Master your practice! A quantitative analysis of Device and system handling training to enable competent interactions with intelligent voice assistants

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL Computers in human behavior reports Pub Date : 2025-02-08 DOI:10.1016/j.chbr.2025.100610
Maximilian Baumann , André Markus , Jan Pfister , Astrid Carolus , Andreas Hotho , Carolin Wienrich
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Abstract

Intelligent voice assistants (IVAs), such as Siri or Alexa, are voice-based artificial intelligence (AI) systems that help users solve everyday tasks using voice commands. Users often have a superficial understanding of the full range of functions IVAs can be used for and how to use them effectively. Since higher knowledge of device and system handling is fundamental for positive interaction quality and self-determined use of IVAs, this study examines how training can contribute to the promotion of variables such as usage aspects, social perception, and self-determined interaction and how such training can be designed. Based on an established competence framework and the principles of learning psychology and media didactics, three online training modules were developed to strengthen the user's device and system handling competence, and their effects on the parameters of competent AI interaction were investigated. A total of 110 students took part in the three training studies. Results of dependent t-tests show that completing training modules improves device and system handling and increases the intention to use IVAs more self-determined. In detail, participants perceive IVAs as more useful, tend to be more explorative and indulgent, feel more competent to use IVAs, and perceive them as less disturbing. Overall, the paper demonstrates the effectiveness of training in improving the perceived usefulness of IVAs, exploratory and indulgent behavioral intentions, and decreasing the disturbance of IVAs. This work has great potential for research and education to improve, explore, and advance user behavior and competent interaction with IVAs, as well as for broader AI applications.
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