Data and code underlying the bachelor thesis: Traits for a virtual coach to be a ”friend”
doi: 10.4121/20099102
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.
- 2022-06-21 first online, published, posted
- Part of Perfect Fit, funded by NWO, project number 628.011.211
DATA
- 2,448 bytesMD5:
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README.txt - 45,833 bytesMD5:
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Charts_Initial_code.xlsx - 1,132 bytesMD5:
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cohens_kappa.py - 14,621 bytesMD5:
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Cohens_Kappa.xlsx - 729 bytesMD5:
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Console_Output_Cohens_Kappa.txt - 224,225 bytesMD5:
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CSV Strings.xlsx - 1,121 bytesMD5:
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data1.csv - 1,021 bytesMD5:
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data2.csv - 353,123 bytesMD5:
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Final_Coding.xlsx - 112,745 bytesMD5:
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Frequencies.png - 2,233 bytesMD5:
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heatmap_matplot.py - 256,345 bytesMD5:
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Initial_Coding.xlsx - 88,360 bytesMD5:
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My_Encoding.csv - 1,004 bytesMD5:
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pbcc.py - 945 bytesMD5:
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phi_coef.py - 1,186,146 bytesMD5:
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Second_Coding.xlsx - 87,045 bytesMD5:
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Second_Encoding.csv - 1,103 bytesMD5:
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spearman.py - 2,036,162 bytesMD5:
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Thematic Analysis Compared Codes.jpg -
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