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Conversational agents : using open card sorting to evaluate the factor structure of the BUS-11

Wermter, C.E. (2023) Conversational agents : using open card sorting to evaluate the factor structure of the BUS-11.

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Abstract:This paper examines the factor structure of the Bot Usability Scale (BUS) as proposed by Borsci et al. (2022). The BUS incorporates aspects of communication, as well as the user’s perception of data security, making it more suitable for the assessment of chatbots than commonly used usability scales (Borsci et al., 2021). Recent research has indicated that the recent version of the BUS-11, has only four instead of five underlying factors (Borsci & Schmettow, 2023). This study investigates the factor structure, with a new approach by deriving factor models from the mental models of users. For the identification of mental models an open card sorting was conducted. The results included the mental models of 47 participants and were assessed with heatmap analyses. The newly created models and the Four-Factor Model by Borsci & Schmettow (2023) were additionally, evaluated with a confirmatory factor analysis. The results indicated that the Four-Factor Model proposed by Borsci & Schmettow (2023) could be identified during the heatmap analysis if a lenient threshold of 30% agreement was applied. The confirmatory factor analysis suggested that the Four-Factor Model by Borsci & Schmettow (2023) was not fitting the data used for the confirmatory factor analysis. Two of the three novel models showed an acceptable fit to the data. Based on the Akaike information criterion and Bayesian information criterion, a hierarchical model with four first-order factors and thee second-order factors provided the best fit for the data.
Item Type:Essay (Bachelor)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:77 psychology
Programme:Psychology BSc (56604)
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