Collaborate? Why bother?

According to “Insights for a Changing Economy” (Volume 3 – Bulletin #4) published by Maguire Associates;  “Higher education institutions don’t leverage the contributions of their internal colleagues very well at all.  That’s why there is such a compelling need to encourage and reward greater collaboration within institutions, with less concern for protecting individual fiefdoms.”  This may often be true.  The question then is who should be collaborating on what – and more importantly why?  Participation in an open collaborative process can be time consuming and potentially disruptive in terms of interpersonal and group dynamics, as well as how groups and teams are organized to get things done.  Collaboration may also involve cultural change and require a willingness to explore new ways of doing things that might be outside the traditional boundaries of how a given profession may be defined.  Why bother?

For example, it seems self-evident that information technology services and the library should collaborate.  There are examples of such collaboration at many higher education institutions going all the way back to the 1990s.  But similar to other collaborations among internal colleagues the results have often been mixed.  However, there is more reason than ever before to move toward a collaborative model of providing library and technology services.  Even so, why bother?  It’s not easy.  Both groups strongly identify with their profession, traditionally defined as “librarian” or “technologist”, much the same way faculty might identify with their academic discipline.  Most of them need to be convinced there is a reason to collaborate more and that it is worthwhile to do so.  (And some may never be convinced).  But it’s still a worthwhile undertaking.  Here’s why:

The need for information technology and library services continues to change at an accelerating rate.  Librarians and technologists are playing an increasingly important role within the overall context of student development in terms of achieving information literacy and technology fluency.  The source of value from the services provided by both librarians and technologists are beginning to fundamentally shift from provisioning information and technology to helping make optimal use of information and technology.  At the same time, there are unmet needs and anticipated changes driven by enrollment increases at many institutions, continued expectations of personalized service and an accelerating rate of technological change.  Both support organizations also face increasing variation in terms of when services are in demand, the nature of the requests themselves, and the differing capability or even willingness to make use of self-service offerings.  Personal preferences are often the subjective basis for opinions of whether or not students and faculty feel well treated.  These are the central challenges of managing both service operations and the reasons why library and IT collaborations are worthwhile.

But what’s the best approach?  Possibilities include:    

  1. Matching the collective expertise of Library and Information Technology Services staff through the natural outcome of a well designed and ongoing professional development program that results in even more integrated services (over time) that will be highly valued by students and faculty. 
  2. Bringing the combined staff together organizationally as a way to collectively improve services that will better support academic programs and magnify the combined group’s joint contribution to the institution’s mission.
  3. Identify a specific set of collaborations that small cross-functional teams self-organize around and define an action plan for.
  4. Other?

The preceding approaches (and others) could be used in combination or independent of one another.  But they cannot assure buy-in and a sustained commitment to advancing the goals of an agreed upon collaboration.  Should formal rewards or consequences be used to incent certain behaviors?  Or should more difficult to craft normative means be relied on?  Is the answer to the question “Why bother?” enough?     

Open Standards

Why is “interoperability” so crucial to the educational use of information and technology? 

Many educational institutions provide access to information about courses, information and technology used in courses and information generated by participants through some form of online learning environment.  Portions of these interrelated types of information are frequently licensed, managed and/or protected from unauthorized use by the institution.  Examples include selectively imported and exported intellectual property, student information, and administrative data.  Other information such as open educational resources may not need to be licensed, managed and/or protected from unauthorized use by the institution.  However, all of these components often get bundled together.  The challenge then is to provide a personalized user experience that is accessed through human and computer interaction within a shared learning environment that combines the following:

  • feeds to and from protected administrative and student information systems
  • authorized access to licensed intellectual property (both software and content)
  • organized selections of open educational resources
  • social constructs for participating in both public and private cohort networks

The integration of information systems, technology infrastructure and third party product and service providers is a basic requirement for providing the kind of learning environment described above.  Interoperability is a crucial enabling capability
for automatically exchanging and interpreting data accurately among two or more information systems, configuring combined uses of technology without the need for customization, and merging complementary content and services from third party providers within a coherent user experience.

Education specific open  standards for “interoperability” can help solve integration challenges within the unique requirements of an educational context.

