Patterns of Media Use in an Activity-Centric Collaborative ... - CiteSeerX

Patterns of Media Use in an Activity-Centric Collaborative Environment David R Millen, Michael J. Muller, Werner Geyer, Eric Wilcox, and Beth Brownholtz IBM T.J. Watson Research One Rogers Street. Cambridge, MA 02142 {michael_muller, werner.geyer, beth_brownholtz, eric_wilcox, david_r_millen}@us.ibm.com +1-617-693-7490 ABSTRACT This paper describes a new collaboration technology that is based on the support of lightweight, informally structured, opportunistic activities featuring heterogeneous threads of shared items with dynamic membership. We introduce our design concepts, and we provide a detailed analysis of user behavior during a five month field study. We present the patterns of media use that we observed, using a variety of analytical methods including thread clustering and analysis. Major findings include four patterns of media use: communicating, exchanging mixed objects, coordinating, (e.g., of status reports), and semi-archival filing. We observed differential use of various media including highly variable use of chats and surprisingly informal uses of files. We discuss the implications for the design of mixed media collaborative tools to support the work activities of small to medium sized work teams.

centric collaboration when they work with a collection of shared items (documents or other objects) that are organized into recognizable structures, optionally with awareness, presence, and notification services about persons, their actions, and recent changes to those shared items. We explored this concept through a research prototype called ActivityExplorer [6, 7, 15], which emphasized sharing at the level of individual items and also at the level of collections of items (activity threads, Figure 1). Unlike previous studies of structured collections of email messages [1, 4, 5, 12, 19, 20] and other types of documents [11, 18, 23, 25, 32], we included synchronous communication artifacts (such as chats and shared screens), and we provided support for fine-tuning of membership on both new and existing documents.

Categories and Subject Descriptors H.5.3 [Group and Organizational Interfaces]: collaborative computing, computer-supported cooperative work, theory and models.

General Terms Performance, Design, Experimentation, Human Factors.

Keywords CSCW, Computer-mediated communication, Activity-centric collaboration, synchronous/asynchronous collaboration,. User study

Figure 1. An Activity Thread including four of the six types of documents

1. INTRODUCTION This paper continues a research program on activity-centric collaboration. In our definition, people engage in activity-

Previous reports on ActivityExplorer focused on architectures for activity-centric collaboration [7] and on an initial examination of how a community of 33 researchers used ActivityExplorer during the first 100 days of operation [15]. This paper uses new data to develop new analyses of activity-centric collaboration in an enhanced prototype: • Five months of usage data

Paper at CHI 2005, Portland OR USA, April 2005.

• Data include additional attributes, such as rich history of accesses and modifications (the 100-day dataset included only the most recent access)

• Analyses focus on media choice of item types (we use the term “media” here to refer to communication channels – e.g., [9]).

2. Background We began this research program to address a gap in existing collaborative environments (see Figure 2). Ad hoc collaboration systems, such as email and chat, are lightweight and flexible. They provide good support for short-term, dynamic communication needs. However, collaborative activities which extend over longer periods of time, or over larger numbers of participants, are notoriously difficult to conduct over email or chat. Discussion databases and structured workspaces are more appropriate to the larger-scale collaborations, but they are difficult to set up. It is particularly difficult to begin with an informal collaboration (e.g., in a chat), and then extend that collaboration to a somewhat larger membership (perhaps in email), and then to extend that collaboration again into a more formal, large-scale environment (a discussion database or a workspace). A second problem is that most collaborative environments support one or at most two types of documents as “first Ad hoc communication (email/IM)

Activity-centric collaboration

P

Formal collaboration (shared workspaces)

P

P

P

P

P

P

P P

P

P P

P P

P

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P P

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2.1 ActivityExplorer ActivityExplorer (AE) is a prototype client that manages multiple types of shared items (we will use the word “item” for any type of document or other shared object) in an environment featuring structured collections of items, synchronous and asynchronous sharing of items, presence (awareness of members’ online status), access control at the level of items or item collections, item status (whether an item is currently being accessed by one or more members), and notifications of selected actions by other members. Members use ActivityExplorer to organize items into one or more item collections, called activity threads (Figure 1). Each person is likely to be a member of more than one activity thread, and therefore AE also provides a list view of all activity threads to which the member has access permission. This list view may optionally show all items in all threads to which the member has access privileges, in which case the list shares some attributes of the multipleobject email-centric view of the Thrasks research program [1, 4, 5]; see also [11].1

P

P P

P

P

environments are restricted to either asynchronous sharing (shared file systems, discussion databases, email) or synchronous sharing (online meetings, chats). There is a trend toward providing both shared asynchronous stores and shared synchronous experiences (e.g., [8]).

