Proceedings of the 35th Hawaii International Conference on System Sciences - 2002
Asynchronous Team Support: Perceptions of the Group Problem Solving Process When Using a CyberCollaboratory Donna K. Dufner University of Nebraska at Omaha College of Information Science & Technology Omaha, NE 68182-0116.
[email protected] Ojoung Kwon California State University at Fresno Craig School of Business Department of Information Systems and Decision Sciences Fresno, CA 93740-0007
[email protected] Abstract The research presented here studied thirty-three groups of student volunteers over a period of three weeks while the groups performed a series of teamwork tasks. To investigate the viability of Web-based group support tools for asynchronous learning networks, student volunteers from four widely distributed universities were assigned to one of four experimental conditions. The conditions are; 2 modes of communication (asynchronous vs. synchronous) x 2 support conditions (with CyberCollaboratory support or without). The groups assigned to the different conditions reported significant differences in perceptions of the group problem solving process. The face-to-face groups felt the process was more efficient, coordinated, fair, and satisfying. Those with CyberCollaboratory support thought the process was more confusing and less satisfying. Comments from the students suggest the reason for these results may be a combination of insufficient training time (one week) and a short period (two weeks) for using the tools to accomplish a fairly simple group task. Interaction effects showed that both the asynchronous groups with CyberCollaboratory support and the baseline (face-to-face) groups found the problem solving process to be more efficient, coordinated, and fair than did either the asynchronous groups without CyberCollaboratory support or the face-to-face groups with CyberCollaboratory support.
Yong-Tae Park California State University at Fullerton Department of Information Systems and Decision Sciences P.O. Box 6848, Fullerton, CA 92834-6848.
[email protected] Qing Peng University of Nebraska at Omaha College of Information Science & Technology Omaha, NE 68182-0116.
[email protected]
Key words: Asynchronous Learning Networks, Virtual Teamwork, Virtual Workgroup Environments, Web-based Teamwork Environments, Collaboratories, Group Support.
1. Introduction In the last few years, many colleges and universities have changed their approach to education by offering various online courses. Online courses provide students having time and location constraints with more opportunity and flexibility in choosing their classes and programs. The advancements of information technology, the Internet technologies in particular, have provided those organizations with the technical infrastructure for course delivery significantly altering the way we view education. We have become the “Networked Nation” envisioned by Hiltz and Turoff [13]. Asynchronous learning networks (ALN) based on Internet technologies have contributed significantly to the success of distance learning due to their ability to bring students to a cyber-classroom regardless of their geographical locations and time constraints [15]. Studies have shown that an ALN, well structured for effective interaction leads to a high level of reasoning due to the extended think time [1] and to better educational outcomes [7], [8], [12]. Without question, distance learning has brought new opportunities to students and educators. However, along with the opportunities came some daunting challenges due
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to the unique paradigm for teaching and learning presented by the reduction or elimination of constraints on time and space [6]. Social and technical coordination present one set of challenges. The social isolation experienced by some distance learners is another. To make distance learning a more meaningful and productive educational experience, it is necessary to provide both educators and students with effective tools and techniques to support the new educational paradigm and to deal with the issues of social isolation and group coordination. ALNs can be enhanced to provide students with team learning opportunities by incorporating collaborative and group learning spaces within the ALN design [2], [5]. Web-based tools embedded within a collaboratory provide a collaborative virtual workplace where tools and structures can be used to control and structure group processes making team projects feasible. Team projects can help relieve the feelings of social isolation reported by some students [5] and can provide successful learning experiences for students in general [5], [9]. Our previous research pilots suggest that asynchronous collaborative tools may provide satisfying learning experiences for students working on group projects in the asynchronous mode of communication. The technology may protect team members from “pressure to closure” [10], by providing extended think time to explore more alternatives [1]. These tools may also level influence among members insuring that all participate as much as they wish [19]. The tools and process structures may also provide a means to structure social and technical coordination more effectively. The objective of this study is to investigate the perceived usefulness of integrated web-enabled, group support tools as social and technical process coordination mechanisms. These tools are embedded within a CyberCollaboratory designed to support team projects in distance learning and ALN based teaching. The research question is, how useful is a web-accessible collaboratory as a support structure for team projects in ALN based and distance education. 