  • characteristics  of the overall user experience which include (but is not always limited to);  branding, ease-of-use across multiple courses, availability of support services, supporting a full spectrum of facilitated interaction among people, providing integrated views of information aggregated in meaningful ways from multiple  sources
  • characteristics of the enabling technology which includes (but is not always limited to); combining software functionality that can be “easily” configured by subject matter  experts and instructional designers for use by students and instructors to interact with relevant content and engage in activities that serve the objectives of a particular program of study and/or course
  • identity management which includes (but is not always limited to); the ability to verify someone’s identity across multiple systems using the same credentials
  • total cost of ownership which includes (but is not always limited to); establishing and maintaining custom interfaces, switching costs, software licensing, system configuration, ongoing maintenance, upgrades, technical support, help desk support, training and documentation
  • information management which includes (but is not always limited to); capturing, storing, organizing, preserving, retrieving, and rendering information in ways that facilitate the accurate and timely exchange of information
  • information security which includes (but is not always limited to); stewardship of personally identifiable information and copyright material – ensuring the confidentiality and security of protected information under federal and state law
  • compliance which includes (but is not always limited to); terms and conditions of software and licensing agreements, along with federal and state laws and regulations pertaining to accessibility

The IMS Global Learning Consortium has developed the following education specific open standards:

Learning Information Services (LIS) – Standards to support interactions and data exchange between learning systems and administrative, student, or human resource systems, including exchange of course rosters, learner profiles, competencies/learning objectives and learning outcomes.”

Learning Tools Interoperability (LTI) – Standards to support interactions, namely launching and data exchange, between learning systems or related applications, either in the enterprise or web-based, enabling incorporation of learning tools, applications, mash-ups, and software as a service within the context of a learning portal or other learning environment.”

Common Cartridge (CC) Standards for organization, publishing, distribution, delivery, search and authorization of a wide variety of collections of digital learning content, applications, and associated online discussion forums used as the basis for or in support of online learning of any type.”

The complete list of IMS Global Learning Consortium interoperability standards projects are maintained here.  A complete list of compliant products and services are listed here.  They are interoperable by design where there is a match with conforming specifications.

IMS Global Learning Consortium interoperability standards have the potential to solve many of the previously mentioned integration challenges based on an open architecture:  

Networked Learning Environment

Why should Chief Information Officers help guide IMS Global Consortium projects and require compliance with these (and other) education specific open standards for interoperability?

Here is one reason why (“A sales representative for SmorgasBoard LMS shows up and reality ensues”):

While supplier adoption is necessary, true standards also require leadership from the institutions to which they provide the ultimate value.  And collaboration among adopting institutions will accelerate both the adoption of the standards and the network effect of wide spread adoption.  The community of Chief Information Officers can take a lead role by requiring conformance with IMS standards during the procurement and implementation of information resources and educational technologies, sharing best practices and taking an active role in guiding priorities for the evolution of IMS standards.

Or are we content with the increasing cost and complexity of integrating both proprietary and open source solutions while our ability to negotiate for the best possible solutions based on price, performance and a host of other factors continues to erode?

Strategic Foresight

I participated in a mini workshop yesterday led by Dr. David Staley principal of The DStaley Group titled “Futures Thinking for Leaders” while attending the 2011 SunGard Executive Summit.  He’s also written a couple thought provoking articles for EDUCAUSE Review titled “Managing the Platform:  Higher Education and the Logic of Wikinomics” and “The Changing Landscape of Higher Education”.  During the mini workshop he shared “9 Habits of Mind for Futurists”:

  1. Curiosity
  2. Imagination
  3. What if?
  4. Openness to Change
  5. Sense Making
  6. Systems Thinking
  7. Peripheral Vision
  8. Challenge Assumptions
  9. Anti-Thinking

These characteristics of how futurists may think (in part) describe a frame of mind and some ways of developing strategic foresight that might help with imagining and articulating what to anticipate and plan for.  These traits were further outlined in a handout from the mini workshop (provided below with permission combined with some of my notes):


  • Interest in something because it’s interesting
  • Interest in the surrounding environment
  • Broad intake of all forms of information (written, audio and visual) outside of one’s primary professional interests


  • Ability to project change onto a volume of space and time
  • To look at a situation and visualize it differently
  • Three types of imagination – 1) Reconstructive  2) Substitution  3) Creative

What if ?