P P

Figure2: From ad hoc communication to formal collaboration

class objects.” For example, most instant messaging environments support text (first class object) and a few graphic indicators, and perhaps URLs (second class object); email supports text (first class) plus attachments or URLs (second class); discussion databases support text (first class) plus attachments or URLs; and so on. Logically, a complex activity may contain diverse resources, such as simple text, formatted text, spreadsheets, graphics, and executable modules, but these diverse documents are either (a) spread across a number of specialized repositories, or (b) attached to a smaller number of first class objects such as texts (email messages, discussion database entries). This diversity of shared resources means that people must monitor and participate in multiple shared venues, dividing their attention and their effort across multiple storage media and multiple communication/notification paradigms. Even if they are successful in this divided attention and context management task, they face difficulties in choosing which medium to use for any new collaborative activity. A third problem, the scope and dynamism of sharing, is derived from the other two problems. Most shared

Each activity thread contains one or more items in a tree structure (Figure 1). Any item may serve as either parent or child in the tree structure. Items may be created by any of several simple operations: creating a new activity thread, including its root item; creating a child item to an existing item in a thread; dragging a document (including an email message) from outside of AE into AE, and dropping the document on the name of a person with whom it is to be shared. Items may be rearranged in the tree, or into other trees (different activity threads), as people’s needs change. Each item has a list of members, who are the people who have access permissions on that document. A user may create an item as the child of the current item, in which case the default is for the child to inherit the membership of the parent item. Membership may also be edited manually for each item, or for an item and all of its child items (i.e., from the branch “out” to all of its leaves), or for the entire activity thread in which the item occurs. In the research prototype, all members have equivalent status and permissions (we recognize that a production version of this concept may require more defined roles for members). In

1

For a detailed differentiation of AE from these and other related research programs, see [15].

keeping with conventional security approaches, people are unable to see items of which they are not members.2 The current version of ActivityExplorer supports six item types: messages (similar to email), files (formatted documents prepared with specialized tools, such as word processors), persistent chats, tasks (action items with externally visible completed/non-completed status), screenshares (including graphical annotations), and folders. Each type of item appears as a first class object in the activity thread, as shown in Figure 1. Users may easily find an item by its name, instead of searching for a message that contains or references the item. Future versions of ActivityExplorer are likely to support search across diverse item types. In summary, ActivityExplorer was designed to address the three problems that we described in the beginning of this “Background” section. ActivityExplorer allows collaboration to begin in an hoc manner, by sharing a single item with selected other members, and then adding diverse items and additional members as needed. Structured collections of items (activity threads) may remain informal, or may grow to have a well-developed formal structure of topics and subtopics, containers and contents (i.e., parent-child tree structure). ActivityExplorer is also inclusive with regard to item types, supporting shared work in the diverse forms of “first class objects,” comprising synchronous or asynchronous text and graphics, as well as more specialized task-oriented item types (e.g., task/to-do items). ActivityExplorer addresses the question of scope and dynamism with shared views of synchronous or asynchronous item types, allowing collaboration to be conducted as object-centric sharing (in effect, turning each item into a “meeting place” when needed) or as collection-centric sharing (similar to conventional shared file systems or folder). Finally, ActivityExplorer supports all of these forms of sharing with a rich set of presence and awareness services at the level of persons and of documents, including a welldeveloped set of alarms and notifications.3

2.2 Key Research Questions We hope to answer the following three questions in this investigation: 2

3

If a member has access to a parent document, but not to its children, then the children are invisible to the member. A more interesting case occurs when a member has access to a child document, but not to its parent: In that case, the parent is indicated as a blank document, without any data or metadata. This approach allows, for example, a member of an activity to request a consultation from an expert who is not a member of the activity: The expert has access to only those documents in the activity that the member chooses to expose to the expert. For a fuller description and evaluation of these presence, awareness, and notification features, see [15].

