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An Agile Approach to Managing Open Educational Resources

Module by: Patrick Masson, Ken Udas. E-mail the authors

Summary: Purpose: Pointing to patterns of change in the adoption and institutionalization of educational resources, the appropriateness of traditional heavy and front-loaded planning and management regimes is challenged in favor of alternative Agile Methods. This article was originally published in Volume 17, Issue 3 of the journal "On the Horizon."


Purpose: Pointing to patterns of change in the adoption and institutionalization of educational resources, the appropriateness of traditional heavy and front-loaded planning and management regimes is challenged in favor of alternative Agile Methods.

Design/methodology/approach: Starting from the simple observation that the original introduction of Course Management Systems to support online learning was ad hoc and evolutionary, rather than planned at an enterprise level, the paper points to the conflict between, and offers a solution for, open and decentralized resources and traditional teaching, learning, support, and management.  By developing a logic to decentralization, a number of managerial strategies to improve agility are provided that address the changing nature of the university from one fundamentally designed to control, to one positioned to influence and adapt under the assumptions of change.

Findings: It is found that many components of the university including teaching, learning content, learning design, content development and management, and core infrastructure is shifting from centralized to decentralized models while current management and governance practices remain centralized resulting in lagging development and increased risk.

Originality/value: The connections made in this paper open a dialog for challenging and changing traditional management and decision-making approaches within the organization, to better account for the environment that decentralized systems create.

Keywords: Agility, Centralization, Decentralization, Decision-making, Distribution, Governance, Management, Open Educational Resources, Openness, Open Source Software, Distributed Learning Environments 


Should your campus deploy a Course Management System? That may seem like a ridiculous question today, perhaps even asking this question implies a fundamental ignorance of an academic institution's responsibilities in providing comprehensive support for teaching and learning.  However, it is only recently that higher education has come to include the Course Management System (CMS) in its enterprise resource planning. In the early years of online learning, many campus decision makers and advising committees were simply unprepared to address issues around CMS functionality and pedagogy, integration with other enterprise systems, such as student information, registration and billing; faculty development and training; curriculum; policies; and other functions within the university. However, while campus administrations debated the merits and feasibility of implementing a new enterprise application devoted to online learning, or to offer course materials via the Internet at all, even without a dedicated system, simply as web pages or download-able files (Butler and Sellbom, 2002), their faculty were slowly moving ahead with technologies already deployed.

According to the 1999 National Survey of Information Technology in US Higher Education, as reported by The Campus Computing Survey (Green, 1999), the predominant technology in use for Internet technologies in courses was email (53.4%). Of those reporting campuses that did offer online resources (38.6%), course content and activities were delivered primarily through traditional web pages (28.1). In fact, the course management system was not even included in the annual survey until the following year, 2000, which stated, "One-seventh (14.6 percent) of the institutions in the survey report using some type of course management tool in their online offerings" (Green, 2000). Highlighting this environment of faculty-driven button-up adoption, while most campuses had not officially adopted a CMS, faculty had already moved to the Internet to support their courses. Again from the 2000 Camus Computing Survey, while roughly 55% of campuses offered "full courses online" only 15% of campuses reported "using some type of course management tool in their online offerings" (Green, 2000). Clearly instructors teaching courses recognized the value of incorporating Internet-based technologies into their courses before their campus' administration did.

It is understandable, considering the many issues regarding the selection of a CMS platform (features, functionality, integration, etc.) and the resourcing to support those applications from a campus-wide perspective (licensing, hosting, staffing, etc.), that any campus implementing a new system would require a significant investment in planning, including needs identification and analysis as well as resource analysis and allocation. Butler and Sellbom (2002) highlight 2002 findings from Illinois State University that the lack of institutional support, lack of financial support, and lack of time to learn new technologies were the most significant barriers in the adoption of instructional technologies. All of these barriers to adoption, it is worth noting, are specific to institutional governance and planning, not among the users, such as faculty, staff or students.

Yet, survey data collected from by the Campus Computing Project provides evidence that the identification and adoption of technology to deliver educational materials and course content was not due to revolutionary vision and planning from the central campus administration, but rather evolutionary discovery through practice among distributed self-identified groups. The use of Internet-based technologies for teaching and learning grew incrementally as faculty were introduced to new services, perhaps originally implemented on campus for reasons other than online learning, but then adapted and adopted to enhance courses (e.g. email, bulletin boards and simple HTML web pages).

