Methodology

This section will provide a detailed explanation of the methodology employed in generating evangelistic sermons using ChatGPT. Furthermore, the process of utilizing a Grounded Theory approach for analysis will be elaborated on.

Data Collection

The data collection process consisted of three distinct rounds utilizing the free version of ChatGPT available on OpenAI’s website26. A total of 27 sermons were generated throughout these rounds. In the first round of data collection, fifteen sermon texts were generated using the prompt: “Write an evangelistic sermon about the gospel with references from the Bible. Conclude with a prayer”. The ChatGPT Feb 13 version was utilized for this round. In the second round of data collection, seven sermon texts were generated using the prompt: “Write an evangelistic sermon about the gospel with references from the Bible. Include personal illustrations. Conclude with a prayer.” For this round, the ChatGPT Mar 14 version was utilized. Lastly, in the third round of data collection, five sermon texts were generated using the prompt: “Write an evangelistic sermon about the gospel.” This rounded utilized the ChatGPT May 3 version. The generated texts were processed by removing additional information that did not constitute part of the sermon which would be delivered such as the title of the generated sermon and its section headers.
The first prompt was designed to generate sermons that follow the typical sermon structure employed by evangelical preachers. This was intended to simulate inputs that Christian users might provide. The second prompt was formulated to facilitate theoretical sampling and investigate the incorporation of personal illustrations within the sermon, as explained in the subsequent sections. Lastly, the prompt used in the final round aimed to compare how ChatGPT would generate an evangelistic sermon with minimal instructions from the user.