DOES TEACHING ONLINE TAKE MORE TIME?

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1 DOES TEACHING ONLINE TAKE MORE TIME? Gregory W. Hislop 1 Abstract Many instructors feel that teaching online takes more time, but there is relatively little data available on this issue. This paper discusses a study that involves detailed recording of instructor time in online and traditional course sections to support a comparison between the two modes of delivery. The presentation describes the study approach and problems encountered in trying to get an accurate picture of instructor time. The presentation also includes results of an analysis of instructor time for a series of course section pairs. Each section pair includes one online and one faceto-face section of the same course taught by the same faculty member. The data provides some general support for the notion that teaching online may take more time than teaching face-to-face. However, the amount of difference tends to be small, and there are some indications that this relationship between teaching mode and time is more complicated than generally assumed. Index Terms Asynchronous Learning Networks, Instructor time, education. INTRODUCTION education has been a very popular, and somewhat controversial, topic in higher education in recent years. The number of institutions offering some type of online education has risen sharply, and there is no sign that this trend will slow down any time soon. In addition, the activity in online education increasingly affects mainstream traditional higher education. Many of the early, larger online education projects involved some form of distance education. Providers of distance and non-traditional education including institutions such as the University of Maryland University College, UCLA Extension Division, and the University of Phoenix were early sponsors of these projects. At the same time however, more traditional education providers also started projects in online education. These included efforts at New Jersey Institute of Technology, Drexel, and the University of Illinois, to name just a few. This second category of project is different in that these projects integrate online education with traditional face-toface education. The online projects involve the same fulltime, tenure track faculty as traditional programs. In addition, while these projects typically include some element of distance education, they also tend to involve students who may be on or near campus. The driving motivations are not limited to serving students at a distance. Instead, motivating factors may also include potential for cost efficiency, time and place convenience for students and faculty, and the possibility of pedagogic improvement. The growth of online education has been accompanied by increased use of information technology in traditional, face-to-face classes. Course Web sites and communication among course participants via are commonplace course elements in many institutions. Additional elements such as class discussion lists, chat rooms, and virtual office hours are also becoming more common. Both these trends indicate that online education is likely to become a common workplace feature for most faculty members in years to come. While we are probably still in an early adopter stage in online education, it seems quite likely that the diffusion of the innovations driving this activity will continue. The early projects already report a substantial degree of integration of online and traditional education [1]. The clear implication is that this is a development with which all faculty members should be concerned. Some of the early interest in online education has been driven by the potential for cost savings. There have been some signs of a gold rush mentality, with institutions discussing huge profit potential from online courses taken by large masses of students, but experience has put most of that speculation to rest, at least for the moment. However, there are many ongoing efforts looking at ways that online and other technology-based education may provide at least some cost efficiency. One key aspect of education cost is instructor time. Since education is generally labor intensive, significant increases or decreases faculty time can have a substantial impact on the total cost to deliver a course. For online education, there seems to be a common opinion that teaching takes more time [2]. However, this opinion seems to be based on impression rather than data. Since this is an important question, there is a clear need for detailed studies that provide quantitative support on this issue. A few prior studies are available that provide some useful data in this area [3] [4]. However, the results do not agree, again indicating the need for additional work. Problem Definition This paper discusses an ongoing study that is creating a detailed analysis of the time it takes to teach online vs. faceto-face classes. The basic research question is: Does teaching online take more time? 1 Gregory.W. Hislop, College of Information Science and Technology, Drexel University, Philadelphia, PA, 19104, hislop@drexel.edu T1F-23

