Even more than in 1979, the development of newer, cost effective technologies and the near ubiquitous (in developed countries) net-based telecommunications system is shifting at least the cost and access implications of ‘getting the mix right’. Further, developments in social cognitive based learning theories are providing increased evidence of the importance of collaborative activity as a component of all forms of education – including those delivered at a distance. Finally, the context in which distance education is developed and delivered is changing in response to the capacity of the semantic web (Berners-Lee, 1999) to support interaction, not only amongst humans, but also between and among autonomous agents and human beings.
Thus, the landscape and challenges of “getting the mix right” have not lessened in the past 25 years, and in fact has become even more complicated. This paper attempts to define a theoretical rationale and guide for instructional designers and teachers interested in developing distance education systems that are both effective and efficient in meeting diverse student learning needs.
Defining and Valuing Interaction in Distance Education
Interaction has long been a defining and critical component of the educational process and context. Yet it is surprisingly difficult to find a clear and precise definition of this multifaceted concept in the education literature. In popular culture the use of the term to describe everything from toasters to video games to holiday resorts, further confuses precise definition. I have discussed these varying definitions at greater length in an earlier document (Anderson, in press), and so will confine discussion here to an acceptance of Wagner‘s (1994) definition as “reciprocal events that require at least two objects and two actions. Interactions occur when these objects and events mutually influence one another”(p. 8). This definition departs from Daniel and Marquis’s stipulation that interaction should refer “in a restrictive manner to cover only those activities where the student is in two-way contact with another person (or persons)” (Daniel and Marquis, 1988, p. 339). As I will argue later and was articulated earlier by Moore (1989) and Juler (1990), interaction between students and content has long been recognized as a critical component of both campus-based and distance education.
Interaction (or its derivative term interactivity) serves a variety of functions in the educational transaction. Sims (1999) has listed these functions as allowing for learner control, facilitating program adaptation based on learner input, allowing various forms of participation and communication and as aid to meaningful learning. In addition, interactivity is fundamental to creation of the learning communities espoused by Lipman (1991), Wenger (2001) and other influential educational theorists who focus on the critical role of community in learning. Finally, the value of another persons’ perspective, usually gained through interaction, is a key learning component in constructivist learning theories (Jonassen, 1991) and in inducing mindfulness in learners (Langer, 1989)
Interaction has always been valued in distance education – even in its most traditional, independent study format. Holmberg (1989) argued for the superiority of individualized interaction between student and tutor when supported by written postal correspondence or via real time telephone tutoring. Holmberg also introduced us to the idea of simulated interaction that defines the writing style appropriate for independent study models of distance education programming that he referred as “guided didactic interaction”. Garrison and Shale (1990) defined all forms of education (including that delivered at a distance) as essentially interactions between content, students and teachers. Laurillard (1997) constructed a conversational model of learning in which interaction between students and teachers plays the critical role.
As long ago as 1916, John Dewey referred to interaction as the defining component of the educational process that occurs when the student transforms the inert information passed to them from another and constructs it into knowledge with personal application and value (Dewey, 1916). Bates (1990) argued that interactivity should be the primary criteria for selecting media for educational delivery. Thus, there is a long history of study and recognition of the critical role of interaction in supporting and even defining education.
Modes of interaction
In earlier work we have illustrated the three more common types of interaction discussed in the distance education literature (Anderson & Garrison, 1998; Anderson, in press) that involve students (student-student; student-teacher; student-content) and extended the discussion to the other three types of interaction (teacher-teacher; teacher-content; content –content) as in figure 1 below. I have discussed the various costs, benefits and research questions associated with each of these modes of interaction (Anderson, in press). Finally, I have suggested that due to the increasing power of computers (Moore’s Law), their increase in functionality when networked (Metcalfe’s Law) and related geometric increases in technical capacity (Kurzweil, 1999), there is pressure and opportunity to transform teacher and peer interaction into enhanced forms of content interaction. Further, the development of programming tools and environments will continue to make this transformation easier and in some cases within the technical domain of non-programming teachers and subject matter experts. However, I have not clearly articulated a theoretical basis for judging the appropriate amounts of each of the various forms of possible interaction.
Figure 1. Modes of Interaction in Distance Education from Anderson and Garrison, 1998
Equivalency of interaction.