  • Most important question futurists ask
  • To increase situational awareness
  • To enhance visioning
  • “What if students no longer demand higher education?”
  • “What if the TED model becomes a new way to deliver higher education?”

Openness to Change:

Consider the history of the environment

  • How was the organization different a generation ago?
  • What are those areas of the environment most susceptible to change? (“Slippable”)
  • Understanding of disruption, discontinuity
  • Understanding of different degrees/rates of change

Corallary:  Openess to continuity

Sense Making:

  • Not just acquisition of data and information from an environment
  • Implications assessment: projecting the potential effects of an event
  • Via your own curiosity, when noting an important change in your environment, asking “what does this mean?”

Systems Thinking:

A system: a set of things interconnected in such a way that they produce their own pattern of behavior over time

  • Complex behavior not simple
  • Non-predictable
  • Simultaneity, not linear cause and effect
  • Feedback loops
  • Individual elements part of a larger whole
  • Small changes can lead to big effects
  • Connections across separate domains

Peripheral Vision:

  • Ability to “imagine the unimaginable” (high impact low probability)

Challenge Assumptions:

  • Ability to identify “load bearing assumptions” in a system
  • “Always” and “Never” scenarios

Anti-thinking:  (barriers to creativity, innovation and change)

  • Tradition/convention/social norms “The way it has always been done”
  • Ideology:  Knowing the answers before the question is asked
  • Constitutions, laws, rules, regulations “What we’re allowed to do”
  • World view: a lens on the world
  • Benchmarking that is limited to imitating
  • Certainty: mental brittleness (versus “mental flexibility”)
  • Fear, Anger
  • Confusion, panic
  • Myths
  • Stereotypes

It seems to me that strategy formulated from the preceding characteristic traits of futurist thinking can lead to foresight that illuminates visionary possibilities.  Good stuff!


Technology enhanced learning environments aren’t ubiquitous yet.  Not in a literal sense anyway.  However, pervasive access to networked information within overlapping spheres of educational context from a diverse range of human-computer interaction is creating a habitat for more ubiquitous learning environments.  That’s at least one conclusion that could be drawn from the 2011 Horizon Report.

The annual Horizon Report is collaboration between the EDUCAUSE Learning Initiative (ELI) and the New Media Consortium.  Each year, the Horizon Report is published based on research used to identify and describe six emerging technologies with considerable potential to both enter mainstream use and have a significant impact on higher education within one to five years.  The full report can be downloaded from here.

The following key trends, critical challenges and technologies to watch are taken directly from the executive summary:

Key Trends

  • The abundance of resources and relationships made easily accessible via the Internet is increasingly challenging us to revisit our roles as educators in sense-making, coaching, and credentialing.
  • People expect to be able to work, learn, and study whenever and wherever they want.
  •  The world of work is increasingly collaborative, giving rise to reflection about the way student projects are structured.
  •  The technologies we use are increasingly cloud-based, and our notions of IT support are decentralized.

Critical Challenges

  • Digital media literacy continues its rise in importance as a key skill in every discipline and profession.
  •  Appropriate metrics of evaluation lag behind the emergence of new scholarly forms of authoring, publishing, and researching.
  •  Economic pressures and new models of education are presenting unprecedented competition to traditional models of the university.
  • Keeping pace with the rapid proliferation of information, software tools, and devices is challenging for students and teachers alike.

Technologies to Watch

Electronic books continue to generate strong interest in the consumer sector and are increasingly available on campuses as well.  Modern electronic readers support note-taking and research activities, and are beginning to augment these basic functions with new capabilities — from immersive experiences to support for social interaction — that are changing our perception of what it means to read.

Mobiles enable ubiquitous access to information, social networks, tools for learning and productivity, and much more.  Mobile devices continue to evolve, but it is the increased access to affordable and reliable networks that is driving this technology now.  Mobiles are capable computing devices in their own right — and they are increasingly a user’s first choice for Internet access.

