The influence of group size on nonmandatory asynchronous instructional discussion groups

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Abstract

In this study, the authors examined the effect of group size on students' behavior in asynchronous, nonmandatory instructional discussion groups. The focus in this study is on four main questions: (a) Does group size affect the proportion of learner–learner and instructor–learner interactions? (b) Does group size influence the number of messages instructors post? (c) Does group size have an effect on the number of contributions that students post? (d) Does group size affect instructor lag time as well as the interval between successive postings? It was found that group size affects all these aspects of asynchronous discussion: The proportion of learner–learner interaction increased as group size increased, while the proportion of instructor messages decreased. Most students participated to a minimal degree and only a small minority of students posted more than 10% of a discussion group's messages. Last, as group size increased, the interval between successive instructors' postings decreased; lag time, however, was not influenced by group size. Results are discussed in terms of the restructured theory of transactional distance by Gorsky & Caspi, 2003, and several explanations relating group size and students' behavior in asynchronous discussion group are suggested.

Introduction

Over the last decade, distance education systems have been evolving rapidly from correspondence-based courses to Web-based instructional environments (WBIE). Recently, Sikora and Carroll (2002) reported that among students in the United States who participated in distance education programs, about two-thirds did so via the Internet. Universities that traditionally deliver courses face-to-face are also implementing WBIE to some extent. The integration of WBIE into traditional course design ranges from very limited (i.e., downloading learning material) to very extensive (i.e., full replacement of in-class meetings). Instruction via the Internet enables course designers to update course content on a semester basis, thereby accommodating up-to-date papers, research findings, and other changes in curriculum. More importantly, WBIE enables access to remote databases using multimedia technologies and allows students to interact, asynchronously or synchronously, in diverse ways (i.e., voice–text).

The authors of this article conducted a study of the impact of group size on patterns of interactions in optional, nonmandatory, and asynchronous instructional discussion groups. These kinds of discussion groups are gaining prominence since many universities and colleges are routinely implementing such services through course websites. Specifically, the following issues were investigated: The amount and kinds of interpersonal interaction (instructor–learner; learner–learner), the proportion of instructor messages, the level of learners' participation (i.e., How many massages do they post? Does a small minority of participants account for most of the messages regardless of group size?), and temporal dimensions such as time intervals between messages (lag time) and between successive postings made by instructor. To begin, a review is presented of the concepts of interaction and dialogue as defined in transactional distance theory (Moore, 1993) and later in its reconstructed version (Gorsky & Caspi, 2003).

Transactional distance theory assumes the centrality of dialogue as a means of facilitating learning. Interaction may be live or mediated through technology; it may be synchronous or asynchronous. The increasing use of technology, its transparency and user-friendliness encourages the use of asynchronous discussion groups and on-line, synchronous chat rooms. Instructors may or may not choose to participate in these forums. These technologies enable students to share ideas, gain insights, and seek support.

Moore (1989) wrote that the term interaction has been misused and “carries so many meanings as to be almost useless, unless specific submeanings can be defined and generally agreed upon.” More recently, researchers (e.g., Reeves, 1999, Rose, 1999, Yacci, 2000) have noted that the term is often defined loosely and inconsistently. For current purposes, the authors opt for a structural definition of interactivity (interaction) proposed by Yacci (2000). He defines four major attributes of the concept:

  • 1.

    Interactivity is a message loop;

  • 2.

    Instructional interactivity occurs from the learner's point of view and does not occur until a message loop from and back to the student has been completed;

  • 3.

    Instructional interactivity has two distinct classes of outputs: content learning and affective benefits; and

  • 4.

    Messages in an interaction must be mutually coherent.

As opposed to Yacci (2000), the authors assume that instructional interactivity also occurs from the instructor's point of view, that is, if an instructor posts a message that leads to a coherent response, this too, is instructional interactivity.

