Comparing How Students Collaborate to Learn About the Self and Relationships in a Real-Time Non-Turn-Taking Online and Turn-Taking Face-to-Face Environment

Comparing How Students Collaborate to Learn About the Self and Relationships in a Real-Time Non-Turn-Taking Online and Turn-Taking Face-to-Face Environment

Mia Lobel
Concordia University

Michael Neubauer
Stanford Linear Accelerator Center

Randy Swedburg
Concordia University

A matched study compares collaborative learning about the self and relationships in two different learning environments. One environment is a traditional university classroom in which participants take turns expressing themselves. The other is online, using the LBD eClassroom©, which allows several participants to express themselves at the same time. The intent was to migrate the content and the process of the course from a traditional face-to-face classroom to an online classroom. By eliminating the constraint of taking turns, a greater quantity of exchanges was shown to be possible in the same amount of time, resulting in a different dynamic to the interactions in the online class. Instead of focusing on interactions between students and the instructor or expert, more interactions occurred among the students. These differences led to a more effective formation of group identity, or polis. The data analysis includes interaction diagrams, GUIDATA©, and the use of time.

For the last five years we have been developing an online classroom. Our design goal was:

The traditional face-to-face experiential and collaborative courses, taught at the university for the last 25 years, are designed for students initially to sit in a circle during a lecture or large group activity, and then break up into four smaller, facilitated groups to collaborate and process in a more intimate setting, and collaborate on the intra- and inter-personal issues brought up during the activities and exercises. Kolb's Experiential Learning Cycle (Kolb, 1984) is one of the cornerstones of this pedagogy. The design, delivery, and evaluation of the face-to-face experiential courses are grounded in the theories of Kurt Lewin (1890-1947), David A. Kolb (1939- ), Jack R. Gibb (1914-1995), William Schutz (?-2002), and other group development theorists. The class sessions are three hours long and meet once a week during a three-month semester.

In 2002, the office of the Dean of Arts and Sciences at Concordia University provided us with a grant to perform a matched study in order to research the progress of our design goals. This article presents some of our observations and the ways we have found to articulate them.

The 2002 Proceedings of the Computer Support for Collaborative Learning: Foundations for CSCL Community conference, held January 7-11, 2002 in Boulder Colorado, presented 75 research papers on collaborative online groups. Of these, 41 papers studied online asynchronous groups, and 33 papers researched synchronous groups. Of the online synchronous research, 31 of the studies were of collaborative groups of four or fewer participants; the largest group studied had seven participants (Neubauer & Lobel, 2003).

Most online university classes in North America have a maximum attendance of 20 to 25 students. The University of Phoenix, an exclusively online university, averages 11 students per class (Symonds, 2003). The research reported in this article describes an online class size of 34 students, four teaching-team members, and sundry visitors, all present and working together in the same environment. To date, we have been unable to locate any other studies comparable to ours in size and in scope.

In the past, Matched Studies have generally focused on comparing the academic results achieved online and face-to-face in the same course. Russell's No Significant Difference Phenomenon (1999) catalogs 355 pieces of research data from 1928 to 1999 that compare distance education and technology to classic classroom education with "no significant difference" in their findings.

From 1997 to 2002, a total of 77 matched studies was reported at the web site: http://www.nosignificantdifference.org/. There were 19 matched study entries in math and science, four entries in languages, and 54 matched studies of general achievement. The research reported in this article appears to be the first to discuss migrating a course about interactive communication and interpersonal relationships to a synchronous online environment, while maintaining the same experience and practice-based pedagogy that was used face-to-face.

In the fall semester of 2001, the same principal instructor taught two sections of the same university-level course, using the same pedagogy with the same team of facilitators. The title of the course was "AHSC/230 Interpersonal Communication and Relationships." One section was taught in the traditional turn-taking face-to-face manner (Section BB), while the other section (Section CC) was delivered online, in the real-time, non-turn-taking LBD eClassroom (Neubauer & Lobel, 2003).

An attempt was made to keep as many factors as possible the same in both groups. Each class was given in 10 evening sessions between 7 p.m. and 10 p.m. The face-to-face session was on Thursdays; the online session on Mondays. The limit on class size was the same. The same learning modules, assignments, and evaluation methods were used. The two groups followed the same pedagogy or learning process. The objectives of each class session are summarized in Appendix I, and an example of a learning module is shown in Appendix II.

The face-to-face section meetings were video- and audio-taped in their entirety. For the online section, the LBD eClassroom collected and archived all student activities: how often they polled the server for new data; how many statements they posted, when and to whom; every time students logged in or out; and all text and images. Students in both sections were administered multiple questionnaires soliciting feedback on numerous measures. Their weekly journals and assignments were kept for further study. In addition, the few emails sent and received by the students and/or by the staff (averaging less than one email per student per week) were collected for further analysis. The data presented in this article are to be considered preliminary findings.

Table 1 lists the methods and measurements used during the matched study. Measurements in boldface are discussed in this article.