So while the specific question introduced above seems out of touch in today's academic climate, especially considering that by 2006, "learning management systems [were] found on 90 percent of U.S. higher education campuses" (Bassett and Burdt, 2007), institutions will continue to face significant challenges around the development and management of online education. Just as institutions have caught up, just as they have come to recognize the value of online learning, the role of the CMS, the tools that define those systems and the support structures needed, from training to technical, the entire ecosystem has changed.

The principles behind the Long Tail, specifically that users will demand a large number of unique items, each in relatively small quantities, (Anderson, 2004) provides not only an explanation for the value of niche tools, but pedagogical approaches and even content creation and distribution. Technical developments such as Open Source Software, Web2.0 tools, Mash-ups, Web Services, Service Oriented Architecture and open standards have enabled the rapid development of new teaching and learning specific features and functionality, integration between disparate enterprise systems and interoperability among tools. Open Content, Open Educational Resources and Open Courseware are raising questions and concerns over Intellectual Property, copyright and ownership. The Course Management, or, Learning Management System as a centralized service is evolving into the Virtual Learning Environment that aggregates distributed resources rather than manages centralized assets at the same time as individual learners are creating their own Personal Learning Environments (PLE) outside formal institutional offerings to discover, store, manage, share and even author educational resources.

Understanding the history and circumstances around CMS adoption can inform future decision-making as the platform evolves from a centrally managed system to a distributed set of resources. Although the adoption of these various educational resources have some similarities, the fundamental contrast is this stark difference in both architecture and administration: a centralized vs. decentralized approach.  Universities have been accustomed, even designed, to function in a centralized manner, which is coherent with the underlying architecture of traditional learning environments and technologies.  The adoption and administration of the various teaching and learning resources of interest today by faculty and students, on the other hand, is inherently decentralized, posing special challenges for organizations whose culture and behaviors tend to value the control that centralization provides.  As there is a functional connection between organizational structure, capacity and, behavior; and the ability to deploy and successfully manage distributed (cross-organizational) systems, just as the teaching and learning resources has become decentralized, so must the organization.

Open Educational Resources

For years EduTools ( has provided detailed analysis of Course Management Systems' (CMS) features and functionality, serving as a primary resource for many institutions in their research and assessment of web-based distance learning options. Indeed, many systems would not even be considered by evaluators without requisite features such as discussion forums, grade books, content drop boxes, email, etc.  The availability and quality of these fundamental tools has historically been the primary assessment criteria for organizations evaluating a CMS for campus adoption, rather than discipline-specific teaching and learning capabilities, the unique needs of academic programs, or even systems integration and interoperability.

Understandably, for campuses focused on developing or managing formalized administrative and educational practices, with heavy investments in existing enterprise platforms and limited internal resources, extended teaching and learning services within academic computing systems beyond industry recognized standards was ceded to CMS developers. Arguably, with such a constrained set of teaching and learning tools available, teaching and learning suffered. However, while the pace of development of features and functionality available within the CMS staggered, especially as CMS developers extended services out into broader enterprise services such as e-Portfolios, portals, Smartcards, etc., rather than deeper into academic tools, the larger community of Internet-based application service providers continued refining and enhancing existing offerings. In addition, new tools and web services, while not originally designed with education in mind, came online. Like earlier technologies such as email, bulletin boards, and listservs, faculty found and began to use these in their online courses and with their students.

The rapid growth of online learning and its applications in distance education, blended programs, and hybrid courses has started raising issues around tool availability, scalability, and access to educational content across disciplines and courses.  Universities that want to offer technology supported educational offerings across multiple disciplines are faced with the need to have access to a wide variety of tools that meet not only general needs such as instant messaging or mico-blogging, but also other discipline specific applications like rendering 3-dimensional molecular structures for organic chemistry or voice recognition for language study.  Although the wide variety of educational applications that are needed for the delivery of a complete curriculum entirely available online at a distance are not feasibly packaged in a traditional enterprise CMS, the tools could be built by distributed teams and made available through a service-oriented architecture (SOA). In fact, one would expect that faculty will look outside of the enterprise CMS to find what they need and then "kludge" the tools together regardless, and that an SOA approach would allow for this behavior while also enhancing learner experience by reducing the "kludge." 