Dialogue, as defined by Moore (1993, p. 24), is more than mere interaction:

The term “dialogue” is used to describe an interaction or series of interactions having positive qualities that other interactions might not have. A dialogue is purposeful, constructive and valued by each party. Each party in a dialogue is a respectful and active listener; each is a contributor, and builds on the contributions of the other party or parties… The direction of a dialogue in an educational relationship is towards the improved understanding of the student.

The restructured model of transactional distance (Gorsky & Caspi, 2003) includes four kinds of dialogue relevant to distance education. Moore (1989) defined the first three while Fulford and Zhang (1993) identified the fourth.

    Instructor–learner:

    An interaction that provides the learner with information, feedback, and motivation.

    Learner–learner:

    An interaction that provides learners with information, feedback, motivation, and a social environment.

    Learner–subject matter:

    An internal interaction in which the learner assimilates and accommodates the subject matter.

    Vicarious interaction:

    A vicarious learner can learn through other students' interactions with the instructor and other students.

The scope of this investigation includes only instructor–learner and learner–learner interactions. The goal of this study is to investigate the impact of group size on interaction in asynchronous discussion groups. A literature review follows.

Compared to the effect of class size on learning outcomes in the classroom, remarkably few research studies have addressed the effect of group size on interaction or learning outcomes in distance education courses. However, these few studies found that on-line group size does have a significant and meaningful impact on interpersonal interaction (instructor–learner, learner–learner). Chen and Willits (1998) found that the larger the learning group, the greater the transactional distance between instructor and learners (as perceived by the learners). Vrasidas and McIsaac (1999) explored participation of students in a small asynchronous discussion group. They found that four students were not enough to generate productive asynchronous discussion. They speculated that if more students were enrolled in the course, more asynchronous interactions would have occurred.

Two other studies dealt with group size in distance education, but the focus was not directly on interaction. Biner, Welsh, Barone, Summers, and Dean (1997) explored students' satisfaction in groups that ranged in size from 1 to 33 and found that learners in small groups were more satisfied with the courses and more apt to exceed their previous academic performance than in large groups. Sugrue, Rietz, and Hansen (1999) compared course satisfaction and students' performance in small (30 participants) and large (63 participants) groups. In this study, learners were taught synchronously via two-way video broadcast, while the instructor alternated between the large and the small groups every other week. Sugrue et al. found that students achieved higher exam scores in the small group relative to the large one, as well as significantly lower students' satisfaction in the large group.

Twigg (2001) surveyed several distance education programs and found that class size was limited to about 9–25 students in programs where high interactivity was deemed important. Field recommendations limited this range from 12 to 20. For instance, in the Distance Education Online Symposium Listserve (DEOS-L), (http://lists.psu.edu/archives/deos-l.html) the common recommendation is to limit enrollment to 20 participants.

Fahy, Crawford, and Ally (2001) maintained that as group size increases, the number of potential learner–learner and instructor–learner interactions grows proportionally. Gorsky and Caspi (2003) proposed another relation between group size and proportion of potential (and actual) learner–learner and instructor–learner interactions. The restructured transactional distance model contends that as group size increases, the potential for learner–learner interaction increases, whereas the potential for instructor–learner interaction decreases. Thus, group size seems to be a major structural determinant regarding levels of interactions in distance education.

Another structural dimension of instructor–learner interaction studied was the temporal. Two aspects of this dimension were identified: (1) the lag time (i.e., speed of reply) between learner-posted messages and instructor reply and (2) the time interval between successive instructors' postings. A review of literature showed that these variables have not been studied. However, these temporal dimensions may affect the amount of participation in asynchronous discussion groups. Knowing that the instructor is present, learners may participate more frequently in the discussion group. In nonmandatory groups, frequent instructor presence may alter learner behavior. Group size may affect instructor's presence in a very simple way: In large groups, instructors are called upon to answer more often; therefore, they are present in the group more frequently.