2. Background of the Study Because of the technological advancement and proliferation of the Internet in recent years, collaborative technologies such as chat, computer conferencing, web boards, and web based learning environments have become affordable and readily accessible. Today teaching students who are geographically dispersed is feasible and desirable. Use of these tools provides support for the individual learner who is being taught through an ALN. On the other hand, support for group projects, group tasks, and group learning experiences using these systems is limited and often lacks the coordination modes and
mechanisms necessary for a group collaborative learning experience. Coordination modes such as an agenda or group decision support tools or processes are the regulatory processes used by a group to manage or regulate group interaction. Social and technical coordination problems plague group work conducted in the asynchronous mode of communication without such process structures. Because the communication is asynchronous, the coordination mechanisms must be embedded within the software [9]. Without the embedded coordination structures the longer delays between questions and responses in the asynchronous mode of communication can cause a group member to report feeling isolated. Lack of coordination structures may also contribute to group fragmentation, member withdrawal, unproductive communication, and failure to complete the group work or task. In order to develop a CyberCollaboratory where coordination can be fostered we decided to implement tools and procedures that would provide specific coordination mechanisms for team members such as an agenda, computer supported facilitation tools, and group decision support system tools (GDSS). 2.1. Modes of Coordination The modes of coordination selected for implementation in the CyberCollaboratory were taken from the morphology developed by Thompson (1967) for organizational unit coordination. The following modes were adopted and operationalized: •
Sequential: An agenda specifies phases of the problem solving process; group members must work on the same agenda item during any time period.
•
Pooled: A structure or standard is adopted to capture and represent individual contributions to a collective group representation such as voting or polling tools. We also added facilitation tools to foster pooled coordination as well.
2.2. The Benefits of Asynchronous Collaboration The benefits of asynchronous collaboration (different time/different place) include more than just convenience. The asynchronous mode of communication may be more effective in some ways than face-to-face communication. Asynchronous meetings generally take place over an extended period of time. The delays between response and feedback that occur in the asynchronous mode of communication provide group members with the opportunity to reflect and think about a problem and examine more alternatives than is possible in a traditional face-to-face meeting. However, we need to develop and test tools that deal with the social isolation and, the social
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and technical coordination issues faced by asynchronous teams.
2.3.
A Collaboratory Defined
The term “Collaboratory” defined by William Wulf [3] is as follows: “…center without walls, in which the nation’s researchers can perform their research without regard to geographical location—interacting with colleagues, accessing instrumentation, sharing data and computational resource, and accessing information in digital libraries.” [14]. For our CyberCollaboratory we have extended Wulf’s definition to include centers without walls specifically designed and built to support teamwork, team projects or collaborative learning opportunities for students being educated via ALN.
3. The CyberCollaboratory Our CyberCollaboratory is a major extension of Wulf’s definition stated above. We are providing “intelligent” and media rich tools that are designed to be Web-enabled, multi-user, tailorable, integrated, and asynchronous. The CyberCollaboratory contains the following software environments:
1.
Intelligent Project Management (Project Management Advisor),
2.
Collaborative Document Production,
3.
Asynchronous Group Discussion (Computer Mediated Conferencing),
4.
Real-time Chat,
5.
Group Decision Support System (GDSS) including Electronic Brainstorming, Idea Organizing, Voting, and,
6.
Group Facilitation.
The GDSS and Group Facilitation are the main technical and social process structures embedded within the software of the CyberCollaboratory. A meeting agenda is also always recommended and uploaded as text to be used as a social coordination process structure for all teams. The initial interface for Facilitation mode is shown in Figure 1. Process structures such as these, which support the coordination of the group’s work, [11] are often absent from asynchronous, collaborative technologies such as Computer Mediated Conferencing (CMC) systems and many Cyber learning tools. While most of these tools have methods for indexing or linking indented lists these simple processes are not adequate for group process coordination.
