QUALITATIVE INVESTIGATION OF TAM
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The native JotForm analysis software is used to review the recent landscape assessment
conducted through the Extension Foundation, along with statistical analysis of select responses
in Python. The one-on-one semi-structured interviews is conducted over videoconferencing
tools, transcribed with artificial intelligence technology, and coded for themes in participant
responses. Ravitch and Carl (2021) state that data organization and management are an
important, ongoing process that supports refining sense-making and are integral parts of the
overall analysis. Post-interview surveys collect qualitative data and are coded in the same way as
semi-structured interviews. The data management plan for this research includes organizing the
landscape assessment data within the native analytics tools of the JotForm survey software. A
precoding process takes place to effectively sort and filter the data based on responses related to
the TAM, focusing on perceived usefulness and perceived ease of use. Additionally, pre-coded
fields are filtered by institutions that have implemented CRM, are evaluating the use of CRM,
have discontinued the use of CRM, or have no plans to use CRM.
Ravitch and Carl (2021) also offer insights into the best data management practices for
transcribing and coding interview data for the second phase of this research. First, the original
audio and video recordings of the interviews are stored on Extension Foundation storage servers,
along with a backup copy on a local computer. Artificial intelligence software native to Zoom is
utilized to generate a verbatim written transcript of the interviews, which are subsequently
verified by comparing it to the original recording and updated manually with any necessary
corrections. According to Ravitch and Carl’s (2021) recommen dation, transcripts are not
“cleaned up” in order to have a set of data that best reflects participants’ responses. The pre-
coding process includes utilizing Google Docs to track changes and highlight areas of the semi-
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