CAPAS 2.0: a computer tool for coding transcribed and digitally recorded verbal reports.

Area of Science:

• Computer Science
• Psychology
• Linguistics

Background:

• Qualitative data analysis, particularly of verbal reports, presents challenges in consistency and efficiency.
• Existing software tools for coding verbal data have limitations in format compatibility and analytical flexibility.

Purpose of the Study:

• To introduce CAPAS 2.0, a novel software tool designed for comprehensive coding and analysis of verbal report data.
• To extend the capabilities of previous tools by accommodating both transcribed text and raw audio files.
• To facilitate robust qualitative data analysis through a localized encoding principle and seamless integration with statistical software.

Main Methods:

• CAPAS 2.0 processes verbal report data from transcribed text files or original digital audio recordings.
• The software presents individual verbal report segments in a randomized order for independent coding.
• A localized encoding principle is applied to ensure consistent and context-specific data categorization.

Main Results:

• CAPAS 2.0 successfully codes both transcribed and audio-recorded verbal report data.
• The software ensures independent coding of segments, enhancing data integrity.
• Coded data is converted into a format compatible with statistical packages like SPSS for further analysis.

Conclusions:

• CAPAS 2.0 offers a significant advancement in the analysis of verbal report data.
• The tool's flexibility in handling multiple data formats and its structured coding approach improve research efficiency and data reliability.
• CAPAS 2.0 empowers researchers to conduct more sophisticated analyses of qualitative verbal data.