The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/9db602be-f748-46d7-b75d-874a1a0c244f

Hensman, Johan; Tesink, Kriss; Albers, Nele; Brinkman, Willem-Paul (2023): Dutch ASA Questionnaire Translation - Translation and Formative Assessment: Rounds 1 and 2. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/9db602be-f748-46d7-b75d-874a1a0c244f.v1

Dataset

• Artificial Intelligence and Image Processing
• Information and Computing Sciences

Artificial social agents, Chatbot, Robot, Translation, Virtual agents

29 May 2023 - 17 June 2023

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by Johan Hensman, Kriss Tesink, Nele Albers , Willem-Paul Brinkman

This is the data and analysis code for the first two rounds of the formative assessment of the Dutch translation of the English Artificial Social Agent (ASA) Questionnaire. This questionnaire can be used to characterize interactions between humans and ASAs.

The original English questionnaire can be found with this DOI: 10.4121/19650846.

Studies

The formative assessment so far consists of two rounds of assessing the correlation between original English questionnaire items and their Dutch translations. English items with too low correlation scores in a round are retranslated and re-assessed in the subsequent round. The assessment consists of people who indicate having Dutch as their first and primary language, being fluent in English, and being bilingual rating the English items and their Dutch translations for the human-ASA interaction depicted in a 30-second video clip. The studies were run on the online crowdsourcing platform Prolific.

So far, we have only done the first two of three rounds (each consisting of a translation of English items into Dutch and a subsequent evaluation of the resulting correlations based on a crowdsourcing study). The two studies were run between the 29th of May and the 17th of June 2023.

The studies have been pre-registered here: https://osf.io/adknw.

Data

For each of the two rounds, we provide the ratings for the English and Dutch questionnaire items as well as data on the characteristics of the participants (age, gender, highest completed education level from their Prolific profiles). A random identifier called "rand_id" can be used to link the data files.

In case of questions, please contact Nele Albers (n.albers@tudelft.nl) or Willem-Paul Brinkman (w.p.brinkman@tudelft.nl).

• 2023-06-26 first online, published, posted

4TU.ResearchData

.zip, .md, .pdf, .py, .rmd, .csv, .txt, .sav, .rmd

• This work is part of the multidisciplinary research project Perfect Fit, which is supported by several funders organized by the Netherlands Organization for Scientific Research (NWO), program Commit2Data - Big Data & Health (project number 628.011.211). Besides NWO, the funders include the Netherlands Organisation for Health Research and Development (ZonMw), Hartstichting, the Ministry of Health, Welfare and Sport (VWS), Health Holland, and the Netherlands eScience Center.

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems, Interactive Intelligence