After years of sometimes acrimonious debate, it seems clear that there is no single media that supports the educational experience in a manner that is superior in all ways to that supported via other media. Clark’s (1994) and Kozma’s (1994) classic debate and the long list of “no significant difference” studies compiled by Russell (2000), give evidence to a very complicated interaction between content, student preference and need, institutional capacity and preference, and teaching and learning appraoces to learning. Despite the high degree of rhetoric from constructivist and feminist educational theorists of the value of interaction creating interdependence in the learning sequence (Carr, Litzinger, & Marra, 1997), there is also evidence that many students willfully choose learning programs that allow them to minimize the amount of student-teacher and student -student human interaction required (May, 1993). Further, in my own distance teaching I have been informally polling students for years about the relative advantage and disadvantage of various forms of mediated and face-to-face, synchronous and asynchronous educational activities. From these polls I conclude that there is a very wide range of need and preference for different combinations of paced and un-paced; synchronous and asynchronous activity and also a strong desire for variety and exposure to different modes and modularity’s of educational provision and activity.
From these observations and from the literature debate, I have developed an equivalency theorem as follows.
Sufficient levels of deep and meaningful learning can be developed as long as one of the three forms of interaction (student–teacher; student-student; student-content) are at very high levels. The other two may be offered at minimal levels or even eliminated without degrading the educational experience.
High levels of more than one of these three modes will likely deliver a more satisfying educational experience, though these experiences may not be as cost or time effective as less interactive learning sequences.
This theorem implies that an instructional designer can substitute one type of interaction for one of the others (at the same level) with little loss in educational effectiveness - thus the label of an equivalency theory. There are a number of other corollaries and implications based on current post-industrial education context that can be drawn from this theorem and I have attempted to provide a start at this process in the following lists.
Differentiating between high and low levels of interactivity is largely a quantitative exercise in which a researcher, developer or the participants themselves count the number of times they are actively engaged with the other participants or content. There is some evidence to suggest value in “vicarious interaction” in which non-active participants gain from observing and empathizing with active participants (Sutton, 2001; Fulford & Zhang, 1993). However, high levels of interaction generally requires the actors to be personally active and engaged in the interaction. Obviously, there are qualitative differences in the extent of individual involvement in the interaction. However, these differences are largely individualized and difficult to proscribe or assess across the large numbers of participants as are typically found in current education systems. Thus, for planning or development purposes designers are encouraged to build into their programs strategic amounts of each type of interaction and to develop activities that will encourage this amount of interaction.
Examples of application the equivalency theorem to popular education delivery modes
The following examples illustrate the operation of the equivalency theorem in most common forms of campus and distance delivered education systems.
The traditional lecture mode of delivery has medium levels of student-teacher interaction, usually low levels of student-student interaction and medium to low levels of student-content interaction. For these reasons I am not alone in critiquing the lecture format (Garrison, 2000) and note its historical evolution as reading from very scarce content (hand-scribed books). Its value in an era of ubiquitous content is thus reduced. Recent efforts at enhancing lecture theatres through use of multimedia equipment and especially enabling access to net resources in “smart classrooms” will increase the quality of student –content interaction and thus the potential to increase levels of deep and meaningful learning.
Efforts at enhancing teacher student interaction through an increase
in teacher immediacy (McCrosky & Richmond, 1992) or through use of
theatrical or multimedia presentation techniques, can also be expected
to increase the quality of student –teacher interaction. Further efforts
at enhancing student-student interaction in the classroom through case
or problem based learningn activities have long been shown to increase
not only student achievement but also student completion and enjoyment
rates (Slavin, 1995). In these type of activities increased student-student
interaction is substituting for student-teacher interaction.
When classroom delivery takes the form of traditional seminar among relatively small numbers of students and a teacher, the levels of student-student and student-teacher interaction increase with generally increased levels of learning and satisfaction. Access to “smart classroom” technologies is generally less necessary in seminars as high level of learning are already being achieved through high levels of student-student and student-teacher interaction.
Traditional distance education delivered via mail or electronic correspondence
In this mode specially designed independent study materials are constructed with the explicit intent of providing high levels of student-content interaction. As noted, attention to the creation of a personal voice in the content and the attention to ways to create a “guided didactic interaction” in the text materials can create high levels of student-content interaction. In more recent times, independent study materials have been enhanced and delivered electronically in the form of java applets, automated testing and quiz forms of feedback, simulations, adaptive computer assisted instruction and other applications of “learning objects”. Each of these technologies enhances student-content interaction and thus if well designed and applied appropriately is likely to enhance the learning experience. Student-teacher interaction is possible in independent study but generally does not happen to a great extent with the majority of learners (Coldeway, 1991). Rather, efforts are made to create study paths that allow student to learn with minimal amount of interaction with teacher, other than to provide occasional formative and definite summative student assessment. Student-student interaction is also usually minimized allowing for maximum flexibility, start and finish times for courses and capacity for students to set their own pace through the learning content. Thus, independent study provides high levels of learning by maximizing student-content interaction and getting away with minimal amounts of student-teacher and student-student interaction.
