Rounding up the JLeRN Experiment

We have reached the end of the JLeRN experiment, at least the end of the current JISC funding for Mimas to set up a node on the Learning Registry and examine its potential. One part of the process of rounding up ideas and outputs generated through the experiment was a meeting of those who had engaged with it, held on 22nd October. This post providers pointers to two sets of resources associated with that meeting: the blog posts etc. that people who attended it wrote after the event, in order to summarise what had been discussed, but first a quick round-up (mostly from Sarah Currier) of posts that describe what the people who attended had been doing with the Learning Registry.

The Story So Far? – by David Kay
A summary of some of the “headline ‘findings’” of a series of conversations that David has been having in an attempt to pin down the nature of the Learning Registry and its potential.

Understanding and using the Learning Registry: Pgogy Tools for searching and submitting – by Pat Lockley.
Pat has been very involved in the Learning Registry from the start. This blog post gives you access to all four of his open source tools that work with the Learning Registry, set up to work with our JLeRN node. They are very easy to install (two of them plug very easily into Chrome) and try out, plus Pat has made some brief videos demonstrating how they work. The tools use the Learning Registry to enhance Google (and other) searching, and support easy submission of metadata and paradata to a node. There is also a sample search you can use with the Chrome tools that should show you how it works pretty quickly.

Taster: A soon-to-be released ENGrich Learning Registry Case Study for JLeRN – by the ENGrich Project.
The ENGrich project are working on a case study on why and how they have implemented a Learning Registry node to enhance access to high-quality visual resources (images, videos, Flash animations, etc.) as OERs for engineering education at university level. Their work has involved gathering paradata from academics and students; this taster gives you an overview. A really interesting use case. Please pass this one on to anyone working with engineering resources too!

Taster: some ideas for a use case on paradata and accessibility opportunities –by Terry McAndrew
Terry is an accessibility expert from JISC TechDis, he came to our first Hackday and got us thinking about how the Learning Registry model for capturing and sharing paradata might be useful for people to share information about how accessible resources are. We commissioned him to write up a use case for this; look here to see his beginning thoughts, and add any of your own.

How widely useful is the Learning Registry?: A draft report on the broader context – by David Kay
The JLeRN team have been keeping half an eye from the start on the potential affordances the Learning Registry might offer the information landscape outwith educational technology: what about library circulation data, activity data and activity streams, linked data, the Semantic Web, research data management? And what if we are missing a trick; maybe there are already solutions in other communities? So we commissioned a Broader Context Report from David Kay at Sero Consulting. This is his first draft; we’re looking for feedback, questions and ideas.

I reported on some information about the current status of the Learning Registry in the US and some other related initiatives (slideshare) based on information Steve Midgely had sent me in reply to an email.

Summaries/reflections from after the meeting

Registrying – by Pat Lockley
Pat’s summary of his presentation on how the Learning Registry affects the interactions between developers, service managers and users.

Experimenting with the Learning Registry – by Amber Thomas
A round-up of the meeting as a whole, pulling out a couple of the significant issues raised: the extent to which the Learning Registry is a network, and the way some real tricky problems have been pushed out of scope…but are still there. Some really useful comments on this post as well, notably from Steve Midgley on increasing adoption of the Learning Registry in the US.

JLeRN Experiment Final Meeting – by Lorna M Campbell
Another summary of the meeting, summarising the uses made of the Learning Registry by projects represented at the meeting, mentioning some subject areas where the use of the Learning Registry to store information about curriculum mapping may prove useful and questions from Owen Stephens about alternative approaches to the Learning Registry.

At the end of the JLeRN experiment – by Phil Barker
My summary of the meeting, covering the issues of whether the Learning Registry is a network or just isolated nodes (-not much of a network, yet), whether it works as software (-seems to) and why use it and not some alternative (-it’s too early to tell).

Watch this space for more information and case studies from some of the people mentioned above, and for the official JLeRN final report.

JLeRN Reporting: Skills and Capacity in the UK for the Learning Registry

This is one of a series of posts from the JLeRN Experiment, forming sections of what will be our Final Report. Please send feedback and discussion in the comments section, as your own blog post response, via Twitter (hashtags #jlern #learningreg) or on the OER-Discuss and Learning Registry email lists. To see all the posts, click here.

JLeRN Draft Report: 3. Skills and Capacity in the UK

Who has skills and expertise?

As far as we can tell, only a small number of JISC and JISC CETIS staff, the JLeRN team, and those few dozen who have attended Learning Registry or JLeRN events are familiar with the Learning Registry concepts and use cases. See the previous report section on Appetite and Demand to get a feel for who has been following and participating in this work. Obviously there are probably other lurkers out there whom we haven’t met (yet)- feel free to make yourselves known in the blog comments!

Direct technical experience with the Learning Registry in the UK HE sector consists of (and please let me know if I’ve missed anyone!):

• JLeRN developer Nick Syrotiuk;
• The ENGrich team at Liverpool University, and their local technical staff who have worked with them setting up a Learning Registry node;
• Julian Tenney and his colleagues who work on Xerte at Nottingham University, who took an early interest in the Learning Registry when it started;
• Pat Lockley, formerly of Oxford University, now maintaining an interest in his own time outwith his current post; see his blog post for JLeRN describing and giving access to four Learning Registry tools he has developed.
• Those working on the JISC OER Rapid Innovation projects SPAWS (see blog posts here), RIDLR (see blog here) and Xerte/Xenith (see blog posts here) teams.

We have unfortunately lost the expertise of one key JISC CETIS expert: John Robertson; and two key developers: JLeRN’s Bharti Gupta, and Jorum’s Steven Cook (who worked on developing a CakePHP Datasource for Jorum to use with the Learning Registry). All of these people had become skilled in various aspects of the Learning Registry and all have now moved outwith JISC’s community.

