The Partner Modelling Questionnaire: A Validated Self-Report Measure of Perceptions toward Machines as Dialogue Partners

Recent work has looked to understand user perceptions of speech agent capabilities as dialogue partners (termed partner models), and how this affects user interaction. Yet, partner model effects are currently inferred from language production as no metrics are available to quantify these subjective perceptions more directly. Through three phases of work, we develop and validate the Partner Modelling Questionnaire (PMQ): an 18-item self-report semantic differential scale designed to reliably measure people’s partner models of non-embodied speech interfaces. Through confirmatory factor analysis, we confirm that the PMQ scale consists of three factors: communicative competence and dependability, human-likeness in communication and communicative flexibility. Our studies show that the measure consistently demonstrates good internal reliability, strong test-retest reliability over 4- and 12-week intervals, and predictable convergent/divergent validity. Based on our findings, we discuss the multidimensional nature of partner models, while identifying key future research avenues that the development of the PMQ facilitates. Notably, this includes the need to identify the activation, sensitivity, and dynamism of partner models in speech interface interaction.

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Publication Details

Journal
ACM Transactions on Computer-Human Interaction
Published
2025-04-17
DOI
https://doi.org/10.1145/3729170
Citations
2
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
4.96
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article

The Partner Modelling Questionnaire: A Validated Self-Report Measure of Perceptions toward Machines as Dialogue Partners

Leigh Clark, Daniel Rough, Anna Bleakley, Odile Dumbleton et al.
2 citations
ACM Transactions on Computer-Human Interaction
AI in Service Interactions
4.96
article

The Partner Modelling Questionnaire: A Validated Self-Report Measure of Perceptions toward Machines as Dialogue Partners

Leigh Clark, Daniel Rough, Anna Bleakley, Odile Dumbleton, Diego Garaialde, Philip R. Doyle, Holly P. Branigan, Iona Gessinger, Benjamin R. Cowan, Justin Edwards
article en
2 citations

Abstract

Recent work has looked to understand user perceptions of speech agent capabilities as dialogue partners (termed partner models), and how this affects user interaction. Yet, partner model effects are currently inferred from language production as no metrics are available to quantify these subjective perceptions more directly. Through three phases of work, we develop and validate the Partner Modelling Questionnaire (PMQ): an 18-item self-report semantic differential scale designed to reliably measure people’s partner models of non-embodied speech interfaces. Through confirmatory factor analysis, we confirm that the PMQ scale consists of three factors: communicative competence and dependability, human-likeness in communication and communicative flexibility. Our studies show that the measure consistently demonstrates good internal reliability, strong test-retest reliability over 4- and 12-week intervals, and predictable convergent/divergent validity. Based on our findings, we discuss the multidimensional nature of partner models, while identifying key future research avenues that the development of the PMQ facilitates. Notably, this includes the need to identify the activation, sensitivity, and dynamism of partner models in speech interface interaction.

ACM Transactions on Computer-Human InteractionVol. 32(4)
University College Dublin (IE), University of Dundee (GB), Swansea University (GB), Foundry (United Kingdom) (GB), University of Oulu (FI), University of Edinburgh (GB)
Openalex Percentile: Top 6%
AI in Service Interactions
4.96
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