The changing focus of online learning design from passive and asynchronous information acquisition to one that focuses on interaction, co-creation, and social interaction, has prompted educators to think outside of the CMS enterprise box and start considering new tools and techniques that enhance new learning approaches and liberate creativity.  Commonly found examples include technologies providing:

  • Authoring: blogs, wikis, discussion forums (e.g. WordPress, pbWiki, JForum);
  • Communications: instant messaging, IP telephony, microblogging (e.g. IM, Skype, Twitter);
  • Repositories: archiving, content sharing, distribution (, DSpace, YouTube, iTunes)
  • Social Networking (e.g. FaceBook, Flick'r, Flock, MySpace);
  • Virtual Environments (e.g. Croquet, SecondLife, SimCity, etc.).

We can easily suggest that content can also be viewed in the same way as software in terms of taking advantage of distributed authorship and revision of content that is supported through decentralized storage, cataloging, and publishing systems allowing for more efficient collaboration, sharing, use, and reuse.

Open Educational Resources (OER), including Open Source Software (OSS), is a social phenomena that changes some of the core relationships among content and software developers, and users, including teachers, learners, program managers, learning designers, and technology managers.  The growing influence of both OER and OSS on the thinking of academics and academic administrators is something that is now impacting the operations of colleges and universities.  The social phenomenon of open source production has recently spread to open educational resources, which is the development and distribution of teaching and learning materials used in education.  Although OSS and OER are commonly first thought of in terms of products, the underlying processes and structures that enable the creation of these assets are what will help support vertical and horizontal decentralization.  For example, James Dalziel (2007) on Terra Incognita made this connection obvious in a recent post when he described Open Source Teaching, which combines the process described in a learning sequence (codified relationships between learning activities) and the educational resources that support the sequence.  This moves the term open source from software that supports education and educational content available for use, directly into the teaching and learning process, supported by a community that allows for decentralized sharing authoring, and reuse.

There are numerous examples of co-dependent practices between OSS and OER, with open standards serving as a catalyst for technical interoperability and open licensing catalyzing open educational resources.  For example, the use of an open packaging standard such as IMS Common Cartridge, coupled with the use of open content, reduces many barriers to content deployment and exchange.  That said, the simple coupling of OER and Common Cartridge falls well short of the ideals of decentralization that sits at the center of efforts like WikiEducator and Connexions.  One appealing aspect that is influential when assessing such resources is their broad applicability, that is, their use does not impose any specific work-flow or output and thus is suitable for a variety of faculty, for a variety of courses, for a variety of activities. Specifically, a wiki can be used for personal journaling, a group writing tool, a portfolio, or a content repository.  Deploying one application provides multiple teaching and learning modalities. Another benefit, in addition to applicability, is portability in that these resources provide inherently low-barriers to adoption. Most are freely available at little or no cost, readily accessible as a web service, simple to learn and administer, and each can be incorporated quickly into a course without external, and minimal internal, support. Again looking to the wiki, we find that several free and open source options exist (too many to list here) and can be integrated into a course as simply as inserting a link into the CMS. Each provides first-person administrative control for enabling/disabling features, creating users, assigning permissions and establishing groups. And finally, as the "edit, save, link" functionality of a wiki is essentially uniform across wiki's mirroring common word processing tools, little training or support is needed outside of the class.

Indeed, wiki software, perhaps more than any other application type, illustrates the connection between OSS and OER supporting decentralized education.  A very nice illustration of this can be found at WikiEducator, which uses a wiki to support a wide variety of distributed functionality including materials authoring, storage, and delivery, in an environment that leverages distributed collaboration in an open environment.  In the case of WikiEducator, there is a very strong connection between the notion of distributed community and open educational resources (OER).  All content posted on WikiEducator must be distributed using a Free Cultural Works approved license to help enable the distributed nature of the community, content sharing, creation of derivative works, and reuse.  We see here an intimate relationship between openness, distribution, decentralization, and sustainability.