Having stated that student-teacher interaction is generally low, there are ways in which it can be expanded in a cost effective manner. In particular the call center system developed at Athabasca University allows students extended access (7 days a week, 12 hours a day) to tutors who are equipped with frequently asked question databases, course syllabi, and limited amount of content knowledge) to answer a wide variety of student inquiries in timely fashion. Adria and Woudstra (2001) report that over 65% of student questions and concerns are handled successfully by call center tutors, thereby reducing the cost of student-teacher interaction without reducing the quality.
Audio and video conferencing
Audio and video conferencing provide slightly less accessible and leaner interaction between and amongst teachers and students due to the inherent technological distance between students and teachers imposed by the mediating technology. There is a further reduction in paralinguistic clues in audio teleconferencing as opposed to video conferencing, so that in some there are only medium levels of student-teacher interaction. Student –content interaction is also at medium levels, if the conferences are enhanced with graphics or net cruising capability as is supported in many of the new internet based conferencing systems now appearing on the market. High levels of student –student interaction is possible and indeed is the mantra of proponents of conferencing education systems (Roberts, 1998; Parker & Olgren C., 1980). However, there is much anecdotal and some empirical evidence (Kirby & Boak, 1987) that teachers often use the media almost exclusively for lecture type delivery. If the conference is designed to support high levels of student-student interaction, then there is high potential for high levels of learning. I have been particularly struck by the differences in the amount and intensity of student-student interaction as delivery of video and audio conferencing has moved from the dedicated learning center to the home or workplace. I documented the extent of student-student interaction in the learning center that was not shared with other sites or the teacher that I referred to as “side talk” and found that in approximately the cases this conversation was both on track and I felt conducive to learning (Anderson & Garrison, 1995). Now as we have progressed to delivery direct to individual home, I notice a drop off of student-student interaction as the side talk channel is reduced or eliminated and the distractions of the home life or alluring availability of web surfing and email, make it more challenging to engage students in student-student or student-teacher interaction.
High levels of learning using video or audio conferencing require designers to build in high levels of student-student interaction since the other two modes of interaction are impaired by the media restrictions.
The current stampede of educational institutions to mount and deliver “web courses” has given rise to a large variation of models and modes of delivery. All use the web differently making categorization difficult. Web-based courses delivered using audio or video graphic systems such as Centra or E-Luminate share the same technical and pedagogical strengths and weaknesses of earlier video and audiographic systems. Canned streaming video lectures share more characteristics with the delivery classroom in which they were captured, than the more radical forms of instructional design that the web is capable of supporting. Earlier forms of computer assisted instruction are now being ported to the web, thus reducing the inconvenience and cost of burning and distributing CDs while retaining most of the pedagogical characteristics of their earlier instructional format.
The most common and currently most pedagogically attractive forms of web delivery described in the literature are those based upon extensive use of text based computer mediated communications. In our content analysis studies of transcripts of these interactions (see a variety of papers by Anderson, Garrison, Archer and Rourke at www.atl.ualberta.ca/cmc) we have shown how creation of adequate levels of cognitive, social and teaching presence leads to deep and meaningful learning. This form of distance delivery places a premium on quality student-student interaction that is supported in a format that allows for asynchronous reflection and scholarly expression in text format. This high level of student-student interaction capacity allows for reduced student –teacher interaction, the capacity to make good use of peer moderators (Rourke & Anderson, 2002) and facilitates student sharing and discussing student-content resources garnered from the web.
