Preprint: “Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors”

We are excited that our paper “Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors” by Manuela Züger and Thomas Fritz was accepted for CHI 2015 and like to share a preprint with you.

Interruptions of knowledge workers are common and can cause a high cost if they happen at inopportune moments. Our paper presents a lab and a field study with a total of 20 software developers, where we examined the use of psycho-physiological sensors to measure interruptibility of a knowledge worker in a real-world context.

The results show that a Naïve Bayes classifier can be used to automatically assess states of a knowledge worker’s interruptibility with high accuracy in the lab as well as in the field. This demonstrates the potential of psycho-physiological sensors to avoid expensive interruptions. For instance, such a classifier could be used to automatically turn of notifications while a knowledge worker’s interruptibility is low.

The preprint of the paper can be downloaded here.

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