Resolving Gender Difference in Problem Solving Based On the Analysis of Electroencephalogram (EEG) Signals

  • Norlaili Mat Safri Universiti Teknologi Malaysia
  • Ahmad Zuri Sha'ameri Universiti Teknologi Malaysia
  • Narina A. Samah Universiti Teknologi Malaysia
  • Shaparas Daliman Universiti Malaysia Kelantan
Keywords: Problem solving, electroencephalogram (EEG) signals, gender differences, partial directed coherence (PDC), power spectrum estimation (PSE)


Problem solving is regarded as one of the core work-related abilities and skills, which are highly demanded by the workplace and industry. Current literature suggests that problem solving abilities might differ from one individual to another due to biological factors such as brain activationa, cognitive functions and hormones, as well as due to socio-cultural and socio-economic factors like gender roles, self-perceptions and stereotyping. Hence, this study used electroencephalogram (EEG) signals to investigate the differences in problem solving skills among the Malaysian undergraduates based on their gender differences. 29 undergraduate students from the Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM) served as the subjects of the experiments in this research. Specifically, 16 female and 13 male subjects engaged in two main problem-solving tasks: mental arithmetic task and Tower of Hanoi (TOH) task. The EEG data were analysed using partial directed coherence (PDC) and power spectrum estimation (PSE). Based on the results, female subjects achieved only 1% higher performance in mental arithmetic task, while male subjects achieved about 13% higher performance in TOH task. The differences in terms of the functional connectivity between brain regions, i.e. in PDC, as well as the power distribution of 6 EEG waveforms, i.e. delta, theta, alpha, beta, gamma and high gamma bands are also highlighted and represented graphically in this paper.


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How to Cite
Mat Safri, N., Sha’ameri, A. Z., A. Samah, N., & Daliman, S. (2018). Resolving Gender Difference in Problem Solving Based On the Analysis of Electroencephalogram (EEG) Signals. International Journal of Integrated Engineering, 10(7). Retrieved from