e-LEARNING DESIGN 2.0: EMERGENCE, CONNECTED NETWORKS AND THE CREATION OF SHARED KNOWLEDGE by Colleen M. Carmean

ROD SIMS, Ph.D., Faculty Mentor and Chair ELENA KAYS, Ph.D., Committee Member PATRICIA McGEE, Ph.D., Committee Member

Harry McLenighan, Ed.D., Dean, School of Education

A Dissertation Presented in Partial Fulfillment Of the Requirements for the Degree Doctor of Philosophy

Capella University June 2008

© Colleen Carmean, 2008

Abstract This research study explored design practices that support emergent e-learners in creating and sharing digital, networked knowledge. Using a conceptual framework that modeled use of the technologies and emergent practices under investigation, this study used Web 2.0 tools and connected networks in exploring effective practice. A social network analysis (SNA) of the Blogosphere community was done in phase 1 to locate globally trusted experts regarding e-learning and networked knowledge. Collective inquiry between these bloggers was then used in phase 2 to create new understanding of digital, shared knowledge environments. Participants explored ideas and best practices via open-ended electronic survey questions, which were then summarized and confirmed via a collective Wiki. Summary tag clouds were produced on each question to help the researcher and participants better visualize consensus in the responses. A qualitative summary of findings indicated the importance of support for trust, social software, independent and just-in-time discovery, and connected networks of learners. The study concluded that the how to of connection, shared knowledge, and collaboration will become radically richer and more innovative with the adoption of Web 2.0 tools and technologies. The challenge will be in making shared knowledge tools and practices better understood, incorporated and supported throughout the organization. This study proposes the need for a new design practice of shared knowledge architecture that offers a more integrated and dynamic learning environment, embedded in the information worker’s daily workflow.

Dedication My deepest gratitude goes to friends and loved ones who stayed supportive when I seemed to drop off the face of the earth during the doctoral years. Thank you to my beloved, Bill Keenley, who was (mostly) understanding and sacrificing of his own needs and to Alida and Julia Baranowski, although I was so seldom there when you needed me.

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Acknowledgements If I have seen a little further it is by standing on the shoulders of Giants. -Sir Isaac Newton So many gracious and great minds have contributed to my understanding. First, for the hard work and faith of my dissertation committee: Rod Sims, my patient committee chair; Elena Kays, whose inspirational thinking led me into the research topic; and Patricia McGee, the most generous colleague, friend, advocate and sounding board that a doctoral student could find. Along the way, many scholars were guides on the path: Dr. Carole Barone, whose support at EDUCAUSE helped me see myself as a scholar; Dr. Gary Brown, who taught me to love assessment; Dr. Alice Christie, fearless in her advocacy of learner independence; Dr. Cari Spring, lifelong friend who encouraged language, passion and precision; Dr. Ellen Wagner, inspiration to women in the field; Dr. Michael Williams at Capella University’s School of Business and Technology, who helped simply because he loves research design; and Dr. Ali Jafari – colleague, friend and the smartest man I know. A thank you also goes to Dr. Larry Johnson at the New Media Consortium (NMC) for graciously hosting the project Wiki at the Horizon Project. My amazed thanks to the study participants who gave generously of their knowledge: Nirmala "Nimmy" Bangalore, Shawn Callahan, Stephen Downes, Lilia Efimova, Peter-Anthony Glick, Denham Grey, Harold Jarche, Tony Karrer, Alan Levine, Jim McGee, Clive Shepherd, George Siemens, Ray Sims, David Snowden, Luis Suarez, and Jack Vinson. My research design hunch was that the best bloggers are generous with knowledge and these very busy people surpassed all expectations.

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Table of Contents Acknowledgements

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List of Figures

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CHAPTER 1. INTRODUCTION

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Statement of the Problem: Design for Emergent learning

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Background of the Study

3

Purpose of the Study

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Research Questions

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Significance of the Study

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Definition of Terms

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Assumptions and Limitations

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Relationship of the Study to Researcher Experience

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Conceptual Framework for the Research

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Organization of the Study

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CHAPTER 2. LITERATURE REVIEW

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The Shift to Shared Knowledge

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Emergence Theory

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Characteristics of Emergent learning

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ORGANIZATIONAL LEARNING

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Knowledge Management

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Social Knowledge

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New Technologies for Organizing Knowledge

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The Role of Instructional Systems Design

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Conclusion

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CHAPTER 3. METHODOLOGY

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Research Design

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Phase 1: Social Network Analysis

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Phase 2: Collaborative Knowledge Design

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Confidentiality

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Reliability and Validity

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Generalizability

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Purpose of the Research

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CHAPTER 4. DATA ANALYSIS AND RESULTS

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Phase 1: Social Network Analysis

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Phase 2: Collaborative Knowledge Creation

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Summary of the Data

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CHAPTER 5. RESULTS, CONCLUSIONS AND RECOMMENDATIONS

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Overview of the Research

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Limitations of the Study

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Conclusions and Implications

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Creating a Shared Knowledge Architecture

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Recommendations for Future Research

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REFERENCES

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APPENDIX A. FLOW OF THE DATA COLLECTION

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APPENDIX B. REQUEST TO PARTICIPATE

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APPENDIX C. INFORMED CONSENT

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APPENDIX D. PARTICIPANT SURVEY

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APPENDIX E. WIKI RESULTS ON SHARED FINDINGS

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APPENDIX F. LIST OF PARTICIPANTS

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List of Figures

Figure 1. SNA of initial study data (623 nodes)

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Figure 2. SNA first pass on centrality (623 nodes)

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Figure 3. SNA of initial data plus blog rolls of central nodes (881 nodes)

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Figure 4. SNA K-Core analysis of URLs with 2+ connections (112 Nodes)

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Figure 5. SNA K-Core for 4+ connections (33 Nodes)

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Figure 6. SNA Node labels for 3+ incoming ties (24 Nodes)

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Figure 7. Tag Cloud for Survey Question 1 Responses

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Figure 8. Tag Cloud for Survey Question 2 Responses

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Figure 9. Tag Cloud for Survey Question 3 Responses

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Figure 10. Tag Cloud for Survey Question 4 Responses

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Figure 11. Tag Cloud for Survey Question 5 Responses

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Figure 12. Tag Cloud for Survey Question 6 Responses

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CHAPTER 1. INTRODUCTION Emergent, persistent, self-paced, accessible and immediate: the Internet and highspeed connectivity have changed workplace learning as much as much as they have changed the workplace itself (Lankshear, 2003; Siemens, 2005). The digital work environment now provides the possibility of high-speed, flexible access to as-needed resources, performance support, sounding boards and learning tools (Braun & Schmidt, 2006; E. Wagner, 2001). Technology enabled a change in the way we seek information and knowledge, but critics claim that support for tools, training and use has kept up with neither the demand nor the expectations of the learners (Grudin, 2006; McAfee, 2006; Quinn & Hagen, 2006; Sharma, 2003; Williamson & Iliopoulos, 2001). Workers no longer need to wait for information, training or instruction. Expectations of where we learn, when we learn and how we learn have shifted from the formal training and classroom environment to include an any time, connected network of resources (Siemens, 2006). Frank and Robin (2004) claimed that digital access, and the digital learner, changed the nature of knowledge itself. “In the connected world, experts are people who know where to find information, how to make sense of it and what to do with it" (p.42). Reports on workplace practices from government and the private sector concur (King, 2001; Pantazis, 2002) and stress the need for new environments that provide just-in-time support and allow workers to assume greater responsibility for their own, independent learning and skill development.

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Evidence suggests that the nature of learning itself has changed in the information age. In a study of 275 of industry's chief learning officers, McStravick's (2007) key findings were that, although training still accounted for 40% of the delivery mix, more strategic attention was needed on informal knowledge acquisition, including its measurement and alignment with work flow. Informal, as-needed, decentralized and personalized learning, enabled and shared through digital connectivity, is creating new, unstructured and unexpected emergent networks (Downes, 2005). Connecting and exploring resources through independent discovery, learners are defining a knowledge framework absent of control or guidance. A new decentralized, distributed, independent e-learning is driving organizational effectiveness and as-needed knowledge. Emergent learning: self-directed, just-in-time, distributed, digital, and connected to a larger network or community.

Statement of the Problem: Design for Emergent learning Enabled by increased digital access and connectivity, online learning networks create compelling new questions for design, support and assessment (Downes, 2006; Irlbeck, Kays, Jones, & Sims, 2006; Snowden, 2003b). As digitally connected learners turn toward just-in-time knowledge and resources, designers are being asked to rethink their practice and to discover new ways to support and capture learner-generated knowledge within the larger, connected learning network (McStravick, 2007). The problem for emergent learning design is in determining a practice that supports the needs of the just-in-time, independent learner while at the same time ensuring each learner’s contribution to the knowledge network.

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According to Norris, Mason and Lefrere (2004) the larger organization is successful only when all individuals have the skill, motivation and opportunity to independently and democratically participate in the use of the tools in place. Despite this need, research, evidence and consensus on design for distributed knowledge is limited. Challenges include the complexity of such an undertaking when it requires new technical and theoretical understanding of dynamic knowledge flow, e-learning and collaboration design (Nissen, 2005). A number of researchers (Hutchins, 1995; Kays, 2004; Irlbeck et al, 2006; Kays & Sims, 2006; Gunawardena et al, 2006) have claimed that such an endeavor would demand new and not yet understood roles and practices in design for elearning environments. Technology created problem and opportunity for organizational knowledge, but not the solution. Disk storage, collaboration tools and effective search logic now makes it technically possible to put all organizational knowledge online and to easily find the information needed (O'Reilly, 2005). Yet, tools alone have not created an effective learning environment. Missing is the application of theory and tools into successful practice. Research on how and where industry is now exploring and evaluating the tools, practices and processes of shared knowledge would allow for a better understanding of the requirements and practices of successful emergent learning design.

Background of the Study if instruction represents a form of delivery, and if we are beyond delivery, then we have reached a stage where we are beyond instruction (Sims, 2006 p.2)

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Information workers are now asked to learn, do, share, mix, combine and create new knowledge from a variety of media-rich Intranet and Internet material, but have often been left on their own to determine effective use of the tools, resources and material available (Kurtz & Snowden, 2003). This is especially true where needed information changes overnight, but an organizational understanding of dynamic knowledge and how to support just-in-time learning has not kept pace with the needs of the learners (Nissen, 2005). To make sense of changing information – to continuously gather, analyze, negotiate, synthesize and share complex data - is an expected outcome at all levels of the organization and yet a collective understanding of the framework (tools, processes, operational support and management) is missing (Allee, 2002). Building shared knowledge (or intellectual capital) within the organization includes creating a learning environment where individuals are supported and encouraged to build community, share expertise and recognize the experts that are everywhere in the organization (Allee, 2000). It is no longer feasible for a segment of the organization to package and disseminate what someone might later need to know. Siemens (2005) claimed that technology enables a new learning environment where the pipe itself is “more important than the content within the pipe” in creating new knowledge (Conclusion). In environments where information changes quickly, finding information when needed is now more valuable than knowing or learning just-in-case information (Rosenberg, 2001). Downes (2005) claimed that organizational knowledge practices have created a need for designers to take on a new workplace environment that supports grassroots, decentralized, social learning networks. He noted that this cannot be done without a better understanding of the social, collaborative tools and technology that

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make new learning ecologies possible. Similarly, Nardi and O’Day (2000) claimed that effective information ecology would also include support for context-specific habitats: environments that include not just the technology, but the people, practices and values inherent in use of knowledge technologies. Despite significant challenges identified in an accompanying movement from instruction to knowledge networks, Siemens (2005) noted that learner-centered environments will not be successful unless new connectivist models and design practices are created to make use of technology in the support of distributed, connected, just-intime, negotiated knowledge.

Purpose of the Study This research study sought to determine effective e-learning design practices that best support emergent learning and the creation of shared, organizational knowledge. The study investigated e-learning design practices that best align with emergent learning and the creation of organizational knowledge. The study explored practices, ideas and experiences related to fostering self-directed, just-in-time learning. Some believe that design challenges related to self-regulated e-learning can better be understood by looking to emergence theory (Downes, 2005; Johnson, 2001; Kays & Francis, 2004). By studying the process by which complex systems organize themselves from the bottom up and through independent decisions, these authors suggested we can best understand and support the current shift in the creation of knowledge through the self-organizing principles of emergence. Using this framework in the design of learning environments may better satisfy organizational knowledge as design focuses on needs and motivation at

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the individual level – and the effects of that level on the whole. In looking at new characteristics of online learning, Kays (2004) suggested that online learning demands a serious rethinking of traditional instructional design approaches. “Such models may not adapt well to the complexity and non-linearity that the new online environment involves, making it necessary for newer, more responsive models to be developed” (p. 5). Creating new emergent learning models could give designers a better opportunity to tap the “full potential of interaction and community networks” that are at the core of the new social and collaborative practices found in online, informal learning environments (Irlbeck et al., 2006, p. 171). Specifically, emergence-based design would offer a new lens for a pressing, new problem: creating a learning environment that supports and encourages persistent, individualized learning which contributes to organizational or community knowledge. Moving from Instructional Design to Learning Design Learning research has created a rich body of evidence that meaningful learning is an individualized experience created and negotiated by each learner (Bruner, 1990; Piaget, 1983; Vygotsky, 1986). In the digital workplace, technology and Internet connectivity has aptly enabled this individualized pursuit of knowledge but research is still needed on effective use, support and assessment of distributed, organizational and often just-in-time knowledge (Allee, 2002; Grudin, 2006; Pratt, 2006; Snowden, 2003b). A lack of awareness amongst learning designers is given by Stephenson (2003) for the adherence to traditional instruction paradigms and the lack of learner-initiated practices. The purpose of the study was to create an evidence-based framework for design of

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emergent learning environments that is “decentralized, distributed, disintermediated, disaggregated, disintegrated, democratic, dynamic and desegregated” (Downes, 2006). Design for new organizational knowledge environments must look past the old push models of delivering content and create pull environments for finding information within individualized, self-directed learning (J. S. Brown & Hagel, 2005). The challenge includes knowledge management that supports a change in “culture, behaviour, internal structures, interfaces to its environment and indeed its motivation to do so” (Williamson & Iliopoulos, 2001, pp. 37-38). Thus, design for emergent learning demands creation of environments that support just-in-time collaboration, contribution, and management of information that is available whenever and wherever needed. Effective design should also support use of the knowledge objects and processes used in daily work and should do so at the learner’s desktop (Allee, 2000). According to Brown (2000), designers entering this field will need a better understanding of the social aspects of the learning environment and of the tools that make it possible to capture and share tacit knowledge within the organization. Organizational effectiveness depends on making what is known available to those who need it, and in doing so "supports the creation, archiving, and sharing of valued information, expertise, and insight within and across communities of people and organizations" (Rosenberg, 2001, p. 66). Design that removes itself from the daily, shared information flow of the workplace can no longer meet the needs of the information economy. Exploring the Role of the Social Web Adding to the challenge of effective design within an emergent learning paradigm was an understanding of how knowledge acquisition is best supported by the social and

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collaborative technologies of the Internet. Due to the introduction of more interactive and social technologies, learners no longer simply retrieve needed information online (Alexander, 2006). They can now comment, combine, share, notate and collaboratively come to consensus on the information found. They can also personally rate, assess and evaluate information and contributions. (O'Reilly, 2005). Workplace collaboration technologies that allow for tracking resources, projects and people create new opportunities to make sense of information which is "complicated, complex and chaotic" (Snowden, 2003a, p. 13). Unfortunately, access and the tools alone are not enough. Implementation and use have been slow to produce consistent outcomes or accepted practices in new learning environments (Cross, 2006; Hodgins, 2000; Rosenberg, 2001). These new social technologies, often called Web 2.0, create great opportunity for participation and construction of shared knowledge (Grudin, 2006), but some claim they provide no guarantee of more effective, engaging, or collaborative knowledge-building environments (Lueg, 2001; Stahl, 2000). Effective use and participation in all needed parts of the organization is still a challenge to be addressed (Barnett, 2006; Grudin, 2006; McCafee, 2006) and the study looked to experts to share how they were addressing these challenges. Research has provided much insight in a short time regarding the value of participation and collaboration within e-learning environments (Palloff & Pratt, 2005), and it is evident that Web 2.0 technologies have provided new opportunities for elearning, collaboration and shared knowledge, but as Braun (Braun & Schmidt, 2006) stated “…this is only the first part of the story” (p.5) . The challenge in shared knowledge creation is still in the determination of practices and technology usage that would support

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effective participation within the vast array of tools now available (Hiltz & Turoff, 2002). Rasmussen (2002) stated that to successfully gather, organize and share knowledge, regardless of tools chosen, design support is required in the use of these new technologies. Therefore there is a need to better understand how design (choice of tools, practices, support and evaluation) could create a more effective emergent learning paradigm. Research Questions The guiding research question for this study focused on new practices and responsibilities in the design of emergent learning. By looking to current practice in the workplace, the study asked: What is the nature of learning design in an unstructured, justin-time, emergent learning environment? To address this question, several specific areas of inquiry were addressed: 1.

What are the inherent characteristics (tools, processes, practices, systems, support structures) of emergent learning environments?

2.

How might design foster collaboration and networking in emergent elearners?

3.

In what ways does emergent learning suggest new roles for design, instruction or performance improvement in the practice of organizational knowledge management?

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Significance of the Study Creating organizational knowledge is at the heart of effective business practice. The rapid deployment, but unrealized progress of social technologies within the organization adds to the urgency of understanding effective use in creating shared knowledge. Effective access, use, and participation across the enterprise would create a more complete, dynamic and consensual repository of organizational knowledge. Emergence theory tells us that together, each working independently, we are all collectively smarter than any of us alone. Traditional design and instructional practices do not recognize this idea in practice, focusing instead on the isolated performance and assessment of the individual. New understandings and practices in emergent learning design would provide for improved capture of knowledge, expertise and understanding within the organization.

Definition of Terms Tools of the participatory Web are introduced to the market on a rapidly accelerating basis, and this study can focus on but a few that are known to have garnered some success and support within the enterprise community. Current, broad tools of Web 2.0 that the study considers relevant to organizational knowledge creation include WeBlogs (Blogs), Wikis, shared and dynamic tagging of content (folksonomies), shared bookmarks (such as Furl and de.lic.ious sites), shared image repositories (such as flickr™), and collaboratively-owned documents (such as Google Docs™). Intranet shared project and file services are also of interest to the study’s focus on organizational knowledge management.