2 The section that follows discusses issues related to answering this question, and presents the approach taken in this study. Following that, the next section presents the study results, along with some discussion. The final section of the paper provides some conclusions and indications for future work. ISSUES AND APPROACH The issue of instructor time is complicated by the great variation in educational environments. No one study in one environment will provide a definitive answer to the question this paper addresses. Instead, a series of studies will start to allow patterns and impacts of key variables to become clear. To this end, this section begins with some discussion of the study environment to provide context for the study. Study Environment The College that is the subject of this study began a longterm initiative in early 1994 to develop online education and build on earlier projects in computer mediated communication such as Hiltz and Turoff [5] [6]. Although the online project has included offering a variety of online undergraduate courses, the focus of the effort has been online graduate degree programs aimed primarily at working professionals in information systems and software engineering. At present, the College has about 150 online students. The courses in this program are completely online and completely asynchronous. There are no face-to-face course meetings, and no activities that must take place on a particular day at a particular time. However, courses do run on a regular term schedule, have deadlines, and have activities that are scheduled for particular time segments within the term. The courses exemplify a particular style of online education that is characterized by high levels of interaction among course participants, including both student-to-student interaction and student-to-instructor interaction. More generally, the style used in this project fits the general label of asynchronous learning networks or ALN fostered by the Sloan Consortium for ALN [7]. This approach clearly affects the amount and nature of instructor time required for course delivery. The platform for the courses is a groupware environment accessed via the web. Course content consists of text and graphics with no significant use of audio or video. Because of the emphasis on interaction, discussion is a major element of many of the courses. This tends to change the nature and amount of static material in many of the courses, and therefore affects course development time. Course development (or more correctly, conversion from face-to-face offering) is performed by one of the faculty members who teach the course. Compensation for this effort has varied. In some cases, faculty members have simply done the work as part of routine assignment. In other cases some financial support or reduction in teaching load (typically one course) has been provided. Overall, the approach to course development has been to keep conversion cost low. Estimated conversion costs are typically five to ten thousand dollars, with most of that expense being faculty time. Additional discussion of the online course environment may be found in [8]. A discussion of the evaluation approach and framework is contained in [9]. Defining Time to Teach The basic goal of the study is to compare the amount of time it takes to teach online vs. face-to-face. For this study, time to teach is limited to time spent by the faculty member during the term. The study does not consider time spent for course preparation and conversion prior to the term. Although this other time is relevant to total cost, we have chosen this more limited frame for several reasons. First, there are no clear boundaries for work on course content outside the term. In part due to the technical content of the courses, the faculty members tend to be working on course content continuously for both traditional and online courses. It would be difficult to know when to start the measurement, and what to include. Second, viewed generally, cost would be a more appropriate measure for course creation or conversion rather than time. In traditional education, course preparation is labor intensive. In online education, preparation may be much more capital intensive (e.g., creation of a video based course requires much more capital equipment than a traditional course). This makes instructor time measurement less useful (less generalizable across settings) for studying course preparation. Finally, for the study environment, initial course conversion cost is kept low (and fairly uniform) by design. Measurement Approach There are a variety of issues that make accurate and complete measurement of teaching time difficult. This section presents these issues and outlines the approach taken in the study to address them. Confounding variables Studies like this do not have the luxury of a controlled experimental environment. As such, it is difficult to control confounding variables. From the perspective of experimental design, the independent variable is mode of delivery (face-to-face or online) and the dependent variable is instructor time. Some of the variables that may affect this relationship in the uncontrolled environment are: course subject and particular content, instructor, class size, students, and various environmental factors such as technical problems. To control these affects as much as possible, the study consists of matched pairs of sections. Each pair contains one section in each delivery mode. Both sections in a pair are the same course (with no major changes in content) taught by the same instructor in the same or successive terms. The T1F-24

3 study controls for class size as part of the analysis, and assumes that students are equivalent across sections. The study controls somewhat for environmental factors by categorization of instructor time. Subject cooperation A key issue for this project is to get and maintain cooperation and commitment from the instructors participating in the study. The instructors need to keep detailed time logs of all course activities for two full terms (quarters in this environment). Several initial efforts at collecting this data failed because of this issue. For the current study, the instructors are paid a stipend for collecting the data. Payment is dependent on delivering complete time logs for the pair of course sections. Data collection To further support the data collection, instructors are provided with a standard time logging form. The form is provided as both a word processing document and a spreadsheet. Instructors may enter data in either form, or print the form and enter data using pencil and paper. Data consistency To help instructors provide consistent data, the time logging form provides a standard set of categories to describe the course activities. The categories and their definitions are shown in Table 1. Activity TABLE I INSTRUCTIONAL TIME CATEGORIZATION Description Administration Add/drop; class evaluations; other administrative activities Discussion discussion with the whole class via the online discussion area or broadcast to the class to/from students (individuals or groups but not the entire class) Grading Lecture Materials Other or off-line grading or review of student work Face-to-face lecturing or other group activities (e.g., scheduled class meetings) Preparing or changing course materials during the term Work not fitting particular categories (Please name the activity) Phone Phone calls with students Preparation Preparing for class during the term (e.g., lecture note review or background reading) Talk Face-to-face informal discussion / meetings / talk with students (e.g. before and after class) Technology Technology problems or time learning about the online environment RESULTS AND DISCUSSION In the first year of data collection the project captured detailed time log data for four pairs of course sections. These pairs included three different courses and three different instructors. There are a variety of interesting possibilities for analyzing this data. In aggregate, across the four pairs, total instructional time does not differ much by mode of delivery (333 hours online, 347 hours face-to-face). However, that is only the beginning of the story, since there is considerable variation among the pairs. Figure 1 summarizes total hours per section for the four pairs. In reviewing this figure and those that follow, note that these courses are on a quarter term. A face-to-face class has 30 contact hours in ten class weeks plus an exam period in the 11th week. An online class lasts for the same 11 weeks. In Figure 1 we see a mixed picture, with two online sections taking more time, and two taking less time than the corresponding face-to-face section. It is also interesting to note that with the exception of pair four, the difference is not that large within each pair. Total Hours FIGURE 1 TOTAL COURSE DELIVERY HOURS Figure 1 is useful for checking the general impression instructors have about the time it takes to teach online. It seems reasonable to speculate that instructors form this impression based on a general guess about total class hours, and not a more detailed analysis. To the extent that this is true, Figure 1 does not provide good support for the common impression that teaching online takes substantially more instructor time. Figure 2 provides a natural extension of Figure 1 by normalizing the data by class size. Here a somewhat different picture emerges. The instructor hours per student T1F-25

