EEG-based evaluation of cognitive and emotional arousal when coding in different programming languages
|Author:||Rajendra Desai, Amit1|
1University of Oulu, Faculty of Information Technology and Electrical Engineering, Department of Information Processing Science, Information Processing Science
|Online Access:||PDF Full Text (PDF, )|
|Persistent link:|| http://urn.fi/URN:NBN:fi:oulu-201706022496
A. Rajendra Desai,
|Publish Date:|| 2017-06-02
|Thesis type:||Master's thesis
Cognitive psychology is a study of the brain, an organ that behaves as a complex computing system. The brain signals generate electrical signals, which can be interpreted meaningfully in line with the actions performed by the brain using various computational devices and measures using electroencephalography methodology. In this thesis, the signals obtained from the brain are processed to quantitatively study and compare the brain activities of coders while programming in two different programming languages. In this research, we have chosen the structured programming language C and the scripting language Python for comparison. Previous empirical research comparing various programming languages in a controlled manner identified attributes such as correctness, robustness, syntax, efficiency, etc. as parameters that characterize those programming languages (see e.g., Nanz and Furia, 2015; Garcia Jarvi, Lumsdaine, Siek and Willcock, 2003). This thesis aims to build upon the previous findings and compare the psychological effects during programming tasks. Emotiv Epoc is a Brain Computer Interface device used for reading and analyzing brain signals in this study. Understanding the usage of the Emotiv device and the corresponding software tools is an essential part of this thesis work. Thus, in this thesis a pilot study is planned and a controlled experiment is conducted in order to collect and evaluate the data collected from the Emotiv Epoc device and self-reports to derive meaningful statistical results and interpret the emotional and cognitive activity of the participants. The pilot study aims to understand how emotions and/or cognitive load vary while coding in C and Python. Initial study involves understanding the EEG method, principles and complexities involved with the collection of data. The core part of the thesis consists of planning and conducting a lab experiment, which involves six participants performing predefined tasks in C and Python, and answering a series of questionnaires. The collected data is analyzed in SPSS tool based on factors like time, performance (correctness), and questionnaire-based self-reports. EEG signals are analyzed in this thesis up to the point of artifact removal (Filtering and ICA using MATLAB and EEGLAB). The results of the thesis reveal findings from emotional and EEG data analysis which have been captured from an experimental setup using the Emotiv device, software developers as participants and software programming tasks. The thesis helps to understand the steps to perform such an experimental study and to assimilate the emotional and cognitive load that affects the brain when performing programming. The particular comparison of C and Python as programming languages shows the high correlation between the programming language characteristics (such as syntax and time to code) and emotional and cognitive behavior of the programmers.
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