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For purposes of identifying expert contributions and leveraging enterprise knowledge, one social technology used in the methodology of the study is the WeBlog (or blog), as this easy-to-use technology has the ability to allow retrieval of contribution by ranking as well as exploration of comment, critique and linking to original source of posted information (Barnett, 2006; Grudin, 2006). A number of terms related to Web 2.0, especially in its role in organizational knowledge and social networks are defined below. Authentication: Key to most social software is the ability to manage permissions on creation, editing, commenting, etc. This is via authentication, or the management of user identification via accounts and passwords. Blog: shortened, popular term for WeBlog. Blogosphere: interlinked Web community of all Blogs. Emergent learning: Self-directed, individualized, informal learning that contributes to distributed knowledge within a larger organization or network. Informal learning – Seeking knowledge “just in time”, without classes, workshops, grades, attendance, or sequenced instruction. Knowledge management: a range of organizational practices and policies used to identify, create, represent, and distribute knowledge for reuse, awareness and learning across the organization. Learning environment: Although learners can create a learning environment from any situation (book, a hallway conversation, call to the Help Desk, IM a friend, Google or Wikipedia), for the purpose of this study, this would be an online environment designed to enhance a student's learning experience by including computers, software and the Internet in the learning process. Emergent learning environments currently in the

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workplace include tools for electronic communication (e-mail, threaded discussions, chat, collaborative documents, and editing tools); Web publishing; searchable file services; search engines and subject directories; user-determined tagging of data; and Internet links to outside resources. Learning organization: A term coined by Senge in the early 1990’s, a learning organization contains a culture where individuals continually expand their capacity to learn and create, where expansive patterns of thinking and risk are nurtured, where teamwork is expected, and where people continually work to see the whole (systems thinking) together. Social knowledge, shared knowledge: Distributed understanding, expertise and collaboration in the creation of information; knowledge reached by consensus across a social network or organization. Social network analysis, social network theory: Social network theory views relationships in terms of nodes and ties. Nodes are the individuals within the networks, and ties are the connections. Social network analysis (SNA) is a map of ties between the nodes that make up a network or community. Social software: see Web 2.0 Web 2.0: Originally coined by Dale Dougherty of O’Reilly Media and brought into popular use by Tim O’Reilly soon after (O'Reilly, 2005), the term refers to a new generation of software and hardware of the Internet that allows for participation and collaboration, and has the emergent characteristic of being better and more valuable the more people use it and contribute to the whole. Web 2.0 social software examples include blogs, Wikis and social networking environments that contain personal profiles of skills

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and interests. Tools of the Web 2.0 framework include (a) Google logic, which displays results of search in order of ranking by number of other sites that link to the retrieved site and (b) the ability to tag a contribution by dynamically defined category for grouping results across diverse media. WeBlog: A site that runs via the user’s Web browser, enabling journal-like entries without needing special skills or coding. These are posted on a regular basis and displayed in latest chronological order. The social aspect of the technology is that each post allows for comments or trackbacks from the readers of the blog. An additional social aspect is the blog roll of trusted or influential bloggers that a blog displays and links to from its site. Special search engines like Technorati and the Google Blog Search tool display results of the Blogosphere by recentness or by popularity (links of trust) to that blog. Wiki: a Web site that allows visitors to easily add, remove, and edit collaborative content. Wikipedia, the online encyclopedia of approximately 7.5 million articles in more than 250 languages written by volunteers, is the most well-known Wiki.

Assumptions and Limitations Organizational culture is subjective and often cannot easily be captured, described or generalized. It is an assumption of the researcher that studying the design and evaluation of collective knowledge creates a number of possibilities for error. These may be due to personal misunderstanding or misinterpretation, as well as the unique ideas and organizations of the individuals contributing to the study. Data collected and participant responses may also be influenced by a number of unknown, unrevealed or unrealized

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conditions or cultural idiosyncrasies of the community, workplace, technology in place, or participant’s experiences. Limitations of the study include replicability of results due to size of population; timeframe of the study; topic of analysis; methodology and selection tools; interest and skill set of the participants.

Relationship of the Study to Researcher Experience The exploration of e-learning design within this study relates to questions of characteristics, practices and support for emergent learning. The focus for these questions arose out of the researcher’s own experiences in providing technology support and training for a large university. Even in an environment where learning was encouraged and where diverse offerings received high evaluations, attendance at training sessions continued to drop. Feedback showed that participants felt that the timing was never easy or right, the level of difficulty never ideal for the individual and that the learners were prone to forget what they had learned before they needed to use it. In response, expensive online learning modules were purchased from a major technology training vendor, but the contract was cancelled two years later for lack of employee use. Learners wanted just-intime, skill-specific, individualized access to solutions and advice (ASU Institutional Planning and Research, 2004). A search of the literature and query to a higher education Information Technology (IT) services listserv showed that few IT organizations had tackled the challenge of establishing an environment for anytime, just-in-time learning. Again in response to feedback, the ASU technology group implemented a Wiki software service as a site for participants (anyone interested, but targeted at technology staff across the institution) to collect and share common technology-related issues and

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answers. After awhile, participants stopped maintaining the site, despite acknowledged belief in the value to customers that might be seeking information. Participants had gathered the ideas, organized the data, and implemented the original environment but did not sustain it (Technology in the service of the New American University, 2006). The challenges of ownership; identifying and claiming expertise; making difficult to categorize information explicit; return on investment (ROI) for time expended; and social issues of ownership, collaboration and sustaining engagement were significant and never solved.

Conceptual Framework for the Research The approach to the research question was a two-phase study. Phase 1 consisted of a social network analysis (SNA) that identified community-identified experts within the Internet blogger network that is studying, exploring and creating shared knowledge related to the research topic. Using this community, the Blogosphere, allowed the study to tap into a rich new resource of nascent, field-based, distributed knowledge not available in the research literature. By using the authors of popular blog sites related to the research topic as study participants, the study embraced an emergence theory premise that knowledge which is created, determined, and vetted by an interested collective of individuals has a validity and value equal to that of academic experts. The knowledge of the collective provides great insight, especially in new knowledge domains, and the collective experience of community-trusted nodes from an SNA analysis would provide valuable insight into emergent learning design. Adhering to the emergence framework,

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this research study used new social technologies, SNA analysis and collaborative participation to research design for emergent learning environments. Using blog-specific search tools to find the most studied and respected enterprise contributors on the topic, the study SNA recorded not just blog search engine results, but would also comb and record the blog rolls (permanent links to trusted resources) from each of blog sites retrieved in the search. By including the links to blogs that each retrieved blogger reads, recommends, critiques and follows, an SNA analysis would be able to determine community consensus on not just the most read (blog search engine results) but also the overall most trusted experts doing work and research in the field of emergent learning and organizational knowledge management (blog rolls). Turning to this community of practice on the Blogosphere gives academic research new access to the work of respected practitioners in the field, and for the study, the SNA would provide a map to practitioners’ ranking within their own online knowledge community. Within a blogging community, experts on a subject are identified as those whose posts are most often visited and responded to, and whose sites are most often recommended by other bloggers (Herring et al., 2005). Blog search engines rank contributions by simple freshness (most current links first) or by relevance/authority (most valued links first). This study looked to results based on relevance/authority. Each of the blog search engines use proprietary mathematical formulas to determine results weighted by authority. These formulas, although different for each engine, include results based on inbound links (pages that link to the results page), freshness of the information posted, blog roll links and links to other pages at the retrieved site (Gill, 2004). The results of the relevance/authority results were collected and combed through the SNA for

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their blog rolls. Gill (2004) compares the dual results (number of links and blog rolls) to academic comparison of both the number of citations for an article and of prestige of a journal where the article was published. Being listed in a blog roll reflects a reputation for consistent and valued contribution, participation, and value in sharing knowledge. By SNA mapping of both links and blog rolls, a better picture of current online expertise of the Blogosphere regarding organizational knowledge and emergent learning would be identified and documented for later access to the ideas and successful practices of community-identified experts. Digging into a third layer of findings, the most linked to (trusted) blogs – based on preliminary SNA of the blog rolls – were combed and the blog rolls at those sites also recorded in the data set. Allowing the Blogosphere’s identified experts to further identify the experts that they trust created a point in time picture of trusted knowledge flow within the Blogosphere. In phase 2, a qualitative study of best practices and successful experiences of these experts were collected, studied and summarized. In this phase, participants were asked to explore insights, perceptions, ideas and experiences regarding design practices in support of distributed organizational knowledge. Beginning with a summary draft of (a) terms, (b) ideas from participant blogs, and (c) results from the participant interview questionnaire, a first draft of consensus was posted to a Wiki site and made available to the participants for corrections, revision and additions. Asking these community-trusted experts to participate in the collective review, comment and creation of new knowledge on design practices for emergent learning provided evidence for new practices and roles for designers, and created a new framework for the use of social technology in research.

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Much as Linstone and Turoff describe the Delphi method of discovering and vetting participant knowledge, a Wiki was used in this study as “a method for structuring a group communication process, so that the process is effective in allowing a group of individuals, as a whole, to deal with complex problems” (Linstone & Turoff, 1975, p. 3). In this case, the group of individuals were Blogosphere-identified experts in just-in-time, informal learning and its contribution to community knowledge. The research study explored building consensus on emergent learning design practices in the expectation that participant knowledge and experience would provide valuable, community-based knowledge not found in the academic research regarding tools, practices, and impediments to defining and supporting emergent learning and shared knowledge.

Organization of the Study The study is divided into five chapters. This chapter is an introduction, including background on emergent learning and organizational knowledge, purpose of the study, and exploration of the significance of the research questions. Chapter 2 provides a view into the literature related to as-needed learning, including the need for design and support; organizational learning and knowledge management; and social networks, social knowledge and social technologies. Chapter 3 details the methodology and design of the study, including the population and sample, data collection process, instrumentation, and plans for analyzing the data. Chapter 4 presents the results of the analysis. Chapter 5 offers an interpretation of the results, including implications, conclusion and recommendations for further study.

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CHAPTER 2. LITERATURE REVIEW Anchored in the tools of the Internet, the information age changed the way we find, connect, share and exchange information. This has created both rich potential and new challenges for the conceptual framework of learning design. Even more pronounced than Brown predicted (1999), the Internet defined a new learning ecology where we are able to be our own “private, personal reference librarian, one that knows how to navigate through the incredible, confusing, complex information spaces and feel comfortable and located in doing that,” (Some Cyberage Shifts). Enterprise workers now seek knowledge when they need it: from experts, from colleagues, from Google, from the literature and from the latest company reports (Anderson, 2007). It’s done in the office, in the conference room and in the field (Wagner & Robson, 2005). A new learning ecology, built on Internet technologies and personalized, anytime access to abundant information now drives the enterprise knowledge environment. Just as the tools and environment have changed, so have practices and expectations of the worker and the workplace. This chapter explores the literature related to understanding these Cyberage shifts for individualized e-learning, organizational learning, knowledge management, the social construction of digital knowledge, new technologies used in the creation and organization of knowledge, and the changing role of e-learning design in supporting dynamic knowledge access and creation.

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The Shift to Shared Knowledge Lankshear (2003) claimed that more than just the presence of the high-speed information access has created a culture of independent, anytime discovery and suggests that four dimensions related to digital information changed the nature of learning. These were (a) changes in the tools we use, (b) in shared concepts of knowledge, (c) in learners themselves, and (d) in new ways of knowing and learning. Rennie and Mason (2004) come to a similar conclusion in their claim that the shift from the classroom to what they term the Connecticon happened for three reasons: (a) digital capacity for immediate information capture, storage and retrieval; (b) online ability to support, extend and expand communication; and (c) capability of the Connecticon to support proactive, self-directed and experiential learning (p.144). Whether we may have relearned how to learn is a question of debate in the literature. One assumption is that learners, especially those comfortable with technology, organically changed habits, methods, and strategies for seeking and acquiring knowledge (Oblinger, 2005; Prensky, 2001). Pierre Levy, anthropologist and professor of hypermedia at the University of Paris, first addressed the idea of a bottom-up, selforganizing digital learning environment in his research on the collective intelligence potential within cyberspace culture. The knowledge space is brought to life whenever we initiate human relations based on ethical principles. These include individual improvement through skills acquisition, the efficient transformation of difference into collective wealth, the integration of the exchange of knowledge within a dynamic social process in which each of us is

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recognized as a unique individual is not prevented from learning by programs, prerequisites, a priori classifications, or prejudices about what is and is not worthwhile knowledge (p.13). Levy contended that the culture of the Internet creates "a form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills" (p.13). For Levy, connection forms a new way of defining knowledge and moves us from the current information economy to a new social economy of distributed knowledge generation. "No one knows everything, everyone knows something, all knowledge resides in humanity" (p.13-14). Others claim deep learning has always been shared, social and situated (Bandura, 1977; Lave & Wenger, 1991; Marchese, 1998) and that technology has just made this more achievable through the Internet’s anytime access to information, resources and community (Chickering & Ehrmann, 1996; Siemens, 2005). Rennie and Mason (2004) further pointed out that the reasons for a shift away from instruction may go much deeper than our adaptation to new tools, and that some learners, including members of the younger digital generations, actually have no natural instinct for self-directed learning. Independent learning is not necessarily a preferred learning style but a necessity of the digital age. Enterprise learners are driven by the changing demands of the workplace and to daily performance goals related to retrieval of real-life, how-to answers and to learning from the work experience of peers, colleagues and situated experts (Boud, 1998). Knowledge needed for the information workplace may simply be most effectively met through just-in-time and self-directed learning.

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Enterprise excellence now requires that workers learn new skills, in new ways, if they are to be prepared for an information economy that demands self-direction, decisionmaking, digital collaboration and individual contribution to organizational knowledge (Balz, 2005; Kurtz & Snowden, 2003; Szulik, 2006). Cross (2006) also made the case that organizational effectiveness demands virtual teamwork and collaboration skills found through workplace e-learning tools and environments. Calling this informal learning, Cross (2006) proclaimed “courses are dead,” (p.39) and cited a number of corporate studies that explore the notion that more than 80% of workplace learning is now done outside the formal learning environment of sponsored classes and training (pp. 243-244). Although the data may support a shift in workplace practice that Cross addressed, the enterprise focus on performance negates any claim that informality is the cause of shift away from instruction and training. The workplace now demands just-intime, rather than just-in-case learning (Gersten & Evans, 2004; McStravick, 2007). Research questions exist throughout the literature regarding the characteristics and conditions that have created the demand for learning that now takes place outside the traditional face-to-face environment. Although the phenomenon is growing throughout many diverse educational venues (Ramaley & Leskes, 2002; Siemens, 2005), this study and literature review focuses on aspects that specifically affect the information workplace. It includes history, characteristics, requirements, and challenges to successful creation and support of as-needed learning and organizational knowledge. Focusing on the role that personal learning plays in creating distributed knowledge, the term emergent was chosen to describe the learning phenomenon addressed. This study looked to emergence theory to describe an as-needed, independent

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behavior that contributes to a larger, distributed knowledge environment. In choosing the term, the study looked to recent research findings on various, diverse applications of emergent behavior. This behavior reflects inter-related but independent actions of individuals and the role of the behavior in creating new patterns of self-organization within the larger group.

Emergence Theory Complicated phenomena are known to emerge out of seemingly simple, unaware systems. Theoretically, emergence is a notion of causality, and although controversial in application, is based on evidence that patterns arise within large, complex systems that are a result of the activity of independent, unrelated small parts (Corning, 2002). Application of emergence theory in diverse environments allows for better understanding of how coherent structures, patterns and properties of complex systems emerge during a process of unstructured self-organization (Goldstein, 1999). Simply put, the whole is greater than the sum of the parts. Surowiecki (2004) used the application of emergence to explain a principle of collective wisdom, where all of us together know more than any some of us, and by exploring fields as diverse as mass culture, psychology, economics, artificial intelligence and political theory, demonstrated how collating the knowledge of the collective produced smarter, better ideas and solutions than by relying on the decisions of any expert, even brilliant, few together. Johnson (2001) made the theory accessible in the example of ant colonies, where working without leaders or plans, soldier ants adapt to their environment, each acting independently and unaware of the complex system, but acting in ways that collectively alter the size and behavior of the colony to

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suit conditions of survival. Hutchins (1995) applied emergence theory to cultural complexity and sea navigation, arguing that cultural systems have cognitive properties of their own that have a summative difference from the individual cognitive properties of the individuals who participate in them. Web 2.0 intelligence depends on application of emergence theory to create smart systems that learn by aggregating independent, emergent data. Following Amazon.com’s lead (http://tinyurl.com/2c6uj9), commercial Web sites will now predict an individual’s preferences by aggregating and offering the further choices of others who have purchased like products. Pandora.com allows each customer to create streaming, personalized radio stations based on its music genome project of feature characterization (http://pandora.com/mgp.shtml). The station, and the system, grows smarter as hundreds of musical attributes are analyzed as interest matches are verified for each song by each listener. The system learns with each response and the response becomes a part of what is collectively, not consensually, determined regarding the musical features of the song. Within complex systems, whether biological, cultural, political or informational, the selforganizing capabilities of individuals within collective create valuable patterns of complex awareness.

Characteristics of Emergent learning Operating within the domain of digital connectivity, the complexity of emergence does little to narrow the range of independent learning characteristics described in the literature, and encompassing terms include descriptions as varied as emergent (Downes, 2005; Kays & Sims, 2006) informal (Cross, 2006), digital and millennial (Dorman, 2000;

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Prensky, 2001), lifelong (Stephenson, 2003), pervasive (Norris et al., 2004), selfdirecting and self-regulated (Areglado, Bradley, & Lane, 1996) and incidental (Marsick & Watkins, 2001). Aspects of these learning characteristics all include qualities of access, discovery, independence and self-direction. Areglado, Bradley and Lane (1996) addressed deeper characteristics of this personalized learning, which include: (a) the ability to articulate learning needs and set relevant goals, (b) self-motivation and self-discipline, (c) self-confidence, (d) ability to develop new strategies and objectives for problem-solving, and (e) awareness of personal learning strengths and weaknesses. In the knowledge economy, the application of these characteristics includes the development of skills in finding, sorting, evaluating and summarizing data to answer questions or solve problems. Demonstration of these skills has been labeled information literacy or fluency (American Library Association, 2007), and is seen not as innate to the learner or learning style, but as a competency that can and must be developed in the educated individual. An additional component related to emergent learning in professional environments includes the ability not just to retrieve and synthesize information, but incorporating the process of communicating, sharing, negotiating and coming to agreement with others regarding the results (DeSanctis, Fayard, Roach, & Jiang, 2003). In the broader domain of e-learning, Wenger (1999) described the sharing and negotiation inherent in information exchange as well as the social nature of meaningful learning experiences. Although focused on the online classroom, Palloff and Pratt (1999) also provided valuable understanding of the role of participation within the learning community in their exploration of collaboration and engagement unique to online

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environments. They made a strong case for the value of e-learning’s potential, especially for the "introverted student who may not feel comfortable speaking out or asking for help in a face-to-face setting" as well as the “ability to be more thoughtful about their interactions" (p. 164) due to the characteristics of the online medium itself. They later made the case that the combination of technology, collaboration spaces for groups, and the individual’s sense of ownership and self-expression allow for an effectiveness in virtual community that has become a “a critical factor to the success of business projects” (Palloff & Pratt, 2005 p. 14). Emergent learning could thus be summarized as the creation of meaningful connected knowledge through individualized discovery. Design and support for new emergent learning networks would need to consider retrieval, sharing, collaborating and problem solving via a connected, digital environment. In the workplace specifically, King (2001) claimed that an organizational culture that can create and support emergent learning will see increased productivity and results. King added that successful outcomes would be demonstrated by finding information; organizing and synthesizing it; generating new knowledge from the information available; and negotiating, sharing and collaborating in its dissemination. McStravick (2007) noted that a future component of informal workplace learning will be support for assessment and for ensuring alignment with organizational need. Emergence-based learning design must find a way to support individual, personalized, anytime learning and ensure that the learning outcome contributes to a distributed organizational knowledge environment.