As a historical note, these seemingly straightforward findings may be significant. A half-century of research into the relation between class size and learning outcomes in traditional classrooms has yielded inconclusive findings; therefore, it is ostensibly surprising to find that group size does indeed influence outcomes in distance education settings. There is, however, a reasonable basis to suppose that this may be the case. Lazear (2001) pointed out factors that interact simultaneously with the variable class size in traditional classrooms: behavior and disciplinary issues (class size effects are larger for less well-behaved learners), age and attention spans (optimal class size varies directly with the attention span of learners), and group segregation by ability (for good learners, class size may rise with no detrimental effects on outcomes). Disciplinary issues, attention spans, and homogeneous grouping are less relevant for university level distance learners. Therefore, it seems that group size may indeed be a relevant and significant factor, as the above-cited findings indicate.

Adding information collected in public, not necessarily in instructional, discussion groups, completes this review. Similar to the present research, participation in these groups is nonmandatory. In research of public discussion groups, Hiltz and Turoff (1978) noted that conferences with less than 8–12 active participants would, after a short while, fail to produce enough new material to justify their continued use of the system. Thus, they set a lower boundary for an optimal number of participants.

In public discussion groups, Jones (2000) found that a small minority of participants posted a large proportion of messages and increasing the number of participants did not increase user contributions. This finding has not provoked studies so far. Nonmandatory instructional discussion groups may provide a relevant starting point to test the generality of this finding.

Moreover, Jones (2000) claimed that the upper boundary for the number of optimal participants is determined by cognitive factors, in particular “information overload.” When the group is too large, participants are confronted with too many data items. To cope with information overload, participants may choose to end participation, ignore parts of the discussion or participants (for instance by filtering), or to split the discussion group into subgroups. Thus, Jones' analysis suggests that, on the one hand, group size is not an important factor because the number of active participants does not influence contribution, and in any group size, a small minority posts most of the messages. On the other hand, behavior of participants is influenced by group size, especially when it becomes too large.

The study raises four questions:

  • 1.

    Does group size influence the proportion of learner–learner and instructor–learner interactions?

  • 2.

    Does group size influence the proportion of instructor messages posted to the group?

  • 3.

    Does group size influence the distribution of the number of messages per student? In other words, does a small minority of participants indeed account for most of the messages regardless of group size?

  • 4.

    Does group size affect instructor posting rate: instructor–learner lag time and instructor posting interval?

Section snippets

Background

The Open University of Israel is a distance education university designed to offer academic studies to students throughout Israel. Established in 1974, the university offers a home study system based on textbooks, tutors, and study centers throughout the land. This year's enrollment is more than 38,000 students.

The classic text–tutor system was enriched in 1999 with the introduction of WBIE, wherein each course has its own website. Course sites are intended to simplify organizational procedures

Sample

The sample included 47 out of about 200 courses that offered nonmandatory, asynchronous discussion groups during the spring semester of 2002. Courses were randomly sampled from each of the four university faculties: humanities, social sciences, natural sciences, and exact sciences. Table 1 presents the sample population of the study.

Procedure

The basic unit studied in this research was a “message.” Each message was categorized according to the following criteria: (1) authorship (instructor or student)

Results

A total of 7706 messages were analyzed. Instructors initiated 235 messages; learners initiated 2996 messages. Of instructor-initiated messages, 75% remained unanswered. Of learner-initiated messages, 19% remained unanswered. All initiated messages that received one or more responses (that is, interaction loops) were divided as follows: 1768 instructor–learner interactions (the term instructor–learner interaction relates to interactions initiated either by instructors or learners) and 694

Discussion

In this study, several questions concerning the influence of group size on interactions in a nonmandatory, WBIE were asked. Before discussing the implications of each specific research question, it should be noted that the environment studied was utilized actively by a minority of the learners enrolled in the courses (15%). Of these 15%, it was found that about 80% posted one to three messages during the entire semester. That is, only 3% of the university students enrolled in these courses

Conclusions and implications

The authors conclude that only a limited number of learners actively participate in nonmandatory discussion groups. This is in accord with similar findings from synchronous discussion groups (Kelsey, 2000) as well as asynchronous, public discussion groups (Jones, 2000).

Two implications emerge from the study. First, to increase learner participation in asynchronous, nonmandatory discussion groups, a larger group size is called for. This creates a greater potential for interaction, especially

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