CyberCollaboratory Interface
Figure 1. The CyberCollaboratory in Facilitator Mode
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From previous research we know simple group process structures such as a meeting agenda, voting tools, or facilitation can help an asynchronous group achieve goals. Groups without even these simple tools may not be able to establish and maintain pooled or sequential [17] group processes and may resort to working through a task as individuals working alone. Facilitation software was developed to provide an extra layer of coordination above and beyond the GDSS tools to add further support for both sequential and pooled modes of group work. Access to computer based process structures can be controlled in the CyberCollaboratory either by a facilitator (a human using the tools) or through software mechanisms such as timers. Team members are provided access to a specific structure such as brain storming for a specified period of time. Once a pre-specified period of time has elapsed the brainstorming function will close automatically and can no longer be accessed. The facilitator can go back and extend times for specific tasks if he or she wishes. However, once access is closed the group members must move on to the next step in the process. Earlier studies showed that without clear coordination such as a facilitator mode subjects would initiate participation after an extended period of time had elapsed (e.g. at the end of the process during voting) and throw the entire group into chaos [4]. Successful and satisfying work in the asynchronous mode of communication requires regular, steady participation in the group processes. The facilitation mode is designed to keep the group members working on each sub task together.
4.1. The Variables
4. Experimental Design and Hypotheses
The entire study examined perceptions of media richness, system satisfaction, and the group problem solving process. Investigation of student perceptions of the group problem solving process under the four research conditions is of special interest. The impact of the coordination mechanisms are expected to be experienced the most during the decision processes of the group. Therefore, the hypotheses dealing with perceptions of the group problem solving process are presented and the research findings for the group problem solving process are the focus of this paper.
The study presented here is an experiment following two pilot studies. The pilots were conducted to insure the validity of the research design, the methodology, and the functionality of the CyberCollaboratory. To investigate the usefulness of the CyberCollaboratory as an asynchronous team support structure, a 2x2 factorial design was developed as shown in Table 1. Included in the cells is the total number of groups and students who originally volunteered and were assigned to groups for the experiment. Mode of Communication Asynchronous Face-toface CyberGroups = 9 Groups = 9 Collaboratory Subjects = 36 Subjects = 36 No CyberGroups = 9 Groups = 11 Collaboratory Subjects = 36 Subjects = 45 (baseline)
Since this study attempts to investigate the perceived usefulness of the CyberCollaboratory in support of asynchronous teamwork, the following research variables were studied:
4.1.1. Independent: Manipulated CyberCollaboratory •
Access
•
No access
Mode of Communication •
Asynchronous
•
Face-to-face
4.1.2. Dependent •
Perception of problem solving ability
4.1.3. Pre-experimental measures •
Preconceived attitudes
•
Preconceived perceptions
•
Previous experiences
4.2. Hypotheses: Perceptions of the Group Problem Solving Process
H1: Groups supported by the CyberCollaboratory will report that the group’s problem solving process is more efficient than will groups without CyberCollaboratory support. H2: Groups working in the asynchronous mode of communication will report that the group’s problem solving process is less efficient than will groups working in the face-to-face mode of communication.
Table 1. 2X2 Factorial Research Design
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H3: Groups supported by the CyberCollaboratory will report that the group’s problem solving process is more coordinated than will groups without CyberCollaboratory support. H4: Groups working in the asynchronous mode of communication will report that the group’s problem solving process is less coordinated than will groups working in the face-to-face mode of communication. H5: Groups supported by the CyberCollaboratory will report that the group’s problem solving process is more fair than will groups without CyberCollaboratory support. H6: Groups working in the asynchronous mode of communication will report that the group’s problem solving process is less fair than will groups working in the face-to-face mode of communication. H7: Groups supported by the CyberCollaboratory will report that the group’s problem solving process is more understandable than will groups without CyberCollaboratory support. H8: Groups working in the asynchronous mode of communication will report that the group’s problem solving process is less understandable than will groups working in the face-to-face mode of communication. H9: Groups supported by the CyberCollaboratory will report that the group’s problem solving process is more satisfying than will groups without CyberCollaboratory support. H10: Groups working in the asynchronous mode of communication will report that the group’s problem solving process is less satisfying than will groups working in the face-to-face mode of communication.
5. Experimental Procedures All groups followed the same experimental procedures. Each subject completed a consent form, a pretest questionnaire, a task questionnaire, a training questionnaire and a posttest questionnaire. Each group performed a training task over a period of one week, the Vendor Selection Task, and the Experimental Task over a period of two weeks, The Parking Lot Allocation Problem. Both tasks can be classified as toy tasks. Descriptions of the tasks and copies of the questionnaires can be obtained from the authors.
