An EEG-Based Cognitive Load Assessment in Multimedia Learning Using Feature Extraction and Partial Directed Coherence

Moona Mazher, Azrina Abd Aziz*, Aamir Saeed Malik, Hafeez Ullah Amin

*Corresponding author for this work

Research output: Contribution to journalArticle (journal)peer-review

63 Citations (Scopus)

Abstract

Assessing cognitive load during a learning phase is important, as it assists to understand the complexity of the learning task. It can help in balancing the cognitive load of postlearning and during the actual task. Here, we used electroencephalography (EEG) to assess cognitive load in multimedia learning task. EEG data were collected from 34 human participants at baseline and a multimedia learning state. The analysis was based on feature extraction and partial directed coherence (PDC). Results revealed that the EEG frequency bands and activated brain regions that contribute to cognitive load differed depending on the learning state. We concluded that cognitive load during multimedia learning can be assessed using feature extraction and measures of effective connectivity (PDC).

Original languageEnglish
Article number7992998
Pages (from-to)14819-14829
Number of pages11
JournalIEEE Access
Volume5
DOIs
Publication statusPublished - 26 Jul 2017

Keywords

  • Cognitive load assessment
  • electroencephalography
  • learning process
  • partial directed coherence

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