Analyzing Novice and Expert User's Cognitive Load in using a Multi-Modal Interface System

• Published in: 2018 26th International Conference on Systems Engineering (ICSEng) pp. 1 - 7
• Main Authors: Baig, Muhammad Zeeshan, Kavakli, Manolya
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2018
• Subjects: Brain modeling; EEG; Electroencephalography; Expert; Expertise; Gesture; HCI; Headphones; Human computer interaction; Keyboards; Multimodal Interface system; Novice; Speech; Task analysis; Three-dimensional displays
• DOI: 10.1109/ICSENG.2018.8638206

Learning and usability of a 3D modelling system depend on direct and indirect human-dependent factors. These factors need to be studied in order to design a state-of-the-art computer tool or software. In this paper, we have presented a novice/expert analysis of a 3D modelling system in which user used two different sets of inputs i.e. keyboard/mouse and speech/gesture to draw the 3D object in AutoCAD. To analyse the user's cognitive workload, we have used electroencephalography (EEG) signals and extracted various frequency bands and power spectral density (PSD) estimates. EEG signals and questionnaires were used to understand the user's behaviour. The results showed that users find i t d ifficult to dr aw a 3D object using the multi-modal input speech/gesture compared to keyboard/mouse. A significant change in theta and alpha bands activity was observed during the analysis. We found that novice users were relatively comfortable in using multi-modal interface system then the expert users which indicates that novice users can learn to use the multi-modal input more quickly then the expert users.