The term "Open," once reserved for OSS, was adopted as part of the rethinking of course materials and content under the OER moniker, and is now being applied more to the entire university, as a general descriptor or pronouncement of philosophical orientation, leaving many questions to be asked and addressed.  The most appealing qualities of OER-applicability and portability-are indeed valuable when assessing viability (do these resources work?) and feasibility (will these resources work in courses?), however, institutions deploying them must understand how such non-traditional resources will fundamentally change not only the teaching and learning practices within the class, but also traditional governance and decision-making enterprise-wide.  Each of these resources can be defined as remote, decentralized and distributed. Respectively, this means they are hosted and administered off-site by organizations under no obligation to the institution, faculty or students (remote); governance and decision-making is not controlled by a single authority, nor is adoption, which is independent and informal (decentralized); their development is undertaken by multiple self-interested groups as independent or collaborative efforts outside the direct influence of those that may rely on them (distributed). While OER, including OSS, can extend technical and pedagogical opportunities, serious consideration should be invested in order to understand how their adoption can affect organizational behavior, current institutional operations, curricula, individual courses: ultimately academic and possibly even institutional success.  This is where the openness and decentralization bump into traditional approaches to organizational management and leadership.

Distributed Systems

Many faculty members and academic administrators are now feeling the pull between the centralized nature of many university information systems, learning tools, and workflows and growing pressure to adopt more resources that require decentralized sourcing and management. An organization's orientation to managing risk and its understanding of the objective value and nature of intellectual property such as courseware are factors in managing distributed assets and the production of value.  In an effort to reduce risk many organizations depend heavily on processes that are based on the central control of resources and workflows.  Part of this stems from the frequently held notion that their technology and content resources are their "competitive" advantage, and that they are able to maintain that advantage by applying direct control over resources through centralization to protect their investment.  For example, this attitude seemed widely held when CMSs were first becoming part of the online learning technology support structure.  Universities looked at their CMS deployment as a way of separating themselves from other institutions.  This can also be recognized in the way many colleges treat their course materials, preferring to close them off and spend resources protecting and maintaining them, rather than opening the resources and allowing for distributed ongoing maintenance and improvement.  The use of centralized control, as a risk reduction strategy, may be rooted in the growing variety of institutional types that are present in the sector and the fear associated with shifts within market demand.

To help illustrate the dynamics within higher education, which may be viewed as threatening, according to the National Center for Education Statistics (2007), during the 10 years spanning from 1996-1997 to 2006-2007 the total number of accredited degree granting institutions grew approximately 7.5%, but there was a significant disparity within the sector.  The number of public institutions decreased slightly, while private institutions increased by almost 14%.  Within the private sector though, the number of accredited non-profit institutions decreased by more than 3%, while accredited private for-profit institutions grew by over 60%.  Please see Table 1 for details.  This trend is interesting because it represents shifting market pressures. Private, for-profit institutions account for all of the institutional growth across the entire American higher education sector.

Table 1: Changing Profile of US Accredited Degree Granting Institutions 

Table 1
Year All Institutions Public Private Private Non-Profit Private For Profit
1996-1997 4009 1702 2307 1693 614
2006-2007 4314 1688 2626 1640 986
% Change 7.61% -0.82% 13.83% -3.13% 60.57%

The ascendancy of for-profit post secondary education in the United States seems to have caused significant concern with the sector.  It might be that the for-profit universities tend to be more control-oriented and proprietary than other types of universities, but it is also easy to note a shift in the attitudes of traditional non-profit public and private higher education organizations as they have increasingly come to think of other providers as competitors rather than peers.

Just as there seems to be less trust within the sector and the impulse for higher degrees of control, there is the also a growing need to support decentralized infrastructure for teaching and learning.   To accommodate this growing need, over time and with experience, university faculty and administrators will become increasingly comfortable with decentralized management and increased connection and dependence on communities.  Although decentralized development and administration has clear advantages over centralization for many applications, reliance on decentralized systems requires some institutional investment to ensure smooth workflows at points of integration and efforts to prevent fragmentation of services.  Managers will have to develop techniques to ensure high quality and predictable user experience and coherence with organizational goals and interests.   Some of the challenges for managing decentralized systems are associated with the differences between the ways that we coordinate centralized resources and the ways that decentralized communities are coordinated. When educational resources are being developed in a distributed and decentralized manner the contributions are not coordinated through direct control and intervention, so the system will rely on:

  • different contributors developing content/code and extending resources;
  • different purposes for development from the points of origin;
  • resources are developed to meet different organizational objectives;
  • resources may be developed for different architectures;
  • funding for each resource may be from different sources with different levels of reliability;
  • each resource is being developed on a different pathway and schedule, making planning for dependencies difficult;
  • there is no explicit connection between projects, tools, content and users;
  • there will be a lack of shared governance;
  • there will be little direct communication across resources or communities.