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Organizational Learning Research related to the study of organizational learning focuses primarily on the ability to harvest what knowledge workers know. This harvest is possible when workers are able to find, create and connect disparate pieces of information and to make sense of the networks of data available (Drucker, 1994; Gold, 2001; Gray, 2000). Although there were a number of significant pre-Internet influences (Levitt & March, 1988; Michael, 1973), seminal work in developing a framework for a digital learning culture in the workplace started with Senge’s (1990) theory of the organization’s value on collaboration and dialogue in continuing to learn. Senge stated that the organization needed to embrace five disciplines to effectively incorporate learning into the culture. These were: (a) building shared vision and support for learning; (b) mental models as a technique to foster creativity and openness to change; (c) team learning, where learning is made explicit and passed on from individuals to the organization as a whole; (d) personal mastery, or the individual's motivation to continuously learn and improve; and (e) systems thinking, or the view of the organization as a function of its environment. Senge’s work influenced a number of important thinkers regarding the role of learning as a team activity. Brown and Duguid (1991) focused on the need to understand community and its different structures and forms within a learning organization. The role of technology and the Web was crucial to their contribution regarding shared knowledge and the social life of learning and information. Laurillard (1999) explored the role of individual in creating shared knowledge, and suggested that learning organizations are built on a common foundation and that higher education must play a larger role in developing a learner’s

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ability to make internal conversations explicit if we are to create successful lifelong learners, learning organizations and a learning society. Garvin’s (1993) work on the learning organization used case studies regarding successfully incorporating five activities into organizational culture: (a) systematic problem solving and experimentation with new approaches, (b) learning from past experience, (c) learning from the best practices of others, (d) transferring knowledge quickly and (e) transferring knowledge efficiently throughout the organization. Following on Senge’s framework, existing literature suggests that organizations with strong learning cultures see (a) increased productivity and competitive success (King, 2001; Stonehouse & Pemberton, 1999); (b) a stronger sense of collaboration and community (Kahan, 2004); and (c) a more structured approach to the capture and exchange of tacit knowledge (Pratt, 2006). The current diffusion of ideas regarding organizational learning was predicted by Easterby-Smith (1997) in his recommending categories for new disciplinary focus into six areas: organizational development, theory, strategy, management, production and cultural anthropology. Despite this diffusion, and the accompanying inability to agree on effective design models, the rich and diverse research in the literature demonstrates the value of continuing to develop strategies and evidence for new ideas and thoughtful design for organizational learning models in the workplace.

Knowledge Management With the materialization of the information age, the corporate world became increasingly aware of the need for not just encouragement and support for organizational

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learning, but for measurement of organizational knowledge. During this time, the field of knowledge management came to mean the technology, systems, processes, and cultural practices that would allow a company to harvest and measure intellectual capital (Demarest, 1997; Gold, 2001). The discipline developed an early framework with Peter Drucker’s work on applying organizational knowledge to daily business processes. Drucker (1994) coined the term knowledge society and began the discussion of ideas regarding the lifelong educational needs of the new knowledge worker who would replace workers of the industrial age through use of a very different set of learning skills. Drucker believed that knowledge would become increasingly social in nature, and that the definition of quality teaching and learning (purpose, value and practice in the workplace) would be redefined to incorporate collaborative knowledge creation skills. Some now claim that a new knowledge age is demanding crucial skills based on knowledge networkers rather than the knowledge worker that Drucker described (M. Chatti, 2007). The other great influence on the field of knowledge management is Ikujira Nonaka, whose collaboration with Takeuchi included wide-ranging ideas of discussions of bottom-up (or what we might now term emergent) knowledge management, and the value of recognizing and harvesting tacit knowledge in the workplace (Nonaka & Takeuchi, 1995). A term originally introduced by Polanyi in regard to business use (1966), tacit knowledge is the personal and hidden knowledge that is known but difficult to describe. Examples of tacit knowledge are know-how rather than know-what; expertise and skill; and deep understanding resulting from previous activities and experience. Early research in knowledge management has been abundant in exploring ways to formalize and share tacit knowledge and is that is crucial to organizational effectiveness.

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Nonaka (1994) explores tacit knowledge by making a case for a learning environment where "knowledge held by individuals, organizations, and societies can be simultaneously enlarged and enriched through the spiral, interactive amplification of tacit and explicit knowledge" (p. 34). He asserted the need to capture workplace knowledge, tacit and explicit, and make it available to the organization as a whole. He also claimed that a learning environment that supports the transfer of an individual's tacit knowledge through "socialization, combination, externalization, and internalization" (p. 34) is at the heart of new possibilities for organizational knowledge creation. Work by Demarest (1997) followed on this by making the case for knowledge management of both tacit and explicit knowledge through a social construction process comprised of four separate parts: construction, embodiment (the container that holds the knowledge), dissemination and use. For Demarest, success of each part of the model depended on the culture and choices of the organization. Whether focused on container or process, personal or shared creation, tacit or explicit, the body of research on knowledge management still rests largely with the practical notion of organizational knowledge as intellectual capital that needs to be identified, captured, shared and effectively used. New work in knowledge management converges with emergence theory in suggesting that a third generation model will look to self-organization and see knowledge as “a thing and a flow” (Snowden, 2003a, p. 24). This research suggested that we are reaching the end of the second generation of knowledge management with its focus on tacit-explicit knowledge conversion. The third generation will need to create "a sensemaking model that utilises self organising capabilities of the informal communities and identifies a natural flow model of knowledge creation, disruption and utilisation" (p. 2).

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For Snowden, then a director of IBM’s Institute for Knowledge, the third generation would also account for an unexplored domain of knowledge that depended on learning “in conditions of extreme uncertainty" and an environment of "strategy, innovation, culture, trust and communication" (p. 12-13). Snowden’s later work in sense-making within complex knowledge environments suggests the information workplace has entered that third generation of knowledge management (Snowden & Boone, 2007).

Social Knowledge A theme that runs through theories of learning, organizational knowledge and knowledge management is the social nature of constructing knowledge. In alignment with constructivist learning theory, this theme centers on the idea that we construct knowledge or understanding of the world through our experiences and interactions (Bruner, 1990). The pioneering social constructivist Lev Vygotsky (1978) theorized that "the distance between the actual development level as determined by independent problem solving and the level of potential development as determined through problem solving under adult guidance or in collaboration with more capable peers" (p. 86) bridges the gap of what can be known and this is where learning occurs. Vygotsky called this the Zone of Proximal Development and influenced a generation of social constructivists in expanding learning theory and creating evidence for the deep value of social knowledge. Learning research and design continues to influence and inform social knowledge creation in the workplace, and the intersection includes cognitive, educational, psychological and cultural influences. Important to the concept of social knowledge value is the work of Lave and Wenger (1991). Creating the influential terms communities of

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practice, situated learning, and legitimate peripheral participation, the authors looked at learning as a social and situated process. An anthropologist (Lave) and a computer scientist (Wenger), they studied diverse communities of midwives, tailors, butchers, and recovering alcoholics to better understand the situated, social and shared perception of meaning that continues to inform current work on digital workplace learning. Like Lave and Wenger, John Seeley Brown focused his research on the intersection of social and situated knowledge. A technology researcher and formerly the Chief Scientist of Xerox Corporation and the director of its Palo Alto Research Center (PARC), Brown has influenced a new generation of systems and learning designers in his exploration of collaboration technology and the potential of the Internet and social technologies. His original work with the historian and social theorist, Paul Duguid (Brown & Duguid, 2000) was greatly influenced by the work of social constructivists in making the case that technology can not create the gains hoped for in the enterprise environment until systems designers recognized that information is dynamic, situated and socially constructed. For Brown and Duguid, enterprise knowledge must be negotiated, vetted and collectively constructed. According to the authors, social systems and software that allow for the collaborative construction of meaning are needed to create the knowledge required for an organization to be successful in an information society. Following their work, research now suggests it is vital for social knowledge – created via distributed, dynamic and collaborative work - to be encouraged within the workplace culture and that contributions to shared, organizational knowledge be recognized (Hall & Graham, 2004; Rosenberg, 2001).

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Organizational knowledge analysts believe a deep understanding of practice is needed, and that there is a direct connection between organizational success and (a) the amount of trust and support in place for the social construction of organizational knowledge, (b) each member’s ability to develop and deploy their own tacit knowledge and (c) availability of tools that can be used to collect, organize, and analyze the information and expertise within a social network (Braun & Schmidt, 2006; Crosse, Borgatti, & Parker, 2002; Snowden, 2003b; Stephenson, 1998). Creating Online Community Learning research within the roles of discourse, negotiation and shared experience has contributed great value to establishing meaning - whether at work or play; in person, on the phone, online in discussion groups, in text messaging or in the chat room. Throughout time and media we have established bonds and meaning by telling stories. Gee (2005) understood the importance of social discourse in making a case for developing shared meaning. We learn by expressing what we know, what we experience, and what we believe to be true. Palloff and Pratt (1999) explored the way this happens online, and although focused on the online classroom, they claimed that we have not yet considered what the online medium brings to community and learning outcomes. "The creation of a learning community supports and encourages knowledge acquisition. It creates a sense of excitement about learning together and renews the passion involved in new realms of education" (p. 163). Kim (2000) made the case, through numerous case studies and examples, that the Internet is no longer about tools, technologies or finding information. It is now about finding and connecting with the people who create the information No longer a static

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Web, it is now a social, negotiated Web 2.0 (Anderson, 2007). Howard Rheingold (1993), founder of one of the first online communities (the Well), had long claimed that online communities provide a unique opportunity for people across time and space to create bonds, meaning, knowledge and value without ever meeting each other. He argued that the absence of physical presence can enhance understanding and that the asynchronous, decentralized, informal, eclectic and self- governing nature of discourse on the Well created a new kind of community. Rheingold more recently extended his vision of community in his research on mobile technologies, demonstrating that the power of synchronous communication via pagers, cell phones and PDAs can mobilize groups across a city, create real-time connection across the globe, spread information instantly across diverse populations, and create instant community (2003). In doing so, he provided strong evidence for the power of technology to create new definitions, tools and places for learning and sharing knowledge. Ong (2002) reached back in history to make a case for a new, digital orality in the emphasis on sharing of experience that online technologies bring to the community experience. Originally, oral cultures were communal, but these community characteristics changed with the printed word. Print itself encouraged individualization, distance, and objectivity. For Ong, secondary orality is post-literate, relying on affordances of a print culture but inheriting some of the characteristics present before literacy. As a product of electronic technologies, secondary orality allows for both individualized and communal expression. It supports instantaneous feedback in communication between people, facilitates exchange of ideas, and allows for preservation of information while still encouraging fluidity. Because of the time-and-distance-spanning capabilities of digital

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communications, secondary orality encourages community but allows for expression of individual reflection, subjectivity and situational focus. In these ways, secondary orality creates an emergent framework that reintroduces many of the community-building features of oral cultures while building on the analytical and individualized characteristics of print, creating a new form of expression for online learners. Social Networks and Knowledge A more scientific way of understanding how knowledge is socially constructed within an environment is in the study of social networks. Explicitly focused on how information travels, social network analysis (SNA) has emerged as a promising technique in research and modern knowledge management (Crosse et al., 2002). Evidence from the collective enterprise community has shown that SNA can play “a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals succeed in achieving their goals” (Wikipedia, 2006, SNA). Recognized as key to effectiveness in information flow and knowledge management, workplace SNA often focuses on determining the hubs or strong nodes often hidden within organizational knowledge. Who do people go to when they need information? Who are the experts that people trust to give them correct information on a topic? How can the organization find and map this knowledge, and thus capture and disseminate what these strong nodes know? For SNA, the value of doing so in the design and analysis of a learning environment would make it possible that knowing the strong nodes, where to find them, and how to create access to them would become a quality built into the environment. Although the history of SNA goes back to 18th-century Swiss mathematician Leonhard Euler, accessibility to understanding and use of SNA grew with the release of

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Albert-László Barabási’s (2002) popular work on SNA and preferential attachment, or the way that hubs (older, stronger nodes on a network) quickly accumulate more, attaching nodes creating a culture that can have negative repercussions for knowledge creation. Regardless of equality in information or value, nodes with fewer attached links have a much lower chance of becoming destination links or having their information disseminated. In an enterprise example, if people are used to going to Sally for information on subject X, and are asked by new staff where to go for this information, more people will be told to go to Sally – even though Jane and Fred also have this information. This can put a strain on access to the hub (Sally), stress the hub’s resources, as well as leave weaker links out of important social exchanges of information. An extension in understanding SNA is Granovetter’s (1973) earlier work on strong and weak ties (not nodes) and the value of weak ties within a network. Granovetter claims that information can travel a greater social distance and more quickly when passed through weak ties. Attachments via weak ties (interests, organizational reporting, and expertise) are more likely to move in circles different from our own and will thus have access to information different from that which we receive. The ability to disseminate information is thus related to the number of weak ties or bridges that can move the information to other parts of the network. A hub may have many attached nodes but lack the variety, or bridges, in their social network to allow for movement or dissemination of information. Sally may have no way of knowing that another department in the organization changed some key criteria related to subject X unless she has ties to that department.

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Gladwell (2000) refers to these weak ties as connectors and makes the case that by utilizing the strength of connectors, behavior can ripple outward until a critical mass or tipping point is reached. Following the notion of emergence theory, this is an example of individual actions independently creating a ripple that influences the greater community. Strongest of all in a Granovetter model is a system that allows for and supports formation of dynamic bridges as needed, without the requirement of any previous ties. Although complex to accomplish, the value of using SNA for organizational knowledge management is in discovery and capture of new knowledge, thus providing a new tool for the capture of knowledge that often remains hidden. Ways this may be done via SNA include (a) being able to discover and build external contributions into the network information flow (Piller, Schubert, Koch, & Möslein, 2005); (b) managing overwhelming volumes of information and creating new collaborations (White, 2006); and (c) building social capital that creates organizational trust, self-development and community (Kilpatrick, Bell, & Falk, 1999). Karen Stephenson posited that new practices in knowledge creation and management will evolve from understanding social networks and that effective organizational knowledge can no longer be met by standard design practices (Kleiner, 2003; Stephenson, 2005). For Stephenson, knowledge design for organizational learning depends on creating, understanding, and strengthening communication channels within the organization. She claimed that organizations need to find new ways to make each individual’s knowledge explicit to others through the capture of individual contributions to distributed knowledge.

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How does an organization support continuous capture of what is known and in a form that makes it available to all? “People have at their very fingertips, at the tips of their brains, tremendous amounts of tacit knowledge, which are not captured in our computer systems or on paper,” says Stephenson (Kleiner, 2003, p.1), and “Relationships are the true medium of knowledge exchange, and trust is the glue that holds them all together” (Stephenson, 2005, p. 248) Stephenson claims that SNA permits the measure of where reliable knowledge, value, and crucial enterprise information reside. According to Cross (2006), this method of capturing organizational awareness is a “powerful means of making invisible patterns of information flow and collaboration in strategically important groups visible” (p. 70). In summary, SNA has potential for making the flow of knowledge accessible to all, capturing knowledge of where expertise and information lies, as well as defining a framework that enables all nodes to share and network their knowledge.

