Student Perceptions of Important Online Instructor Behaviors in Online Courses

Online instructors engage in many behaviors in online courses. They take deliberate actions to design effective learning environments that engage students both cognitively and affectively. Not all of the actions are qualitatively equal in terms of their impact on student success in online learning. The purpose of this study was to determine what instructor behaviors students considered most important for their own success. This study utilized a cross-sectional survey design to answer the following research questions: 1. How important are various instructor behaviors for students enrolled in online courses? 2. What instructor behaviors do students consider to be most important for their success in online courses? The survey instrument, which was administered online, consisted of three sets of items: 64 close-ended items to measure the importance of various instructor actions in online courses, 5 open-ended items for students to indicate the actions that were most important to them, and a mixture of open- and close-ended items targeting students’ experience with online learning and their preferences for various learning contexts. The list of instructor actions was compiled primarily from existing literature on the role of instructor presence and community building in online courses. Additional items were added based on instructor experience. Students were asked to rate each behavior on a scale of 1 (not important at all) to 10 (very important) in terms of its importance for them as students enrolled in an online course. For the open-ended items, students were asked to “write the 5 most important. instructor behaviors for your success in an online class. (You may use behaviors from the list below, or add others).” The close-ended items were analyzed primarily using descriptive statistics. Of particular interest were the items that had the highest mean ratings (as an indication of the behaviors that were considered most important), the lowest mean ratings (as an indication of the behaviors that were considered least important) and the highest dispersion (as an indication of the items for which there was least consensus). We also examined the potential correlations between the number of online courses that students had taken and the ratings on a subset of items. Spearman’s rho was used for the correlation coefficient as both the ratings and online course experience were treated as ordinal scales. For the open-ended items, we engaged in several levels of analysis, including classical content analysis (Leech & Onwebbuzie, 2007) and concept mapping. The purpose of the content analysis was to determine what instructor actions were most important to the students based on the number of occurrences of the code. During the first phase of content analysis, we deductively coded the open-ended responses by assigning the variable names used for the close-ended items. The purpose of this deductive analysis was to determine how the behaviors that the students deemed most important aligned with the close-ended ratings. For any responses that did not have an existing match in the codebook, we created a new open code. At the end of the initial coding pass which had been done independently, we reviewed the coded responses simultaneously. From the final coding pass, we generated frequency data for each code as an indicator of its importance. Due to the hierarchical nature of some of the close- and open-ended items, we constructed a concept map to show the relationship among the assigned codes. This analysis was extremely helpful for representing the specificity in some of the responses. For example, for some students simply being getting feedback was most important whereas for other students, the timeliness or constructiveness of the feedback was most important. By superimposing the results of the content analysis onto the map, we were able to examine both the relative importance of groups of actions and the level of specificity that was important. Among the 10 most important instructor behaviors were making course requirements clear and explicit and responding to students in a timely manner. The behaviors that were least important to students included the instructor having a personal website that they could visit, student ice breakers, and live chats. The implications of these findings help instructors and designers examine the most effective ways to spend time in designing, preparing and administering online learning environments.