Table 1. Methods and measurements used in the matched study

Despite our efforts, there were some differences in the two environments that could not be eliminated. First, the members of the teaching team had different amounts of experience teaching face-to-face and online, as shown in Table 2. While all of the instructors had two or three years of online teaching or teaching assistant experience, their face-to-face teaching experience ranged more widely, from five to 20 years.

Table 2. Face-to-face vs. online teaching experience of the team

Another difference was that video cameras and operators had to be present for all the face-to-face sessions; these were not required for the online sessions. In contrast, the online section had to contend with the vagaries of the Internet: network speeds, ISP connection, reliability of home computers, and other technical issues, which were not relevant in the face-to-face section.

Third, the class sizes turned out to be unequal, as shown in Table 3. The typical size for the online class, counting staff, guests, and observers, was 40 participants. The face-to-face class had 35 people present including students, instructional staff, and the audio/visual recording staff. There were more female than male students in both classes.

Table 3. Number of participants in each class, by gender

Finally, the level of interest prior to taking the course was markedly higher for the face-to-face students: 75% of the face-to-face students recorded their level of interest as high, compared to only 40% of the online students.

In this course, the students learn the process of collaboratively constructing knowledge about the self and others. They learn by experiencing the process within the course. The instructor and facilitators guide them, following steps outlined in the example shown in Appendix II. Each student observes the interactions of other students and his or her own participation in the process. This approach to the construction of collaborative knowledge is the underlying premise of the Applied Human Sciences Department at Concordia, and has been the cornerstone of its face-to-face teaching for over 25 years.

For this project, the learning modules were designed using Kolb's Theory of Experiential Learning (Kolb, 1984) and tailored in both environments to deliver the same experiences and theoretical underpinning of the process. Each session starts with a period of orientation or inclusion. Then there is a cycle of collaborative experiences, personal reflections, and conceptualization. To complete the cycle, the students are given a writing assignment in their weekly journal tied to the experiences of the session.

Figure 1 represents this cycle for one class session.

Figure 1. One week's cycle in the "Kolb's Experiential Learning" Conceptual Map for the learning modules of AHSC/230

The basic template used to design the learning modules for both sections is described below (Appendix II is the learning module for Session 2).

The first 15 minutes of every class is dedicated to a collaborative technique intended to provide the space and the content around which students can meet their inclusion needs and acclimatize to the setting (Schutz, 1988). During this time, the participants test each others' responses and establish expectations. Learning objects during this period take the form of poems, meditation pieces, fables, quotes, and images. This is one way that the two sections differed in design. In the face-to-face class, where students sit in a large circle facing each other, the principal instructor begins each session with instructions for Progressive Relaxation (Lazarus, 1975) and reads out the material that was posted into the eClassroom for online class students to read. A short discussion on the meaning of the learning object provides an easy segue into the next step of a learning module. (example)

Learning about a topic begins with a collaborative activity, which is expected to provide students with an experience that moves them toward the objectives of the class. As Dewey (1938/1997) suggests, the educator provides the total social set-up in which interaction takes place: "equipment, books, apparatus, toys, games played." The much-used Confucian quote (from around 450 B.C.E.): "Tell me, and I will forget. Show me, and I may remember. Involve me, and I will understand," is another way to describe the intent of the concrete experience component. The activities (e.g., role plays, games, and other collaborative tasks) provided at this phase are designed to bring into awareness the participants' experiences of trust or assertiveness, their relationship with conflict or diversity, to name a few examples. Students are also instructed to self observe during the activities, but not curtail their reactions, in as much as possible. (example)

Processing or reflective observation involves reflection, description, communication, and learning from the experience. Students are provided with suggested process questions designed to elicit their reaction to the self and to others during the concrete experience, and to formulate some personal learning goals. Some examples of the process questions are: What helped? What hindered your experience? How would you describe your reactions? What are some strengths and limitations you brought to this experience? What would you like to change and how? (example)

Abstract conceptualization or lecturettes vary in length (approximately 25-60 minutes). Participants synthesize the data generated during the processing section of the module. During the face-to-face class, the principal instructor delivers the Lecturette in a turn-taking discussion format. For the online class, the Lecturette was posted into the LBD eClassroom on illustrated slides. During the online Lecturettes, students read the slides and respond to the principal instructor, to the facilitators, and to each other. They link the material to experience in a non-turn-taking flow as they construct their knowledge about themselves and others. (example)

In this topic-related collaborative activity, participants practice new behaviors to follow up on the learning goals identified during the processing section of a learning module. During this second experience they break into smaller groups, which provide a greater opportunity for risk taking and practice. The activity ends with another small group processing or reflective observation session. (example)

The structured weekly Journals are designed to guide students through a review or another turn through the learning cycle (Kolb, 1984) by fostering reflective observation and abstract conceptualization. The learning journals are used to record observations, link them to theoretical concepts, and formulate a concrete, measurable, observable plan to change/learn an identified interpersonal skill. (example) The data from the journals are used to assess the students' process and accounts for 50% of their grade; each journal is given a pass/fail. (The balance of their grade comes from: 10% for participation and attendance, and 40% for a final paper.)

