This research illustrated a new, parsimonious model that investigators interested in distance education can use to ask meaningful questions about the relative quality of distance education courses (Dominguez & Ridley, 1999). The approach removed the emphasis from student-level data and placed it upon course-based data. Sample data comparing online and traditional higher education courses covering nine disciplines were reported. These data revealed that preparation for advanced courses was statististically equivalent whether the course prerequisites were online courses or their traditional classroom counterparts. The article further explored the usefulness of this framework for identifying a significant discipline-related difference in the relative effectiveness of online and traditional prerequisites as preparation for advanced courses.
In this article, we have further explored an alternative framework for assessing distance education courses (Dominguez & Ridley, 1999). The article reviews the rationale for our new approach and presents a new analysis with updated data to demonstrate an application beyond our earlier presentation. The new application explores an apparent departmental difference found in the new analysis.
Student performance in the here and now of a distance education course is typically at the center of assessment of their effectiveness. That is, investigators usually attend to how well students score on tests, exams, and assignments within the context of the distance education course itself. If comparisons with student performance in traditional classroom settings are to be made, they generally involve courses taken contemporaneously with the distance education course. In this way, assessments of distance education programs have amassed results that resemble a series of snapshots looking at the program and student performance on a semester-by-semester basis.
Using the student-level data within a particular time frame, institutions, distance education programs, and individual faculty have created a detailed portrait of distance education students and have established the comparability of student learning between distance education and traditional settings. This is a good beginning. Now that institutions have overcome the initial hurdles of establishing the first-generation distance education programs, the need arises for more elaborate, action-oriented information.
Focusing on student-level data tells only a limited tale. For example, generating a profile of the "successful" distance education student does not provide institutions with practical information for program improvement or refinement. What can an institution do with this piece of data? It is anathema in higher education to deny students entry into a course based on their demographic profile. Indeed, pushing the envelope of students' abilities is at the core of instruction. Neither does the information really help out individual faculty members interested in improving distance education students' performance. Faculty members simply do not have the power to age a student five years, produce several offspring for them, or boost their G.P.A. half a point. What else can be done to provide institutions and faculty members with action-oriented information about the quality of instruction found in distance education programs compared with instruction in on-campus classes?
We propose a two-pronged shift in distance education investigations. The first shift removes the emphasis on distance education students and places it on the course itself. The second expands the scope of investigations to include distance education students' subsequent performance in other classes. Using these parameters, such an assessment would question how well distance education courses prepare students for further study. Moreover, such an approach would allow institutions to compare student preparation in distance education settings versus their preparation in traditional education settings. …