• Clustering of media types. Are there patterns of media use in the activity threads that develop in AE? Are some threads filled more often with synchronous interaction artifacts (chat transcripts or screen sharing traces) or asynchronous items (files and messages) or a frequent combination of media types? • Social usage of media types. Are media types used in different ways? For example, are some media types used for more private (less public) interaction, with limited membership lists? Are some media types used more often to launch or initiate more extended interactions? Are some media types referred to more often? Are some media types visibly less archival? • Individual differences. Can we observe individual differences in the use of various media types in AE? Are some interaction pairs more likely to use chat, while others combinations of participants share files and messages?

3. Research Methods The AE experimental prototype was used by a group of 33 people (14 interns and their mentors, and other researchers) during the summer of 2003. At the beginning of the field study, we requested intern-mentor pairs to learn about and use AE as a tool to prepare for their initial project poster in the beginning of their internship. We also invited all of the trial participants to use the AE tool for other work activities during the remainder of the summer. Other common collaboration tools (e.g. email and chat) were also available for use by all of the trial participants. To get a sense of the sustained use of the AE tool, we looked at the period 1 April through 2 September, 2003 (which contains two additional months of usage beyond our earlier report [15]), with enhanced usage data during those 60 days. Our understanding of the use of the AE tool was informed by several sources of data. Most of the analyses reported here are based on two kinds of server logs. . The first log covered the entire trial period and provided a complete view of all activities by all of the users. The server “item log” described each item in each activity thread in terms of the following data attributes: name/subject of object, thread in which the object occurred; member(s) of the object (i.e., most objects were shared, but some were private); creation (author, date, time); most recent modification (author, date, time); and most recent reading of the object (reader, date, time). The second log file that we analyzed was a user level “action log.” in which 14 specific user actions (e.g., create, read, delete, or add a new member) were logged. For each action, the following data were captured in the log: date/time, item number, activity thread, and the user’s ID. Our understanding of the use and usefulness of the AE tool was based on several sources of data. We interviewed

4. Results 4.1 Work Done with AE As we noted above, users of AE include 14 intern-mentor pairs, as well as five other researchers. Interns and their mentors engaged primarily in project work – either developing features on research prototypes, or conducting behavioral research. In fact, the first “assignment” from our team to the interns and mentors was the preparation of research prospectus of each intern’s planned research during the summer (these presentations were called “boasters”). The intern-mentor work was thus a combination of technical content and coaching on how to fit the interns’ work into the overall work of the organization. We expected to see relatively “tight,” two-person interaction histories with a duration of about a week for the interns’ “boaster” planning activities. In practice, mentors and interns invited others to join their discussions, with the result that most interns had both an official mentor and several other research staff members who provided mentorlike advice and contributions. In some cases, the intern’s work became the focus of a series of interactions in AE that went on for several weeks, and that involved as many as four additional staff members; in other cases, several interns collaborated together on the same topic. In this way, interns’ research work became more like conventional project work in our research organization. The interactions described above were relatively technical and goal-oriented. In addition to these interactions, interns self-organized about twenty very long series of interactions, on topics such as “Intern Tips and Tricks” or “Photo Directory.” Contrary to our expectations, these interactions tended to go on for a month or two, and to involve more than thirty members. Finally, the AE project team also used AE to coordinate our work, and to write reports and conference papers based

on that work. At least one other team also used AE for this kind of reporting purpose. In summary, people used AE for a variety of purposes, over a variety of different time intervals, with widelyvarying numbers of members. Some of this work had the specific purpose of mentor-to-intern advising, but much of this work was more like the conventional project work that happens in any research or product organization; moreover, the advising work and the conventional work tended to blur into one another. For further information on these phenomena, see [15].