5.1. Survey Instrument Validation The survey instruments (questionnaires) used in this study were validated over a ten-year period through the research efforts of Hiltz and Turoff at the New Jersey
Institute of Technology (NJIT) and their graduate students. In 1998 Dufner and Kwon modified the survey instruments slightly to fit this and other similar studies. The instruments were then revalidated through several pilot studies conducted prior to this study [5].
5.2. Subjects Volunteers were solicited from the following four schools: the New Jersey Institute of Technology, California State University at Fullerton, The University of Illinois at Springfield, and the University of Nebraska at Omaha. Students were given an extra 10 percentage points toward their grade for participating in the experiment. Subjects ranged from undergraduates to PhD students. Of the 153 student volunteers 57 were female and the remainder were male. The volunteers were ethnically diverse including one Native American. However, over 50% were Asians.
5.3. Assignment to Groups and Conditions Subjects were quasi-randomly assigned to groups. Due to the great geographical distances involved (e.g. The New Jersey Institute of Technology is located on one end of the country and the California State University at Fullerton is located at the other) random assignment to groups was not feasible. Each face-to-face group was comprised of students from their home school. Both undergraduate and graduate students were assigned to each group where possible. Each asynchronous group was comprised of students from the different schools. The geographical dispersion of the subjects did add leverage to encourage them to use the tools we provided for the groups. Telephone coordination was virtually impossible given time differences, costs, and schedules.
5.4. Group Procedures Each subject was notified by email of his or her group and condition assignment. The email also contained a list of dates for the performance of the training and research tasks. The CyberCollaboratory groups were informed that CyberCollaboratory training materials were available at a specific URL. The face-to-face groups (baseline) were given a date and time to meet at their school to perform the training and research task with their group. All subjects already had email accounts. Asynchronous groups without CyberCollaboratory support were also contacted by email. These groups were given a task performance schedule and informed that training materials were available at a specific URL. Chat, email and CMC was made available to groups assigned to
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the asynchronous condition without CyberCollaboratory support for performance of their collaborative tasks.
6. Training Since the asynchronous groups were comprised of students located at great geographical distances (2,000 or 3,000 miles), bringing them to the classroom for training was out of the question. Training was self-paced and online for all groups except the baseline or face-to-face groups. The researchers suggested that each student perform a specific training task within a limited period of time (generally two full days to complete each task). Baseline groups were trained in performance of the task during their only face-to face session Students assigned to both face-to-face and asynchronous CyberCollaboratory supported groups were given access to online, automated training in the tools and functionality of the CyberCollaboratory in the form of videos and PowerPoint slides narrated with streaming audio. Asynchronous groups without CyberCollaboratory support were also given access to online, automated training in the form of videos and PowerPoint slides narrated with streaming audio. Training procedures were specified and followed by all researchers at the various schools. All students were guided through the training task, Vendor Selection, using the suggested meeting agenda shown in Figure 2. Email guidance from the group facilitator (a research team member) was also provided to each group during training. Suggested Meeting Agenda 1.
Define Problem
2.
Define Selection Criteria
3.
Define Alternatives
4.
General Discussion
5.
Rate Alternatives
6.
Vote or Straw Poll
7.
Group Decision
How would you describe your group’s problemsolving process? Efficient 1:2:3:4:5 Inefficient Coordinated 1:2:3:4:5 Uncoordinated Fair 1:2:3:4:5 Unfair Understandable 1:2:3:4:5 Confusing Satisfying 1:2:3:4:5 Unsatisfying
Figure 3. Posttest Group Problem-Solving Process Questions Of the 153 original subjects, 105 subjects completed the experiment and all of the questionnaires. Due to the unequal N for subjects and groups for each of the four conditions (Table 2) a “Type I Sum of Squares” analysis of variance is not appropriate (SAS Procedures Guide, 1988). A “Type III Sum of Squares General Linear Model (GLM)” analysis was determined to be the better statistical method for evaluating variance for hypothesis testing (SAS Procedures Guide, 1988). Subjects Completing the Experiment Asynchronous Face-toface CyberGroups=8 Groups=6 Collaboratory Subjects=31 Subjects=20 No CyberGroups=8 Groups=11 Collaboratory Subjects=23 Subjects=31
Table 2. N for Each Condition (Dyads were retained) Subjects are also nested within groups for this experiment. The group itself may be a source of error. Therefore, the GLM analysis of variance was first conducted to test group as an error term. If there was more than a 25% probability that group was not a significant source of error (a conservative criterion) group was dropped from the GLM model and the analysis was conducted again for hypothesis testing.