4 show a consistent pattern, namely that the online courses take more time per student. As with Figure 1 however, it is interesting to note that for three of the four pairs, the difference is not that large. Another interesting feature is that pair 4, which showed the largest difference in total delivery time in Figure 1, shows the smallest difference after the adjustment for class size (about 4 minutes per student). Hours per Student FIGURE 2 COURSE DELIVERY HOURS PER STUDENT Further examination of pair 3, which shows the striking difference in Figure 2, raises the possibility that this pair represents a data anomaly. Pair 3 is the only pair in which the two sections that comprise the pair were taught in the same quarter. The other three pairs were taught in sequential quarters. Logging time for the two pair 3 sections was difficult when the instructor could not clearly identify the section to which the time related. Because of this ambiguity, the instructor logged all Prep time to both sections. The result of this choice is a pattern that differs from the other section pairs. For the other pairs, Prep time for the online section was substantially lower than for the face-to-face section. If pair 3 had a Prep time pattern similar to the other section pairs, most of the time difference shown in Figure 2 would be eliminated. While this provides an interesting possible explanation for the difference in pair 3, there is not sufficient basis to draw a conclusion yet. Another possibility exists to explain the strong opinion that faculty have that teaching online takes substantially more time. This relates to the fact that online courses clearly have a different rhythm to them. The typical face-to-face course in this College meets once each week for three hours. Since many students are part-time, the interaction with them outside of class is limited, and mostly consists of and phone conversations. classes, by contrast, tend to have instructor interactions with the class spread out over the entire week. Figure 3 captures one view of this effect. It compares the number of days in a term in which the instructor logged some activity related to the course for each of the two delivery modes. As with Figure 2, Figure 3 produces a consistent pattern, with the online sections showing more days per term with some course activity. Days per Term FIGURE 3 DAYS PER TERM WITH SOME COURSE ACTIVITY It is also interesting to note that the differences within each pair are larger than the differences in time. Even for the closest pair, pair 4, the online section involved class activities on 30% more days than the face-to-face section. It seems reasonable to speculate that this characteristic of the online classes might easily contribute to a perception that teaching online takes more time. CONCLUSIONS This first study of instructor time for teaching online provides some interesting insights into the issue, but clearly does not settle the question (nor was there any expectation that the study would settle the question). It seems reasonable to conclude that the issue of instructor time is not as clear-cut as has sometimes been indicated in other discussions of online education. That is, it is premature to conclude that teaching online always takes more time than teaching face-to-face if other factors are constant. Although several of the figures presented here indicate a consistent relationship, the differences are not generally large, and there are other factors that may be affecting the outcome in this set of data (exemplified by the anomaly discussed earlier for pair 3 in Figure 2). T1F-26

5 Future work The results of this study clearly indicate a need for additional data, both to see if the general patterns presented here can be demonstrated to represent significant differences, and to allow analysis at a more detailed level. For example, the section pairs in this study show interesting variations in the pattern of activities across courses and instructors. Additional data would allow some meaningful analysis of these patterns. This analysis might provide additional understanding of the basic teaching time question discussed here, and also be useful in identifying ways to improve efficiency of online education. REFERENCES [1] Hislop, Gregory W. and Michael E. Atwood. "ALN Teaching as Routine Faculty Workload." Journal of Asynchronous Learning Networks. 4,3. September [2] National Education Association. A Survey of Traditional and Distance Learning Higher Education Members [3] Visser, James A. Faculty Work in Developing and Teaching Web- Based Distance Courses: A Case Study of Time and Effort. The American Journal of Distance Education. 14, [4] DiBiase, David. Is Distance Teaching More Work or Less? The American Journal of Distance Education. 14, [5] Hiltz, Starr Roxanne, and Murray Turoff. The Network Nation: Human Communication via Computer, 2 ed. Cambridge, MA. The MIT Press [6] Hiltz, Starr Roxanne. The Virtual Classroom. Norwood, NJ: Ablex Publishing Co [7] [8] Hislop, Gregory W. Working Professionals as Part-time Learners. Journal of Asynchronous Learning Networks. 4,2. September [9] Hislop, Gregory W. Evaluating an Asynchronous Graduate Degree Program. Proceedings, Frontiers in Education, 97. Los Alamitos, CA: IEEE CS Press. November T1F-27