I am also impressed with the capacity of the web to support enhanced levels of content interaction and for autonomous agents to be created to assist both teachers and students in the educational process. For example, work by the Open Digital Markup Language defines “an extensible language and vocabulary (data dictionary) for the expression of terms and conditions over any content including permissions, constraints, obligations, conditions, and offers and agreements with rights holders”(ODRL, 2002 website at http://www.odrl.net/). ODRL can thus be configured to allow content itself to control, monitor and manage access to it by students and teachers. An excellent example of the use of student agents is the I-Help system developed by Jim Greer and his colleagues at the University of Saskatchewan (Vassileva et al., 1999). This system allows each student to create an agent that seeks out and negotiates with other student agents for personalized assistance and help (provided by email by other students). The system selects and values previous student assistance finds those students who are most available and most knowledgeable and negotiates a fee for services rendered. Thus, the system is stimulating and tracking student-student interaction, thus allowing less dependence on student teacher or student-content interaction as predicted by my equivalence theorem.
The equivalency theorem proposed in this paper, is not as complicated nor as technically detailed as other theories relevant to distance education (see for example Jaspers, (1991); Saba and Shearer, (1994). However, its simplicity allows it to function as an accessible heuristic for distance education delivery design. The role of theory in science, education and particularly instructional design has been much discussed (Seels, 1997; Garrison, 2000) and is seen as multifaceted. My intent with this article has not been to generate ‘grand theory” that explains and predicts behavior in a system as complex as an educational interaction. Neither is it the type of logico-deductive theory valued in the natural sciences for their capacity to generate testable hypothesis. Rather, it has more in common with grounded theory investigation (Corbin & Strauss, 1990) in which researchers are urged to go beyond description of data to generating inferences about phenomena they encounter in order that both researchers and practitioners are better able to interpret and meaningfully and purposively change their practice.
Wilson (1997) has described three functions that a good educational theory performs. First, it helps us to envision new worlds. The interaction equivalency theorem underlines our capacity to effectively substitute one form of interaction for another. Getting the mix right, involves a series of tradeoffs, and knowing how one type of interaction can effectively substitute for another provides an essential decision making skill in the distance educators’ knowledgebase. Second, a good theory helps us make things. As new communications technology are brought to market, they seek their place in the arsenal of available tools – propelled by often effusive praise of early adopters and salespersons with vested interests. This theory helps us to position them and make judgments as to their potential effectiveness and efficiency in our program planning. Finally, Wilson argues that a good theory keeps us honest. I hope this small theoretical piece encourages dialogue within our community of practice. It challenges us to critically evaluate just how much of the educational process can be composed of interaction with nonhuman entities. And further, how much of the human interaction should take place face-to-face or in real time? None of these questions are easily answered, but such reflective discourse is critical to the growth of our discipline and our individual practice. It is also apparent that this theorem is very much a developing work that will benefit from the comment, critique and expansion by other researchers and distance education practitioners.
Adria, M., & Woudstra, A. (2001). Who's on the line? Managing student communications in distance learning using a one-window approach. Open Learning, 16(3), 249-261.
Anderson, T. (in press). Modes of interaction in distance education: Recent developments and research questions. In M. Moore (Ed.), Handbook of Distance Education. Mahwah, NJ: Erlbaum.
Anderson, T., & Garrison, D.R. (1995). Transactional issues in distance education: The impact of design in audio teleconferencing. American Journal of Distance Education, 9(2), 27-45.
Anderson, T., & Garrison, D.R. (1998). Learning in a networked world: New roles and responsibilities. In C. Gibson (Ed.), Distance Learners in Higher Education. Madison, WI.: Atwood Publishing.
Bates, A. (1990). Interactivity as a Criterion for Media Selection in Distance Education. Annual Conference of the Asian Association of Open Universities . ED 329245
Berners-Lee, T. (1999). Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by its Inventor. San Francisco: Harper.
Carr, A., Litzinger, M., & Marra, R. (1997). Feminist pedagogy, constructivism and systemic change: The search for common ground. AERA . http://www.psu.edu/eis/PAPERS/feminist.pdf
Clark, R.E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29.
Coldeway, D. (1991). Patterns of behaviour in individualized distance education courses. Research in Distance Education, 3(4), 6-10.
Corbin, J., & Strauss, A. (1990). Grounded theory research: Procedures, canons, and evaluative criteria. Qualitative Sociology, 13, 3-21.
Daniel, J., & Marquis, C. (1979). Interaction and independence: Getting the mixture right. Teaching at a Distance, 15, 25-44.
Daniel, J., & Marquis, C. (1988). Interaction and independence: Getting the mix right. In D. Sewart, D. Keegan, & B. Holmberg (Eds.), Distance Education: International Perspectives. (pp. 339-359). London: Routledge.
