Title: Applying data science to gauge virtual assistants' impact on students' well-being during the pandemic

Authors: Swapnil Morande

Addresses: Department of Economics, Management and Institutions, University of Naples FEDERICO II, Napoli, Italy

Abstract: The research offers insights into the impact of the pandemic on students and ruminates on mitigating the negative consequences by using a virtual assistant (VA). In an experimental setting, the study treats 'stress' as a critical factor that relates to students' well-being. The research is exploratory, where mixed-mode data is captured from students using a questionnaire and integrated virtual assistant simultaneously. The research findings establish the role of a virtual assistant to support preventive, predictive, and personalised health. It illuminates heart rate variability as one of the key indicators of perceived stress. As this research is based on the extensive literature on a method called 'photoplethysmography', it can further be scaled for supporting large groups of students. The outcome of the study can be further extended to industries where stress might be detrimental to well-being. The study contributes to the innovative application of data science to reflect on students' well-being.

Keywords: virtual assistant; COVID-19; machine learning; DeepNet modelling; well-being; data science.

DOI: 10.1504/IJADS.2024.139414

International Journal of Applied Decision Sciences, 2024 Vol.17 No.4, pp.513 - 541

Received: 02 Feb 2023
Accepted: 08 Apr 2023
Published online: 02 Jul 2024 *

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