Measuring Cognitive Load of Software Developers Based on Nasal Skin Temperature

TL;DR

This study explores using nasal skin temperature as a non-invasive biometric indicator to measure developers' cognitive load, aiming to reduce physical burden compared to traditional methods.

Contribution

It introduces a novel biometric measure based on nasal skin temperature for estimating cognitive load in software developers.

Findings

Nasal skin temperature measures are more effective than non-biometric measures.

Proposed biometric measures successfully estimated cognitive load during programming tasks.

Nasal skin temperature is a promising non-invasive indicator for cognitive load assessment.

Abstract

It has recently become increasingly important to measure the cognitive load of developers. This is because continuing with a development under a high cognitive load may cause human errors. Therefore, to automatically measure the cognitive load, existing studies have used biometric measures such as brain waves and the heart rate. However, developers are often required to equip certain devices when measuring them, and can therefore be physically burdened. In this study, we evaluated the feasibility of non-invasive biometric measures based on the nasal skin temperature. The nasal skin temperature has been widely used in other fields to measure mental status. In the present experiment, the subjects created small Java programs, and we estimated their cognitive load using the proposed biometric measures based on the nasal skin temperature. As a result, the proposed biometric measures were shown to be more effective than non-biometric measures. Hence, biometric measures based on nasal skin temperature are promising for estimating the cognitive load of developers.