Activity I of Session 2 was designed for the students to collaborate and experience the Schutz FIRO theory of Inclusion which is described in the learning module shown in Appendix II and discussed above. The symmetrical matrix of interaction data collected from the large group sessions as taught in the two environments is analyzed in several different ways. First, diagrams of participation graphically describe the network of interactions within a period of time. GUIDATA is then used to observe the same interactions as they evolved over the time period. How participants use their time during the one hour activity is quantified and compared in the two environments.

Comparison of small group interactions uses Activity I of Session 6. The collaborative activity, which lasted 30 minutes, required students to convince each other of several conflicting perceived realities. A summary of the learning module for this session is shown in Appendix III. For this comparison as well, we present diagrams of participation that graphically describe the network of interactions within a period of time. The face-to-face use of time is then compared in the small and large groups.

The online class (images used with permission of the students)

The face-to-face class (images used with permission of the students)

Interactivity in this course occurs on two levels. Group members interact around the task or the content—"what is being done." They also interact around maintaining social relationships, or the process—"how it is done" (Dimock, 1993). The situation is analogous to an orchestra: The content is the score for all the parts, and the process is the music the parts play together. When many players and instruments, each with their own individual notes, timing, and prominence, play together in dis/harmony, they produce a symphony which is greater than the sum of all the ingredients that went into it.

The symphony that a group produces may be analyzed in various ways. Sociometric measures, a method of socio-psychology as developed by the psychiatrist Moreno (1934), may be applied to analyze interpersonal emotive relationships within a group. These methods can also be used to identify informal leaders, social rankings, and isolated individuals. More recently, social network analysis has led to structural evaluations of various communities created by actors in distance learning classes (Haythornthwaite, 1998, 2001) and other online groups.

A number of researchers (Erickson & Kellogg, 1999, 2000; Kellogg & Erickson, 2002; Light, 2003; Lobel, Neubauer, & Swedburg, 2002b; Viégas & Donath, 1999) have experimented with creating "social visualizations" for online groups. The analysis of face-to-face networks in educational settings has evolved to include sophisticated movies of classroom networks (McFarland & Bender-deMoll, under review) using software tools such as SoNIA (Social Network Image Animator).

These social network and visualization tools offer different perspectives on interactions in learning environments. In this article, we use social network software to visually compare the interactions face-to-face and online. The GUIDATA tool was created to visualize the use of time in the interactions in the different learning environments, similar to SoNIA for face-to-face interactions.

The network diagrams of interaction were created by using the social networking software, Ucinet (Borgatti, Everett, & Freeman, 1999) and Pajek (Batagelj & Mrvar, 1996). The center of the diagram represents the participant to whom most of the statements were directed. The further the participant is from the center of the diagram, the fewer statements that actor made to the center of the group. Every directed interaction (who spoke to whom) is represented by a line between the sender and the receiver of the statement or comment, with an arrow pointing to the receiver. The size of an arrow is proportional to the number of messages delivered.

The data for the online class were retrieved from the archives. A software program was used to collect and arrange the data in a matrix for input into the social network software programs. For the face-to-face class, the data were collected by listening and watching the videotapes and hand recording "who spoke to whom" and for how long. These data were then input into Ucinet in a matrix format.

There were 34 students present in the online class (Figure 2a) and 28 students present in the face-to-face class (Figure 2b) for the processing segment of the learning module under study. There were a total of 95 statements made in the face-to-face classroom; the instructor made 42 statements, and the balance was composed of responses by the students. There were five silent students face-to-face, representing 18% of the class. In the online class a total of 386 statements was sent. In the same time frame, the instructor sent 24 statements, 208 students' statements were directed to the group-entity, and the balance (154) were statements exchanged among the students themselves. There were no silent students online.

Figure 2. Large group collaborative participation for Activity I Session 2 Processing Instructions ("S" are students, "F" are facilitators, "PI" is the principal instructor, and "G" is the group entity) Note: The network graphs are laid out with the Fruchterman-Reingold algorithm in Pajek. The size of the nodes is designed to be proportional to the number of messages received. The arrow sizes are proportional to the number of messages sent.
For an interactive 3-D rendition of these participation diagrams, go here: Figure2a Figure2b

The network diagrams for the large online class illustrate all the participants participating in various forms, creating complex network patterns of loops, trees, and branches. Many patterns are overlapping, with some students participating in several different types. The closed loops represent multiple topic-related exchanges among the members, and can be seen as illustrations of building on the knowledge/comments of others as part of the collaborative process of self-discovery being taught in the class.

The students in the large online class created significantly more closed loops than the students in the face-to-face class. Everyone in the online class participated. One participant, S4, spoke only to the group. In the large face-to-face class, the discussion networks are simple and observable. For example, besides the silent ones, nine participants (40% of the students) were addressed and responded only once, and that exchange occurred between them and the instructor. The non-turn-taking interaction seen online represents a very different mode of communication and collaboration for the larger group.

