Toward using alpha and theta brain waves to quantify programmer expertise

Crk, Igor; Kluthe, Timothy

doi:10.1109/embc.2014.6944840

Cited by 23 publications

(11 citation statements)

References 16 publications

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“…Igor Crk and Timotthy Kluthe [ 53 ] performed a study reporting a binary qualification of a programmer’s expertise through code comprehension using recorded EEG signals from 14 electrodes in 34 participants. By using information of Theta and Alpha bands, the authors could distinguish the expertise with an accuracy from 53% to 63% depending on the task.…”

Section: Background and Related Workmentioning

confidence: 99%

Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

Medeiros

Couceiro

Duarte

et al. 2021

Sensors

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An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers’ cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers’ cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers’ cognitive state monitored using wearable devices compatible with software development activities.

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Section: Background and Related Workmentioning

confidence: 99%

Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

Medeiros

Couceiro

Duarte

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Further research will be needed in order to clarify and explain these relationships. The rapid development of neuroscience research provides more possibilities to uncover the underlying mechanisms of information processing in the brain during computer programming [8] [9]. Knowledge stored in longterm memory and knowledge used in working-memory have previously been found to be good predictors of computer programming skill acquisition in traditional research [10] [11] [12], which has been confirmed by recent research in neuroscience [13] [14].…”

Section: Introductionmentioning

confidence: 81%

“…Consequently, we chose to measure brain activity using EEG which has been successfully used in previous existing cognitive research [15]. In the field of computer programming, a paucity of research exists studying the relationship of EEGs with respect to the cognition of programming dynamics [8] [9]. Although the possible relationship between the memory and programming skill has been depicted in previous research, the use of EEGs in this research is a relatively novel way to explore programming cognition, supplemented by eye tracking to reveal more about how different cognitive models influence programming dynamics and skills.…”

Section: Introductionmentioning

confidence: 99%

“…Triangulating EEG activities and eye movements helped to elucidate cognitive processes involved in program comprehension. Previous research has addressed the functional significance of theta and alpha frequency bands in programming comprehension [8] [9], cognitive activities such as problem solving [18], working-memory operation [19] [20], and semantic understanding [21], which have shown to be involved in computer programming. The present research focuses on theta and alpha bands and their involvement with programming skills.…”

Section: Introductionmentioning

confidence: 99%

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EEG Activities During Program Comprehension: An Exploration of Cognition

Liao

2021

IEEE Access

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This study attempts to explore cognition during program comprehension through physiological evidence by recording and comparing electroencephalogram (EEG) activities in different frequency bands and the eye movements of the participants with high or low programming abilities. An experiment was conducted with thirty-three undergraduate students majoring in Computer Science. We recorded their EEG activities when they were reading two programs with three types of program constructs. At the same time, the participants' eye movements were recorded by an eye tracker to further understand the relationship between the program comprehension process and EEG activities. Experimental results show that the highperformance participants displayed higher performance for working memory (theta power), attention resource allocation (lower alpha power), and interaction between working memory and semantic memory (upper alpha power) in program comprehension tasks of complex constructs, which proves related theories proposed in the existing research on programming and cognition. The results of this study not only offer objective evidence of the roles cognition plays in program comprehension but also provide educators with suggestions for designing suitable pedagogical strategies.

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“…The problem with the Emotiv Headset is that it has limited electrodes with no electrodes in the central lobe (Pz, Cz, Fz) and therefore, it is thought that the system has limited applicability in research. The manufacturer states that the signals from the neighboring electrodes are good enough to perform experiments and researchers have proved the capability of headset in many applications [31]. The subjects were given an open-ended task to depict the real-world setting, which results in complex cognitive processing and analysis strategies.…”

Section: Methodsologymentioning

confidence: 99%

Connectivity Analysis Using Functional Brain Networks to Evaluate Cognitive Activity during 3D Modelling

Baig

Kavakli

2019

Brain Sciences

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Modelling 3D objects in CAD software requires special skills which require a novice user to undergo a series of training exercises to obtain. To minimize the training time for a novice user, the user-dependent factors must be studied. we have presented a comparative analysis of novice/expert information flow patterns. We have used Normalized Transfer Entropy (NTE) and Electroencephalogram (EEG) to investigate the differences. The experiment was divided into three cognitive states i.e., rest, drawing, and manipulation. We applied classification algorithms on NTE matrices and graph theory measures to see the effectiveness of NTE. The results revealed that the experts show approximately the same cognitive activation in drawing and manipulation states, whereas for novices the brain activation is more in manipulation state than drawing state. The hemisphere- and lobe-wise analysis showed that expert users have developed an ability to control the information flow in various brain regions. On the other hand, novice users have shown a continuous increase in information flow activity in almost all regions when doing drawing and manipulation tasks. A classification accuracy of more than 90% was achieved with a simple K-nearest neighbors (k-NN) to classify novice and expert users. The results showed that the proposed technique can be used to develop adaptive 3D modelling systems.

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Toward using alpha and theta brain waves to quantify programmer expertise

Cited by 23 publications

References 16 publications

Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

Can EEG Be Adopted as a Neuroscience Reference for Assessing Software Programmers’ Cognitive Load?

EEG Activities During Program Comprehension: An Exploration of Cognition

Connectivity Analysis Using Functional Brain Networks to Evaluate Cognitive Activity during 3D Modelling

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