At many universities with long histories of involvement with distance learning and large-scale content production, there has been the recognition that traditional methods of course design, content development, and course maintenance is very expensive.  In addition, many universities that rely on pre-developed content find scaling their processes and maintaining flexibility for faculty and learners a significant challenge.  During the past few years there has been increasing interest in the sharing, use, and reuse of content across courses and institutions.  The rise of open educational resources has served as a catalyst for decentralized content management.  Although OER can reduce various barriers for sharing, the creation of derivative works, and reuse of content, efficient distributed content management requires a framework to account for the nature of loosely coupled resources.  The framework must account for a working environment that demands:

  • A variety of tools offering features and functionality that enable creativity and support learner success;
  • A variety of content sources and types ranging from course cartridges, learning objects of various types, and open educational resources stored across a variety of repositories;
  • Reliance on open standards to help ensure dependable integration, discovery, and cataloging, and publishing of content across tools, necessitating common controlled vocabulary for metadata;
  • Workflow that accounts for the dependencies on learner services, course design, content development, and quality assurance, supporting sustainable operational approaches leading to learner success;
  • Integration and interoperability to reduce the complexity of drawing on decentralized application and content resources and the need for customized application specific code; and
  • Different interface design to support a variety of teaching, learning, and administrative needs, and supporting a satisfying and reliable user experience.

There are principles and practices that help define the nature of an organization, what it values, and how it responds to change.  Some organizations will possess qualities that are coherent with the adoption and management of distributed tools and content, creating a virtual learning environment, while others will not. Depending on the nature of the organization, the notion of a distributed VLE and all that comes with it, will be embraced differentially or simply rejected, and the manner in which either happens will reflect the organization's values, competencies, and cultural norms.

Commitment to openness and agility are important organizational characteristics for embracing distributed systems and resources as part of core infrastructure.  For many organizations, openness and agility themselves are not natural cultural norms and must be developed. There are, for example, processes and techniques that support an organization's adoption of flexible design, the development of a strong user-centric and learner focused identity, a strategic approach to online learning, and a commitment to embracing variety rather than ignoring or controlling it. Complexity is a reality and organizations that seek ways of embracing and leveraging it are much more likely to benefit from the use of distributed and decentralized systems than those organizations that invest heavily in long-term planning and implementing processes designed for and based on controlling the environment.

Principles for Enabling Adoption and Management

Many of us who work within educational communities know from first hand experience that things... well, things simply don't go as planned.  In addition, we also know that the more complex the plan and the longer the plan takes to unfold, the less likely it is to go well.  So, why do we do it? After all, reports from a wide range of sources such as the Standish Group's CHAOS report (1995), highlight the fact that a staggering 31.1% of technology projects will be canceled before they ever get completed, while only 16.2% of software projects are completed on-time and on-budget.   Furthermore, for those initiatives that do make it into production, 52.7% will cost 189% of their original estimates. Reasons cited by the Standish Group for failure focus on poor design and planning during initial project phases and an inability to control development. The CHAOS report's assessment was reinforced in a May, 2008, survey by IT Governance group ISACA (2008), that reported IT project failure was due to the following; changing business needs (30%), the project not delivering as promised (23%), the work is no longer a priority (14%), the project exceeds the budget (13%) and finally, the project does not support business strategy (7%). Each of these indicates a disparity between the original strategic vision for the project and the actual business case or operational value.  Reflecting on these outcomes, it is not unreasonable to question if project planning processes actually help to control complexity and ensure project success, or rather if they reinforce general perceptions, assumptions and expectations captured at the point of planning and that may prove no longer be accurate or applicable at the point of delivery.

Agile Methods allow initiatives to be modified, and resources to be developed at the same pace as users can articulate need, reducing the impact of the failure modes cited above. This is a stark departure from traditional front-loaded practices, where success often hinges on the ability to identify all of a proposed system's features, and value, before development begins. The fundamental difference between front-loaded and lightweight approaches used in Agile Methods boils down to processes versus principles.