New Technologies for Organizing Knowledge If research tells us that organizational knowledge is built on trust, negotiation, collaboration and making information available to all, pressing questions arise regarding how theory is put into practice. Organizations struggle with understanding how to capture tacit and shared knowledge, how to make it easy to find once captured, and how emergent learning can best be designed and supported in organizational use (Snowden, 2003b). Numerous models have been proposed in search of the synergistic relationships of tools, knowledge management and e-learning. Possibilities include workplace environments designed for using social constructions of information, creating categories

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of knowledge domains, and treating knowledge as measurable intellectual capital (Sharma, 2003). Regardless of the conceptual framework proposed, numerous researchers, technologists and learning designers believe implementation rests in leveraging both the collaboration culture of digital learners and the tools now readily at the learner’s disposal. For many, implementation of Web 2.0 tools signifies a convergence of theory, software, connectivity and organizational need (Anderson, 2007; Barnett, 2006; Grudin, 2006; Madden & Fox, 2006). The combination of social technologies, social tools, and processes that collect and encourage knowledge creation, sharing, revision, negotiation and collaboration may be crucial to enterprise effectiveness (McCafee, 2006). New possibilities in shared knowledge and digital content management allow for diverse, negotiated, dynamically ranked and organized, collaborative, and often informal and individualized capture of knowledge. One of the emergence characteristics of interest in Web 2.0 applications is the requirement that they get better (richer, more powerful results) the more people use them. Collaboration tools currently found under the umbrella of Web 2.0 systems include shared document containers, WeBlogs, Wikis, tagging content by topic (folksonomies), shared bookmarking, podcasting, and user -vetted content (Anderson, 2007). For proponents, Web 2.0 depends not simply on the collaboration technology of the Web, but as Anderson states, on “harnessing the power of the crowd” (p. 15) and creating “architecture of participation” (p.19). The social nature of Web 2.0 creates a combination of tools, practices, trust and “software that gets better the more people use it” (O’Reilly , 2005, Web as Platform) and creates new potential for shared knowledge and distributed learning. Effective design for this collaborative and

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shared knowledge architecture of participation determines the foundational questions for this research study. The Role of Instructional Systems Design To be effective in emergent learning environments, instructional designers must begin to rethink the practice of the field. Research now makes the case that workplace learning environments should connect and support distributed communities of learners in self-directed and collaborative exploration of the knowledge objects, practices and processes used in daily work (Allee, 2000; Pantazis, 2002). This cannot be done with the standard tools of instructional design (ID). Designers of workplace learning must find new tools and practices for individualized and just-in-time learning, rather than the traditional, sequenced, just-in-case instruction (Cross, 2006). To do so, a better understanding of how to use the new social technologies of collaboration to capture and evaluate tacit, explicit and shared knowledge residing within a community is needed (Brown & Duguid, 2000). Design for informal, anytime, emergent learning would find new ways and means to support individualized and organizational learning through creation, location, collaboration, synthesis and management of dynamic information. Even before unique design issues related to emergent learning called standard ID practices into question, researchers within the field had argued that the discipline was on the cusp of needed change. Gordon and Zemke (2000) began a discussion of ID effectiveness in their attack on prescriptive use of standard ID practices. They claimed that the foundational principles of ID (analyze, design, develop, implement, evaluate ADDIE) demonstrated a dated and ineffective process in an age of rapid change. Some of their main objections were that the model was too slow and cumbersome to work with in

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the real world. Jonassen (1997) pointed out that traditional models were hard-pressed to address the ill-structured problems that “possess multiple solutions, solution paths, fewer parameters which are less manipulable, and contain uncertainty about which concepts, rules, and principles are necessary for the solution or how they are organized and which solution is best” (p. 65). Others made a case for a change in pedagogical approach in ID to better build teaming and collaboration skills in learners (Ellis & Phelps, 2000) and of the need for design models that support more iterative development of materials. Sims and Jones (2003) define their 3PD model as an attempt to transform the traditional ID framework and create “a long-term collaborative process by all that can generate and evolve into focused communities of practice with shared understanding and a philosophy of continuous improvement” (p.16). Nichani (2006) called for empathic design that observes learners, determines unique needs and designs environments that provide solutions. Nichani’s notion of empathizing with the learner echoes Bandura’s (1977) social learning theory with regard to the significance of how learning and understanding is tied first to observation. Even before e-learning and informal learning created new requirements on design, a number of researchers were calling for a new conceptual framework that focused on learning, rather than instruction. The transfer of knowledge through socialization recommended by Nonaka (1994) is still missing in learning and organizational knowledge design practices today. Design for social, digitally-connected knowledge, including incorporation of cultural values related to trust, collaboration and consensus, is dependent on a new understanding and use of the tools and digital practices now available for organizational knowledge creation (Brown & Duguid, 2000; Stephenson, 1998).

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Within these new conceptual frameworks for learning design rests the challenge of assessment. Emergent learning does not lend itself to standardized testing, counts or measures on predetermined materials because the outcomes depend on just-in-time resolution of individual needs. It is this individualized need that Kelly (2003) believes to be the driver for a new approach to instructional design. Deep evaluation techniques related to the context, to performance, to consensus and to organizational value are a more viable approach in creating meaningful assessment of understanding (Gardner, 1999) and contribution to shared meaning (Gardner, 2002). A combination of tools, practices, and technology that support the learner in dynamic location, creation and evaluation of information is needed. Snowden (2003a) claims that this will only happen when we can create environments that address the four knowledge spaces of his Cynefin (habitat) model: the known, knowable, complex and chaos spaces. A potential epistemology for learning design may lie in research influenced by emergence theory (Kays & Francis, 2004; Kays & Sims, 2006), which explores creation of knowledge from the emergent perspective of self-organization within an environment of immersion, collaboration, and context-specific peer support and evaluation. This proposed design theory addresses the significance of relationships, social learning and the reality of complex, self-directed, bottom-up, self-organizing environments for learning. The researchers suggest a focus not on instructional design, but on creating a supportive environment for learners to independently create meaningful knowledge from a vast repository of resources, information, tools and situational criteria. Regardless of the model or framework examined in the application of instructional design to emergent learning, it is clear that the discipline is invaluable to the

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current state of learning design and knowledge management practices. Carlile (2002) points out that instructional designers, traditionally housed within the training and development area of an organization, have seldom interacted with the knowledge management group but this cultural practice denies the organization an understanding of key pieces of the puzzle that needs to be solved. “Without a focus on learning, knowledge management is really only information management or management of potential knowledge. In order to be true knowledge management, the learning segment of the process must take place” (p. 39). Nworie (2004) concurred, and stated that the culture of instructional design includes acknowledging the value in diversity of roles in teaming and project management as well as the importance of evaluation. The practice of ID, applied to emergent learning, would be instrumental to achieving the goals of organizational success in the capture, storage, organization and reuse of information. Thus, the research suggests that although often overlooked in organizational knowledge management, the discipline of instructional design could bring new possibilities to organizational learning and capturing shared knowledge. Traditional design skills, along with new understanding of the possibilities and challenges, are deeply needed to solve the challenges ahead.

Conclusion The literature is ambiguous regarding a clear framework for the successful design and support of emergent learning environments, even though the need is evident and the value to organization knowledge well-demonstrated. Possibilities and ideas for adaptation

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of traditional instructional design theories abound, but evidence of successful implementation and effective practice in support of independent and emergent learning is still missing. New technologies and networking tools provide rich research opportunity for convergence in the creation, identification, sharing and synthesis of organizational knowledge. Research is needed on the inherent characteristics, roles and responsibilities of effective emergent learning design. This study will attempt to fill the gap in the literature by researching, demonstrating and collecting evidence on effective practice in the design and support emergent learning environments. The research will work within the framework being studied by applying Web 2.0 tools - blogging, linking and search ranking, SNA analysis, and a collaborative Wiki – within the research on emergent learning design and the creation of organizational knowledge. Using the tools and practices under investigation, the study will model the use of social technologies and Web 2.0 framework to determine, collect and compare knowledge of design practitioners currently sharing their experience via the Blogosphere. By finding, studying, mapping and bringing together the experiences of respected practitioners designing and implementing emergent learning environments, a better understanding of effective learning design in an unstructured, justin-time, emergent learning environment is anticipated.

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CHAPTER 3. METHODOLOGY The purpose of this study was to investigate effective design for emergent learning, and by doing so, to better understand the practice of e-learning design within a shared knowledge environment. New Internet technologies and the understanding of how affordances of technology have influenced the workplace greatly influenced the design of this study. A two-phase, exploratory methodology that utilized participatory and consensus-building tools of Web 2.0 was used in design of the study. To better understand emergence as a framework of inquiry, the study asked experts identified via the Blogosphere to explore how design could best support learners when finding, creating and sharing knowledge. Through collaborative knowledge building by the participants, the study identified characteristics of effective emergent learning environments and design roles and practices that support these characteristics. To do so, the study captured experiences of identified experts from the Internet community regarding e-Learning and shared knowledge practices. Experiences and ideas were gathered and used to collaboratively determine effective practice. In phase 1, NetDraw™ social network analysis (SNA) software was used to discover and map the strong nodes (respected researchers and designers) within the global community of bloggers working within the topic of emergent learning and shared knowledge. Search terms included various terms for informal, emergent learning as well as organizational knowledge and knowledge management. In this phase, the study used

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the SNA to create a snapshot capture of what Stephenson (K. Stephenson, 1998) labeled trusted knowledge sources. SNA trusted knowledge was located through computing the strength of connected nodes followed via their blogs. Strength of a node was computed based on number of appearances in blog rolls, as well as number of independent links to the blog site. These links were then analyzed for centrality. A network map of the individuals identified by the SNA as most trusted (to whom more bloggers reference or blog roll) was created, and these 22 experts were asked to participate in a survey on emergent learning practice in the workplace. An online summary of the participant ideas, reflections and experiences was compiled and made available to the participants. This summary formed the foundation of a Wiki that the participants could revise over a period of two weeks. The summary data captured a first look at what was collectively known by the participants regarding design for emergent learning experiences, and through the Wiki, the process allowed each expert to review, revise and rethink the shared information at the Wiki site. Based on an emergence framework that claims all of us together know more than any sum of us separately, the collective response created a clearer picture of successful practices in supporting an emergent learning environment and, hosted by the New Media Consortium (NMC, 2008), continues to serve as a public resource for e-learning designers.

Research Design Mixed method research is now considered a separate and distinct choice for research methodology and numerous researchers have recently explored the substitution of social network analysis (SNA) for the traditional quantitative arm of a mixed-method

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study (Birk, 2005). This study used an explanatory (two-phase expansion) research model where quantitative data were first collected and then qualitative data was used to better expand and explain the data (Creswell, 2005). In this study, a mathematical SNA served as the quantitative phase and open-ended survey questions provided the qualitative expansion data. The study hypothesized that an SNA could identify new knowledge regarding emergent learning design through 1) the location and documentation of expertise and 2) follow-up knowledge collected and vetted through these experts would deepen, probe and expand each participant’s understanding of successful practice in emergent learning design. A research triangulation included the (a) SNA of the Blogosphere regarding emergent learning; (b) questionnaire presented to the participants located via the SNA; and (c) the participants’ verification, expansion and editing of the summary of questionnaire findings via a collective Wiki. For the questions asked in this study, and the need to better understand the knowledge embedded within new e-learning design practices, the SNA and collective Wiki provide a demonstration of the rigor and potential for inquiry within new e-learning design practices. Figure A1 explores the flow of this two-phase, exploratory research design.

Phase 1: Social Network Analysis Modern social network analysis had its beginnings in sociometry or the measurement of relatedness amongst members of a group (Wasserman & Faust, 1994). Current research shows a variety of disciplines now using SNA to explore hidden resources and relationships that reside within groups. In probing this methodology, Birk

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(2005) reviews a body of ideas and evidence related to the use of SNA as a research tool to make knowledge known and visible within an organization or community. This research study is based on findings that the SNA methodology can locate and reveal knowledge that resides across a community. New possibilities in the use of SNA technology applied to a community of practice creates opportunity for determining consensus on knowledge through discovery, validation and documentation. In doing a social network analysis of library media specialists, Little (2006) made the case that the methodology allows a unique look into authority, expertise and influence across a distributed community, with the results defined by the members of the community itself. Little claimed that in searching for information or knowledge, one searches first amongst direct contacts, but if the expertise isn't available, a common approach is the snowball method of having others "direct you to someone else who can help you extend and focus your research" (p. 34). Little looked to the earlier work of Monge and Contractor (2003) in using SNA as a way of applying transactive memory theory (distributed cognition practices that create shared knowledge) to a geographically divided community. According to the theory, transactive memory processes include (a) expertise recognition, (b) retrieval of information from the recognized experts, (c) directory updating (Who knows what?), and (d) information allocation (Who else needs to know this information?). Due to the Blogosphere framework of identifying subject matter experts both by 1) blog search engines that identify sites with most frequent visits for a key term and 2) blogger practice of creating blog rolls that list the blogger's trusted and valued sources, the integrated and dynamic information source can be seen as an ideal new SNA

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environment for determining and creating shared knowledge from expertise of respected and valued resources of this distributed knowledge community. Data Collection The data collection for phase 1 of the study was done through recording the results gathered when putting key terms in two separate blog search engines, and by the use of NetDraw™ SNA software to do the analysis of the results. The focus of phase 1 was to quantitatively determine and document expertise on emergent learning and organizational knowledge design. A variety of key terms used in the initial search allowed for a broad retrieval of interested researchers and practitioners writing and working within the research topic. Broad and specific semantic terms that were uncovered in the literature review were used to accommodate the variety of disciplinary practices now focusing on aspects of emergent learning support in the workplace. These included: (a) organizational learning, (b) organizational knowledge, (c) informal learning, (d) just-in-time learning, and (e) emergent learning. The data was collected via the two most popular Blogosphere search engines, Google™ Blog search and Technorati™ Blog search engine, as both use search methods based on proprietary ranking logic, rather than mere newness of results. Technorati uses authority: the number of blogs linking to a Web site in the last six months. The higher the number, the higher is Technorati’s ranking of authority (Technorati, 2007). Google uses relevance: a combination of (a) authority (or number of links into the site) and (b) Google Page Ranking™ that analyzes where the information comes from. Linking pages that have stronger authenticity weigh more heavily in the resulting retrieval order or relevance of listing (Google, 2007).

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The study recorded retrieved blog sites and then followed the retrieved links for most recommended or trusted sites via blog rolls wherever available. From the initial results of search links and blog rolls, the research penetrated into a third layer, recording the blog rolls of most trusted sites found in the data. Hyperlink addresses, calling sites, search engine used, and type of result (content link or blog roll) of these sites were recorded in NetDraw™ and the data made available on the research Web site (Carmean, 2008). Data was analyzed for strength of nodes based on a K-Core analysis of strength of information flow from and to the sites. From the SNA, a visual picture of the trusted and followed bloggers who are thinking, working or researching within the fields of organizational and emergent learning was created. Twenty two resources were contacted and asked to participate in phase 2, with fifteen participants agreeing to contribute.

Phase 2: Collaborative Knowledge Design An assumption of this research study was that experts already sharing their expertise and experience would be interested and willing to participate in a collective inquiry in creating new understanding related to their experiences and research. After contacting the participants via an e-mail request to participate (Appendix B) and receiving informed consent (Appendix C) via e-mail response, phase 2 of the study gathered responses to six, open-ended questions via an online survey (Appendix D). Data Collection The responses were summarized to a shared Wiki that documented an understanding of findings. At the Wiki site, participants reviewed definitions, framework and summary of the findings. They were able to create user accounts and given a two

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week window to extend, revise and enhance findings. This data collection framework provided an open, online and dynamic research opportunity to gather and vet what is known by an identified group of community-trusted resources. It allowed for collaboration and consensus-building in the revision and clarification of understanding by the participants during the Wiki phase of the triangulated process. Results from each phase of the study have been made available as separate study artifacts within the dissertation appendix, based on IRB approval of the public process and on consent of respondents. The study data is archived (Appendix E) and the living document is now public to the wider community via the New Media Consortium (2008). All study artifacts will remain available at the research study Web site (Carmean, 2008).

Confidentiality The shift in knowledge brought about by Web 2.0 culture and the shared, public, and open exchange of information creates an antithesis for participant confidentiality in this study. The participants located via the SNA were public bloggers, and asked to participate in a public, shared experiment in knowledge creation. The participant consent form (Appendix B) acknowledges the non-confidential, public and Internet-based framework for the study. All participants agreed that their blogs, work of the research study, collaborative understanding and results would be available on the open Web. The online survey sent to consenting participants and used to create the initial tag clouds and summary document for the collaborative Wiki is found in Appendix D.

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Reliability and Validity A discovery process is only valid to the degree that it can reveal or verify the practices, resources or realities that it sought to find. The validity of this study is based on the repetition of inquiry regarding the topic explored. Jick (1979) demonstrated mixed method validity through the use of triangulation of diverse methods applied toward the same phenomenon to better understand the findings. Evidence and expertise collected via the Blogosphere, questionnaire sent to the participants, and ability of participants to edit and enhance collective responses and understanding provides the triangulation framework that is believed to be crucial to validity in mixed method research. The ability of the participants to review and enhance the researcher’s summary and understanding of findings via the collaborative Wiki also responds to Cicourel’s (1982) observation that reliability can be tied to the participant’s ability to review, respond and to get clarification of understanding. The multiple approaches to discovery and consensus-building within this study design creates a framework of triangulation and correction that diligently addresses reliability and validity.

Generalizability External validity of the research design, or generalizability of the results, was considered in two categories for ensuring integrity of the study: population validity and ecological validity (McMillan & Schumacher, 2001). The wide net of readers that the SNA will analyze, based on millions of blog sites, brings in a diversity of population never possible before the Internet. Search engine logic, and the ability to focus results across a net that transcends time, place and demographics creates inherent

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generalizability within a digital population. Although the results may not bear evidence that allows for generalization outside of the framework of organizational knowledge, due to the reach of the Blogosphere it is hoped that new knowledge regarding successful emergent learning design practices will be applicable to more diverse environments and learning populations. Ecological validity within the study is focused primarily on ensuring that the semantic net surrounding the constructs of emergent, informal, just-in-time, and organizational learning are understood similarly between the participants and that the terms actually define and address the same understandings across different organizational cultures and practices. The collaborative Wiki included the definitions outlined within the study. By providing a framework of terms and understandings, both at the beginning of the study and embedded within the final participant-created document, operationalization of the study will be placed not in fixed times or places, but in fixed understandings made concrete by agreement of the participants. Although digital information changes the way we may demonstrate validity of research, the foundation of evidence, intention and application remains intact, if not strengthened by ubiquitous access and diverse methods of communication.

Purpose of the Research The primary goal of the investigation was an exploration of environment design that supports emergent learning within the organization. At the core, it seeks to better determine the nature of design within an emergent learning environment. The study worked with participants to collectively gather, document and reach consensus related to

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the research question. Collaborative inquiry asked the participants what is known regarding the characteristics of environment design for emergent learning and shared knowledge. The major contributions of this research study are twofold. First, it explores and documents the use of social network analysis in identification and documentation of knowledge stores as a knowledge design/support tool and second, it uses the results of the SNA to further explore, capture and summarize consensus-built understanding of the nature of e-learning design for the not yet well-understood realm of emergent learning and shared knowledge creation.

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CHAPTER 4. DATA ANALYSIS AND RESULTS This collective inquiry study focused on best practices in e-learning design for emergent environments. Emergent learning was defined as self-directed, individualized, informal learning that contributes to distributed knowledge within a larger organization or network. The definition, and use of the term emergent, was constructed within the framework of emergence theory (Johnson, 2001) and the increasingly complex behavior when individual components affect collective outcomes in connected networks. The study focused on effective design for emergent learning environments, especially within complex organizational knowledge networks where digital learners act independently to create, find and share knowledge. To better understand the role of design and support in emergent learning, the study looked to practitioners now working, designing and writing about their experiences in shared knowledge environments. In the first phase of the study, experts were identified via a social network analysis (SNA) of the Blogosphere aimed at identifying the most read and followed bloggers on the topic. By analyzing the results of blog search engines, the resulting hyperlinks and the blog rolls (recommended blogs) of those links, the SNA identified the most read, trusted, and influential writers on emergent learning and shared knowledge. All SNA within the study was done using NetDraw social network analysis software. In phase 2 of the study, 15 participants across 7 countries were asked six openended questions regarding the nature of e-learning design within unstructured, just-in-

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time, emergent learning environments. These SNA-identified experts participated in a collective inquiry by 1) responding to an electronic survey that broke down the research questions into potentially effective e-learning design practices, and 2) reviewing and confirming the collective summary of findings. The initial summary results were analyzed by the study researcher using visual tag clouds to look for trends, and then summarized to represent all opinions and possibilities, and the findings posted on a participant-shared Wiki. The participants and their blogs became apparent to one another at this point and they were then given two weeks to collectively confirm, edit, and change findings. The revision period also included the option to write to the researcher or talk to each other about the findings.

