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Learning environments have probably been designed to trigger change ever since humanity stepped down from the trees to start using more sophisticated stone tools some two million years ago -- most probably even earlier than that. Since then, however, increasingly larger parts of these learning environments have been turned digital and the design of these environments has been subjected to more and more conscious decisions.

Today not only institutions for formal education such as schools and universities but also most work places and vocational training providers are equipped with at least some kind of tools that bring together people and content artifacts in learning activities to support them in constructing and processing information and knowledge.

With increased mobility, with exploding information offers, and light speed in technological innovation, building and maintaining these learning environments has not become easier. More: it has become the responsibility of the individual, rather than an institution. Supporting learners in building and maintaining their personal learning environment (PLE) therefore has drifted into the focus of attention in learning technology.

Our Jetpack proposal — Mash-up personal learning environment (MUPPLE) — helps to cope with this challenge: MUPPLEs enable learners to capture, actively manage, and share good (best) learning practice.


Using jetpack, we can turn the browser into a recorder of learning practice. Instead of blindly collecting logfile-like information, we can provide a little recording cockpit that accompanies you at the side of running through a learning activity you recurringly use.

The recorder prompts you to explain certain steps in your web handling and to explicate the actions pursued. For example, when navigating to it asks you what action you are performing and with which intended outcome or goal -- and it will discover that you are about to ‘register’ a new ‘learning diary’. This way, an activity script can be built from the recorded activity. The script captures action-outcome-tool statements binding the URL of a tool (function) to certain actions while explicating the intended outcomes such as goals, states, or artefacts.

This script can be used to monitor subsequent workflows (and provide task list like workflow navigation). This script, however, can also be shared with others as a kind of activity pattern. Whenever necessary, the recorder provides depersonalisation facilities to remove usernames from URLs, replacing them with placeholders that prompt user input whenever instantiated. As many web applications today support simple in- and output formats, even more complex data processing and data traveling activities can be designed that make sure learning traces created in one application (e.g. literature search engine) make their way to the other (e.g. bookmark sharing service).

In the mock-up, we have depicted a vision of how the player looks like: The user has selected an activity pattern ‘Collaborative Paper Writing’ to start working with some folks in the same course on their course assignment. The first step in this activity is to a) create a learning diary for this semester assignment. Clicking on the link opens the registration page of WordPress and guides the user through the most relevant steps. Subsequent steps could be (too illustrate the complexity of such activites):

  • store the url of the diary in delicious using a particular tag
  • recover the urls of the other co-learners from delicious via this tag
  • put these urls into your google reader to set up a working learning network
  • use to collect literature
  • store the links to them in delicious again
  • summarise the papers using wordpress
  • import the wordpress feed into a wiki page
  • put the joint course paper together in the wiki
  • use plus to talk about it
  • blog about the paper using a tag 'assignment'
  • notify the lecturer about the assignment being available via google mail

Capturing learning activities in scripts makes the learning experiences hidden in them accessible — and helps with learning a better learning environment which will shape future learning experiences. It can additionally help with building up rich professional competences. And it supports emergence of new practices, rather than prescribing.



Deeper insights into our thinking are published here:

Wild et al. (2008): Designing for Change: Mash-Up Personal Learning Environments, In:, Vol.9, 2008,

Wild et al. (2008): Mash-Up Personal Learning Environments, iCamp project (2005-2008),