Front-loaded processes start out with a heavy investment in the "planning." Needs analysis, requirements gathering, gap analysis, resourcing, etc. all take place before development begins and are expected to remain consistent. Changes are discouraged and may result in financial penalties. Planning is emphasized to mitigate risk and serves as the key to successful technology development. Success in front-loaded processes is often defined by how well a project adheres to the plan, not on the quality of the work or the value of the finished project. Lightweight approaches, such as Agile Methods, do not attempt to plan for the life of a resource, service or system, but rather, provide principles for undertaking tasks as they are identified. Agile Methods address needs which emerge through end user interactions and feedback, were evidence for implementation and value, rather than perceived or anticipated need, drives decision-making providing continuous development of services and systems and the greatest return on investment. Lightweight approaches accept that change will occur based on new information or technologies and provide a framework for incorporating those changes incrementally throughout the project's development and into operations. This is why lightweight management practices are sometimes called evidence-based or emergent.

Agile principles and practices which emphasize individuals and interactions, existing and available resources, collaboration and responsiveness provide organizations with a decision-making and governance methodology for managing the discovery and deployment of open educational resources and their inherent qualities-remotely managed, decentralized governance and distributed development.  That is, within the APM approach, the need for decentralized systems and distributed production is fully recognized, its complexity is embraced, and managed rather than controlled, which is an orientation that has been proven relatively ineffective in practice.  Alternatively, the Agile Manifesto (Beck et. al., 2001), as outlined below, provides principles for the identification, adoption and organizational shift required to support Open Educational Resources.

Transparency and Openness

Build projects around motivated individuals. Give them the environment and support their needs, and trust them to get the job done (Beck et. al., 2001).

All of an organization's policies, practices and projects should be publicly available and open for question, discussion and input from anyone. Transparency provides for a greater understanding among all for not only the reasoning behind current services and systems, but also issues under consideration. Openness capitalizes on transparency, shifting the decision-making authority from a top-down, local and centralized model to a bottom-up, evidence-based, emergent environment. This creates a meritocracy were decisions are based on actual use and feedback, rather than assumptions, affinity or influence. Of note, we do not include "pushed" communications such as newsletters, meeting notes, etc. as transparent or open because they do not provide a forum for discussion or input from stakeholders. Creating transparency, for example, can be achieved through the development of an enterprise wiki that provides a snapshot of the organization. Openness is derived from incorporating the actives and input from the wiki into decision-making, which in turn updates the wiki.

Self Organizing Groups

The best architectures, requirements, and designs emerge from self-organizing teams (Beck et. al., 2001).

Individuals discover and participate in, through transparent and open forums, those initiatives that will most likely impact their personal teaching and learning objectives, professional obligations, academic programs or technologies in use. This professional (sometimes personal) interest, yields better analysis of the issues under consideration and helps identify and refine requirements, leading to systems advancement through more directed and specific features and functionality requests and educational advancement through better content. Individuals assume roles within the groups based on interest, experience, expertise, job function, etc. No one is required to, or restricted from participating. Importantly we do not identify roles for committees, focus groups, advisory boards or other hierarchical control structures within Agile methods. Decision-making should be undertaken by those who self-identify with personal or professional interest in the topic(s) at hand. Interestingly, the lack of participation in a particular discussion might be an indication of its actual value to the organization and ultimately its inherent risk.


Business people and developers must work together daily throughout the project (Beck et. al., 2001).

Once institutional practices become transparent and open, self-organizing groups can discover, and form around, topics of interest. This leads to sharing where all ideas or issues, from anyone, are welcome: individuality, autonomy and diversity are promoted. While input should be honestly assessed and included in decision-making, individual program or project managers must have the authority and autonomy to act. If actions or outcomes do not satisfy use cases, lessons learned can influence future decision-making, allowing discovery to direct development. Agile organizations understand, collaboration is not consensus. 

Storytelling & Use Cases

Simplicity, the art of maximizing the amount of work not done, is essential (Beck et. al., 2001).

Rather than defining every possible scenario that might affect an organization, development/adoption is limited to what can actually be articulated through user-stories, which define current practices, and how stakeholders would like a service or system to behave, as defined in use cases. This contrasts with many strategic or visioning approaches were long-term assumptions are made based on projections or perceived market trends.

Emergence & Evidence-based Decision-making

Welcome change, even late in development. Harnessing change provides competitive advantage (Beck et. al., 2001).