4.2 Activity Threads In our analyses of these diverse phenomena (see [7, 15]), we defined an activity thread as a collection of related and shared objects that have been explicitly combined by the participants into a tree structure. This structure is created by the participants’ ongoing conversation, i.e., each item added (or appended) to an existing item is considered a “reply” to the previous one. During the field trial, 150 activity threads were created that contained from two to 213 items (median = 4), and that contained a total of 2062 items, created by a community of 33 members. Activity threads that contained only a single item are arguably not threads by some definitions, and we will consider their use separately. The intended audience (or participant list) for an activity thread is defined by the collective membership lists for each of the items in the thread. For many activity threads, the same membership list was used for each of the items (45% of all activity threads). Figure 3 shows all of the activity threads, highlighting the number of items and the number of members. 1000 Number of items in activity thread

seven of the 14 interns about their experiences with AE. Interviews covered several broad topics (beginning to use AE, intern-mentor work, collaborating with other interns, responding to notifications), but were deliberately openended to allow opportunistic story-telling and collection of interesting items or item sequences. These interviews were conducted by one member of the team, and took place in each intern’s work area. Interns could illustrate their points by bringing up a particular activity thread or object on the screen, or by showing a resulting paper artifact. A second source of data was a qualitative analysis of the meta data associated with each AE item. This included analysis of the subject, author and members names, and the media type of the items. The contents of specific items were not analyzed in order to protect the privacy of the trial participants. And finally, our understanding of the AE use was informed through participant observation of the authors.

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Number of Members (max)

Figure 3. Activity threads as a function of number of members and number of items; the size of each bubble shows the relative number of activity threads at each coordinate.

There were a number of threads that contained large numbers of items, large membership lists, or both. Examples of activity threads with a large number of members and a relatively small number of items would be

announcements (“Patch your desktop machines”, “Project Code meeting”) and various short help items (“Eclipse tips and tricks” and “Boaster guidelines”). Examples of longer threads with a large number of members (upper right in figure 3) would be: a group-wide FAQ discussion for the AE tool, an Eclipse tutorial discussion, and an organization-wide “Who’s who photo book”. And finally, we found examples of activity threads that were shared among a small group and that contained a large number of items (upper left in Figure 3). These included: a long set of messages and task items for a small software development team, the collaboration efforts of a small group of authors writing a professional paper, and a small group discussing plans for empirical study of a research prototype.

(a)

4.3 Clustering by media types We begin to answer our first research question (see section 2.2, above) by noting that the Activity Explorer application was designed to support work activities using any combination of media types. It was possible that activity threads would be created using familiar media groupings. Several plausible activity patterns are shown in Figure 4. Figure 4a shows a thread made up mostly of messages, with an occasionally associated file (e.g., attachments). This is a common pattern in email interactions. Figure 4b show a kind of thread often found in document databases (e.g., Notes discussion databases). There are a large number of documents which often include presentations, spreadsheets, etc. And finally, Figure 4c, shows an activity thread filled with many task documents. As with other media [10, 24], we naturally expected some kinds of patterns of media use to develop over time. To better see the patterns of media use, we performed a cluster analysis (K-means) of the activity threads. We normalized the thread data by computing the percentage of each activity type for each activity thread, and then clustered the threads by media types. The resulting cluster solution, shown in Table 1, shows the average percentage of item type for each of four easily interpretable clusters. The largest cluster (which contained almost half of all activity threads), was comprised mostly of message objects. These kinds of activity threads would be conceptually similar to most email or discussion group threads and so we have labeled this cluster communication. Most of these communication activity threads were short; 85% of these threads contained 10 or fewer contributions.

(b)

(c) Figure 4 (a-c). Conceptual patterns of activity threads.

Communication Chat File Folder Message Screen Task N

3% 5% 3% 85% 3% 0% 74

Clusters Mixed Coordi nation

43% 15% 2% 22% 16% 1% 30

5% 8% 9% 29% 3% 47% 12

Archival

3% 61% 4% 29% 3% 0% 34

Table 1. Clusters of activity threads, with percentage of each item type occurring in each cluster.

