Affichage de 9 questionnaires
sur un total de 9 questionnaires.
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Public
[PEER 2025 Template] AIA Index to duplicate and translate [EN]
Modifié le 18/12/2025 à 09h08
par
PEER project
This questionnaire of 59 items is the first version of the Artificial Intelligence Acceptance (AI) index. We have developed this questionnaire as part of the European PEER project.
This questionnaire assesses the trustworthiness of an AI assistant, by assessing the different constructs of trustworthiness, as defined below:
This questionnaire assesses the trustworthiness of an AI assistant, by assessing the different constructs of trustworthiness, as defined below:
- User agency
- Technical functioning
- Safety, security and well-being
- Privacy and data governance
- Comprehensibility
- Ethics
- Auditability
- Collaboration
- Anthropomorphism
- Others components of user experience
This questionnaire also includes control items to ensure that:
- The different constructs defined clearly measure trustworthiness
- Trustworthiness is a predictor of acceptance, by measuring the willingness to use the AI assistant in the futur and the trust
- Trust is properly measured
1
Pages
119
Questions
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Minutes
Public
[PEER 2025 - City of Amsterdam use-case] Semi-structured interview [NL]
Modifié le 18/12/2025 à 09h05
par
PEER project
Dit semigestructureerde interview wordt gebruikt om feedback van deelnemers te verzamelen na de gebruikerstest op:
- de AIA-index
- de AI-assistent
- alternatief ontwerp
- de AIA-index
- de AI-assistent
- alternatief ontwerp
3
Pages
32
Questions
15
Minutes
Public
[PEER 2025 - Proditec use-case] Semi-structured interview [FR]
Modifié le 18/12/2025 à 09h05
par
PEER project
Cet entretien semi-dirigé est utilisé pour recueillir l'avis des participants à la suite du test utilisateur sur :
- l'AIA index
- l'assistant IA
- l'AIA index
- l'assistant IA
2
Pages
26
Questions
15
Minutes
Public
[PEER 2025 - City of Amsterdam use-case] Semi-structured interview [EN] to duplicate and translate
Modifié le 18/12/2025 à 09h05
par
PEER project
This semi-structured interview is used to gather participants' feedback following the user test on:
- the AIA index
- the AI assistant
- alternative design
- the AIA index
- the AI assistant
- alternative design
3
Pages
51
Questions
15
Minutes
Public
[PEER 2025 - Proditec use-case] Semi-structured interview [EN] to duplicate and translate
Modifié le 18/12/2025 à 09h05
par
PEER project
This semi-structured interview is used to gather participants' feedback following the user test on:
- the AIA index
- the AI assistant
- the AIA index
- the AI assistant
2
Pages
26
Questions
15
Minutes
Public
[PEER 2025 - Sonae use-case] Semi-structured interview [EN]
Modifié le 18/12/2025 à 09h05
par
PEER project
This semi-structured interview is used to gather participants' feedback following the user test on:
- the AIA index
- the AI assistant
- the AIA index
- the AI assistant
2
Pages
26
Questions
15
Minutes
Public
[PEER 2025 - Sonae use-case] Socio-demographic questionnaire [EN]
Modifié le 18/12/2025 à 09h05
par
PEER project
This questionnaire enables you to obtain essential information about your participants (gender, age, socioeconomic status and disability).
The various criteria assessed by this questionnaire are traditional population segmentation criteria.
If you are targeting a specific population, these indicators will tell you whether your participants correspond to your target sample.
This information will also enable you to check that your sample is representative of the overall population.
This questionnaire also enables you to measure mitigation variable (trust propensity, willingness to accept the use of AI technologies, motivation, effort expectancy, AI literacy, reputation of the company).
These variables allow to control potential biases and confounding factors, i.e. variables that may unintentionally cause systematic errors or distortions and could lead to inaccurate results or non-representative results. Ignoring them could lead to biased outcomes and diminish the impact of the AIA index.
If you want to study different groups of participants, the socio-demographic data will enable you to create your different conditions.
The various criteria assessed by this questionnaire are traditional population segmentation criteria.
If you are targeting a specific population, these indicators will tell you whether your participants correspond to your target sample.
This information will also enable you to check that your sample is representative of the overall population.
This questionnaire also enables you to measure mitigation variable (trust propensity, willingness to accept the use of AI technologies, motivation, effort expectancy, AI literacy, reputation of the company).
These variables allow to control potential biases and confounding factors, i.e. variables that may unintentionally cause systematic errors or distortions and could lead to inaccurate results or non-representative results. Ignoring them could lead to biased outcomes and diminish the impact of the AIA index.
If you want to study different groups of participants, the socio-demographic data will enable you to create your different conditions.
2
Pages
13
Questions
2
Minutes
Public
[PEER 2025 - City of Amsterdam use-case] Observation grid [EN] to duplicate and to translate
Modifié le 18/12/2025 à 09h04
par
PEER project
Observation grid with 2 parts:
- Observation during the task
- Observation during the completion of the AIA index
2
Pages
22
Questions
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Minutes
Public
[PEER 2025 - Proditec use-case] Observation grid [FR]
Modifié le 18/12/2025 à 09h04
par
PEER project
Grille d'observation en 2 parties :
- Observation durant la tâche
- Observation durant l'AIA index
2
Pages
27
Questions
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Minutes