Dewey, J. (1916). Democracy and Education. New York: Macmillan.
Fulford, C.P., & Zhang, S. (1993). Perceptions of interaction: The critical predictor in distance education. American Journal of Distance Education, 7(3 ), 8-21.
Garrison, D.R. (2000). Theoretical challenges for distance education in the 21st century: A shift from structural to transactional issues. International Review of Research in Open and Distance Learning, 1(1) . Retrieved May 21, 2001, from the World Wide Web: http://www.irrodl.org/content/v1.1/randy.pdf.
Garrison, D.R., & Shale, D. (1990). A new framework and perspective. In D. R. Garrison & D. Shale (Eds.), Education at a distance: from issues to practice. (pp. 123-133). Malabar, Florida: Robert E. Krieger Publishing Company.
Holmberg, B. (1989). Theory and practice of distance education. London: Routledge.
Jaspers, F. (1991). Interactivity or instruction? A reaction to Merrill. Educational Technology, 31(3), 21-24.
Jonassen, D. (1991). Evaluating constructivistic learning. Educational Technology, 31(10), 28-33.
Juler, P. (1990). Promoting interaction; maintaining independence: Swallowing the mixture. Open Learning, 5(2), 24-33.
Kirby, D., & Boak, C. (1987). Developing a system for audio-teleconferencing analysis. Journal of Distance Education, 2(2), 31-42.
Kozma, R. (1994). Will media influence learning? Reframing the debate. Educational Technology Research & Development, 42(2), 7-19.
Kurzweil, R. (1999). The age of spriritual machines. New York: Penguin Group.
Langer, E. (1989). Mindfulness. Reading, MA: Addison-Wesley.
Laurillard, D. (1997). Rethinking university teaching: A framework for the effective use of educational technology. ( ed.). London: Routledge.
Lipman, M. (1991). Thinking in Education. Cambridge: Cambridge University Press.
May, S. (1993). Collaborative learning: More is not necessarily better. Amercian Jounral of Distance Education, 7(3), 39-49.
McCrosky, J., & Richmond, V.P. (1992). Increasing teacher influence through immediacy. In Richmond V. P. & J. McCrosky (Eds.), Power in the classroom: Communication, control, and concern. (pp. 200-211).
Moore, M. (1989). Three types of interaction. American Journal of Distance Education, 3( 2), 1-6.
Parker, L. & Olgren C. (1980). Teleconferencing and interactive media. Madison, MI: University of Wisconsin - Extension Press.
Roberts, R. (1998). Compressed video learning: Creating active learners. Montreal: Cheneliere/McGraw-Hill.
Rourke, L., & Anderson, T. (2002). Using peer teams to lead online discussions. Journal of Interactive Media in Education
Russell, T. (2000). The No Significant Difference Phenomenon. Retrieved Nov. 22, 2000, from the World Wide Web: http://cuda.teleeducation.nb.ca/nosignificantdifference/
Saba, F., & Shearer, R. (1994). Verifying key theoretical concepts in a dynamic model of distance education. American Journal of Distance Education, 8(1 ), 36-59.
Seels, B. (1997). Theory development in educational/instructional technology. Education Technology, 37(1), 3-5.
Sims, R. (1999). Interactivity on stage: Strategies for learner-designer communication. Australian Journal of Educational Technology, 15(3), 257-272. http://cleo.murdoch.edu.au/ajet/ajet15/sims.html.
Slavin, R. (1995). Cooperative learning theory, research, and practice. Boston: Allyn and Bacon.
Sutton, L. (2001). The principles of vicarious interaction in computer-mediated communications. Journal of Interactive Educational Communications, 7(3), 223-242. http://www.eas.asu.edu/elearn/research/suttonnew.pdf.
Vassileva, J., J. Greer, J.M.G., Deters, R., Zapata, D., Mudgal, C., & Grant, S. (1999). A Multi-Agent Approach to the Design of Peer-Help Environments. Proceedings of AIED'99. Artificial Intelligence in Education. http://julita.usask.ca/homepage/Agents.htm
Wagner, E.D. (1994). In support of a functional definition of interaction. The American Journal of Distance Education, 8(2), 6-26.
Wenger, E. (2001). Supporting communities of practice: A survey of community-orientated technologies. (1.3 ed.). .Shareware. Available http://www.ewenger.com/tech/.
Wilson, B. (1997). Thoughts on theory in educational technology. Educational Technology, 37(1 ), 22-26.