A second cluster has been named “mixed,” because it contains a significant number of synchronous contributions (chat and screen sharing transcripts), as well as both files and messages. Almost all of the mixed activity threads are short (28 of 30 contain fewer than 10 items). These mixed threads also seem to be good examples of the kinds of informal interactions that grew into longer conversations. Thirteen of these threads began with chats and five began with a screen sharing session. An example of a mixed activity thread would be: 1) meeting planning and preparation that began as a chat and included messages and slide deck files and 2) a mixed media conversation that focused on laptop configurations for the “Internfest” presentations.

type. The distribution of item membership, for the types of items supported in AE is shown in Table 2.

The third kind of activity patterns contained more task objects than the other patterns did, and consequently appeared to be more task coordination oriented. In these coordination activity threads, task forms were used most often, followed by message items. These kinds of activity threads were often used by small groups of software developers and used to informally manage code development.

Table 2. Size of item membership (audience) as a function of item type.

The final activity pattern was used to collect and share files among group members. The archival activity pattern is made up mostly of files (61%) and messages (29%). A significant number of files activity threads (41%) were relatively long and contained more than 10 items. An example of this kind of activity thread would be: a meeting preparation thread in which a number of drafts of the presentation files and handout documents were shared between collaborators or a large shared document collection of research literature used in preparation for a new project. A second example is the 55-item preparation of a conference paper submission, as well as other reports and presentations.

4.4 Social uses of media types 4.4.1 Number of members Our second research question requires examination of how people used different object types to initiate and to sustain their shared activities. Many collaborative environments are designed to support interaction among a common group of participants. The AE tool allows the access list for each item to be defined on an item–by-item basis at the time that the item is created.4 We were a little surprised to observe differences in the number of members that were associated with various media types. Note that it is possible that the choice of item type influenced the number of readers invited to read the item, or conversely the intended audience influenced the selection of a particular media 4

By default, a child item inherits the membership list of its parent; however, any member of the item can change the membership list during or after creation of the item.

Item type message file chat task Folder screen Total

n 1166 518 120 110 90 58 2062

# of members (invited readers) 10 63% 37% 83% 17% 97% 3% 85% 15% 88% 12% 88% 12% 73% 27%

Most chats are limited to a small membership (< 10 members). There are at least two explanations for this. One is that chat conversations are inherently less formal and more private, and are thus likely to be shared only with partners in relatively tight social relationships [9]. The content may be useful as “articulation objects,” (e.g., [2, 21, 22, 26]) moving the work activity forward via points of coordination, in this case by providing conversational scaffolding of those points of coordination. Indeed, the authors of a chat may not desire a larger audience for more ephemeral conversations about work. A second explanation for the small memberships in chat is that the activity explorer tool was in some way biased to encourage less sharing of chat items. The chat creation interface defaults to two-person chats. This would result in the creation of a two-person membership list.

4.4.2 Singleton interactions While we have focused the analysis thus far on activity threads (interaction collections with more than a single item), there were a significant number of interactions that consisted of a single item. The distribution of these items, across media type, can be seen in Table 3. One surprise is that a considerable majority of these items are chat transcripts. Furthermore, these chat orphans are then also frequently deleted. This suggests that chats may often be used for discussions that are sensitive or very private. While we envisioned informal chats frequently spawning longer activities, it appears that they were often held as isolated conversations. We assume that the higher rate of deleted chats indicates that the nature of the interaction was considered to be less archival for some reason. It is possible that the chat transcripts were so informal or private that a permanent record was undesirable. Further, 10 of the 18 chat transcripts that were deleted were quite short (fewer than 10 turns) and 70% were left unlabeled.

chat collection file message screen task Total

Singletons n % 146 70% 3 1% 17 8% 34 16% 7 3% 3 1% 210 100%

# deleted n 18 3 6 6 3 1 37

Table 3. Singleton threads (length = 1).

4.5 Individual differences in media use The final analyses presented here will show that the pattern of media use was not consistent across all individuals in the trial. We counted the number of time participants in the trial contributed to activity threads for each of the four activity thread cluster types (described above). The distribution of participation for the 10 most frequent participants in the trial can be seen in Table 4. Comm

Mixed

Coord.