Phase 1: Social Network Analysis The first phase of the study, the SNA to locate experts, began by doing searches in two blog search engines (Google™ Blog Search and Technorati™) on key terms found in the literature to identify characteristics of emergent learning in work place environments: informal learning, just in time learning, organizational knowledge, organizational learning, and emergent learning. The hyperlinks or uniform resource locators (URLs) collected revealed 91 active, personal blog links retrieved from the two search engines. Each valid URL (hyperlink) was then searched for blog rolls, which are a list of the author’s favorite or “most trusted” bloggers. From this third search, 451 blog rolls were determined for a total of 623 initial nodes (Figure 1). Each of the red dots of this SNA is either a link from 1) searches up to 50 returns deep for each search engine in on each term and 2) tracking and adding the

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URLs of the blog Rolls from all relevant and available links. Although the figure demonstrates a chaotic picture of knowledge on the Internet, it began the process of disentangling and determining the knowledge relationships embedded in trust by progressively focusing on the centrality of the nodes within the SNA (Alvarez-Hamelin, Dall'Asta, Barrat, & Vespignani, 2005).

Figure 1. SNA of initial study data (623 nodes)

A measure of social connectedness, or centrality, within an SNA can be determined by a procedure known as a K-Core that searches for relationships where members are connected to some number (K) of other members (Hanneman & Riddle,

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2005). Running this analysis on the 623 nodes (Figure 2) located 32 centrally connected nodes (central blue dots). In the Blogosphere, these would be considered the most read, respected or trusted nodes on the network regarding the topic of inquiry – emergent learning.

Figure 2. SNA first pass on centrality (623 nodes)

A number of these 32 central nodes had been entered in the data set as secondary blog roll links found at the sites determined from the original searches. By then searching these link sites and combing for further trusted blog rolls of these 32 SNA-identified bloggers, the study added 258 more nodes (URLs of blog sites) in a second layer of

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inquiry for a final total of 881 final nodes (Figure 3). This allowed the expert pool to focus on not just initial results of the search engine, but a more precise look into the Blogosphere by recording who the trusted experts on the topic were all following.

Figure 3. SNA of initial data plus blog rolls of central nodes (881 nodes)

A more orderly pattern of connections was beginning to emerge, but the visual data now clearly showed more links out to low-traffic sites than referral links into trusted sites. The majority of nodes seemed to be end-nodes with only one or two connections.

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To be able to determine a clearer picture of expertise and trust of readers a blog site, the K-Core procedure within the SNA analysis would need to be run to determine centrality and allow the data set to drop least-connected nodes and provide a better picture of expertise. The first centrality selection analysis on the data set of 881 nodes revealed 112 trusted nodes based on 2 or more connections to those nodes (Figure 4). Instantly, 769 least connected nodes dropped away.

Figure 4. SNA K-Core analysis of URLs with 2+ connections (112 Nodes)

The next centrality run revealed only 47 nodes with 3 or more links (SNA levels of trust) in the decreasing pool of bloggers. At this point, the analysis was still not able to

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separate incoming and outgoing links and merely recorded activity, so a number of the nodes that remained in the analysis pool were bloggers that followed numerous respected bloggers, but may not be followed by other bloggers. Continuing to drill down intro centrality revealed a final 33 nodes for 4+ connections (Figure 5), and the picture was now clear enough and the data set small enough to be able to begin to see nodes displaying heavy incoming traffic. SNA trust analysis was beginning to reveal the nodes that search engines or other bloggers respected. Certain nodes were beginning to stand out.

Figure 5. SNA K-Core for 4+ connections (33 Nodes)

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From this data set, one last analysis was done (Figure 6) that eliminated nodes that had less than 3 incoming ties and to display node labels (URLs of the blog sites). Incoming link centrality (followed/referenced by others) dropped the final prospective participant pool to 24 nodes (plus nodes for the two search engines).

Figure 6. SNA Node labels for 3+ incoming ties (24 Nodes)

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The potential participant pool would consist of these 24 nodes. Participant names and country locations are listed in Appendix F, and were made available on the public Wiki site (NMC, 2008). The original Wiki findings were also copied out at close of study and are available in Appendix E. Phase 1 thus explored and determined previously unidentified knowledge resources on the Internet. Using SNA as a method of identifying distributed identification of expertise, phase 1 of the study was able to identify the blog sites of practicing experts in emergent learning design. Expertise was defined by combining values of relevance (Google™ Blog Search), authority (Technorati™), and peer referral of the blogger community exploring aspects of emergent learning. This was done to tap into and test viability of new resources for identifying knowledge on the Internet and to locate expertise that might best understand the relatively unexplored convergence of distributed knowledge, technology and e-learning design. Visiting the blog sites of the 24 nodes revealed that in two separate instances, a single author owned two sites, thus decreasing the participant pool. In another instance, one site had joint authors. Thus, of 24 sites examined, 23 requests for participation were sent out. Authors of the sites were contacted electronically regarding a request to participate in the study (Appendix B). Of these 23 potential study participants, 15 initially agreed and 1 joined on later in the study.

Phase 2: Collaborative Knowledge Creation In the second phase of the study, the research questions were addressed through a process of (a) online survey, (b) analysis of survey findings, (c) visual and qualitative

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summaries of findings posted to a participant-shared Wiki, and (d) participant verification via the Wiki of distributed understanding and consensus. The online survey, hosted at SurveyMonkey.com, consisted of 6 open-ended questions (Appendix D) that could best address the study’s 3 core questions. Participants were given 2 weeks to respond, at which time the results were compiled for each question using both visual tag clouds (Figures 8-13) and via a narrative summary. Using tag clouds, important concepts or recurring themes are revealed as larger fonts in the words or phrases, creating a cloud of recurring ideas within the original text. Once the narrative summary and tag clouds were posted on the Wiki, participants were given two weeks to question, confirm or revise the findings. Each was able to create an account and password at the site and edit the narrative. One invited participant, not able to respond in the survey phase, did participate in the collective review and revision of the findings. The visual summaries of raw data for each question via tag clouds were produced at IBM’s Many Eyes™ analysis and visualization site (International Business Machines, 2008). Tag clouds were created by loading the unedited text of all responses for each question. The narrative summary for each question was created by 1) examining the tag clouds to determine overarching themes, and then 2) manually crafting a single response that represented focus points as well as any strongly held beliefs. Attention was given to representing agreement as well as all minority opinions. Language of participant responses was changed for spelling, grammar and consistent voice and tense. Although the summary was compiled by the researcher, by sharing the data with the participants via the NMC collective Wiki open only to the participants for review and shared access, any misrepresentations, new shared understandings or omissions was open for correction.

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Research question 1: Inherent Characteristics This research question began the inquiry of effective design by exploring the nature of the phenomenon under investigation. Question 1 of the survey corresponded, asking: What are the inherent characteristics (tools, processes, practices, systems, support structures) of emergent learning environments? Overall, participants noted the effect of emergent properties on shared knowledge and learning. Within this framework, they stated the need to support and encourage diversity – of tools, ideas, ability and approach. Tools might include any effective collaborative technology: forums, Blogs, Wikis, and an online "who knows what" or "ask the expert" facility. Other possibilities include references, communal authoring, personal profiles, intuitive back-channels (e-mail, Skype, IM), concept mapping, image storage and display, text forums, private spaces (sec. 4). The participants identified greater need for development of connections via use of social software, systems and processes. This would be done via an open culture of practices, support for the individual learner/worker, and access to information through community and collaboration tools.

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Figure 7. Tag Cloud for Survey Question 1 Responses

The participants were then asked to explore research question 1 more deeply, but directly addressing the inherent, just-in-time nature of emergent learning. Survey question 2 asked the participants: How might an organization foster the independent, asneeded knowledge acquisition at the core of emergent learning? Participants responded that the organization must create a culture that practices and rewards independence in learning, thinking, and knowledge acquisition. Aspects of fostering this culture would include letting go of control and supporting collaboration through tools supported and approaches that are encouraged. An organization fosters by using the practices in their action. This would be accepted norms of using IM, Wikis, shared document editors for their processes, and not sending documents by email attachments, The organization might do things to recognize and reward network knowledge acquisition, or to make it obvious as its culture. All documents, information is available to all users in the network, so it is pervasive.

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From the bottom up, through grassroots, through a critical mass of early adopters who can test the waters and see what they are like. They would be the ones helping the business evaluate whether it is worth while exploring or not. Trying to push it top down, corporate wide is not going to happen. It's got to be viral, personal, unrestricted, open to everyone, letting command and control go once and for all! (sec. 5).

Ease of access to information and tools throughout the organization, but not constrained or required in use, was listed as necessary support for finding as-needed knowledge. Creation of information-rich environments, where the means of acquiring are diverse, was also believed to foster knowledge acquisition. Participants agreed that reward, time for learning and reflection, and for individual experimentation are valuable to a culture of independent knowledge acquisition.

Figure 8. Tag Cloud for Survey Question 2 Responses

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In summary, participants believed that diverse Web 2.0 social tools, rich support structures (including time, systems and resources), and open access to colleagues and information are inherent characteristics of effective emergent learning environments. Within that framework, no matter how rich the tools and infrastructure, the collaboration skills at the core of effective distributed knowledge must be learned. A culture that supports emergent learning must trust, reward and support independent paths to personal learning in creating shared, distributive knowledge. Research question 2: Collaboration and Networking Significant to understanding effective design for emergent learning is how learners share what they have learned. Within the participant survey, this was asked directly in survey question 3: How might design foster collaboration and networking in emergent e-learners? Participants responded that encouraging communication and networking via the use of diverse social tools and organizational practices is necessary to a culture of collaboration and networking. Employ the usual technology suspects such as discussion boards, Wiki, web-conferencing solutions, IM, VOIP, etc. Use hot links for documents. Facilitate physical meet-ups through architectural design and orchestrated face-to-face events. Support and encourage communities of practice and other community and network constructs. Identify and address roadblocks via organizational network analysis (sec. 6).

In practice, time, encouragement and reward for collaboration were deemed significant. “No one collaborates for the sake of collaborating” (sec. 6). Participants

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agreed that people need support in learning how to collaborate if they are to think, socialize, share information and work as teams. The environment created needs a framework that encourages informal communication and community, allows participants to collect and pass along stories, and provides mechanisms for open, informal conversations and exchanges.

Figure 9. Tag Cloud for Survey Question 3 Responses

Moving deeper into research question 3, survey question 4 addressed the difficulty of collaborating or sharing of tacit information that often goes unstated or is difficult to describe. Survey question 4 asked: How might an organization foster better expression and sharing of tacit knowledge within the organization? Response of the participants noted that fostering better expression and sharing of tacit knowledge is at the heart of shared, organizational knowledge. Following the original work of Polyani (1966) and Nonaka (1994), participants described some of the difficulties in eliciting tacit knowledge embedded in the workplace. Although expressing direct experience was

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described as a challenge, some claimed that, pace Nonaka, it may not be valuable to the organization to denote experiential knowledge as tacit, and thus made mysterious. “While there may be forms of knowledge that I can best acquire through experience rather than formal instruction or transmission, we should identify that and work out ways to help others acquire experience more quickly and more effectively” (sec. 7). Others made the case that tacit, experiential knowledge may be the most powerful knowledge available and that when systems support story-telling within the community, they create a culture that shares experience. Cultures that promote tacit knowledge do so by incorporating knowledge sharing sessions, mentoring, training, retaining relationships with departing key staff, sanctioning pairing, rotation, shadowing on the job, and structured on the job training (OJT) - all in an aggressive manner to create a culture of sharing experience (sec. 7).

Figure 10. Tag Cloud for Survey Question 4 Responses

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Most agreed that encouraging the sharing of personal experience – whether through mentoring, community conversations, story-telling or more formal job training – is extremely valuable to the organization that seeks more effective sharing of organizational or distributed knowledge. Research Question 3: New Roles for Practitioners The last of the study’s 3 research questions sought to bring much of the core experience of the participants forward into new practices for e-learning design. This research question explored: In what ways does emergent learning suggest new roles for design, instruction or performance improvement in the practice of organizational knowledge management? Participant survey question 5 approached this topic by first asking participants about their own experiences: Are there tools or practices that you have found to be especially effective in finding, creating and encouraging organizational knowledge? Participants replied that the tools of Web 2.0, applied differently for diverse environments, have great potential for a changing practice in supporting personal learning environments and shared knowledge practices. These social, collaborative, tools for participants included blogs, Wikis, podcasts, RSS / Atom feeds, podcasts and social bookmarks. Technology explored by the participants also included group meeting tools that provide shared creation/expression, critical thinking tools, workplace job aids, performance analysis tools, informal learning tools, and personal knowledge management tools. Implementation and support for system environment tools were also seen as effective possibilities for knowledge access. These might include a people directory, mentoring schemes, search tools, teleconference tools, and large group processes.

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Practices thought valuable included after action reviews and support for communities of practice.

Figure 11. Tag Cloud for Survey Question 5 Responses

Overall, the participants shared rich history and deep experience in testing, implementing and demonstrating value of new collaborative technologies and practices in support of emergent e-learners, but made the case that technology is not enough. The organization must have a central drive to support use of the tools if emergent e-learners are to be effective at finding and sharing knowledge. It is not the tool or the practice, but purpose. “The idea is that having clear direction and a means to get there helps remove a lot of uncertainty around whether a given idea is going to provide value” (sec. 8). The last survey question (6) also helped to define new design practices by asking: Are there tools or practices that you have found to be especially effective in finding, creating and encouraging organizational knowledge? Participant response reflected their

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greatest priority in creating a more effective digital workspace. Many replied that although technology will certainly be the driver, learning designers will fare better by focusing on the cultivation of a new, social mindset within the organization. Social, Web 2.0 collaboration tools are vital but will not succeed without support for their use, as “our practices of using them are often guided by old sets of values and internalized routines” (sec. 9). Effective design of emergent learning environments depends on an organizational culture conducive to knowledge sharing. Participant experience was that social technologies make little difference without the trust, openness, and culture that supports the individual in their discovery and contribution to the whole. An environment that encourages and supports curiosity, independence, empowerment, fuzzy boundaries and shared controls of knowledge creation is vital to an effective digital workplace. The goal of the environment would be to allow for better digital connectivity through knowledge skill development and demonstration in each, individual member of the organization. The environment should be seamless, allowing technology to seem to move more into the background, while simultaneously becoming even more powerful and understood by the user. For designers of these environments, it “will continue to be a challenge dealing with locating information, fuzzy boundaries, shared controls, knowing what we really need, how to find it and taking responsibility and risks to go for it” (sec. 9).

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Figure 12. Tag Cloud for Survey Question 6 Responses

Phase 2 Findings Upon close of phase 2, the final version of participant findings (Appendix E) was copied from the Wiki site, and the site itself was made open and available to the NMC social knowledge community for ongoing exploration. All original tag cloud figures are available in color via the participants’ Wiki site (NMC, 2008) and these and all SNA figures are available at the author’s research site (Carmean, 2008). Asking practicing, well-respected experts across seven countries to reflect on their experience in preparing for an emergent learning paradigm produced a rich, thoughtful look at practices of the vanguard of a profession in transition.

Summary of the Data Review of the data collection and analysis for this two-phase, mixed methods study was provided in this chapter. In phase 1, potential participants were located via a social network analysis of the Blogosphere. To determine expertise, a reductive analysis

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of centrality was able to locate 22 of the most followed and trusted bloggers on topics related to the practice of design for shared knowledge and emergent learning. In phase 2 of the study, 15 participants from 7 countries answered an electronic survey of 6 openended questions regarding better understanding of effective practice in design and support of emergent learning environments. Survey responses were summarized by the researcher using visual tag clouds and narrative summary. Results were then placed on a Wiki that study participants were able to review for representation, understanding and consensus. At this stage, one more invited participant was able to contribute in the data revision and review phase of collective understanding. The final version of findings was then copied from the Wiki and is available in Appendix E. Once the revision period closed, the Wiki site was then made openly available at the New Medium Consortium host site for the NMC community to continue to edit, improve, and provide new or contrasting ideas (NMC, 2008).

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CHAPTER 5. RESULTS, CONCLUSIONS AND RECOMMENDATIONS This chapter is organized into five sections that explore research findings regarding e-learning design for emergent, shared knowledge environments. These chapter sections include: (a) overview of the research, (b) limitations of the study, (c) conclusions from the data, (d) creating a shared knowledge architecture, and (e) recommendations for future research. Overview of the Research This study focused on understanding emergent learning environments where learners act independently to create, find and share knowledge. The research was premised on increasing evidence that digital, networked connectivity has created a justin-time knowledge culture where learner expectations are not being met by current practice in e-learning design. The study focused specifically on organizational knowledge and looked at (a) inherent characteristics of emergent learning; (b) fostering collaboration and networking in knowledge environments; and (c) ways that emergent learning suggests new roles for design, instruction or performance improvement. To answer these questions, the study design focused on practitioners now working, designing and exploring workplace e-learning environments and used the world’s largest shared knowledge environment, the Blogosphere, to identify potential study participants. The study located 881 data points based on search engine and blog roll results related to the research search terms. Via a social network analysis (SNA) of

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expertise, as determined by referral of trust in the readership, the SNA analysis of the data identified the 22 most read, trusted, and influential writers on workplace e-learning and shared knowledge. Of these experts, 16 agreed to participate in a collective inquiry exploring the research questions. In phase 2 of the study, participants spread across seven countries were asked six open-ended questions regarding unstructured, as-needed and shared knowledge. The data from the Web-based survey was first analyzed using tag clouds (Figures 7-12) to identify themes, duplication and consensus. The researcher then did a qualitative analysis, searching for exceptions, disagreement or new ideas. Initial findings were summarized to a participant-shared Wiki hosted at the New Media Consortium Web site (NMC, 2008). The participants were given two weeks to confirm, edit, enhance or disagree with the compiled findings. Changes were accepted on the site, as well as via e-mail and by phone. All participants signed off on agreement regarding final results. The Wiki findings are available in Appendix E, and the NMC intends to keep the Wiki site available to the public for further sharing of knowledge and ideas.