An important difference between the online and face-to-face large group is the identity of the central hub of interactions. During the online discussion, the group entity is at the center of the network, while during the face-to-face discussion it is the instructor who becomes the center. This means that in the online class, there were more statements addressed by the students to the group as a whole than to the instructors, or to each other, whereas in the face-to-face class the students addressed the instructor more often than they addressed each other. Another interesting difference is that the group entity does not appear to have the same prominence or influence in the traditional face-to-face environment as it does online.

This group-centered vs. authority-centered pattern of interaction represents a value shift in the teaching paradigm of the experiential courses. A classroom designed to be interactive and collaborative in any environment is expected to serve as an arena in which appropriate self-disclosure, feedback, and discovery take place. Openness and translucence are seen as factors that facilitate the trust formation needed to risk these behaviors (Gibb, 1964). This is true face-to-face, but online the process itself is also made transparent, so that everyone can see all the ingredients that go into the class narrative.

The online interaction diagrams look as if the center of the group becomes a physical space, akin to the ancient polis defined as a community center, or a place where community dialogue occurs. The definition implies a sacred ground, where members exhibit and leave their offerings for all to see and use. The online interaction patterns observed further substantiate that a group is a distinct entity formed by the members, but greater than the sum of its parts, with its own idiosyncratic character and life span. The group entity phenomenon observed attests to the power of the group to publish itself, that is, to create its own narrative, to be preserved, and read at a later time. The implications are fundamental to teaching and training that depend on collaborative learning, no matter where it occurs. In the online class, the 100% participation and the active interaction attest to this. In the face-to-face class, 18% of the students did not verbally join into the interactive collaboration while in the large group.

During online class discussions, students have the advantage of all their instructors',"facilitators'," and all their peers' points of view, whereas face-to-face students benefit mostly from the instructor's statements. As the students recorded in their journals, it does make a difference that online, the network of collaborative information generated remains accessible to the participants exactly as it was created, independent of interpretation and memory. The Scroll Back function and the Archives proved to be invaluable teaching and training tools that allowed participants to refer back to the exact instructional or relational narrative that occurred. The student journals identified the use of these functions for feedback on behaviors; they searched for specific examples to illustrate statements; they accessed them to settle differing perceptions of events.

Since it is postulated that the polis is in fact a repository of information, one of its aspects may correspond to the "babble" (humor, asides to neighbors, sub vocalizations, etc.) identified in the face-to-face videos. Face-to-face, the instructor reports using the class "babble" to gauge everyone's energy and excitement level, at times modifying the instructional material as a result. Online, the instructor reports using the asides, images, emoticons, and statements sent to the group entity, the polis, in much the same way. That is, the components that are visible to all may serve similar verbal, visual, and temporal functions as the face-to-face classroom "babble."

The small group Activity 2 of Learning Module #6, which lasted 30 minutes, required students to convince each other of several conflicting perceived realities. The four interaction diagrams in Figure 3 depict some typical small group interactions. In addition, they point to important differences between online and face-to-face group dynamics, and between the nature of large and small groups in both modalities.

Figure 3. Two of the four breakout groups online and face-to-face for Activity I of Session 6.
For an interactive 3-D rendition of these diagrams go here: Figure3a Figure3b Figure3c Figure3d

Table 4. Message counts for the graphical data in Figure 3

A brief comparison of the online and face-to-face small-group interaction characteristics reveals a difference in participation patterns. In the face-to-face class, the interactions in the small groups are almost symmetrically distributed and all students speak to all the other students (which is the reason for small face-to-face breakout groups.) The number of exchanges among the participants in the face-to-face small-groups describes a fairly even participation level, as shown by the size of the blue (Figure 3c) or orange circles (Figure 3a) representing each participant. (The more statements a participant receives, the larger their circle becomes.)

Face-to-face, in the Orange and Blue groups, students and facilitators send and receive about the same number of statements, as they take turns at the activity, confirming the serial turn-taking nature of face-to-face communication, and confirming the convention of face-to-face interaction whereby one's comment does not go without a response. The online groups, in contrast, are quite different from one another. In the online Orange group, members spoke more to the group (42%) than they did to each other (28%). In the online Blue group, students spoke more among themselves (51%) than they did to the group as a whole (26%). In Figures 3b and 3d, this is represented by the tighter clustering of the Blue group members, compared to the Orange group members, around the group entity. The percentage of statements made between the facilitators and the group entity (Blue=16%, Orange=18%) is almost identical between the two online color groups, suggesting that modeling by the facilitator may not have been a factor in the groups' behaviors. In Figure 3d, it is clear that the facilitator and the group entity are positioned near the center of the group, unlike in Figure 3b, where the facilitator and the group entity are off center, near the edge of the group. Facilitation style and the role it plays in the online group's dynamics is a topic for future examination.