Archival

attributed to recording, tracking and reporting on software bugs/changes for the project. Three members of the trial (DL, UC, XE) participated most often in archival threads. One participant was the intern coordinator for the summer. He used archival threads to share photographs taken during the summer. One grouping of photos helped create a sense of local community by sharing informal snapshots taken at social events (e.g., afternoon tea), while a second group contained snapshots taken on a mini research expo event. The other two frequent participants in archival threads were user interface designers and they shared a large number of graphic files. In half of the cases, the patterns of media use reflected specific characteristics of the work task or job role. The software engineers participated in a high percentage of coordination threads as they jointly work on a project. The intern coordinator and graphic/User interface designers shared a higher percentage of file items. These results suggest that there may be patterns of media use for a wider selection of work processes and specialized job roles. We will take this topic up again in sections 5 and 6.

Total

5. Discussion

items

The results of the field trial in this paper describe in considerable detail the usage patterns for a small group of mentors, interns and researchers for a period of five months. The restricted sample, the somewhat specialized nature of the work done in this organization (i.e. software research), and the length of the trial prevents immediate and widespread generalization from the results we observed. A large-scale technology trial is underway and we will be able to study the long-term use with larger and more varied samples of AE tool users.

HW

30%

6%

25%

39%

396

DL

49%

1%

6%

43%

357

LE

86%

2%

1%

10%

166

CB

34%

17%

37%

12%

155

NM

61%

-

19%

21%

117

EK

79%

4%

10%

7%

98

NS

76%

6%

-

19%

90

DB

95%

2%

-

2%

88

UC

14%

5%

-

81%

83

XE

16%

-

3%

81%

64

Table 4. AE participation in each of the activity clusters for most active participants.

Five of the top ten participants contributed most frequently to communications threads, which is not very surprising, as most of these participants were quite experienced users of online collaboration tools including forums and discussion databases. Two of the participants (HW and CB) were substantial participants in coordination threads. As you may recall, these kinds of threads are comprised of a large percentage of “task” items. These two participants were co-developers in a software development project, and adopted use of task items to coordinate their work. Analysis of the activity threads reveal that much of this interaction can be

Nevertheless, we would argue that the results of the trial reported here are an important contribution to our understanding of the nature of the interaction and tool use in a richer and more integrated collaborative environment. It is clear that the AE trial allowed us to study a very interesting range of mediated interaction from short interactions among a couple of people, to a longer multiitem conversation among a large group of workers. The patterns of media use that we observed using a cluster analysis of the activity threads shows clearly that the AE tool supports a variety of working styles and covers a range of work activity structures. Some interaction patterns follow the more typical conversation pattern (e.g., the communication pattern), while others are more centered on a collection of files (the archival pattern). Closer investigation of the archival pattern shows a number of distinct work activities supported. As noted above, at least one file collection consisted of photo image files, used to capture meeting highlights and to create a photo directory of interns and mentors. Other file collections were used to pass presentation slide files among team members working

collaboratively on a presentation. Yet another file collection served as a shared document repository to allow a team to create a common understanding of important parts of prior art related to an invention disclosure. The coordination pattern suggests to us that there may be a need for additional support of more structured forms of collaboration. The mix of messages and task forms reveals a form of activity management or informal workflow. We have begun to think about additional item types and item interrelationships that could support formal and informal work processes. The mixed collection pattern is perhaps the most interesting. We had hypothesized [15] that many of the current collaborative tools are somewhat restrictive in the kinds of collaborative interaction that were possible, because of the small number of media choice available for the interaction. Indeed, as we reported in [15], people chose to combine heterogeneous objects into threads in 81% of the threads of length 2 or more (i.e., threads of length=1 could not, by definition, contain heterogeneous objects, because they contained only one object), and the modal number of types of object per thread was three. In this report, we extend our initial finding of widespread use of heterogeneous objects, with our more detailed examination of the mixed pattern of threads. The mixed pattern of use supports our view that participants in a collaborative work activity will often use a mix of media types, some less formal (e.g., chat), some highly visual (e.g., screen sharing), along with some mix of more traditional messages and files. Research into how people collect documents to support large-scale activities has shown similar patterns of combination of files, messages, and task assignments [1, 5, 11, 13, 32]. Much of what we learned about specific user behaviors centered on chat conversations. We were surprised to find chat conversations were not used more often to begin longer activity threads – despite the fact that people reported using the information in chats as many as five days (mean) after the last new contribution to the chat.. We were also a bit surprised that chats remained shared among only a small group of people, despite the support for sharing of persistent chats inherent in the AE tool. Furthermore, chats were the single largest group of singleton interactions (i.e. a “singleton interaction” is a thread consisting of a single root item, with no children) and were often deleted from the persistent store by their members. One reasonable explanation is that, while some chats have persistent value, many other chats may be used for small groups, or subsets of larger groups, to coordinate work activities. The chat behavior we observed also suggests that many chat discussions are more personal or private. The patterns of interaction reveal individual variation in the use of various media support by the AE tool. These

