Comparing Programming Language Comprehension between Novice and Expert Programmers Using EEG Analysis

Lee, Seolhwa; Matteson, Andrew Stuart; Hooshyar, Danial; Kim, SongHyun; Jung, Jaebum; Nam, GiChun; Lim, Heuiseok

doi:10.1109/bibe.2016.30

Cited by 50 publications

(49 citation statements)

References 13 publications

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“…Psycho-physiological analysis has also been used in the study of cognitive skills and information processing in programmers. Lee et al [137] present a study in which they examine the differences between novices and experts in programming comprehension. They used EEG to record the neural activity and found clear differences between novices and experts.…”

Section: The Other Hci Systemsmentioning

confidence: 99%

A Survey on Psycho-Physiological Analysis & Measurement Methods in Multimodal Systems

Baig¹,

Kavakli²

2019

MTI

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Psycho-physiological analysis has gained greater attention in the last few decades in various fields including multimodal systems. Researchers use psychophysiological feedback devices such as skin conductance (SC), Electroencephalography (EEG) and Electrocardiography (ECG) to detect the affective states of the users during task performance. Psycho-physiological feedback has been successful in detection of the cognitive states of users in human-computer interaction (HCI). Recently, in game studies, psycho-physiological feedback has been used to capture the user experience and the effect of interaction on human psychology. This paper reviews several psycho-physiological, cognitive, and affective assessment studies and focuses on the use of psychophysiological signals in estimating the user's cognitive and emotional states in multimodal systems. In this paper, we review the measurement techniques and methods that have been used to record psycho-physiological signals as well as the cognitive and emotional states in a variety of conditions. The aim of this review is to conduct a detailed study to identify, describe and analyze the key psycho-physiological parameters that relate to different mental and emotional states in order to provide an insight into key approaches. Furthermore, the advantages and limitations of these approaches are also highlighted in this paper. The findings state that the classification accuracy of >90% has been achieved in classifying emotions with EEG signals. A strong correlation between self-reported data, HCI experience, and psychophysiological data has been observed in a wide range of domains including games, human-robot interaction, mobile interaction, and simulations. An increase in β and γ-band activity have been observed in high intense games and simulations.

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Section: The Other Hci Systemsmentioning

confidence: 99%

A Survey on Psycho-Physiological Analysis & Measurement Methods in Multimodal Systems

Baig¹,

Kavakli²

2019

MTI

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“…Apart to that many researchers has applied the EEG to identify the brain regions when doing software decoding [22] [23]. Researchers has shown the difference between active regions of brain of software experts and novice in software engineering using EEG technique [24].…”

Section: Other Approaches To Study Program Comprehensionmentioning

confidence: 99%

Underlying Mental Factors Contributing to Software Complexity

Jain,

Singh

2020

IJEAT

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Software complexity and program comprehension are inversely related. Higher the code complexity, poorer the comprehension. But we neither have good software complexity measure, nor do we understand how the program comprehension took place in human mind. This is because we know so little about the working of the human brain; how it processes internal and external information. In this paper we have identified 5 mental factors which adds into the code complexity. In order to explain these factors, we took 10 code snippet pairs in C language (2 each for every factor). Code snippets in pair are identical - in terms of number of variables, operators, control structure- but we believe one of the snippets in pair is carrying the higher cognitive load due to underlying mental factor identified. To the best of our knowledge these factors identified here in this paper are not used in calculating the code or software complexity. We believe these identified mental factors can be validated by various brain imaging and Eye tracking techniques like EEG and fMRI. They can also be validated by conventional software experimental methods. We believe these identified factors will increase our understanding of Program comprehension as well as it will lead better software complexity measure. This could be very useful in computer science education. The very process of understanding how the human mind decode the software can be possibly understood. In long run this could help us in better understanding of the functioning of human brain.

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“…They detected activation specific Broadmann-areas during code comprehension [Siegmund et al, 2014].In their follow up work they investigated the difference between bottom-up program comprehension and comprehension with semantic cues in terms of brain areas involved [Siegmund et al, 2017].A group led by Heui Seok Lim uses a full EEG device, like the one proposed in this research. However, they focus mostly on exploring how the mind of developers evolved from novice to experts in program comprehension tasks, and therefore have a completely different focus than ours [Lee et al, 2016].…”

Section: Studies Of Biometric Sensors To Evaluate the State Of The MImentioning

confidence: 99%

“…The data collection at companies will also be performed through suitable questionnaires and surveys, using the best standards in the field as can be applied in software engineering, as described in [Pedrycz et al, 2011, Ivanov et al, 2016. Additional data will be collected from full capacity EEG devices, one instance of which is already in use for feasibility studies at Innopolis University using the on one side the recent experience collected in software engineering [Lee et al, 2016] and on the other the decades long competence presence in neurosciences.…”

Section: Background Researchmentioning

confidence: 99%

Toward a Better Understanding of How to Develop Software Under Stress – Drafting the Lines for Future Research

Brown

Ivanov

Rogers

et al. 2018

Proceedings of the 13th International Conference on Evaluation of Novel Approaches to Software Engineering

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Software is often produced under significant time constraints. Our idea is to understand the effects of various software development practices on the performance of developers working in stressful environments, and identify the best operating conditions for software developed under stressful conditions collecting data through questionnaires, non-invasive software measurement tools that can collect measurable data about software engineers and the software they develop, without intervening their activities, and biophysical sensors and then try to recreated also in different processes or key development practices such conditions.

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Comparing Programming Language Comprehension between Novice and Expert Programmers Using EEG Analysis

Cited by 50 publications

References 13 publications

A Survey on Psycho-Physiological Analysis & Measurement Methods in Multimodal Systems

A Survey on Psycho-Physiological Analysis & Measurement Methods in Multimodal Systems

Underlying Mental Factors Contributing to Software Complexity

Toward a Better Understanding of How to Develop Software Under Stress – Drafting the Lines for Future Research

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