Data and code underlying the bachelor thesis: Traits for a virtual coach to be a ”friend”

doi: 10.4121/20099102.v1
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: 10.4121/20099102
Datacite citation style:
Ali, Mahira; Albers, Nele; Brinkman, Willem-Paul (2022): Data and code underlying the bachelor thesis: Traits for a virtual coach to be a ”friend”. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/20099102.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This dataset contains data and code snippets from the analysis performed during the thesis, "Traits for a virtual coach to be a friend".  Here, an investigation has taken place to what characteristics the virtual coach must possess to establish this friendly relationship. Thus, the main research question is: What are the reasons for seeing the virtual coach as a stranger or friend? This research has been based on a retrospective study performed by Albers and Brinkman. Here, five hundred participants interacted with the text-based virtual coach Sam - developed for the Perfect Fit project to convince smokers to quit by performing small activities - in five separate sessions.  Afterwards, each participant rated the relationship with the virtual coach, followed by an explanatory free-text response to which thematic analysis was applied. The quality of the thematic analysis has been ensured by researcher and method triangulation. Researcher triangulation, where multiple

researchers were involved, determined the reliability of the coding scheme generated during thematic analysis. Method triangulation, which supported the findings, was executed with the free-text responses, literature, and quantitative data, containing demographic and smoke-related characteristics.

 

history
  • 2022-06-21 first online, published, posted
publisher
4TU.ResearchData
format
*.xlsx, *.py, *.txt, *.csv, *.png, *.jpg
funding
  • Part of Perfect Fit, funded by NWO, project number 628.011.211
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems, Interactive Intelligence

DATA

files (19)