Augmented reality refers to the layering of information over a view or representation of the normal world, offering users the ability to access place-based information in ways that are compellingly intuitive.  Augmented reality brings a significant potential to supplement information delivered via computers, mobile devices, video, and even the printed book.  Much simpler to create and use now than in the past, augmented reality feels at once fresh and new, yet an easy extension of existing expectations and practices.

Game-based learning has grown in recent years as research continues to demonstrate its effectiveness for learning for students of all ages.  Games for education span the range from single-player or small-group card and board games all the way to massively multiplayer online games and alternate reality games.  Those at the first end of the spectrum are easy to integrate with coursework, and in many institutions they are already an option; but the greatest potential of games for learning lies in their ability to foster collaboration, problem-solving, and procedural thinking.  

Gesture-based computing moves the control of computers from a mouse and keyboard to the motions of the body via new input devices.  Depicted in science fiction movies for years, gesture-based computing is now more grounded in reality thanks to the recent arrival of interface technologies such as Kinect, SixthSense, and Tamper, which make interactions with computational devices far more intuitive and embodied.

Learning analytics loosely joins a variety of data-gathering tools and analytic techniques to study student engagement, performance, and progress in practice, with the goal of using what is learned to revise curricula, teaching, and assessment in real time.  Building on the kinds of information generated by Google Analytics and other similar tools, learning analytics aims to mobilize the power of data-mining tools in the service of learning, and embracing the complexity, diversity, and abundance of information that dynamic learning environments can generate.

I read the 2011 Horizon Report while on vacation at a Disney resort in Florida.  It provided an appropriate backdrop in many ways.  The Disney theme parks employ a variety of computational devices and information systems simultaneously in order to provide distinct entertainment venues.  Sometimes patrons may not necessarily even be aware that they are doing so.  At other times the interaction with the technology is the entertainment.  Some of the experiences offered by Disney are also meant to both educate and entertain (a.k.a. “edutainment”). 

There’s another interesting concept referred to as “u-Learning” or ubiquitous learning.  But what does a u-Learning environment consist of?  How does it differ from “edutainment”? 

The College of Education  Ubiquitous Learning Institute at the University of Illinois at Urbana-Champaign is one organization that is focused on exploring the concept of u-Learning.  Dr. Chris Dede, Timothy E. Wirth Professor in Learning Technologies at Harvard University, gave a presentation titled “The Evolution of Ubiquitous Learning: Semi-Smart Objects, Intelligent Contexts, and Cyberinfrastructure” at the Ubiquitous Learning Institute launch on April 7, 2010 which provides some interesting insights and visionary possibilities.  A 48 minute video of Dr. Dede’s presentation can be viewed here.   

But we’re still left with the question posed by Dr. Dede, “What would an expert model of ubiquitous learning look like if we saw one?”

Social Media Analytics

A conversation I had last week with the CEO of a social media start-up, along with an article from the February 4, 2011 issue of the Chronicle for Higher Education titled, “Can New Online Rankings Really Measure Colleges’ Brand Strength? Unlikely, Experts Say” by Kathryn Masterson has me thinking about social media analytics.  The article poses some interesting questions that colleges and universities are beginning to ask:

  • “Colleges and marketers are just starting to try to understand how to measure the success of their social-media efforts, says Mr. [Michael] Stoner.  Many are counting “touches” – the number of Twitter followers, the hits to a web site, the number of friends or comments on a Facebook page.  The more difficult question, he says, is what do these measurements mean?  Do tweets, blog posts, and Facebook “likes” translate into someone choosing your college, recommending it to a friend, attending an alumni event, or making a donation?”
  • “Are more people now seeing that the university is creating the next generation of leaders, that Stanford faculty are experts in their field, and that the university is making a difference in solving world problems?  Do alumni feel connected to the community?”

The few university and college integrated social media communications plans I’ve seen make little or no mention of using analytics, or even a shared dashboard technology platform, both of which could be used in an attempt to help answer portions of these questions. 

However, rankings of college and university online influence are beginning to be publicized.  This might change the scope of social media strategies going forward along with how information and technology are used by institutions that seek to improve rankings.  Klout’s Twitter analysis report on most influential colleges on Twitter and Global Language Monitor’s “TrendTopper MediaBuzz” college rankings were each mentioned in Kathryn Masterson’s Chronicle of Higher Education article.  Both attempt to provide relative indicators of brand equity and online influence based on rankings of higher education institutions using different criteria derived from social media sources.

