Teacher-Student Interaction and Learning in On-Line Theological Education. Part III: Methodological Approach

Many theological educators ask how on-line classes can provide students with the kind of personal teacher-student interaction that is needed in a healthy and holistic approach to preparation for ministry. A quantitative study was undertaken for the purposes of examining the relationships between three major types of teacher-student interaction (organizational, social, and intellectual) and two types of learning outcomes (cognitive and affective). Seminary students from nine seminaries accredited by the Association of Theological Schools were invited to complete a Web-based survey about their experience in on-line courses. In the first two sections of this four-part report, the research concern was introduced and the theoretical framework was reviewed. Literature relevant to teacher-student interaction in on-line higher education, the teacher-student relationship in theological education, learning outcomes in higher education, and the Web-based survey research approach used in this study was considered. This third section explains the author's methodological approach to the research, the results of which will be reported in Part IV.

Notes

¹The investigation was limited to Web-based courses with no face-to-face component in order to limit potentially confounding factors. Vrasidas and McIsaac found that when a course has both face-to-face and online interaction, the online component can suffer in amount and quality (1999, 29).

²This is only an approximate number, since the newsletter cited cautioned that the list was not complete. At that time a total of 244 member and candidate schools were listed in the ATS website directory.

³This occurrence was probably attributable to unclear communication. Many e-mails and phone calls were needed to keep the process flowing. Although the directors responded with good will and as quickly as their crowded agendas allowed, there were inevitable miscommunications and delays.

⁴Dillman's widely used “Total Design Method” for mail surveys prescribes a one-week interval between the initial mailing and each of the three reminders (1978, 183). By contrast, Crawford et al. report that they and others have found that “if people are going to complete a Web survey, they do so within the first few hours or days” (2001, 147). Though this was also found to be true in the present study, it was generally not possible, working indirectly through the various directors, to get reminders out to potential participants less than a week after the previous communication.

⁵For alternate but similar approaches, see Grubb and Hines, 2000, 368; Coppola, Hiltz, and Rotter, 2001, 2; and Anderson, Rourke, Garrison, & Archor, 2001.

⁶The method used to maximize these values was to drop the weakest item and recalculate until the value of coefficient alpha stopped increasing.

⁷All three are professors of education and authors of major publications on learning: Lorin W. Anderson (University of South Carolina), David R. Krathwohl (Syracuse University), and Klaus D. Issler (Biola University).

⁸This scale consists of two questions: “On a scale of 0–9, how much did you learn in the course, with 0 meaning you learned nothing, and 9 meaning you learned more than in any other course you’ve had?” and “How much do you think you could have learned in the course had you had the ideal instructor?”

⁹The Richmond, Gorham, and McCroskey scale calculates a “learning loss” value by subtracting student estimations of learning from their estimation of learning in the ideal situation. Therefore, the smaller the value, the more cognitive learning the student perceived as achieving. This way of measuring produces the negative correlation.

¹⁰Missing data were plugged with the mean of the remaining responses (Cohen, 1983, 292). The columns were moved because the Quask software downloaded the data in reverse order for any given screen in Section Two.