Limitations of the Study A number of limitations must be noted in the design and approach used in this study. First, the data reflected the personal experiences and understandings of 16 participants. Were the SNA to be run again today, the identification of experts, as well as collective understanding of those same experts, might very well reflect a very different picture. Personal experience and understanding of a select group of practitioners creates the possibility that what is now known or believed to be true by leading thinkers can

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change as quickly as the individual tools and practices being considered by the participants. Similarly, many of the findings relate to the use of specific social technologies that offer potential for better digital collaboration. With the rapid change in tools available, the likelihood is strong that today’s magic bullet will be tomorrow’s forgotten technology as new Web 2.0 applications are released and improved. Further studies would be needed to determine whether the tools explored will prove to have long term effect on participation and creation of shared knowledge. Given the rapid changes in these technologies, the study design’s use of research tools enabled by the Internet is also a limitation to be considered. The use of SNA for analysis, of a Wiki for collective inquiry, of tag clouds to understand first-look data, and of the Blogosphere to identify trusted experts will all need further exploration and evidence of value as research tools. Although they provided access to rapid and shared understanding in collective inquiry, only their continued use in research design will determine their reliability and effectiveness in practice. Lastly, the study focused specifically on emergent learning as related to the workplace and the demands for organizational knowledge creation. Although much of the evidence suggests that emergent learning is a phenomenon of access and connectivity that affects behavior of digital learners everywhere, findings and recommendations on practice are strictly limited to the digital workplace. To further generalize these outcomes and new understandings, it would be necessary to test the framework in other environments. Especially valuable would be further research on potential application of emergent learning to higher education and the digital learner now rising in the population there.

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Conclusions and Implications A significant change in how we think about learning design must happen to effectively respond to the needs of the digital learner. In alignment with the original organizational dynamic predictions of Schein (1992), new uses of technology necessitate new practices and better understanding of tool use in learning and knowledge creation. Findings in this study correspond to research on the potential of social technologies and networked connectivity to create new opportunity to aggregate individual knowledge contributions in creating shared and radically different understanding (McAfee, 2008; McGee, 2007). Findings also demonstrate that effective use of the variety of tools now available demands better understanding and selection for use from the diverse Web 2.0 and knowledge work tools now available. In response to the digital learning shift, the traditionally limited and divided responsibilities of instructional designers, trainers, systems developers, experts, performance advisors and knowledge managers blur when serving just-in-time learners. Rigid roles, set curriculum and inconvenient courses no longer serve the needs or the pace of the digital workforce. Isolated learning ill-prepares those entering a dynamic and inter-dependent work environment. Study findings correlate with claims that effective design for shared knowledge must forego traditional approaches and decisions, allowing use to determine outcomes. McGee (2007) states that in designing a system for emergence, the designers leave a number of these decisions open; waiting for users to fill in the blanks. So, for example, instead of locking down a taxonomy for categorizing documents, the

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designers might provide a tagging system to allow a folksonomy to emerge from the idiosyncratic choices of each user (¶ 3). Emergent learning is forcing a shift from instructional design practice to creating possibility for tool use, dynamic learning and knowledge creation. Changing the intention, tools, process and method of delivery for the next generation of learning designers should respond to emergence in networked participation, but current design models and practices ignore collective understanding at the heart of emergent learning. “The bottom-up hive mind will always take us much further than even seems possible,” but at the same time, “the bottom-up hive mind will never take us to our end goal. We are too impatient. So we add design and top down control to get where we want to go” (Kelly, 2008, ¶ 26). This shift in bottom-up design will succeed only if next-generation designers participate by framing top down resources while understanding their own inability to predetermine or control outcomes. Successful top down design for bottom-up learning, created by a shift to social, networked knowledge that puts the information of the world at our fingertips, depends on better understanding of the needs and characteristics of emergent learning. Although previous generations of educators have claimed that it’s not about the technology, in reality, this may not be true today. The proliferation of innovative, disruptive technologies now available and being used suggests that perhaps at this point in time, technology is intrinsic to the experience of shared knowledge creation. We learn differently when the act is enabled through a shared knowledge architecture and a distributed network of information access. Emergent learning IS about technology and about its disruptive, transformative possibilities.

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Inherent Characteristics of Emergent Learning Throughout the study findings, the research question regarding inherent characteristics returned to the learner’s ability to find, create, modify and share knowledge. New, emergent systems determine expertise by continuously aggregating the knowledge of the collective. Amazon.com tells us what books we will enjoy by aggregating the readings of others with similar interests. Google finds our resources by ranking the sites most chosen by the collective. Digg allows the audience, not the media, to choose top stories of the day. Similar logic drives networked expertise across the organization but participants were clear that success within organizational knowledge environments demands better training, implementations, support and practices. Top-down design and support is still needed if the learner is to be proficient in accessing and evaluating this new aggregated, shared, and socially-constructed expertise. Study findings were similar to those long claiming digital network dynamics will be centered on a “two-way flow of power and authority based on information, knowledge, trust and credibility, enabled by interconnected people and technology” (Husband, 2007, ¶ 2). Participants stated that better learner understanding of the social tools that make dynamic knowledge possible will be needed if we are to see effective practice realized. If the strength of a learning ecology is in the contribution of all members, then trust that the organization can support new ideas, risks and mistakes is a vital characteristic. This will not come easy to current cultural practices in the workplace and will demand a new way of thinking about socio-technological environment design and the very nature of distributed knowledge.

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Support for these emergent networks will require a radical reinvention of purpose within the practice of design. Designers must understand how technology now drives and demands what Argyris (1991) had identified as reexive or double loop learning and its focus on self-reflection and personal responsibility. Design would reflect solutions for the learner to dynamically find and evaluate information when needed. New learning environments would be designed to support, organize, and make sense of shared information retrieved from the global storehouse now available online, seamlessly integrated from the organizational data and the expertise and resources available in diverse modalities (people locators, job aids, discussion boards, etc). Expectations are that deep learning must be made more contextual and immediate to the learner’s needs. As participants stated, “there is no curriculum in the real-world and attempts to impose one will interfere with whatever learning might actually be there to be had” (sec. 5). Connected learners have not only changed how they learn, but how they seek and synthesize information. The prediction of a new literacy is now being realized in the collective understanding of the digital learner. Whether this new literacy is labeled visual, post-oral, information or digital, the outcomes and behaviors suggest an evolution of human capability and understanding (Ong, 2002; Ridley, 2004). This shift must be met by a new, reflective practice for learning designers if they are to be responsive to learners seeking deeper understanding of tools, process and possibilities in their search for the right information at the right time, via the right technology. Fostering Collaboration Change has been rapid in the development and acceptance of social technologies such as blogs, Wikis, RSS feeds, resource locators, folksonomies, collaborative

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documents, search tools, etc. Dynamic knowledge can be made easier with a deeper understanding and implementation of these social practices and tools now available. Responses to the question of design that fosters collaboration indicate that practice should focus more on the importance of the network itself and the strategic adoption of Web 2.0 tools. This should be done “in order to help empower knowledge workers to share, collaborate and network with other peers without the hassle of having to figure it out by themselves first” (sec. 6). Collective use and shared understanding should/must result in more effective use of the tools. Enabling each learner’s enhanced digital literacy and use of social technologies within the daily workflow becomes the purview of the workplace designer. This position, still undefined in current practice, is becoming a more strategic need in the digital workplace and may include the responsibility of educating the next generation workforce in currently unmet skills for a digital economy. If print-centric educational institutions continue to fail learners in developing these needed visual literacy skills (Metros & Woolsey, 2006), it will become imperative for the digital workplace itself to create literacy in decoding and encoding of non-print material. To do this, designers would need to provide not training but “the places, people, and resources needed” (p.82) to become visual producers of new knowledge. Following the predictions of Nonaka (1994), an aspect of this literacy would include the knowledge worker’s ability to share tacit knowledge and experience not easily captured in print or in transmission of information. The learning environment must allow for the capture of what is known as well as what is written. Cultures that promote tacit knowledge “do so by incorporating knowledge sharing sessions, mentoring, training,

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retaining relationships with departing key staff, sanctioning pairing, rotation, shadowing on the job, and structured on the job training (OJT) - all in an aggressive manner to create a culture of sharing experience” (sec. 7). Creating environments that support tacit knowledge and more direct communication between individuals, whether in finding justin-time subject matter expertise or in sharing of stories, provides for access to the experience of others and enable access to the more elusive and expert knowledge embedded in a community. Capturing experience as story telling can also be done with new technologies that might include podcasts, videos and case studies. Tacit knowledge thus becomes explicit understanding through experience shared. Study findings on the value of creating opportunity for exchange of community-based knowledge aligned with Gurteen’s (2008) KM work on Knowledge Cafes that create a space for a community to “surface their collective knowledge, share ideas and insights and to gain a deeper understanding of the subject and the issues involved” (What is a Gurteen Knowledge Café?) A shift from elite knowledge acquired to the search for knowledge within the collective is thus turning instructional practice on its head. Within the network, no one is as smart as everyone. Where the content has been the focus of instructional design of the past, now it is the learners and how they interact with each other and participate in content creation that must be the focus of emergent learning design. New Roles for Designers Learning ecologies, dynamic knowledge, and living connected networks are becoming strategic to enterprise success. Knowledge is no longer static and technology has become an untended ecosystem for our social connections throughout the network

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(Naisbitt, Naisbitt, & Philips, 2001). Understanding, defining, and supporting these ecologies and ecosystems will be crucial to how we learn, do, and succeed in the workplace. A transformative change is needed in how we conceptualize design if the field is to be relevant in meeting the needs of the digital learner. A broader, more technical and more strategic approach to incorporating emergence in design is demanded and a new field of practice seems required. This study’s research findings were much in alignment with claims that high tech and high touch have converged to create new possibility. Technology has come to define our interrelationships and even to become a part of how we define ourselves. Shirky (2008) makes the case that social, networkconnected technologies will amplify group communication in as transformative of ways as the printing press amplified the individual mind and the phone amplified two-way communication. A new learning design that focuses on the support of a knowledge culture, of digital literacy, of participative and independent exploration is at the heart of successful emergent learning. Within the study, participants agreed that this framework is still little understood in practice and that although “the tools and possibilities are now easily available, our practices of using them are often guided by old sets of values and internalized routines” (sec. 9). Design practice needed must encompass tools, process, and support for a high tech/high touch knowledge exchange. Also within the practice, it will be understood that technology “will make little difference without the trust, openness, and culture that supports the individual in their discovery and contribution” (sec. 9). Incorporating these new technologies into workplace learning has potential only because "the beating heart of the Internet has always been its ability to leverage our social

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connections" (Madden & Fox, 2006, p. 5). It is not about adopting the latest and greatest, but rather in sorting through the tools and finding the sustainable innovations embedded within meaningful use that is at the heart of a new practice (Wagner, 2008). A practice that explores and implements innovation by determining affordances, best practice, synthesis, value and application would be at the heart of sustainability. In the knowledge economy, more is expected of the learning designer than the creation of predetermined instructional experiences. Emergent learning design primarily demands creation of an environment that supports dynamic, as-needed, networked knowledge. Evidence from the study, enterprise requirements, and an increasing body of research suggest that design practice in adult learning must shift away from instructional models and structured learning outcomes. Instructional models no longer meet the need of dynamic knowledge seekers. New design requirements for emergent learning will embody design of knowledge networks that encompass tools, practices, machines, search engines, job aids, expertise locators and social connection supports. As the study participants stated, this “change in knowledge skills will demand an environment that fosters the ability to find, create, share and disseminate information” (sec. 9). A new conceptual framework for next generation learning design would include a new design practice for emergent learning and distributed knowledge creation. Inclusion of this practice within the community of instructional and learning designers is needed if the field is to remain relevant for networked learners. Through creation of new practices in design for emergent learning, the field would also contribute valuable understanding and incorporation of diverse strategies for participatory learning. Tools embedded within this design framework would be chosen to meet the needs of the particular enterprise,

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discipline or learner community, but would be comprised of collaboration tools now being tested by the global and digital network. The environments would consist of tools chosen from enterprise (e.g. SharePoint™ and GroveSite™), people and expertise locators, free and open social software (FOSS) such as blogs, Wikis, shared documents, etc as well as connecting to ubiquitous access, strong search logic and a new, always available digital world of information online.

Creating a Shared Knowledge Architecture Traditional e-learning design practices have not met the needs of the anytime learner. Despite impressive growth of the emergent learning paradigm, thoughtful creation of the environment needed to support the learner has gone unrealized. Brown’s (1999) vision of a learning ecology has self-realized without planning, much as a city might without architects. This ill serves learners who must navigate increasingly complex tools, requirements, projects and problems in the digital workplace. Requirements of that workplace have become more complex with the pace of change in a global and digital economy. Meanwhile, the essential experience of learning design has held constant. Instructional designers still work within a framework that defines the predetermined subject and sequence of experience. Instructional design models vary in approach and elasticity, but seldom do they stray far from the paradigm that an expert will define and supply the content while the designer frames the process, approach and outcomes. Standard design practice still does not recognize the role of emergence in the collective or of hive mind expertise in the dynamic aggregation of new subject matter knowledge. Just-in-case design remains the profession’s standard while just-in-time

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learning networks build a chaotic, vibrant ecology of new knowledge from the social technologies and search tools available to them. Just as electricity changed the length and course of a day, networked knowledge shifts the learning paradigm for the workplace as quickly and as decisively. An emergent phenomenon in knowledge acquisition is that the whole is greater than the sum of its parts, which has resulted in a largely unrealized need for a new shared knowledge architecture offered through knowledge architects who replace e-learning designers and who can better address the flow of information and the search for dynamic knowledge, answers, solutions, support and collaboration. This new architectural practice is needed but the need is largely unmet: in the digital workplace, in the growth of the anytime elearner in higher education, in the increasingly networked communities of practice and inquiry seeking place online. The networked learner and the affordances of aggregate knowledge are making current e-learning design practices increasingly irrelevant for learners seeking meaningful, collaborative, distributed knowledge and digital skills. The profession most prepared to meet this new demand, instructional design, has largely ignored the paradigm shift, perhaps because it cannot meet the challenge in its current training and cultural practice. A new practice of knowledge architecture may be more suited to a degree in a new discipline, school or interdisciplinary collaboration. Training in this new practice would need to understand dynamic knowledge and the learning interactions that create knowledge rather than dispense it. Much like a profession that plans for ongoing experience, next generation designers will learn to create environments that take on a life of their own. One can look to landscape architecture as a model to be considered when defining a new knowledge practitioner. Landscape

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architects study requirements of the project, and then choose the flora that best suits the needs of the terrain, intention, and needs of the user. The architect does the research on selection of materials, and then designs, puts in place and sets up supports for care of the landscape. The architect would not assume, plan or control the activities of those that live or visit within that site. Similar professional understandings seem necessary for a new practice in emergent learning design. This practice MUST incorporate responsibility for an integrated architecture of tools and support for knowledge discovery, collaboration, creation and problem solving. A knowledge architecture that supports dynamic learning ecologies requires diverse skills in supporting community; defining and evaluating tools and their affordances; creating as-needed scaffolding supports; and implementing new knowledge aggregators. Success in a practice of shared knowledge architecture depends on understanding right skills and applications for top-down design for the needs of a bottom-up digital network. Successful design and support for increasingly sophisticated social tools, the location of trusted resources, and increased understanding of evaluation and synthesis of knowledge aggregation demands a complex skill set. Shared knowledge architecture will not be easily understood by those not versed in a number of diverse, disciplinary and technical practices. Transformational understandings of the digital shift brought about by Web 2.0 will be needed from the academy if a degree is to be viable in a new disciplinary field of knowledge architecture. This can happen only if the academy is capable of accepting the socio-technological changes brought about by the digital world. As Wesch (2008) states in presentations “the most significant problem in higher education is the

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problem of significance itself.” Relevancy in preparing a new generation to not just acquire knowledge, but to create knowledge is to embrace new understandings of emergent design. Understandings would include digital knowledge aggregation; the conditions of new, digital literacies; and the digital shift’s effect on human capability and behavior. One wonders whether credentialing this skill set can be expected from higher education. The lack of scholarly research on many of the topics contained within the research study and the value of the Blogosphere in determining expertise and understanding not found within the academy is evidence of the rift between scholars and collective discovery. Badke (2008) makes the case that, despite its movement to electronic format of print material, the academy lives in an analog world unwilling and unable to embrace a paradigm shift that lessens the status of elite knowledge. The next generation of learners, digital natives who have little use for analog or elite knowledge, see little value in this post-hegemonic approach to learning. If the academy, mired in an institutional culture that resists collectively determined expertise, cannot take on the task of reinventing the learning paradigm needed for the digital work force, the paradigm will emerge from the bottom-up. Shared knowledge architects will learn from the collective and from a self-inventing community of inquiry how better to support learners in creating the knowledge and skills needed in a digital, global, rapidly changing world economy. While instructional design is offered as an educational or educational technology degree, many of the issues explored by knowledge management practitioners have a history of research and standards developed in business schools. At the same time, technical research and evaluation is offered in applied computing programs within arts

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and science colleges. Nuances of interface, message design, etc are situated in communication. Issues of learner support, evaluation and training remain within the foundation of education programs. In the knowledge economy, the workplace learner might need designers with an applied understanding of how each of these fields contribute to better solutions in finding, creating, sharing and evaluating information.

