Trainbot: A Conversational Interface to Train Crowd Workers for Delivering On-Demand Therapy

Conference paper (2020)

Authors

Tahir Abbas Eindhoven University of Technology
Vassilis-Javed Khan Eindhoven University of Technology
Ujwal Gadiraju Web Information Systems - EEMCS
Panos Markopoulos Eindhoven University of Technology
Research Group
Web Information Systems (EEMCS) (TU Delft)
Copyright: © 2020 Tahir Abbas, Vassilis-Javed Khan, Ujwal Gadiraju, Panos Markopoulos
More Info
expand_more

Published Date

2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Web Information Systems

Abstract

On-demand emotional support is an expensive and elu- sive societal need that is exacerbated in difficult times – as witnessed during the COVID-19 pandemic. Prior work in affective crowdsourcing has examined ways to overcome technical challenges for providing on-demand emotional support to end users. This can be achieved by training crowd workers to provide thought- ful and engaging on-demand emotional support. Inspired by recent advances in conversational user interface research, we investigate the efficacy of a conversational user interface for training workers to deliver psychological support to users in need. To this end, we conducted a between-subjects experimental study on Prolific, wherein a group of workers (N=200) received training on motivational interviewing via either a conversational interface or a conventional web interface. Our results indicate that training workers in a conversational interface yields both better worker performance and improves their user experience in on-demand stress management tasks.