of game-based learning on student performance. For this reason, an empirical study was conducted which comprises the comparison of traditional learning and game-based learning. The participants were lower primary school students of age group 6-8 years. GSR NUL-217 logger sensor was used to record the physiological signals of each participant in real time. An Android-based game intervention named “KidsZoneApp” was developed which included mathematics and English lesson plans according to the student's curriculum. The collected log data was used to calculate the changes in different dimensions of completing the task. ANOVA yielded a very significant difference between game-based learning and traditional learning groups. Overall, the results showed that game-based learning contributed to increased students' performance levels. Significantly, students under game-based learning completed the task in lesser time as compared to traditional learning.

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Physiological Model to Classify Physical and Cognitive Workload During Gaming Activities

Cited by 2 publications

References 4 publications

Gray-level co-occurrence matrix of Smooth Pseudo Wigner-Ville distribution for cognitive workload estimation

Gray-level co-occurrence matrix of Smooth Pseudo Wigner-Ville distribution for cognitive workload estimation

Investigating the Impact of Gamification in Children Using GSR

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