There are other tools  available to measure online influence as well, some of which are nicely outlined at onefortyHootSuite is one example of a social media dashboard that has grown in popularity and is likely to be found in use at many campuses.  SAS Social Media Analytics is a somewhat different offering that appears to be more geared toward enterprise-wide applications and seems to go beyond monitoring of activity.  But there is little evidence that any of these offerings are being applied as an enterprise-wide platform within higher education institutions for the coordinated use of social media across (or often even within) academic programs, constituent relations, student services, public announcements, etc.  The sprawling use of social media continues without much overall strategy beyond enacting policies for appropriate use, awareness campaigns and “how to” type of training. 

Has any higher education institution made it a priority to implement an enterprise-wide platform to provide integrated views of aggregated information that identify who was reached through a given use of social media, the context within which groups or individuals were engaged through such use, and what sort of response the outreach may have triggered?

Wikipedia “Presearch”?

The Vice President and Publisher of digital and reference content for Oxford University Press Casper Grathwohl wrote an article in The Chronicle Review titled, “Wikipedia Comes of Age” that was recently published by the Chronicle of Higher Education.

There are many legitimate reasons to be concerned with the indiscriminant use of Wikipedia as an authoritative source of information when doing any kind of research.  I’ve had first hand disappointments myself using Wikipedia even as a starting point for becoming familiar with a topic of interest.  Even so, I still find Casper Grathwohl’s article well written and from an interesting perspective worth considering.  There are three portions in particular that I highlighted which are quoted below:

  1. “We all acknowledge that the Internet is evolving at a dizzying pace.  From the point of view of information delivery, it is fascinating to watch the way in which layers of authority have begun to emerge.  That development should come as no surprise—a natural progression in any new knowledge system is for it to divide into layers of information authority.  Not all information is created equal.  The bottom layers (the most ubiquitous, whose sources are the most ephemeral, and with the least amount of validation) lead to layers with greater dependability, all the way to the highest layers, made up mostly of academic resources maintained and validated by academic publishers that use multiple peer reviews, trained editors, and scholarly reviewers.  When the system is effective, the layers serve to reinforce one another through clear pathways that allow queries to move from one layer to another with little resistance.”
  2. “A study carried out by Alison Head and Michael Eisenberg, published in a March 2010 edition of the Web journal First Monday, surveyed university students about their research habits and, in particular, how they begin research projects. Most of the nearly 2,500 students who responded said they consult Wikipedia, but when questioned more deeply, it became clear that they use it for, as one student put it, “pre-research.”  In other words, to gain context on a topic, to orient themselves, students start with Wikipedia.”
  3. “For a knowledge system to function effectively, its users must have an intuitive understanding of the layers it contains.  Today, when starting a serious research project, students are faced with an exponentially larger store of information than previous generations, and they need new tools to cut through the noise.  Intuitively they are using Wikipedia as one of those tools, creating a new layer of information-filtering to help orient them in the early stages of serious research.  As a result, Wikipedia’s role as a bridge to the next layer of academic resources is growing stronger.”

These excerpts from the article do not convey the full context the article provides for how the author’s own personal experiences and observations led him to certain conclusions.  As a result, it’s worth reading the entire article along with the numerous and sometimes passionate comments linked to the online version.  Wikipedia has a way of generating spirited discussion within higher education circles and there are several well articulated points of view among the comments people made.

Meanwhile, students are using Wikipedia for research and education regardless of whether or not the practice should be considered “good” or “bad” even as the debates about the integrity of Wikipedia as a an information resource continue.  Apparently, whether or not Wikipedia should be allowed or forbidden as part of research and education is not discouraging students from using it.

Chief Technology Officer at UMassOnline Patrick Masson did some research recently and found that Wikipedia is made available via links from 270,000 .edu website domains.  He also found that 2,388 links to Wikipedia were provided from the 40,000 course sections hosted by UMassOnline. 

Is there a “pre-search” role for Wikipedia in research and education as an information resource that should somehow be supported by librarians and educational technologists?