Recommendations for Future Research Certain areas of inquiry that might guide further studies and inform the practice of emergent learning and shared knowledge design became apparent in the course of this research. As mentioned in the limitations, an exploratory study can only provide a single lens into an understanding of the phenomenon under investigation. Multiple perspectives on new practices in support of the digital learner will be necessary to better understand the transformation of design practice underway. Whether we now look to changes in elearning related to knowledge networking (Chatti, Jarke, & Frosch-Wilke, 2007), mobile learning (Wagner, 2005), design for workflow learning (McStravick, 2007), or personalized learning environments (Dolog, Henze, Nejdl, & Sintek, 2004) it is inevitable that networked connectivity and social technologies are changing how we learn and only diverse, thoughtful research on effective practice will allow for understanding of how best to meet the needs of the digital learner. Knowledge network software is already being released into the enterprise market with little understanding or design for effective use. Research on potential for knowledge environments supported by tools like Microsoft SharePoint™ Technologies, Epsilen™, or Google Sites™ would bring the field more in alignment with needs of the workplace

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learner. Research is also needed on the diverse technologies uncovered as favored by networked e-learners, especially the use of blogs, Wikis, shared documents, social bookmarking, RSS feeds, digital story-telling tools, search tools and expert locators. In particular, when given the choice, which tools will be most successful and most readily used in creating and in finding knowledge within the organization? More specifically, learning design research might want to determine ways to study what singular affordance (Carmean, & McGee, 2008) or collectively researched and understood value of a new technology is to be realized in its particular adoption in meeting learner needs. One can pare an orange with a set of pliers, but it makes a mess of the orange. Similar can be said of the current use of social software. A blog is not a Wiki is not a shared document, and thoughtful practice will be needed to determine how best to raise this level of understanding and practice of tool selection in the new digital knowledge worker. Study participants also expressed a desire to better understand incentive in contribution to shared knowledge. They believed research is needed on exploring aspects of the culture shift that will support the creation of distributed knowledge networks. Design for contribution is much less understood than design that allows for the learner’s retrieval of shared knowledge. Research on the conditions, incentives and reasons that participants share their knowledge would be beneficial for learning designers and knowledge managers. This study demonstrated that e-learning design is shifting to include environment design that supports personalized, as-needed knowledge. How best to design environments that assist e-learners in finding, creating and sharing information is a rich

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field for potential research. Tools to best support that practice and the design skills needed to effectively use the tools are yet to be defined. How to prepare new practitioners for the changing skills required of a learning designer has barely been explored in instructional design curriculums and evidence in the Blogosphere suggests educational preparation is not responding to a business need. In a recent survey of degrees needed or useful in the practice, results suggested that only 27% have or need a degree in the field (Bean, 2008). Comments attached to this Web data suggest that degrees are little valued because currently an ID degree “opens many doors but that's about it. Nothing I learned is actually applied today.” Another suggested that is because very few programs understand the learning shift, but are valuable in shared experience wherever they do. “I focused on Communities of Practice and learned quite a bit. Much of what I learn feeds right into these changes we see in the industry with the focus on informal learning and social media.” Finally, it would be of great help to the next generation of e-learning design and research practitioners to understand the potential of social networks for their own discipline. Creating a more organized, digital community of practice within the design community may be needed if the discipline is to advance a rich conceptual framework related to the next generation of e-learning. If, as emergence theory claims, the whole is indeed greater than the sum of its parts, then it would benefit learning designers to participate in their own distributed knowledge environment. In this way, they could share possibility, increase relevancy and transform practice. Emergence, connected networks and the creation of shared knowledge are clearly needed within a new community of

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shared knowledge architects most able to define the e-learning experience for the next generation of digital learners.

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APPENDIX A. FLOW OF THE DATA COLLECTION

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APPENDIX B. REQUEST TO PARTICIPATE Request to Participate in a Study on Knowledge Design Researcher: Colleen Carmean Title of Research Project: Design 2.0: Emergent learning and Organizational Knowledge Greetings! As a PhD candidate at Capella University, I am researching new tools and practices in elearning. My dissertation focus is “emergent learning” – informal, just-in-time, selfregulated learning that contributes to collective knowledge creation and management. Evidence in the literature suggests that new technologies and the affordances of Web 2.0 greatly increase possibilities, but that the tools are not enough and new learning design and support practices would improve successful creation and sharing of knowledge. The first phase of my research was to do a social network analysis of trusted Bloggers who are writing on topics related to the research questions, and in the opinion of other Bloggers, your Blog is one of the most visited or trusted sites. It is my theory that collecting and vetting the ideas of thought leaders regarding potential tools, practices and processes of emergent learning will advance the practice of e-learning design and knowledge creation. I am asking up to ten community-identified trusted resources to: - answer a questionnaire regarding experiences and ideas related to Web 2.0 tools and practices related to learning or organizational knowledge creation - participate in a Wiki experiment that revises, revisits and elaborates on the collective findings from the summary of the questionnaire results and responses. If you’re interested in participating or have any questions, please visit the study Web site for more information: http://cmcarmean.googlepages.com. You’ll find the consent form available at the site. Please reply to this email regarding your interest in participation and, if interested, more information and details will follow. Colleen Carmean ([email protected]; 602-291-7198) PhD Candidate, Capella University Program: Instructional Design for Online Learning Dissertation Committee: Dr. Rod Sims (chair), Elena Kays, Patricia McGee

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APPENDIX C. INFORMED CONSENT CONSENT FORM FOR RESEARCH Researcher: Colleen Carmean Title of Research Project: Design 2.0: Emergent learning and Organizational Knowledge Greetings! As a noted Blogger on the topic of digital e-learning and knowledge creation, you have tentatively agreed to take part in a research project described below. The original email query regarding the project, sent to you by Colleen Carmean, is attached below. If you have any questions related to the study or your participation, Colleen Carmean ([email protected]), the person mainly responsible for this study, will gladly discuss them with you at any time. You must be at least 21 years old to be in this research project. Description of the project: You have been asked to take part in the study that collaboratively determines effective practice in the design and support of independent e-learning and shared knowledge creation. What will be done: If you decide to take part in this study here is what will happen: phase one entails a questionnaire on effective practices, tools and processes that can be used to support informal, self-regulated learning and how that knowledge can best be made available to the larger group The data will be collected and summarized by the researcher and published as a first draft on the study’s Wiki site. Along with the initial findings, a collection of terms, definitions and core understandings that come from the literature and from a review of participants’ Blogs will be posted. The Wiki will be opened to participants and over a period of a month, where participants will collaboratively revise, suggest new content, vet and collaborate on collective understanding of new possibilities for effective practice in the design and support of emergent, self-organized learning and knowledge creation. Risks or discomfort: No risks or discomforts are expected from the knowledge you choose to share.

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Benefits of this study: Although there will be no direct benefit to you for taking part in this study (rewards, incentives, etc), participation in a research project on the nature of connected, digital knowledge by a group identified as the Blogosphere’s most ‘trusted’ experts on the topic, along with the ability to shape new knowledge on nascent e-design practice could prove beneficial to your own work on the Blogosphere and in your professional life. Confidentiality: The research design of this study is an Internet-based summary of findings, published via a Wiki. Due to the public nature of your Blogging, and the study’s use of collaborative, Internet Wiki to explore knowledge, confidentiality is necessarily waived. All documents, findings and information related to the study will be published as links off the researcher’s Web site (http://cmcarmean.googlepages.com), and available publicly. Phase one questionnaires will be anonymous as to individual contribution with only the results and ideas published to the site for further vetting by the participants. Decision to quit at any time: The decision to take part in this study is voluntary. If you decide to take part in the study, you may quit at any time. If you wish to quit, simply inform Colleen Carmean ([email protected]) of your decision. Your name will not be published in the findings, but any contributions of knowledge and ideas will remain on the Wiki. Rights and Complaints: If you are not satisfied with the way this study is performed, you may discuss your complaints with Colleen Carmean via email ([email protected]), phone (602-2917198) or Skype (Colleen Carmean). In addition, you may contact Colleen’s dissertation chair and research sponsor, Dr. Rod Sims ([email protected]) or write to Capella University with your concerns. Your signature on this form means that you understand the information and you agree to participate in this study. Please Fax the signed consent form to Colleen Carmean at 602543-3260 or attach digital signature to the document and return via email ([email protected]).

________________________ Signature of Participant

________________________ Signature of Researcher

_________________________ Typed/printed Name

_Colleen M. Carmean_______ Typed/printed name

__________________________ Date

____________________ Date

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APPENDIX D. PARTICIPANT SURVEY Design and Support for Emergent Learners and Organizational Knowledge 1. Introduction and Participant Agreement Greetings and thank you for participation in this research study on the effective design and support of shared knowledge environments. By completing the survey you are indicating that you have received the Request to Participate and agreed to the Informed Consent document. Both are posted at http://cmcarmean.googlepages.com/ The questions enclosed are open-ended in hopes of better capturing your beliefs and understandings regarding tools, practices and processes that can best support shared knowledge. For purposes of the study, the term "emergent learning" is used to explore the as-needed/anytime/just-in-time learning now experienced and shared in connected network environments. Once all participants have responded to the survey and the data is summarized, you will be asked to affirm, revise or add new understandings to the results. You will receive an email with the Wiki results link once it is open for edits. The entire process should take approximately six weeks, with current status always available at the research site. If you have questions or concerns about participation, please contact the researcher before proceeding. Please continue when ready to answer six open-ended questions regarding your experience, research or understanding of the issues related to design and support of shared knowledge environments. Again, thank you for your time and your gracious participation. Colleen Carmean [email protected] cmcarmean.googlepages.com

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2. Questionnaire 1. Your Name (for validation only; individual responses will remain anonymous and the summary results a collective understanding)

2. What might INHERENT CHARACTERISTICS (tools, processes, practices, systems or support structures) of effective emergent learning environments contain?

3. How might an organization foster the INDEPENDENT, AS-NEEDED KNOWLEDGE ACQUISITION at the core of emergent learning?

4. How might an organization foster the SHARING, COLLABORATION and NETWORKING that many now claim to be at the core of organizational knowledge?

5. How might an organization foster better expression and sharing of TACIT KNOWLEDGE within the organization?

6. Are there TOOLS or PRACTICES that you have found to be especially effective in finding, creating and encouraging organizational knowledge?

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7. What ONE issue is of greatest priority in creating a more effective digital workplace?





Summary data will be analyzed and posted for your approval, revisions and/or comments in early February. A link to the Wiki site with the summary results will be sent to you via email and posted at the study research site. Thank you for your generosity and for the contributions you consistently make via your Blog! Colleen Carmean [email protected]

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APPENDIX E. WIKI RESULTS ON SHARED FINDINGS (Artifact of http://horizon.nmc.org/wiki/Shared_Knowledge_Project)

Shared Knowledge Project e-Learning Design 2.0: Supporting emergence, connected networks, and shared knowledge * Contents 1 Introduction 2 Participants 3 Key Terms 4 INHERENT CHARACTERISTICS of effective emergent learning environments 5 Fostering INDEPENDENT, AS-NEEDED KNOWLEDGE ACQUISITION 6 Fostering SHARING, COLLABORATION and NETWORKING of organizational knowledge 7 Fostering better expression and sharing of TACIT KNOWLEDGE 8 Potential TOOLS or PRACTICES for finding, creating and encouraging organizational knowledge 9 GREATEST PRIORITY in creating a more effective digital workplace Introduction This document began a snapshot summary of diverse ideas on emergent learning in the workplace. Based on a dissertation research project,* it began with a Social network analysis (SNA) of the Blogosphere. A request to participate was sent to 22 of the most trusted Bloggers writing on topics related to anytime e-Learning and shared knowledge. Six open-ended questions were answered by 15 participants and the results summarized to this Wiki. Participants were then asked to confirm, edit or revise the diverse findings over a period of two weeks. All participants were aware that answers regarding design and support for emergent learning vary according to context, culture and experience. Many stated that there are neither universals nor easy answers, but in general, there was great awareness of the potential residing in the collective. Bloggers have seen first-hand the diverse research, experience and wisdom that resides there.

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Presented here are ideas that represent consensus, difference and a number of basic tenets regarding a digitally connected network of knowledge and reflect the potential ahead for what the Horizon Report 2008 claims will be a collective intelligence available in the patterns, correlations and flow. This research is targeted toward better understanding of emergent e-learners. How can an organization best approach the design and support of a network where individuals, teams, projects and groups are required to find, create and share knowledge daily? Can we collectively define current best (and worst) practice that supports the needs of the digital knowledge worker while at the same time supporting and ensuring each learner’s contribution to the knowledge network? A number of gracious, busy, trusted Bloggers agreed to explore understanding by answering six open-ending questions. Responses were summarized and the tag clouds produced through Many Eyes. Participants were then asked to review, revise and confirm understanding and agreement with the ideas gathered. Once the study phase closes, the Wiki will remain open at the NMC, and hopefully evolve as the community continues to explore the HR theme of collective intelligence and emergent knowledge. Participants Of the 22 invited participants, 15 responded by participating in the survey phase. These generous, community-trusted Bloggers included: Nirmala "Nimmy" Bangalore - India (Aa...hah! Thinking Inside the Blog) Shawn Callahan - Australia (Anecdote) Stephen Downes - Canada (OL Daily) Lilia Efimova - Netherlands/Russia (Mathemagenic) Peter-Anthony Glick - England (Leveraging Knowledge) Denham Grey - USA (Knowledge-at-work) Harold Jarche - Canada (Harold Jarche: Strategies for online collaboration) Alan Levine - USA (CogDogBlog) Jim McGee - USA (McGee's Musings) Clive Shepherd - England (Clive on Learning) George Siemens - Canada (elearnspace) Ray Sims - USA (Sims Learning Connections) Luis Suarez - Spain (ELSUA: A KM Blog by Luis Suarez) David Snowden - Wales (Cognitive-Edge) Jack Vinson - USA (Knowledge Jolt with Jack) One invited participant, Tony Karrer - USA (eLearning Technology) contributed at the Wiki review phase.

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Key Terms Blog: See WeBlog Emergent learning: Self-directed, individualized, learning on demand that contributes to distributed knowledge within a larger organization or network. Seeking knowledge “just in time”, without classes, workshops, grades, attendance, or sequenced instruction. Knowledge management: a range of organizational practices and policies used to identify, create, represent, and distribute knowledge for reuse, awareness and learning across the organization. Learning environment: Although emergent learners can create a learning environment from any situation (book, a hallway conversation, call to the Help Desk, IM a friend, Google or Wikipedia), for the purpose of this study, this would be an online environment designed to enhance a student's learning experience by including computers, software and the Internet in the learning process. Emergent learning environments currently in the workplace include tools for electronic communication (e-mail, threaded discussions, chat, collaborative documents, and editing tools), Web publishing, searchable file services, search engines and subject directories, tagging and Internet links to outside resources. Learning organization: A term coined by Senge in the early 1990’s, a learning organization contains a culture where individuals continually expand their capacity to learn and create, where expansive patterns of thinking and risk are nurtured, where teamwork is expected, and where people continually work to see the whole (systems thinking) together. Organizational knowledge: Knowledge that is created, shared and made available throughout an organization. Key to the concept of knowledge management, organizational knowledge is information that is comprehensively gathered and is key to an organization's operations, processes and success. Social knowledge: Distributed understanding, expertise and collaboration in the creation of information; knowledge reached by consensus across a social network or organization. Social network analysis, social network theory: Social network theory views relationships in terms of nodes and ties. Nodes are the individuals within the networks, and ties are the connections. Social network analysis (SNA) is a map of ties between the nodes that make up a network or community. Social software: see Web 2.0 Web 2.0: Originally coined by Dale Dougherty of O’Reilly Media and brought into popular use by Tim O’Reilly soon after, the term refers to a new generation of software

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and hardware of the Internet that allows for participation and collaboration, and has the emergent characteristic of being better and more valuable the more people use it and contribute to the whole. Web 2.0 social software examples include Blogs, Wikis and social networking environments that contain personal profiles of skills and interests. Tools of the Web 2.0 framework include 1) Google logic, which displays results of search in order of ranking by number of other sites that link to the retrieved site and 2) the ability to tag a contribution by dynamically defined category for grouping results across diverse media. WeBlog or Blog: A site that runs via the user’s Web browser, enabling journal-like entries without needing special skills or coding. These are posted on a regular basis and displayed in latest chronological order. The social aspect of the technology is that each post allows for comments or “trackbacks” from the readers of the Blog. An additional social aspect is the “Blog roll” of trusted or influential Bloggers that a Blog displays and links to from its site. Special search engines like Technorati and the Google Blog Search tool display results of “the Blogosphere” by recentness or by popularity (links of trust) to that Blog. Wiki: a Web site that allows visitors to easily add, remove, and edit collaborative content. Wikipedia, the online encyclopedia of approximately 7.3 million articles in 252 languages written by volunteers, is the most well-known Wiki. This page is a Wiki page. INHERENT CHARACTERISTICS of effective emergent learning environments Tag cloud for participant responses (link) Inherent characteristics were defined as tools, processes, practices, systems or support structures that need to exist within the environment. Dealing with information is more challenging in times of abundance versus times of stability. The exponential growth of information that defines much of our world today requires an approach that is capable of scaling. Despite the value of acquiring information and knowledge as-needed, no single individual can make sense of the complexity and abundance on their own. Social networks and collective intelligence are an important way of making sense. As such, the dominant characteristics of emergent learning environments might include an open, networked, not hierarchical structure that allows for an open flow of unstructured, findable information. To accomplish this, regardless of tools or systems, the organization needs to give up control to the network and to the learners. Support for diversity, and diversity of opinion, is core to effective emergent environments. Concepts are understood in relation to other concepts. As such, the more diverse our information sources, the more accurate our understanding. Transparency and openness would include the ability to see into the communications of the organization.

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Tools might include any effective collaborative technology: forums, Blogs, Wikis, and an online "who knows what" or "ask the expert" facility. Other possibilities include references, communal authoring, personal profiles, intuitive back-channels (e-mail, Skype, IM), concept mapping, image storage and display, text forums, private spaces. New tools in the workplace must allow users to network with each other less publicly. There would be absolutely no censorship, low risk for making mistakes, and a minimum of rules. An atmosphere where mistakes are accepted and encouraged, with examples of others learning from mistakes. Users would be encouraged to contribute content for the benefit of all users, participating in a culture that celebrates learning. This would include processes that inspire learning before doing and tools that facilitate learning, as well as a culture of learning where experimentation is encouraged and where people are recognised for what they know and also how they collaborate with others. Perhaps for emergent learning to occur you also need challenges, fewer resources so that there is a feeling that we need to be resourceful to succeed but most importantly a group of people who share values such as a love of learning, hard work, quality, who know failure is required for learning, know that reflective practice is required. Tools would be networked, run over multiple platforms, changing or evolving, and would be ones in use among external colleagues as well. In general digital material needs to be fragmented, and search mechanisms non-hierarchical. Customization and personalization features would exist within the system to encourage autonomous learning, resource feeds and channels from a diverse range of sources. Connectivity to other systems and other learners would be in place. An expectant behavior is that users are not dependent on user manuals or training classes to learn systems and tools, but instead learn by doing, by using the emergent environment itself. Systems would also provide functions to access and tap into a broad, loosely connected network of colleagues. Learners need the ability to get at previously-accessed content and the ability to connect to other people in a similar learning track. Communities of practice are often discussed as good places for emergent learning, but this doesn’t mean that learning through socializing in a community (re: legitimate peripheral participation) is always effective. New members need scaffolding and support to fully access the available community resources and understandings. Mentors – others who can help you through the learning process should be available within the environment. Access to all kinds of learning resources (mainly people and information, not courses) would be easy to find. Information and knowledge are now democratised from the perspective where everyone is empowered to have a voice and a say in whatever the matter that may drive their interest. The ease of use of those various social tools is helping knowledge workers understand they are now in control of the flow of information, their knowledge, and how they connect with others.