8. Findings
Figure 2. (Watson, 1987): Suggested Meeting Agenda Used by All Groups
7. Data Analysis The dependent variables were measured using Posttest, Task and Training questionnaires. The posttest questions regarding the group problem solving process are presented in Figure 3. These questions serve as the basis for testing the hypotheses presented here.
The asynchronous groups reported that the group problem solving process was more efficient than inefficient, more coordinated than uncoordinated, more fair than unfair, more understandable than confusing, and more satisfying than unsatisfying; although none of these findings were significant. The face-to-face groups reported that the problem solving process was more efficient, more coordinated, fairer, and more satisfying than the asynchronous groups (significant with means of 2.39 and 1.96, 2.35 and 1.94, 2.22 and 1.71, and 2.39 and 1.96 respectively). Hypotheses 2, 4, 6 and 10 are supported. CyberCollaboratory users reported that learning how to use the CyberCollaboratory in the asynchronous mode of communication was confusing. These subjects also
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reported the problem solving process was more confusing than those not supported by the CyberCollaboratory, significant with means of 2.12. and 1.72 respectively. However, group was a significant error term for this variable and for the variable satisfying/unsatisfying. Further exploration of these group effects is merited for future research.
8.1. Analysis of Variance The results of the analysis of variance using the GLM models are shown in Tables 3 through 7. The letters A or B next to the means indicate a statistically significant difference in the means. Hypotheses 1, 3, 5, 7,and 9 are not supported. These results may be due to the steep learning curve associated with using the CyberCollaboratory. In addition, the asynchronous training that was required by the geographical dispersion of the subjects, and the limited time for training may have contributed to the lower perceptions of the group problem solving process. Groups were only given 1 week of online, asynchronous training due to the class scheduling constraints of some of the participants. Furthermore, some of the comments found at the end of the posttest support the assumption that training and the steepness of the learning curve may have contributed to the lower satisfaction levels reported by the CyberCollaboratory supported groups for this experiment. For example: “Uploading was confusing – you link to different pages and begin to feel lost.” “Improve the instructions for idea organizer and the facilitator function.” Future research groups will be trained for two weeks or more. Additional training and experience using the system might serve to reduce the confusion reported by CyberCollaboratory students. Efficient (1) versus Inefficient (5) Face-toAsynchronous face Cyber2.36 2.35 Collaboratory No Cyber 2.44 1.71 Collaboratory 2.39 A 1.96 B GLM Test of Hypotheses (df=1, 104). Group was not a significant error term. Asynchronous: F=2.97, Pr>F =.09 CyberCollaboratory: F=1.84, Pr>F =.18 CyberCollaboratory* Asynchronous: F=2.13, Pr>F=.15
Table 3. Efficient/Inefficient
Coordinated (1) versus Uncoordinated (5) Asynchronous Face-to-face Cyber2.26 2.25 Collaboratory No Cyber2.48 1.74 Collaboratory 2.35 A 1.94 B GLM Test of Hypotheses TYPE III SS (df=1, 104). Group was not a significant error term. Asynchronous F=2.83, Pr>F =.10 CyberCollaboratory F=. 61, Pr>F =.44 CyberCollaboratory *Asynchronous F=2.33, Pr>F=.13
Table 4. Coordinated /Uncoordinated Fair (1) versus Unfair (5) Asynchronous Cyber Collaboratory No Cyber Collaboratory
2.30
1.51
2.22 A 1.71 B GLM Test of Hypotheses (df=1, 104), Group was not a significant error term. Asynchronous: F=3.60, Pr>F =.06 CyberCollaboratory: F=. 69, Pr>F =.41 CyberCollaboratory *Asynchronous: F=1.07, Pr>F=.31
Table 5. Fair/Unfair Understandable (1) versus Confusing (5) AsynchronFace-toous face Cyber2.12A 2.16 2.05 Collaboratory 1.72B No Cyber1.96 1.55 Collaboratory GLM Test of Hypotheses, Group was a significant error term. Asynchronous: (1,29), F=3.19, Pr>F =.37 CyberCollaboratory: (1,29) F=3.43, Pr>F =.15 CyberCollaboratory* Asynchronous: F=.63, Pr>F=.43