In the online small group discussions, participation is less evenly distributed than face-to-face, with some students interacting more or less than others. For example, in Figure 3b, one student (S7) "spoke" six times to the group as a whole and twice to the facilitator. Not addressing anyone else, and not being addressed by anyone other than the facilitator, left this student (S7) a relative outsider compared to the rest of the participants in the online Orange group. Compare this to the face-to-face Orange group, where everyone participated, almost equally.

In the online small groups, the greatest number of statements is again sent to the group entity, the polis, which emerges as the largest hub of influence in the online small groups, similar to the online large groups.

Common sense suggests another important difference between teaching face-to-face and online, as related to small breakout groups. Face-to-face, the instructor can only be in one place at a time. Online, the instructor can be everywhere, observing all the interactions in the small breakout groups. It appears that multitasking is also a skill that develops with practice over time. The implications and the applications of this possibility are beyond the scope of this article.

A comparison between the small and large groups, face-to-face and online (Figures 2 and 3) further validates the suggestion that face-to-face interactions in large learning groups are teacher- or expert-centered, while online and in real-time, members of large learning groups, in addition to learning from the instructor, can be observed to construct knowledge with each other. Small face-to-face groups appear to be more democratically distributed, the main reason for creating face-to-face breakout groups. The difference between face-to-face large groups and face-to-face small groups is dramatic.

Online, the differences between large and small groups are less pronounced. The size of the group does not appear to influence the creation of the online polis.

The data for the online class in Figure 2 were collected from the class archives by a software program written to create an Instrument called GUIDATA. This instrument provides all participants with an ongoing graphical representation of online interaction in real time. This instrument Graphically Unwraps the Interaction Diagram Along the Time Axis and is available to the participants as the interactions occur and any time afterwards. The GUIDATA expresses the loops found in Figure 2 as arrows that join head to tail, as speaker responds to speaker, or as speaker responds to several speakers. The data for the face-to-face class were collected by watching the videotape, coding the students, and manually tracking who spoke to whom and for how long.

Each square in the diagram represents a participant producing an utterance. Each row is a minute of interaction. Each column is a participant. For the online class, the participants are arranged according to their small blue, green, orange, and purple breakout groups. The principal instructor is shown as a red square in both diagrams.

Figure 4a. Guidata for the online session under study

Figure 4b. Guidata for the matched face-to-face session under study

The diagrams in Figure 4 illustrate different types of interactions, and, since interaction is the learning process in the experiential model, suggest that a different learning process is taking place in the two modalities. The online class interactive discussion in which participants are not required to take turns is vigorous, multivariate, and multileveled, with lines of communication connecting everyone into the web of the class narrative (Figure 4a). The face-to-face class turn-taking discussion appears anemic in comparison (Figure 4b). The visual evidence that online students generate greater data flow among themselves suggests that they are creating a "polis," and learning about and from each other. In contrast, the face-to-face students use the instructor almost exclusively as their learning resource. The GUIDATA for the entire three hour online Inclusion learning module #2 is here.

The GUIDATA for the online class also highlights the tendency of online students to interact more with members of their own small groups than with members of the other breakout groups. This behavior needs further study, since in the face-to-face class, small group identity did not appear to be as significant during large group face-to-face class sessions.

The empty squares in the face-to-face GUIDATA represent the silence of those who are not participating, due to the restrictive nature of sequential turn-taking inherent in the face-to-face environment. Some additional face-to-face restrictions as recorded in the student journals were: a finite time frame, fear of public speaking, and a fear of being misunderstood. It appears that many potential contributions face-to-face are silenced, when compared to the messy and busy-looking interaction pattern in the online environment.

Interactivity is at the core of the matched study presented in this article. It is assumed that in an emotional climate of trust and acceptance, interaction among participants in a collaborative group will lead to more effective goal formation. This, in turn, imparts a sense of control to those involved, which further increases trust, data flow, and so on. Of course, this process reversed will produce the equivalent downward spiral: Fear may lead to silence, which reduces known options or choices and leads to low productivity and a sense of dissatisfaction with oneself and the group (Gibb, 1964). The course content and process is built on the rationale that visibility yields awareness, accountability, connection, productivity, and well being. Feedback and self-disclosure are seen as effective tools for reducing the blind area of an individual's or a group's Johari Window (Luft, 1969), and freeing up the energy that was used to hide, to do the work.

The object of the matched study was to observe how two very different communication environments affect interactivity and learning. Many aspects of the face-to-face and the online environments can be seen both as assets and liabilities. For example:

Unlike face-to-face, and in addition to the archives, each online participant also has the ability to scroll back any number of messages "in the now," to confirm a perception, or to seek a concrete example for feedback purposes. Unlike face-to-face, the messages sent online remain exactly as experienced the first time. It appears that the online environment in which the study was conducted allows participants to experience both the whole and its parts. As Parrish (2000) notes, this has "the potential to alter significantly the structure of socialization and political discourse. The form of interaction, just as important as the content, shapes the way people think and act" (p. 18). If, moreover, the culture is one where a polis is encouraged, respected, and valued, it stands to reason that it will be the ideas of the participants, rather than their race, gender, or age, will prevail.