Traditional approaches for planning rely on front-loaded processes using; assumptions, projections, trends, scenario planning, etc. In other cases direction is defined through executive vision, affinity programs, operational experience and authoritative expertise. Organizations should not attempt to define all of the features or functions of a service or system before deployment. Rather, services and systems are identified and described through the collective wisdom of the crowd and then adopted, enhanced or even abandoned, based on the actual use of those services and systems by the community.

Iterative & Incremental Development

The highest priority is to deliver continuously improving services. Deliver working systems frequently, from a couple of weeks to a couple of months, with a preference to the shorter time scale (Beck et. al., 2001).

Assess and implement new or revised resourses within a three month iterative cycle, were small incremental changes are developed at the same pace as the user community can articulate needs and solutions or feedback is assessed from prior work. Because the changes associated with development or adoption of enhanced resources are small, extending current services or systems only to the point of actual descriptions rather than implementing entirely new projects and their associated dependencies, workflows, policies, etc., consequences associated with failure are reduced.

Continuous and Rapid Feedback

Business people and developers must work together daily throughout the project (Beck et. al., 2001).

Business Intelligence (help desk reports, wiki activity and authoring, monitoring, etc.) all provide almost near real-time analysis of use and consequences of use as resources are designed, developed and deployed or adopted.

Courage, Honesty and Maturity

At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly (Beck et. al., 2001).

Collaboration is not consensus, program managers must have the authority and autonomy to act, but they must also have the courage. Organizations should promote a culture that embraces exploration, discovery, knowledge and understanding. Staff must be honest with themselves and their colleagues in their assessments of current operations and developments and mature enough to abandon current ideas, and adopt others proven more viable/feasible.


As much of the original discovery and innovation in online learning happened within the context of faculty members experimenting with new technologies at the class level, as opposed to administrators working at the strategic level, we must consider why this is the case and how organizations can not only support but foster continued emergence from the faculty that has benifited teaching and learning as well as institution so well.  The impulse of many academic administrations is to control activities through the development of policy, procedure, and ownership of assets, requiring centralized management systems.  Academic managers throughout the university are facing new and significant challenges, which will require a reorientation from managerial approaches based on assumptions of centralization and control, to those based on assumptions of decentralization and organizational adaptation.  From teaching capacity, to content sourcing, and infrastructure, we see virtually every traditional core competency of the modern university being distributed.  The university's ability to effectively possess and control these "assets" is slipping away, moving the organization's distinctive competency from controlling and managing assets to managing organizational structures and behaviors to support agility.   Noting that under the best circumstances individual classes have served as the crucible for creativity and the aggregation of decentralized and disparate assets, we might ask if there are management principles that allow this to happen more generally, and what it would take to align the principles of Agile Methods with managerial practice within the university.


Anderson, C. 2004, 'The Long Tail', Wired Magazine, October, 2004, viewed 1 February, 2009,<>

Bassett, E. & Burdt, C. 2006, 'Beyond Learning Management Systems', EdTech Magazine, October - November, 2006, viewed 1 February, 2009,<>

Beck, K. et. al. 2001, 'Manifesto for Agile Software Development', viewed 1 February, 2009,<>

Butler, D. L., & Sellbom, M. (2002), 'Barriers to Adapting Technology for Teaching and Learning' Educause Quarterly, no. 2 November 2002, pp. 22 - 28

Changing Business Needs and Unmet Expectations Are Leading Causes of Technology Project Failure (2008), ISACA

Cooke, D, Gelman, L, & Peterson W. J. 2001, ''ERP Trends' The Conference Board Survey, viewed 1 February, 2009<>

Dalziel, J. (May, 2007). Learning Design and Open Source Teaching, the Impact of OSS and OER on Education, posted on Terra Incognita, viewed February 1, 2009 <>

ERP Survey Results Point to Need For Higher Implementation Success (2002), Robbins-Gioia, LLC, viewed 1 February, 2009<>

Green, K.C. (1999), 'The 1999 National Survey of Information Technology in US Higher Education', The Campus Computing Project, October 1999

Green, K.C. (2000), 'The 2000 National Survey of Information Technology in US Higher Education', The Campus Computing Project, October 2000

National Center for Educational Statistics 2007, Digest of Educational Statistics, US Department of Education, Washington DC.

The CHAOS Report (1995), The Standish Group.

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