differences can be explained in several ways. A role-based assignment (i.e., intern coordinator) resulted in a distinctive central communicative mode, with a high degree of file sharing. Interest in a common activity (i.e, development of a particular software application) resulted in a distinctive pattern of sharing of task items. And finally, individual communication preferences may explain the differences observed in message and chat frequencies among trial participants.

6. Implications for Design The original design intent for the AE tool was to provide a collaborative environment that supported a mix of different communication media. The specific design supported varied media types in general and in a reasonably consistent manner, and may easily be extended to include other types of media. However, rather than thinking in terms of specific media, we are considering different approaches to the next steps with AE.

6.1 Enhancing ActivityExplorer Based on our understanding of AE use, it may be desirable to think about designing for patterns of use. The communication collection pattern that we observed resembles other shared messaging environments, and there may be a natural set of tool enhancements to be added, for example, indexing and searching capabilities that are common in messaging forum tools, would no doubt add high value for that pattern. The archival collection pattern is similar to other content collections, and would benefit from incorporating some of the interaction features of those systems. For example, version control for document collections is an important design challenge and one that will need to be included in future mixed-media collaborative environments. Innovative visualization and interaction methods for large document collections such as [14, 17, 27, 29, 30, 31] may also be useful for supporting version tracking and mapping various social views onto shared documents.

6.2 Improving task/activity management The coordination pattern presents the challenge of better managing informal workflow or semi-structured activities. While examples of task management have been tried for email [1, 4, 5, 28], attention has only recently been paid to informal workflow in ad-hoc collaborative environments. Some early design ideas to support collaboration and workflow in collaborative development environments is underway [3]. A more formal and complete theory of activity management may provide design guidance for support of informal workflow [13]. This theory may, in turn, help us to understand how to highlight certain “landmark” tasks or activities that can serve as coordination points for their members [16].

Across the four types of collection patterns, we have seen what might be called “higher-order patterns” in which a group of people tend to be members of a shared set of multiple activity threads (or a collection of item collections). It may be useful to provide a view of activities in common with one or more other members [13]. This concept leads us to reconsider the value of helping users to visualize patterns of sharing in user interfaces [16].

6.3 Support for Genres of Collaboration Finally, our examination of individual differences in the use of activity patterns of AE usage tells us again that people use AE in diverse but recognizable ways. Conventional work in HCI and CSCW has often associated medium (e.g., chat vs. discussion database) with activity pattern (e.g., informal exchange vs. formal discussion, respectively). Our results suggest the need for higher-order genres of media to support genres of activity patterns that transcend individual media types (e.g., communication pattern vs. archival pattern).

7. Conclusion Our work with ActivityExplorer has investigated both new technologies for collaboration, and new adaptations that people have made of the technologies to support their ongoing work. Through this work, we have observed and evaluated the use of diverse media in collaboration, and – more significantly – we have begun to understand how people make use of those diverse media together when their collaborative environment allows them easily to share heterogeneous item types and collaborative styles with one another. We have also begun to use social network diagrams as visualization aids to understand how collaborators make differential use of various media. These observations and evaluations help us envision the design of new functionalities in ActivityExplorer and other collaborative experiments, as well as inform the design of products to support people’s collaborations in organizations.

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