Table 6. Understandable/Confusing
8.2. Interaction Effects The asynchronous groups having CyberCollaboratory support and the face-to-face groups having no CyberCollaboratory support reported that the problem solving process was more efficient, coordinated, and fair than did the asynchronous groups with no CyberCollaboratory support and the face-toface groups with CyberCollaboratory support (Tables 8, 9, and 10). Both the asynchronous and face-to-face groups with CyberCollaboratory support found the problem solving process to be less understandable and
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2.16
Face-toface 2.00
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satisfying than did the asynchronous and face-to-face groups without CyberCollaboratory support (Tables 11 and 12). Satisfying (1) versus Unsatisfying (5) AsynchronFaceous toface Cyber2.31 2.36 2.25 Collaboratory A No Cyber1.89 2.26 1.61 Collaboratory B 2.39 A 1.96 B GLM Test of Hypotheses. Group is a significant error term. Asynchronous F=3.16, Pr>F =.08 CyberCollaboratory F=3.21, Pr>F =.08 CyberCollaboratory* F=.99, Pr>F=.32 Asynchronous
Table 7. Satisfying/Unsatisfying These findings may also indicate that the CyberCollaboratory has a steep learning curve and more effort is required to learn and to use the medium. The CyberCollaboratory may not be suitable for tasks of short duration (i.e. two weeks) for novice users as was the case in this study. Efficient (1) versus Inefficient (5) Asynchronous Face-to-face Cyber.18 -.18 Collaboratory No Cyber -.18 .18 Collaboratory
Table 8. Interaction Effects Efficient/Inefficient Coordinated (1) versus Uncoordinated (5) Asynchronous Face-to-face Cyber0.1825 -0.1825 Collaboratory No Cyber-0.1825 0.1825 Collaboratory
Table 9. Interaction Effects Coordinated /Uncoordinated Fair (1) versus Unfair (5) Asynchronous Face-to-face CyberCollaboratory No CyberCollaboratory
0.1575
-0.1575
-0.1575
0.1575
Understandable (1) versus Confusing (5) Asynchronous Face-to-face Cyber-0.075 -0.075 Collaboratory No Cyber0.075 0.075 Collaboratory
Table 11. Interaction Effects Understandable/Confusing Satisfying (1) versus Unsatisfying (5) Asynchronous Face-to-face Cyber-0.185 -0.185 Collaboratory No Cyber0.185 0.185 Collaboratory
Table 12. Interaction Effects Satisfying/Unsatisfying
9. Conclusion The groups assigned to the different conditions reported significant differences in perceptions of the group problem solving process. The face-to-face groups felt that the process was more efficient, coordinated, fair and satisfying. Those with CyberCollaboratory support thought the process was more confusing and less satisfying. Comments from the students suggest that the reason for these results may be insufficient training time combined with a short amount of time using the tools for a fairly simple group task. Interaction effects showed that both the asynchronous groups with CyberCollaboratory support and the baseline face-to-face groups found the problem solving process to be more efficient, coordinated, and fair than did the asynchronous groups without CyberCollaboratory support and face-to-face groups with CyberCollaboratory support. This research provided us with valuable feedback regarding the steep learning curve associated with using the CyberCollaboratory in the asynchronous mode of communication. A previous research pilot where a real world task of longer duration (one semester) [5] showed an initial steep learning curve followed by high to excellent levels of satisfaction with the system at the end of the semester. Real world tasks where students have the time to learn to use the system may be most suitable for the CyberCollaboratory. Using the CyberCollaboratory for tasks of longer duration and of more importance to the subjects may result in richer, more productive learning experiences for asynchronous groups performing collaborative tasks.
Table 10. Interaction Effects Fair/Unfair
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