Time, and the perception of it, is an area in which face-to-face turn-taking interactions differ vastly from online non-turn-taking interactions. In order to compare the two environments on this measure, the online data, in terms of written words in a comment, were converted to the elapsed time a speaker would have taken to read the words out loud. The conversion rate was taken to be 150 words per minute (wpm). This rate is a hard word limit for turn-taking auditory interactions in any medium (face-to-face, on the phone, webcast, etc.) to remain comprehensible. "An investigation of the speaking/lecture rate of 10 college instructors reported an average rate of 150 words per minute (wpm), inclusive of brief pauses between utterances" (Sanderson, Siple, & Lyons, 1999, p.13).

Face-to-face time use was measured by watching the videos and using a stopwatch.

Figure 5. Cumulative Distribution Function (CDF) of face-to-face time use for the interactions shown in Figure 2b and Figure 3a (The solid lines are logarithmic curve fits to the data with the associated residual, R2)
Click images to enlarge

Face-to-face time was used up by a small percentage of the group. In the Cumulative Distribution Function (CDF) shown in Figure 5 for the large group, seven of the participants used 80% of the time available for collaborative discussion, and three of those participants were the principal instructor and two facilitators. In the small group, even though the participation diagrams were shown to be evenly distributed (Figure 3a), 80% of the time for the collaborative discussion was taken up by the facilitator and two other students.

There is no equivalent CDF for online time use; however, as shown below, time can be represented in the online environment.

Figure 6a. Face-to-face time use by participant for the network of interactions shown in Figure 2b and the GUIDATA shown in Figure 4b. The length of each red bar represents the time used during each comment by each participant.
Click image to enlarge

Figure 6b. Online time use by participant (rows) during and after the activity period (green) for the half hour described in Figure 2a and 4a. The blue bars represent comments that exceed the 150 wpm limitation of face-to-face interaction. They could not have been made in the face-to-face turn-taking environment.
Click image to enlarge

Figure 6 is another way to represent the concept of time contrasted with the use of the equivalent time-frame in the online environment. In the Session 2 learning module activity under study, students were asked to "mill around" and find a series of three people who exhibited an ascribed attribute (i.e., spoke four languages or had children, etc.), and engage in brief discussions with as many other students as possible. In addition to the 30 minutes of the processing period presented in this article, Figure 6 contains the interaction during the "milling around" Activity 1 that preceded it.

For the face-to-face class, the Activity 1 period is depicted as a solid green square (Figure 6a), because participants were milling around the room, interviewing each other, and talking all at once. All individual utterances disappeared into the solid block of group hum/buzz for 28 minutes. The subjective experience was that of energetic, upbeat conversation, composed of everyone and representing no one. The length of each red bar corresponds to the length of time a speaker took during the face-to-face turn-taking interaction. Once the Processing period begins, the red bars in Figure 6a clearly portray how the 30-minute turn-taking time-frame was apportioned among the participants, with the Instructor using up the lion's share of the available time.

For the online class, the green shaded region identifies the 30 minutes of interaction during the collaborative activity. As reported by the facilitators and instructor, the interactions were as vigorous and as distributed as face-to-face, the main difference being that the online statements are transparent, available to everyone as they unfold. Each column in Figure 6b is one minute of elapsed time during the online discussion. The red bars represent statements totaling 150 words. The blue bars in the same column represent the statements that would not be possible to make in a face-to-face turn-taking environment.

The total time of the statements represented by the blue bars is 46 minutes. It would therefore take a total of 76 minutes to speak out loud all the written statements generated by the online students during the 30-minute processing period. In other words, in a turn-taking discussion, only the red statements could have been shared within the 30 minute period; there would not have been time left for the 46 minutes the blue statements would have required.

There is significantly more collaborative data flow in terms of words and messages generated in the online environment than in the traditional face-to-face turn-taking setting. Online class students will send and receive more intended messages to and from each other than face-to-face students can send and receive from their peers. It is postulated that the increase of messages among participants would further facilitate the construction of collaborative knowledge. As data flow is linked to Trust Formation (Gibb, 1964), it may also be postulated that trust levels, and thus permission to share thoughts and ideas, would be higher among the students in the online class than in the face-to-face class. An analysis of Figure 6a and 6b generates predictions as to which group would be most likely to learn more from one another, and which group is most likely to learn more just from the instructor.

As we explore the characteristics of non-turn-taking collaborative interactivity, the findings continue to gather into a substantial and persuasive body of evidence that synchronous text and graphics-based communication methods will prove to be superior to turn-taking collaboration tools such as audio and video web casts, in terms of the amount of communication that can be generated. As mentioned above, the hard limit for expressing oneself in turn-taking spoken interactions is estimated at 150 wpm, and with normal group "babble time," this word limit of data flow becomes perhaps as low as 130 wpm. As noted by Foulger (2002), however, most people can talk (150 WPM) an order of magnitude faster than they can type (20 WPM), read (300-1500 WPM) at least twice as fast as people typically talk, and process information at least five times faster (800 WPM) than people typically talk, suggesting speed advantages for both spoken (production) and computer-mediated (reception) modalities of interaction.

