Twitter’s clouds are an interesting branding choice for a service that asks us to squeeze our thoughts into tiny 140-character installments. Clouds, like tweets, are so much more than they appear to be. They are open to interpretation. We see things in clouds, in their shapes, in their movements, that have nothing at all to do with their physical embodiment as water drops. I’ve never seen a cloud that didn’t look like something else:

Hamlet: Do you see yonder cloud, that’s almost in shape of a camel?
Polonius: By th’ mass, and ’tis like a camel, indeed.
Hamlet: Methinks, it is like a weasel.
Polonius: It is backed like a weasel.
Hamlet: Or like a whale.
Polonius: Very like a whale.

Now, some of us may see more than others, but we are all relentless meaning makers. The world around us is not a given, as they say, but rather it is constructed. In Twitter that construction relies on 140-character building blocks. Tweets, like clouds, are suggestions, intimations, that drift by, and sometimes they project the deeper concerns of the follower who reads them. I’ve never seen a tweet that didn’t look like something else. For example:

Observe the signs: the lone tweet, the extended time lapsed since posting, no followup, the default avatar. The tone is confident and crotchety, methinks. It suggests that, against their better judgment, the author fell victim to the peak of inflated expectations, then, at mid-tweet, with better judgment restored, fell into the trough of disillusionment. The ballistic progression through the stages of the hype cycle hints at long-time expertise, long enough for evolved cynicism, brief enough to have sustained hope. Could this be an abandoned eduTwitter account? If tweets are like clouds, this one says there is rain is in the forecast. Stay out of the rain it warns. If you are serious about technology-supported learning environments (and I am! Iam!), then Twitter is all wet.

Of course, I grant you, some of us may see more in these tweets than others.

TheMime’s twitter style is more detached, but equally jaded. The author tweets a single ellipse, and only an ellipse, every couple of days. They have been doing this since November, and have attracted over 5,000 followers.* The tone is whimsical, the delivery reliable. You may hope for more, they suggest, and you will get more … of the same. More of the same? Oh yes, I know this pattern. It is the one that seems to emerge whenever educators start to use digital technologies in their practice. The pattern looks something like this:

Most digital technologies are originally developed for or adapted by researchers or commercial interests. But it is fair to say that teachers and trainers are among the most enthusiastic and innovative adopters. We all want to embrace the promise to enhance the experiences of our students or improve learning outcomes. Many of us share our experiences. The online literature about the use of digital technologies in education is bursting with enthusiastic accounts of what was done, why it was done, how it worked, what impact it had on students, and what challenges it posed for teachers. In fact, this generosity formed my expectations about Twitter long before I set up an account. But read more closely, and you will see that much of the discussion is not about anything new or transformational; rather it is about the recurrent, persistent issues in education. There are notable exceptions, but most of these experiments with digital technologies feel as if they are just that—simple experiments with technology. These are our ellipses. Some important aspects remain mostly unchanged: the underlying design of the curriculum, the purposes and means of assessing, and the imbalance of power between teacher/trainer/facilitator and student/trainee/learner. There are reasons, of course, why we do not capitalize on the potential of digital technologies to change the relationship between students and learning. Still, I can’t help but feel somewhat disheartened that potentially transformational technologies are often used in somewhat predictable ways.

If tweets are clouds, is the long term forecast is overcast and unchanged? I turned to the twittersphere for fellowship and forecast. Is there anything new under the sun?, I tweeted. Apparently yes, says Dave Ferguson:

What appeals to me about digital technologies is that they throw into contrast any differences of opinion we may hold about their use. Variations in the pattern become immediately evident. For example, I don’t think I’ve ever been inclined to compare technologies and clouds before Twitter. Doing so reveals my underlying constructivist assumptions about education and I how go about achieving them. Tweets are like clouds. In 140 characters or less, I can see established paradigms and am free to interpret alternative views. That’s a lot of transformational power packed into an edutweet, and that’s where I see sun peaking behind the clouds.

* And more now that TheMime has been featured on Boing Boing. If you still have doubts that tweets are ideal fodder for meaning making, check out the comments.

