Assessing the contribution of the individual alpha frequency (IAF) in an EEG-based study of program comprehension

Empirical studies of programming language learnability and usability have thus far depended on indirect measures of human cognitive performance, attempting to capture what is at its essence a purely cognitive exercise through various indicators of comprehension, such as the time spent working out the meaning of code and producing acceptable solutions. We present evidence of the relative contribution of experience and the individual alpha frequency (IAF) to achieving correct performance during program comprehension tasks, specifically that more experience and higher IAF are both associated with an increased likelihood of correct task performance, with experience playing the greater part.

[1]  P. Welch The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .

[2]  Ulman Lindenberger,et al.  Individual alpha peak frequency is related to latent factors of general cognitive abilities , 2013, NeuroImage.

[3]  A. Anokhin,et al.  EEG Alpha rhythm frequency and intelligence in normal adults , 1996 .

[4]  G. Sparacino,et al.  A novel method for the determination of the EEG individual alpha frequency , 2012, NeuroImage.

[5]  G. Thut,et al.  Mechanisms of selective inhibition in visual spatial attention are indexed by α‐band EEG synchronization , 2007, The European journal of neuroscience.

[6]  Simon,et al.  Mental models, consistency and programming aptitude , 2008, ACE '08.

[7]  W. Klimesch,et al.  EEG alpha oscillations: The inhibition–timing hypothesis , 2007, Brain Research Reviews.

[8]  Igor Crk,et al.  Toward using alpha and theta brain waves to quantify programmer expertise , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  Tore Dybå,et al.  Evaluating Pair Programming with Respect to System Complexity and Programmer Expertise , 2007, IEEE Transactions on Software Engineering.

[10]  W. Klimesch Memory processes, brain oscillations and EEG synchronization. , 1996, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[11]  Andreas Stefik,et al.  Understanding Programming Expertise , 2015, ACM Trans. Comput. Hum. Interact..

[12]  W. Ray,et al.  EEG alpha activity reflects attentional demands, and beta activity reflects emotional and cognitive processes. , 1985, Science.

[13]  Elsbeth Stern,et al.  When intelligence loses its impact: neural efficiency during reasoning in a familiar area. , 2003, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[14]  Rodney J Croft,et al.  Investigating evoked and induced electroencephalogram activity in task-related alpha power increases during an internally directed attention task , 2006, Neuroreport.

[15]  Charles L. Hulin,et al.  Adding a Dimension: Time as a Factor in the Generalizability of Predictive Relationships , 1990 .

[16]  W. Klimesch EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis , 1999, Brain Research Reviews.

[17]  J. Lisman,et al.  Oscillations in the alpha band (9-12 Hz) increase with memory load during retention in a short-term memory task. , 2002, Cerebral cortex.

[18]  D. Cox The Regression Analysis of Binary Sequences , 2017 .

[19]  K. A. Ericsson,et al.  Expert and exceptional performance: evidence of maximal adaptation to task constraints. , 1996, Annual review of psychology.

[20]  Cláudio T. Silva,et al.  A User Study of Visualization Effectiveness Using EEG and Cognitive Load , 2011, Comput. Graph. Forum.

[21]  W. Klimesch,et al.  Alpha frequency, reaction time, and the speed of processing information. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[22]  Tyler S. Grummett,et al.  Measurement of neural signals from inexpensive, wireless and dry EEG systems , 2015, Physiological measurement.