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Time itself would be a characteristic of the environmental culture: time to reflect and to think, without the pressure of deadlines. Reflection would be a constant, even in the middle of the deadlines. Self-driven learning, knowledge and skills are a part of that reflection – knowing how you learn, being able to identify learning needs and opportunities, get yourself through the process, etc. If the only thing an organization rewards is busyness, then emergent learning (or learning of any kind) is not likely to happy. If the time is available, then a variety of practices prove useful in supporting learning. Practices such as trip reports, project journals, and after action reviews all make it easier to reflect on the raw materials of experience to get to better learning. These practices work quite effectively for individual knowledge workers as well as for groups and project teams. Processes might include built-in knowledge capture and formalisation of lessons learned capture. They would include definition and diffusion of best practices. These practices would include formal rewards & recognitions of knowledge sharing. Cultural practices would encourage creativity, risk-taking and mistakes made along the way. These knowledge-driven tools and processes must be given the same level of support as "traditional" business processes. Support would include an IT/IS department with the right skills to support new knowledge tools and services. The environment should be smart, with an ability to provide visibility of people and content, including social network applications and effective enterprise search to discover and make connections with existing content. It could also provide external orientation (customer, partner, academic, analysts, and other thought-leader). Some believe that open source and open standards can encourage system growth and development. Fostering INDEPENDENT, AS-NEEDED KNOWLEDGE ACQUISITION Tag cloud for participant responses (link) Availability of tools is likely the most important aspect of as-needed knowledge. Learners will often find and serve their own needs when they have access to tools. However, it is important to note that organizations will require greater levels of involvement in setting up the ecology of learning, fostering use, etc. than is often assumed. Much like the internet consists of a developed infrastructure, so too will emergent learning activities rest on a well thought out infrastructure that gives the appearance of transparency and use without hindrance. The challenge for organizations is to determine what needs to be managed and what needs to be fostered. Hiring independent and passionate people and then making sure that the independence and passion are not killed by the rules and routines will foster knowledge. Again, one of the most important things is making time for reflection and learning and creating an atmosphere of learning from mistakes and reward for those who share their expertise by rating this highly in performance reviews.

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An organization fosters by using the practices in their action. This would be accepted norms of using IM, Wikis, shared document editors for their processes, and not sending documents by email attachments, The organization might do things to recognize and reward network knowledge acquisition, or to make it obvious as its culture. All documents, information is available to all users in the network, so it is pervasive. From the bottom up, through grassroots, through a critical mass of early adopters who can test the waters and see what they are like. They would be the ones helping the business evaluate whether it is worth while exploring or not. Trying to push it top down, corporate wide is not going to happen. It's got to be viral, personal, unrestricted, open to everyone, letting command and control go once and for all! Other actions that can foster independent learning include ensuring that most knowledge capture takes place during normal business processes. By rewarding & recognizing the provision of knowledge by individuals, especially when not directly concerned by the requester’s purpose. By making the necessary tools available and encouraging people to find information and knowledge through all possible ways. A primary reservation about top-down approaches, however, is that efforts to establish uniformity of practice and transferability of learning, while well-intentioned, general stifle the process rather than fertilize it. Organizations need to give up the notion that they can control learning in any meaningful sense. There is no curriculum in the real-world and attempts to impose one will interfere with whatever learning might actually be there to be had. Beyond providing time, organizations can offer examples of learning in practice, role models of multiple approaches to effective learning, and an informationrich environment that is easy to access (stop trying to limit or control the web sites I can visit, for example). Be patient and not expect to see a payoff in the next quarter’s results. 'Independent as-needed knowledge acquisition' isn't an organizational virtue. That is to say, projects initiated by the organization, for its own benefit, are rarely of the sort that benefit learners, and hence rarely are of the type of learning described. Perhaps it's much more an organizational culture thing than any initiative or project or management process. Organizations that encourage staff to be open, to collaborate on non-work projects with people in other organizations, to share freely, to experiment and fail (etc) are organizations that will foster learning. In such cases, it is likely that the initiatives will be created by - and owned by - the employees, not the organization. The potential of informal learning on the Web is that it can let us be wolves in our learning. We have the means to connect with other members of the pack all over the world. We don’t have to revert to sheepdom so that we can be scheduled for the next course or workshop or whatever the all-knowing organisation has decided is best for us. “I don’t need your course, I’ll learn it on my own and I’ll find others who are willing to help me”.

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Informal, emergent learning is linked to critical theory and that is to question authority, seek the truth and question our own perceptions of reality. Thinking for yourself may be subversive for the organisation but it is necessary for individual growth, as with any child growing into adulthood. The organisation should create opportunities for people to have authentic experiences, and when they can't get those experiences give them the opportunity to hear the stories of other people who have had those experiences, combined with running through scenarios that spark real, reflective thinking. Leaders in the organisation (organisations by themselves don't do anything and can be viewed as an emergent property) need to be thinking of the experiences people need to have to improve their knowledge and the ability for the group to get things done. Recognize achievements, celebrate failures as learning opportunities, allow staff to experiment and fall forward, encourage out of work relationship building and networking, allow 15% of time for personal projects. Establish some version of reflective activity, both individually and collectively. Generous policies and budgets regarding Blogging, book purchases, professional society memberships, attending conferences, etc encourage shared knowledge. Develop ongoing relationships with academic communities. Help employees create their own personal learning environment (PLE). Provide incentives for teaching (both to internal and external audiences) Fostering SHARING, COLLABORATION and NETWORKING of organizational knowledge Tag cloud for participant responses (link) Sharing, collaboration, and networking are not ends to themselves. No one collaborates for the sake of collaborating. Instead, these activities occur in the context of achieving certain tasks. Collaboration and networking are natural responses to the current environment of information abundance. What often prevents people from collaborating, sharing and networking is a lack of skills in how to participate (media literacy skills) or the existence of corporate reward systems that suggest personal achievement is vital. What gets rewarded gets done. Provide mechanisms for making individual interests and expertise easily visible for others (e.g. via Blogging, smart personal profiles, opportunities for an exposure); create conditions for chance encounters with interesting others; Provide and support easy to use communication and collaboration tools, but not require their use. Recognize and reward teams in addition to individuals. Formally allocating weekly time for each collaborator (e.g. the often quoted “20% time” at Google). Allow time to socialise, network, "to stop & think" & be creative within

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exploration. Instilling these values in employees, from the top, is a start. By being visible with actions on public web sites, but using group organizational tools such as tagging for managing organizational information, keyword search, online collaboration tools. Trust that core group of early adopters who are on the bleeding edge of technology will drive the corporate adoption of social tools in order to help empower knowledge workers to share, collaborate and network with other peers without the hassle of having to figure it all out by themselves first. In a networked environment, every node has the ability to influence and contribute to the entire network. One way to encourage contribution is through promoting the use of networking tools, especially collaborative tools that allow for independent inquiry. One example of such a tool is social bookmarking (furl, de.lic.ious, ma.gnolia). Another tool to encourage and promote the use of a personal feed reader, so that each learner can determine their interests and pull in new knowledge on the topic. Demonstrate shared knowledge at the top levels. Encourage people to talk, to share and to explore independent knowledge. Highlight teaming and group success, rather than individual achievement. The organization should get out of the way and give up the notion of control. A culture of shared knowledge doesn't impose arbitrary or artificial barriers on who can or should collaborate, share, and network. Secrecy is never a useful part of strategic business behavior. The organization should reward & recognize individuals who are effectively sharing their knowledge. Another way is to introduce the concept of communities of practice and implement the action-oriented approach. Encourage informal communication and community, collect and pass along stories, allow open questions, foster building core documents, attach contact information to artifacts and documents. Don't try and formally manage it. Allow people to choose their own collaboration tools in a social computing environment. The organization should provide communications tools and encourage (but not require) their use. Make it easy to find others with similar interests – via tools and social network applications. It is important that the organization remove constraints that prevent sharing. Most often, security is an organization's prime concern, and this makes communication very difficult. The organization needs to open these channels of communication (sometimes literally, as frequently internet ports are blocked and software, such as Blogger, disabled). We have seen this already, with organizational postal services, telephone services, and email. The same logic should extend to the provision of Blogs, Wikis, RSS feeds, community websites, etc. Employ the usual technology suspects such as discussion boards, Wiki, Webconferencing solutions, IM, VOIP, etc. Use hot links for documents. Facilitate physical meet-ups through architectural design and orchestrated face-to-face events. Support and

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encourage communities of practice and other community and network constructs. Identify and address roadblocks via organizational network analysis. Finally, the organization needs to have policy support for open communication. Typically organizations tightly control all public emissions, requiring that staff obtain prior approval from a public relations office before communication. These constraints need to be lifted, replaced by a foundation of trust within a framework of guidelines and expectations. Fostering better expression and sharing of TACIT KNOWLEDGE Tag cloud for participant responses (link) It is important to recognize that tacit knowledge cannot be stored or communicated. It is understood and thus the idea of capturing tacit knowledge is contradictory. Tacit knowledge is only produced through direct experience, and isn't shared per se. Perhaps it would be best to abandon the notion of tacit vs. explicit knowledge. This has been a terrible diversion and confusion created by Nonaka. Marking some kinds of knowledge as tacit makes it appear mysterious and different from other kinds of knowledge. Yes, “I know more than I can say,” but the objective is for me to work on making what I know more explicit and transparent to myself as well as to others. While there may be forms of knowledge that I can best acquire through experience rather than formal instruction or transmission, we should identify that and work out ways to help others acquire experience more quickly and more effectively. Having said that, experience (tacit knowledge) may be the most powerful kind of knowledge available, and as such, the need for this knowledge must be articulated within the organization. Those who can share their story need to see that it is valued, who needs it and why it should be shared. To make experience accessible, the organization should create conversation spaces. Tacit knowledge cannot be made explicit in a manner different from how it is created in the first place. As such, conversations and tools that foster conversation are vital. As is the time to converse. Tools that can evoke tacit knowledge might include interview podcasts, videos, capture of story-telling and case studies. Another support for tacit knowledge is through one of the organisms that has been mainly ignored to date, but which has been able to save plenty of different businesses from disappearing: communities. The perfect ground to help foster the sharing of tacit knowledge within the organization is through fostering community. Making use of the latest social software tools both inside and outside of the corporate world will accelerate the adoption of new models of collaboration and knowledge sharing, which in the end are only going to benefit everyone! Encouraging direct synchronous communications between individuals (face-to-face, video conference, instant messaging) allows sharing of knowledge in situ. Unstructured

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communication and formally allocating weekly time for each collaborator to socialise, network, "to stop & think" & be creative fosters tacit knowledge exchange. Cultures that promote tacit knowledge do so by incorporating knowledge sharing sessions, mentoring, training, retaining relationships with departing key staff, sanctioning pairing, rotation, shadowing on the job, and structured on the job training (OJT) - all in an aggressive manner to create a culture of sharing experience. Organisations should aim to increase their storyability, that is, the likeliehood of whether stories are told in the organisation. It helps to give clear definition around what you expect people to talk about -- and what you expect them to NOT talk about (legal issues). Stories are told when remarkable things happen or when people have remarkable experiences. Means of producing direct experiences of successful performance are well known and should be incorporated across diverse cultures. For example, police departments pair inexperienced officers with experienced officers for just this purpose. Other types of modeling and simulation can also generate tacit knowledge. There is also the element of tacit knowledge as being a property of a community (eg. a 'community of practice' as defined by Kuhn or Wenger). The idea is to enable new staff to 'think like' more experienced staff, which requires exposure to conversations and interactions. Therein, tacit knowledge becomes experience told, shown and shared. Potential TOOLS or PRACTICES for finding, creating and encouraging organizational knowledge Tag cloud for participant responses (link) Tools that might work in one case will not necessarily work in another, but again, certain practices encourage collaboration and sharing of knowledge. Reflection time, spaces for dialogue, opportunity to help/share, information literacy, and a culture that encourages free exchange of ideas are cultural practices that encourage shared knowledge. Tools or practices may vary, but those that fit the way people (individuals!) work and address their needs first, before addressing any organizational needs are more likely to be embraced. The practice of forming communities of practice and allowing their members to communicate freely and directly, and whenever possible, to meet up physically at least once/year. Knowledge sharing sessions, communities, expert locators, portals. The use of after action reviews as the simplest tool to get people to thinking about and reflecting on the lessons to be taken away from experience. Focus on helping individual knowledge workers enhance their personal, local, knowledge as the fastest way to increase organizational knowledge. If you want an organizational step to go beyond the support of individual learning, encourage those who are learning to

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teach what they know to others. It increases their rate of learning and the conversations help move the individual learning throughout the organization. Practical tools, applications and processes for training and organisational development include critical thinking tools, workplace job aids, performance analysis tools, informal learning tools, personal knowledge management tools (Blogs and social bookmarks, etc), and tools to help people move from problem to solution. Whatever the content creation systems, they should to be public and transparent with work. Lots of Web2.0 stuff could potentially fit into that category, but it’s not only the tools themselves, but the attitudes of implementing them (e.g. as a company you can introduce Blogging) that would grow into a lively knowledge ecosystem, if done right. Socially, tools like supported forums and Wikis provide space for knowledge exchange. Most likely, successful organizationally supported tools would be easy to personalize, easy to start using in a bottom-up way (e.g. no need to get acceptance of everyone and convince IT guys for a huge investment), social (let people talk to other people, not to databases), simple and easy to use job aids. Tagging tools for collecting, sharing resources are useful. Mainly, Blogs, Wikis, podcasts, RSS / Atom feeds, podcasts and social bookmarks. Group meeting tools that provide shared creation/expression. (Connect/Elluminate). Yes, the usual suspects, but put together into an explosive combination of them all really does help knowledge workers create, find and encourage organizational knowledge. Tools empower the individual to be in control of the knowledge they share, with whom they share it and at the pace they would want to share. Storytelling, business narrative (different to storytelling - more like anthropology), people directory, Blogs, Wikis, social bookmarking, mentoring schemes, collaboration support teams, search, teleconference, large group processes (world cafe, open space, future search). Building joint concept maps, sharing stories, narrative databases, capturing best in class practices, attaching contact information to key artifacts, recognition of failure as a learning opportunity, rewarding knowledge reuse and collaborative activities are excellent practices for sharing knowledge. The telephone and email have been exceptionally successful communication tools in the past. When combined with effective personal record-keeping, these tools result in the generation of a substantial body of personal knowledge for the staff member. More recent tools that have been effective where used include instant messaging, discussion lists (web and email-based), and content management systems. Again, though, their use must be combined with a personal record system - which is why the organization should encourage practices like Blogging.

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In the end, there needs to be a central drive for all these tools and conversations. Theory of Constraints has been found to be an excellent mechanism to set strategy for an organization. With these things set and related tools in place, people can bring out their knowledge around how to implement strategy. The idea is that having clear direction and a means to get there helps remove a lot of uncertainty around whether a given idea is going to provide value. GREATEST PRIORITY in creating a more effective digital workplace Tag cloud for participant responses (link) For many respondents, the answer rests in the cultivation of a new, social mindset within the organization. Although the tools and possibilities are now easily available, our practices of using them are often guided by old sets of values and internalized routines. Social technologies will make little difference without the trust, open-ness, and culture that supports the individual in their discovery and contribution. That people feel empowered to be expressive, to participate, that their voices count, and that they feel comfortable with a place/space of less order is of vital importance. Organizations need to create an internal culture conducive to knowledge sharing. Ways to ensure this culture include making curiosity acceptable within the organization. Help people recover their innate curiosity and root out the organizational practices that discourage and suppress curiosity. Give up control to create shared knowledge. Along with cultural change is the issue of changing the skill set needed of knowledge workers. A new, participatory culture will demand what some call new media literacy which could include: leveraging social media in problem-solving, the sample and remix of content, scanning multiple resources for meaning, pooling knowledge and resources with others working toward a common goal, networking with people and through machines to build collective intelligence, and working with diverse communities and perspectives to achieve consensus-built solutions. A change in knowledge skills will demand an environment that fosters the ability to find, create, share and disseminate information. A new media literacy in knowledge workers will depend on an environment that allows for the capture of personal values, that builds and maintains networks and effectively collects feedback. Support for knowledge work will include trust over distance, and issues of control resting in the realisation that working from home, remotely, from the Web, can be just as effective as working from the office. Managers need to understand their team members are not hovering around their own workplace. Workers can be productive when they are mobile, thriving, constantly on the road, working from home, and as such the best way to keep in touch with them is through the digital workplace: The Internet. It will continue to be a challenge dealing with locating information, fuzzy boundaries, shared controls, knowing what we really need, how to find it and taking responsibility

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and risks to go for it. For young and old, digital and digital-averse, information overload will continue to be a challenge as new habits and strategies are developed to help us move from information scarcity to information abundance. Getting older people who have made it to the top without technology to understand how technology can take the next generation to the next level. As technology becomes more intuitive, making the “how to” of connection, sharing, and collaboration will become radically easier and better understood throughout the organization – getting technology more into the background, while simultaneously becoming even more powerful and understood. * Originally created as part of a dissertation research project by Colleen Carmean, Capella University. (Committee: Rod Sims (chair), Elena Kays, Patricia McGee) Retrieved from "http://horizon.nmc.org/Wiki/Shared_Knowledge_Project" Powered by MediaWiki Creative Commons BY-NC-ND 2.0 * This page was last modified 21:08, 29 February 2008. * This page has been accessed 224 times. * Content is available under Creative Commons BY-NC-ND 2.0.

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APPENDIX F. LIST OF PARTICIPANTS

(Blogs and participants listed with permission as part of study) Name Country Blog URL Blog Name ________________________________________________________________________ Nirmala "Nimmy" Bangalore – nirmala-km.Blogspot.com

India Aa...hah! Thinking Inside the Blog

Shawn Callahan www.anecdote.com.au

Australia Anecdote

Stephen Downes www.downes.ca

OL Daily

Lilia Efimova Blog.mathemagenic.com

Mathemagenic

Canada

Netherlands/Russia

Peter-Anthony Glick – England leveragingknowledge.Blogspot.com Leveraging Knowledge Denham Grey denham.typepad.com

USA Knowledge-at-work

Harold Jarche www.jarche.com collaboration

Canada Harold Jarche: Strategies for online

Alan Levine – cogdogBlog.com

USA CogDogBlog

Jim McGee www.mcgeesmusings.net

USA McGee's Musings

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Clive Shepherd – clive-shepherd.Blogspot.com

Clive on Learning

England

George Siemens www.elearnspace.org/Blog

elearnspace

Canada

Ray Sims – USA Blog.simslearningconnections.com Sims Learning Connections Luis Suarez – http://www.elsua.net David Snowden www.cognitive-edge.com Jack Vinson www.jackvinson.com/

Spain ELSUA: A KM Blog by Luis Suarez Wales Cognitive-Edge USA Knowledge Jolt with Jack

Tony Karrer – USA elearningtech.Blogspot.com/ eLearning Technology (contributed at the Wiki review phase)

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