This qualitative research project developed a model over time through a detailed, in-depth Simplifying Conditions Method (SCM) interview (Reigeluth, 2001) of community college faculty members at an Indiana community college. Four faculty members, who met the credentials to be considered Subject Matter Experts (SMEs), were interviewed to determine the learning episodes to include within a faculty-training program for the conversion of a traditional course to an online course. The tasks identified were then organized and placed into a comprehensive Data Categorization Table. Included within this Data Categorization Table are complexity ratings and time required for each learning episode.

This newly devised instrument, the Data Categorization Table, is divided into five major learning episodes that are further subdivided into tasks and sub-tasks. Using this Data Categorization Table, course designers can effectively transform traditional courses to effective online learning experiences. This Data Categorization Table can also be used as the basis for the creation of a comprehensive web-based or traditional training program for course designers unfamiliar with the process of converting a traditional course to an online course.

It was concluded from this research that the SCM process can be an exceptional SME interview methodology. Supplementing the SCM process, the researcher used the open source FreeMind mind-mapping software. FreeMind facilitated the collection of data during the SCM process. Constructing the individual mind-maps and consolidating the data from the multiple interviews generated a specific sequencing of learning episodes, tasks and sub-tasks necessary to convert a traditional course to an online course. As these mind-maps were created, the SMEs also identified several quality issues now facing faculty teaching online courses.