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

Abstract

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.

Towards the Measurement of Mental Effort in Software Engineering: A Research Agenda

“…. Some studies found that the increasing cognitive load impacts on developers' performance during the cognitive process, such as, comprehending source code [6,19]. In the case of certain level of cognitive workload jeopardize the developers' comprehension, then the software project probably will be compromised too [14].…”

“…Finally, another fact about cognitive load, is that it is affected by the level of experience, and besides that, it can vary across individuals. For instance, Lee 2017 [14] controlled the cognitive load in relation to two experience levels (experienced and no experienced), while in [6] analyzed the cognitive load in relation to 5 categories of experience (from sophomore to seniors one). Therefore, the question is, which are the appropriated categories to analyze the cognitive workload?…”

“…Furthermore, the cognitive load indicators have been used for many purposes in research of software engineering. Igor Crk 2016 [6] measured the cognitive load to classify and categorize the level of program comprehension of software developers. Sebastian Muller [19] used machine learning techniques that used cognitive load indicators to point quality concerns in a source code.…”

“…Another sensor that could be used to collect cognitive load is a wristband that captures information such as heart beating, and respiratory rate, information's which are related to cognitive load. Cognitive load: The cognitive load is obtained through the reflection of the signals provided by the previously devices [6]. While users are concentrated in a task, the devices captures the manifestations of their body.…”

“…Applications: There are a lot of applications which researchers in the software engineering research field are interested such as, identifying the level of expertise of developers [6], measuring the task difficulty according to developers' perception [19,14], and improving the developers' well-being [10]. However, there are many shortcomings which academia and industry must overcome in order to deploy the cognitive load indicator in realistic scenarios definitively.…”