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Description Strategy Selection in Collaborative Spatial Tasks

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Man-Machine-Environment System Engineering (MMESE 2022)

Abstract

Objective—To examine the efficiency of description strategies people used in collaborative spatial tasks. Methods—Study1 asked participants (N = 30) to describe the location of specific objects under different spatial conditions. The experimental conditions contained different spatial layouts (regular, irregular) and visibility of the interactive partner’s perspective (available, unavailable). We recorded all the utterances and categorized them by the description strategies involved. Study2 tested the efficiency of these strategies. Participants (N = 30) were guided by different kinds of descriptions to make spatial judgments. Results— (1) There are four spatial description strategies most commonly used: Addressee-centered, Exocentric, Object-based and Egocentric. (2) Participants’ spontaneous descriptions were affected by their partner’s viewpoint. When the partner's viewpoint is unavailable, they tend to represent spatial information exocentrically. (3) Organizing spatial instructions in an exocentric way led to better task performance. Conclusion—If the collaborators have common cognition of spatial directions and references, exocentric reference frame could maximize the efficiency of spatial interactions.

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Acknowledgement

This work is supported by the Space Medical Experiment Project of China Manned Space Program (No. HYZHXM03001), and Funding Project of National Key Laboratory of Human Factors Engineering (No. SYFD061902, No. SYFD061903).

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Correspondence to Yu Tian .

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The study was approved by the Department of Psychology, Zhejiang Sci-Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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Zhu, Y. et al. (2023). Description Strategy Selection in Collaborative Spatial Tasks. In: Long, S., Dhillon, B.S. (eds) Man-Machine-Environment System Engineering. MMESE 2022. Lecture Notes in Electrical Engineering, vol 941. Springer, Singapore. https://doi.org/10.1007/978-981-19-4786-5_59

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  • DOI: https://doi.org/10.1007/978-981-19-4786-5_59

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  • Online ISBN: 978-981-19-4786-5

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