In studying online learning, researchers should examine three critical interactions: instructor-student, student-student, and student-content. Studentcontent interaction may include a wide variety of pedagogical tools (e.g., streaming media, PowerPoint, and hyperlinking). Other factors that can affect the perceived quality of online learning include distance education advantages (e.g., work and family flexibility) and antecedent personal characteristics (e.g., experience and gender). The study indicated that instructor-student interaction is most important, twice that of student-student interaction; that some student-content interaction is significantly related to perceived learning; that antecedent variables are not significant; and that distance education advantages/flexibility, although significant, are less important than other interactions.

Using structural equation modeling (LISREL) with a sample of business students, this study addresses important issues with respect to student evaluations. After reviewing past research and using exploratory factor analysis, confirmatory factor analysis suggests the existence of five latent variables in student evaluations: organization, workload/difficulty, expected/fairness of grading, instructor liking/concern, and perceived learning. Next, adding structural paths, these variables are used to model the formation of student evaluations. The models developed demonstrate that student evaluations may lack discriminant validity, the extent to which a measure does not correlate with other constructs it is not supposed to measure (e.g., expected/fairness of grading does have a large impact on ratings of teaching ability). Moreover, the use of student evaluations is compounded by the common usage of global measures in student evaluation practice. Here, the use of overall course value and instructor rating are contrasted. The results are disparate, raising questions about the use of summative measures (i.e., of what should they be composed, if used at all).

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