BACKGROUND
Files underlying the statistical analysis reported in the paper

Li, F., Fitrianie, S., Bruijnes, M., Abdulrahman, A., Guo, F., & Brinkman, W. P. (2023) Mandarin Chinese translation of the Artificial-Social-Agent questionnaire instrument for evaluating human-agent interaction. Frontiers in Computer Science, 5, 1149305.

doi:10.3389/fcomp.2023.1149305

with this URL:
https://www.frontiersin.org/articles/10.3389/fcomp.2023.1149305


The Artificial-Social-Agent (ASA) questionnaire is an instrument for evaluating human-ASA interaction. It consists of 19 constructs and related dimensions measured by either 24 questionnaire items (short version) or 90 questionnaire items (long version). This study presents a Mandarin Chinese translation of the ASA questionnaire. 
With the translation procedure of the ASA questionnaire, including forward translation, formative bilingual assessment and backward translation, we determined the final Mandarin Chinese version of the ASA questionnaire.

We gave both the final version of the translated and original English questionnaire to 242 bilingual crowd-workers to evaluate 14 ASAs. The analysis was carried out on evaluation scores collected in questionnaire surveys, in which bilingual participants were recruited to rate human-ASA interaction in a video clip on both English items and corresponding Chinese translations. To validate the Chinese translation version of ASA questionnaire, correlation and variation between the English and Chinese ASA questionnaire were analyzed, for item level, construct/dimension level and the short version of the ASA questionnaire. 

Furthermore, combining human-ASA interaction evaluation of 532 mixed international English-speaking participants in our previous study, and 242 bilingual participants in this study, multilevel analysis was implemented to compare human-ASA interaction between these two cultural backgrounds.

Corresponding author: Willem-Paul Brinkman, w.p.brinkman@tudelft.nl; Fengxiang Li, fengxianglire@126.com

This work was funded by the Dutch 4TU - Humans and Technology, Pride and Prejudice project, and the China Scholarship Council (CSC) [grant number: 202006080121].

19 April 2024

Files can be found at

https://doi.org/10.4121/12bb2e67-85f0-41c0-bd34-4cca100e4aaf

Note: The original 10 December 2022 "Questionnaire translation and validation paper-analysi.rmd" file contained an error with regard to comparison of Human-ASA Interaction between different cultural backgrounds.  For each second construct/dimension, the means were swapped between Chinese and English data in the output tables, and consequently, the plus and minus signs for the delta and CI values were also wrong. This has been corrected in 20240419 version of the file.

==================================================

FILES

(1) Questionnaire translation and validation paper-analysis 20240419.Rmd
     The corrected R markdown file is a plain text file that contains markdown and R code chunks of the statistical analyses reported in the journal paper. Correction relate to section "Comparison of Human-ASA Interaction between Different Cultural Backgrounds".   

(2) Questionnaire translation and validation paper-analysis 20240419.pdf
     This is the knitted R markdown pdf file. It presents the data structure of data files, and analyses results reported in the following subsections of the journal paper:
     1) Correlation between English and Chinese ASA Questionnaire; 
     2) Variation between English and Chinese ASA Questionnaire; and 
     3) Comparison of Human-ASA Interaction between Different Cultural Backgrounds.

(3) Transformation from raw data to the input data files.Rmd
     The R markdown file is a plain text file that contains markdown and R code chunks of transformation of seven raw data files to the pre-processed input data files  'data01.sav', 'data02.sav' and 'data_culture.sav'.

(4) Transformation from raw data to the input data files.pdf
     The knitted R markdown pdf file explaining how we transform raw data files into the three pre-processed input data files used for further analysis in the study. Interpretations of results are also included in the file.

(5) header.tex
     We use the R  package 'ctex' to generate the knitted R markdown files that contain Chinese characters. This file contains the format commands of 'Contents' and 'Table'.

(6) Questionnaire translation and validation paper analysis.bib
    This file contains literature references in the markdown file 'Questionnaire translation and validation paper-analysis.Rmd' and 'Transformation from raw data to the input data files.pdf'.

(7) Transformation from raw data to the input data files.bib
     This file contains literature references in the markdown file 'Transformation from raw data to the input data files.Rmd' and 'Transformation from raw data to the input data files.pdf'.
     
(8) Pre-processed Data files
    1) data01.sav
    2) data02.sav
    3) data_culture.sav

    
The content of pre-processed and original raw data files is described in the file "Transformation from raw data to the input data files.pdf".

