PuzzleAide: Comparing Audio and Embodied Assistants for MR Puzzle-Solving

Conversational Virtual Agents (CVA) have great potential to assist users in their task performance. Whether these agents need to be embodied or not was the main research question of the present pilot study. To answer this question, we designed and developed a Mixed Reality (MR) application for solving a physical puzzle while interacting with a CVA. Eleven participants took part in our between-subject pilot study and interacted with two different representations of a CVA (i.e., voice-only and embodied agent). In this short paper, we descriptively report on the participants’ problem-solving time, the number of assistance requests they made to the CVAs, and the social presence they perceived while doing so.

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Published
2024-09-13
DOI
https://doi.org/10.1145/3677386.3688899
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
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article

PuzzleAide: Comparing Audio and Embodied Assistants for MR Puzzle-Solving

Gustavo Marfia, A. Lux, Fariba Mostajeran, Frank Steinicke et al.
Intelligent Tutoring Systems and Adaptive Learning
article

PuzzleAide: Comparing Audio and Embodied Assistants for MR Puzzle-Solving

Gustavo Marfia, A. Lux, Fariba Mostajeran, Frank Steinicke, Pasquale Cascarano, Shirin Hajahmadi, Kevin Heuer, Gil Otis Mends-Cole
article en

Abstract

Conversational Virtual Agents (CVA) have great potential to assist users in their task performance. Whether these agents need to be embodied or not was the main research question of the present pilot study. To answer this question, we designed and developed a Mixed Reality (MR) application for solving a physical puzzle while interacting with a CVA. Eleven participants took part in our between-subject pilot study and interacted with two different representations of a CVA (i.e., voice-only and embodied agent). In this short paper, we descriptively report on the participants’ problem-solving time, the number of assistance requests they made to the CVAs, and the social presence they perceived while doing so.

Universität Hamburg (DE), University of Bologna (IT)
Openalex Percentile: Top 87%
Intelligent Tutoring Systems and Adaptive Learning
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PuzzleAide: Comparing Audio and Embodied Assistants for MR Puzzle-Solving — Gustavo Marfia, A. Lux, et al. · (2024) | TGRS Research Map | TGRS