140 Characters Or Less originally appeared on Portable Learner on March 12th, 2009

The common definition for design patterns one that is potentially incomprehensible unless one is already familiar with patterns is that they are solutions to recurring problems that can be used repeatedly in many contexts (Alexander, Ishikawa, & Silverstein, 1977; Guidelines for E-LEN Centres, 2004). However, the solutions are intentionally incomplete. Within their structure, patterns combine analysis and solutions to problems that are responsive to context, informed by theory and best practices. They focus and advise but do not constrain creativity. Thus, patterns guide rather than prescribe: a characteristic that makes them potentially valuable tools for designing complex learner managed systems.

The use of design patterns and pattern languages originates with architect Christopher Alexander, who sought to reconceptualise approaches to building design and town planning. Driven by the conviction that many forces that shape modern life damage our wellbeing, he sought deeper, recurring patterns in human activities that intuitively improve our environment. He articulated these patterns into a set of conceptual tools such that ordinary people as well as architects could shape the environment in which they live (Alexander, Ishikawa, & Silverstein, 1977).

Since its development in the 1970s, Alexander’s thinking on design has received warm reception in surprisingly varied professions and disciplines. In software engineering, patterns have been used to represent successful models of information systems (see HillsideNet Patterns Library) and human computer interaction (for example, Tidwell, 1999). More recently, education technologists have looked to patterns to solve problems such as collaborative activities in Computer-Supported Collaborative Learning (CSCL) systems (Hernández Leo, Asenio Pacrez, & Dimitriadis, 2004; Baggetun, Rusman, & Poggi, 2004) and learning management standards (Avgeriou, Papasalouros, Retalis, & Skordalakis, 2003), and to capture teaching practices in their respective disciplines (for example, from the Pedagogical Patterns project, Esckstein, Marquardt, Manns, & Wallingford, 2001, and also Bergin, 2002; Frizell & Hubscher, 2002).

Structure and Elements of Design Patterns

‘Go Berrypicking’ is one example of the lifelong learning patterns we have identified (There are a few more). Based on Bates’s (1989) Berrypicking model of information retrieval, it identifies a typical problem encountered in the information-rich world of the Internet: finding appropriate resources online. Pattern structure is fundamental to its value, and this pattern uses a variation of the Alexandrian pattern structure (other variations include Goodyear, Avgeriou, Baggetun, Bartouluzzi, Retalis, Ronteltap & Rusman, 2004, and Bergin, 2002). Like all such patterns, it is written in second person, and in this case is directed to the learner, has a name, and these key elements separated by asterisks (***):

• The context for the problem that prevents an over-generalised solution.
• The forces that describe in what contexts users apply the pattern, followed by the key
  problem (in bold). The forces of the problem clash, constrain, and communicate the nature of both problem and solution.
• ‘Therefore …’ (Also in bold) introduces the archetypal solution. It describes how to apply the pattern correctly and includes consequences, limitations and disadvantages of the solution.
• Further information and examples (in italics) about its use, including references to related work and contraindications to support the pattern’s use.

[title] GO BERRYPICKING**
[context] You want to search online about a topic that is unfamiliar to you.
***
[forces] The sheer volume and variability of sources on the internet make search complex. If you are unfamiliar with the domain, you may not know what sources exist, how to frame the research question, or what search terms to use. Unfortunately, search engines typically require that you present an structured, precise query that can be matched to the database contents to produces a single set of results (note: there are exceptions).
[problem] An underdeveloped research question produces less meaningful search results.
***
[solution] Therefore, use the results to refine and redefine your research question until the results are meaningful.
Search is iterative: the search question and result co-evolve. Start with just one feature of the broader topic and move through a wide variety of sources. Retrieve information a bit at a time, not all at once. Look for potential ideas and new directions and repeat with a refined query. Bates (1989) calls this strategy berrypicking and the shifting nature of queries an evolving search. You may be tempted to restrict your search among a small set of familiar sites. (Tauscher & Greenberg, 1997 in Candy, 2004). However, a broadly scoped search will offer more
opportunities. ‘Berries are scattered on the bushes; they do not come in bunches’ (Bates, 1998, p. 4). Don’t get lost. After pursuing a string of new directions, you may find yourself far a field from where you started, and unable to assimilate this new information into the original context. Fortunately, there are patterns for that too.
***
[further information] Bates (1989) suggests six ways to search for bits and pieces: footnote chasing, citation searching, journal run, area scanning, subject searches in bibliographies and abstracts, and author searching. These could be explicated as subpatterns. The online bookshop, Amazon.com, lets you find books by linking to other books by the same author, on the same topic, with the same reviewer or even other purchasers. CiteSeer, a database of computer and engineering documents that uses autonomous citation indexing, lets you query through a chain of documents.
Note: See family of patterns associated with assimilating information and insights.