This study has presented the preliminary findings of a matched study conducted to investigate similarities and differences between two teaching environments: the traditional face-to-face (turn-taking) environment and an online (non-turn-taking) environment called the LBD eClassroom. Two sections of the same course were compared. The course objectives, the content, and the teaching pedagogy (experiential learning) were the same, as were the teaching team, the time frames and duration, the assignments, and grading criteria. Due to the nature of the study, there were some variables that could not be kept constant, such as student interest in the course at the outset.

Instruments like the GUIDATA were employed as social proxies used for online social visualization, and as instantaneous feedback tools. Because the most striking differences between learning face-to-face and learning online that emerged from these methods are related to interactivity, the tone of this article may suggest a preference for online education, which showed more plentiful and distributed interaction. This is not our position, however. Each environment has its distinct advantages and opportunities for teaching. The issue is not which venue is better or worse. The goal of the inquiry is to understand both the similarities and the differences in order to formulate online learning theories and improve teaching effectiveness across the board.

In the non-turn-taking collaborative interaction that occurs in the online environment used in this study, there is no theoretical limit for the data flow in number of words that can be generated. The effective limit is based on a synthesis of the groups' combined reading, comprehending, and typing skills. Because the LBD eClassroom is designed without auto-scrolling, participants read, comprehend, and respond at their own speed. Everyone can generate and send data when they are ready, and get as much data as they want at any given time. Once a message is posted into the LBD eClassroom, it becomes transparent and remains available to everyone; there is no need to repeat, or to take notes. In contrast, in the face-to-face class session, all words, statements, and interactions disappear and are held only in an individual's memory.

The most substantial findings of this research to date regarding differences between turn-taking and non-turn-taking collaborative interactions are related to the issue of time. Intriguing questions are raised: Do participants who are engaged in the environment of synchronous non-turn-taking communication used in this study in fact create more time for themselves? What are the implications and applications of the extra 46 minutes it takes to read out the statements generated in a 30-minute real-time online peer-centered collaborative discussion vs. a face-to-face turn-taking instructor-centered discussion? If time is money, the participants in the online class are richer than their face-to-face counterparts. May one also assume that if information is power, and the data flow generated online is not only larger, but more varied, visible, and lasting than face-to-face, that online students would be more productive and have a better sense of self and others?

McLuhan (1969) wrote about how the linearity of a print-based information technology limits people's thought patterns. Words follow words, lines follow lines, paragraphs follow paragraphs, pages follow pages and so on, in a single, one-way necessary order, from the first page to the last. In McLuhan's view, learning through a linear medium discourages flexible, open-ended, multidirectional, and multidimensional thought. "Instead of being authoritative, books become authoritarian, demanding we think in a straight line, from a fixed point of view" (Alexenberg, 2004). Designed to be read in privacy, McLuhan believed that books encourage isolation and non-involvement with others, so that the book's medium becomes stronger than its content. One could make a similar statement about turn-taking interaction as well. As one utterance follows the next, the process of taking turns (i.e., the anxiety of waiting/fearing to be called upon or blowing the chance, etc.) may become more important than the message ultimately shared, often out of sync as a result of having had to wait for one's turn.

The Internet is a new text- and graphics-based medium, with a powerful non-linear potential. As a medium, it can foster a polylogue of words and images where freshness, vividness, and acute awareness permeate the discussions. Venturing into this new land may change us, no matter how we cling to the familiarity we know. We propose that one of the changes, at least as regards synchronous CMC, may involve turn-taking and the nature of group participation.

We wish to thank Dean Martin Singer for his support of this study. We also wish to thank our colleagues, the camera team, and the students for the generous gift of their personal time, effort, and resources.

Alexenberg, M. (2004). An interactive dialogue: Talmud and the new. Parabola, 29 (2), 32-36.

Batagelj, V., & Mrvar, A. (1996). Pajek, a freeware software program for large network analysis. University of Ljubljana, Slovenia. Retrieved July 24, 2005 from http://vlado.fmf.uni-lj.si/pub/networks/pajek/

Borgatti, S. P., M. G. Everett, & Freeman, L. C. (1999). UCINET 5.0 Version 1.00. Natick: Analytic Technologies.

Dewey, J. (1938/1997). Experience and Education. New York: Simon and Schuster.

Dimock, H. G. (1993). How to Observe Your Group, 3rd ed. North York, ON: Captus.

