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

Authors

  • Tahir Abbas Mirpur University of Science and Technology
  • Vassilis-Javed Khan Eindhoven University of Technology
  • Ujwal Gadiraju Delft University of Technology
  • Panos Markopoulos Eindhoven University of Technology

Abstract

On-demand emotional support is an expensive and elusive 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 thoughtful 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.

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Published

2020-10-01

How to Cite

Abbas, T., Khan, V.-J., Gadiraju, U., & Markopoulos, P. (2020). Trainbot: A Conversational Interface to Train Crowd Workers for Delivering On-Demand Therapy. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 8(1), 3-12. Retrieved from https://ojs.aaai.org/index.php/HCOMP/article/view/7458