Taken together, the ‘Go Berrypicking’ pattern captures an essential aspect of the online search experience. However, it is not full featured enough to create a working blueprint for a complete online search. Rather, like all design patterns, this one makes sense when it is seen in context of its neighbouring patterns. Patterns are nested with other smaller, related patterns and within even larger patterns that describe supersets and whole structures such as a class, a community or an e-learning program. A pattern language is a structure for nested design patterns.

For example, ‘Go Berrypicking’ is part of a cluster of patterns for ‘locating information sources and assistance’ that includes ‘Choose a well marked trail’ and ‘Trust a secondary source’ among others (It’s easier to see this in a hyperlinked version of the pattern cluster).

‘Locating information sources and assistance’ itself is a component of an online learning pattern language, for which we have used Candy’s online learning model (2004) to lend structure to and represent the power of nested patterns. Our goal was not to structure a pattern language for lifelong learning, a rather large undertaking, but rather to explore its value for designing technology-supported lifelong learning spaces.

Some of the information in this post was published in a paper, Design Patterns for Complex Learning

Design Patterns, Pattern Language originally appeared on Portable Learner on November 21st, 2006

Design patterns and pattern language are a smart way to represent the analysis and solution of a problem in a way that is sensitive to context, and informed by theory and evidence.

Last year with the support of my advisor, Terry Anderson, I spent a semester exploring the ways in which information technologies support lifelong learning. I stumbled across two quite remarkable works that gave the independent study course its form: Philip Candy’s comprehensive 2004 report for the Australian Department of Education, Science and Training called Linking Thinking: Self-Directed Learning in the Digital Age, and the European Commission’s E-LEN project, which used design patterns as a way to collect best practices to establish a network of e-learning centres. Juxtaposing lifelong learning, information technologies, Candy’s Online Learning model and a method for creating design patterns, we came up with the wonderful collection of lifelong learning design patterns represented in the pattern map below. With the news that our paper has been accepted for publication, with minor revisions, I thought it would be useful to collect all this information in one place before I tackle said revisions.

What are Design Patterns?

Design patterns originate in the work of the architect Christopher Alexander. Software engineers have enthusiastically adopted them in their practice, and now other fields, such as educational design, are also showing interest. Alexander’s definition of a pattern is that it:

…
describes a problem which occurs over and over again in our environment, and then describes the core of the solution to that problem, in such a way that you can use this solution a million times over, without ever doing it the same way twice.

Patterns offer a way to integrate both both the analysis and solution of a problem, in a way that is sensitive to context and informed by theory and evidence. Their value is that they suggest, rather than prescribe, a solution. Solutions are intentionally incomplete: they offer guidance but require embellishment. This makes them deceptively difficult to write and, frankly, require a good deal of effort to use.

The Patterns

You can navigate the patterns from the pattern map (recommended) or directly from the pattern links that follow. All of these patterns were first published on The Common Loon, the weblog I used to support the independent study course. These patterns are designed for lifelong learners (not professional designers or educators) and are represented in the form created by Joseph Bergin and his colleagues on the Pedagogical Patterns project.

Links to patterns: Be a designer | Check for quality | Choose the well-marked trail | Extend your reach | Extract it! | Go berrypicking | Mark your own trail | Tag it! | Triangulate | Trust a secondary source

Patterns for Complex Learning originally appeared on Portable Learner on July 7th, 2006

Rorschach inkblots exploit this tendency, and our interpretations of these images supposedly project some deeper concern. I took these snaps last week during an early morning canoe paddle through still waters of Lac Taylor.

Do you see what I see? Or do you see something else entirely?

Rorschach Wilderness Blots originally appeared on Portable Learner on June 28th, 2006

The Common Loon is a weblog about technology supported lifelong learning. It meanders a little (let’s call it exploratory learning), but nonetheless stumbles onto something interesting: the use of patterns in lifelong learning design. Another product of Athabasca U’s Masters of Distance Education programme. If you visit, skip right to the patterns part.

The Common Loon Feed

The Common Loon originally appeared on Portable Learner on January 5th, 2005