Erickson, T., & Kellogg, W. (2000). Social translucence: An approach to designing systems that support social processes. Transactions on Computer Human Interface. Retrieved July 24, 2005 from http://www.pliant.org/personal/Tom_Erickson/st_TOCHI.html

Foulger, D. (2002). Building time machines: Thinking about the future of interpersonal communication. Oswego State University Cognitive Science Lecture Series, 2002. Retrieved August 16, 2003 from http://www.oswego.edu/~dfoulger/research/timeInMedia2/

Gibb, J. R. (1964). Climate for trust formation. In L. P. Bradford, J. R. Gibb, & K. Benne (Eds.), T-group Theory and Laboratory Method (pp. 279-308). New York: Wiley.

Haythornthwaite, C. (2001). Exploring multiplexity: Social network structures in a computer-supported distance learning class. The Information Society, 17 (3), 211-226.

Kolb, D. A. (1984). Experiential Learning. Englewood Cliffs, NJ: Prentice-Hall

Lazarus, A. (1975). Learning to Relax (Tape). New York: Institute for Rational Living, Inc.

Lobel, M., Neubauer, M., & Swedburg, R. (2002a). Elements of group interaction in a real-time synchronous online learning-by-doing classroom without f2f participation. USDLA Journal, 16 (4). Retrieved July 24, 2005 from http://www.usdla.org/html/journal/APR02_Issue/article01.html

Lobel, M., Neubauer, M., & Swedburg, R. (2002b). The eClassroom used as a teacher's training laboratory to measure the impact of group facilitation on attending, participation, interaction, and involvement. International Review of Research in Open and Distance Learning, 3 (2). Retrieved July 24, 2005 from http://www.irrodl.org/content/v3.2/lns.html

McFarland, D., & Bender-deMoll, S. (under review). Classroom structuration: A study of network stabilization. Obtained from the Authors.

McLuhan, M. (1969). Guttenberg Galaxy: The Making of Typographic Man. New York: New American Library.

Moreno, J. L. (1934). Who Shall Survive? Washington, DC: Nervous and Mental Disorders Publishing Co. Reprinted in 1953 by Beacon House, Beacon, NY.

Neubauer, M., & Lobel, M. (2003). The Learningbydoing eClassroom. Learning Technology, IEEE Computer Society, Learning Technology Task Force (LTTF), 5 (3). Retrieved July 24, 2005 from http://lttf.ieee.org/learn_tech/issues/july2003/#8

Neuhauser, C. (2002). Learning style and effectiveness of online and face-to-face instruction. American Journal of Distance Education, 16 (2), 99-113.

Russell, T. L. (1999). The No Significant Difference Phenomenon. Raleigh: North Carolina State University.

Sanderson, G., Siple, L., & Lyons, B. (1999). Interpreting for Postsecondary Deaf. A report of the National Task Force on Quality of Services in the Postsecondary Education of Deaf and Hard of Hearing Students. Rochester, N.Y.: Northeast Technical Assistance Center, Rochester Institute of Technology. Retrieved July 24, 2005 from http://www.rit.edu/~netac/publication/taskforce/interp/

Viégas, F., & Donath, J. (1999). Chat circles. Proceedings of the SIGCHI Conference on Human Factors in Computing System, Pittsburgh, PA. Retrieved July 24, 2005 from http://web.media.mit.edu/~fviegas/chat_circles.pdf

Mia Lobel (M.Ed.) is a psychotherapist in private practice, a part-time faculty member at Concordia University, Montreal, Canada, and a life-long Community Developer. She has co-founded The Women's Information and Referral Center, Head and Hands, the PTU /Montreal General Hospital and the Westmount Psychology Center. Mia's client list includes the R.C.M.P., the Presbyterian Church, the Montreal Protestant School Board, and Kanasatake Social Services. She attributes her current interest in developing an online classroom into which she can migrate her teaching content, without compromising the pedagogy she uses, to her difficulties with technology. Mia says: "If I can do it, anyone can!"
Address: Westmount Psychology Center, 4211 Ste Catherine West, Montreal, QC H3Z 1P6 Canada

Michael Neubauer (MSEE) is an Engineering Physicist at Stanford Linear Accelerator Center (SLAC), Stanford, California, and an international consultant. He developed the software used to collect the interaction data online in real time from the LBD eClassroom application, and is a co-founder of Learningbydoing, Inc. Mike has working experiences with the technology used in most all analog and digital collaboration tools over the last fifteen years. Mike is also a telecommuter, working between Montreal and SLAC for the last five years. He has written and co-authored a number of papers on distance education as well as linear collider technology.
Address: 4527 St. Dominique, Montreal, QC H2T 1T7 Canada

Randy B. Swedburg is Professor and Chair of the Department of Applied Human Sciences at Concordia University in Montreal, Quebec. His major research interests are in the areas of lifelong learning, successful aging and lifestyle. Dr. Swedburg holds or has held the following titles: Fellow and Director, Concordia University Centre for Mature Students; Senior Fellow, American Leisure Academy; Past President of the American Association for Leisure and Recreation; Fellow, North American Society for Health, Physical Education, Recreation and Dance; and, Vice-President, Institute Development, Elderhostel Canada.
Address: Concordia University, 7141 Sherbrooke Ouest, Montréal, QC H4B 1R6 Canada