Where the gaps are

As the afore-mentioned Appetite and Demand blog post notes, we’ve had enough interest and use cases coming in to make us feel the involvement we’ve had at Mimas has been worthwhile. Feedback from the institutions and projects working with or dipping their toe into JLeRN and the Learning Registry has mostly consisted of requests for easier entry to and navigation of the existing Learning Registry documentation, and simple Web apps and APIs to enable exploring, publishing to, searching and extracting from a Learning Registry node, as well as tools for capturing and collating paradata.

JLeRN has done a little to move forward with tools: we have the JLeRN Node Explorer by Nick Syrotiuk; Pat Lockley’s tools which we have facilitated access to through presentations slots and this blog; and we’ve tested using an OAI-PMH utility, developed in the U.S., to extract Jorum metadata and publish it to a node with its keywords converted into Learning Registry tags. We have kept our own node up-to-date in terms of software releases, and experimented with installing nodes on Ubuntu and Windows. We never found capacity to try out a cloud-hosted node – our American colleagues use Amazon Web Services, but we could never get to the bottom of how to manage costs within a UK university funding environment. Nor was there much call for experimenting with the more complex architectural proposals of the Learning Registry, namely, linking nodes in networks and communities.

What would be needed for the Learning Registry to move to the next level in the UK?

As the previous Appetite and Demand section noted:

“[…] those who recognise the gaps in paradata provision are interested in the Learning Registry at a strategic level, but this invariably raises an accompanying problem of expectations management. In describing the problem area the Learning Registry is aimed at, and the innovative approach being taken, it can be easy to latch onto this work as the next big thing that will solve all problems, without recognising that there is (a) a lot of work to be done, and (b) that work would require a well-supported infrastructure, both technically and in terms of communities, shared vocabularies, and so on.”

The JLeRN team have found that working with the Learning Registry code and specifications has been, to date, relatively straightforward. There is an initial steep learning curve in becoming familiar with the documentation and concepts, but the CouchDB-based software itself is easy to install and manage. As Pat Lockley has said, it is “state of the art”.

However, an example of an obvious weak spot is the limited vocabulary of the Learning Registry Paradata Specification, which throws into sharp relief the idea that any scalable implementation of the Learning Registry as an architecture will bring about some very familiar requirements: communities will need to agree on such issues as vocabularies, degrees of openness, licensing, shared content standards, and so on. That the Learning Registry as a technical investigation has chosen to push these concerns back out to the community, thus avoiding more years of technical discussion and testing around interoperability, does not mean that these concerns have evaporated. Moreover, JLeRN has asked David Kay of Sero Consulting to prepare a brief on where the Learning Registry sits in the broader context of the Web, linked data, research data management, activity data and libraries. There may be parallel development going on and we need to keep an eye on that.

What it does mean is that, if we are to close the gap between the strategic enthusiasm for the potential wins of the Learning Registry, and the small-scale use case and prototype testing phase we are in, we will need a big push backed by a clear understanding that we will be walking into some of the same minefields we’ve trodden in, cyclically, for the past however many decades. And it is by no means clear yet that the will is there, in the community or at the strategic level.

JLeRN Reporting: Appetite and Demand for the Learning Registry

This is one of a series of posts from the JLeRN Experiment, forming sections of what will be our Final Report. Please send feedback and discussion in the comments section, as your own blog post response, via Twitter (hashtags #jlern #learningreg) or on the OER-Discuss and Learning Registry email lists. To see all the posts, click here.

JLeRN Draft Report: 2. Appetite and Demand

Interest in the Learning Registry in the UK: a summary

Following on from the Hackday in January 2012, where considerable interest was shown in JLeRN, there were well-attended sessions at the CETIS Conference 2012 and OCWC/OER12. However, conference sessions and a Developer Challenge at developer-specific events Dev8D and Dev8eD were less well-attended, despite effort put into publicising JLeRN and encouraging participation. Those events were for developers working on the ground rather than project managers or strategic thinkers; it seems the immediate benefit of the Learning Registry to coders wanting to code cool stuff was not yet apparent, although if you are interested in some exceptions to that, see our blog post about Pat Lockley’s plugins here and our own JLeRN Node Explorer here.

Building on this early buzz, a small number of institutions have shown an interest in trialling implementation of the Learning Registry around well-defined use cases meeting real community needs, although only one has followed through: Liverpool University have implemented their own node to support their ENGrich work (a JLeRN Case Study is coming on this). There have also been projects hoping to try out the Learning Registry approach as a side issue to their core work (e.g. Xenith, ORBIT- see below), recognising the potential value and wanting to take advantage of JLeRN while it was available to help. However, lack of capacity on both sides prevented much happening beyond discussion.

Learning Registry: popular with JISC OER projects

Six projects working with the Learning Registry were funded in the JISC OER Rapid Innovation Programme, and one FE-based project involved JLeRN in its bid, but was not funded. Two JISC OER Programme projects (ENGrich at Liverpool University and ORBIT at Cambridge University) have also initiated collaboration with JLeRN; we have supported ENGrich with their node and commissioned a case study, whereas with ORBIT we only managed some initial discussions on the idea of sharing semantic data using the Learning Registry, an idea we would’ve loved to explore further.

Are others interested in the Learning Registry, sans funding?

Where people have secured funding (or institutional support in the case of ENGrich) directly related to the Learning Registry, they have been able to collaborate with JLeRN. It is important to note that these projects, while they relate to very real use cases, are small scale and exploratory, like JLeRN itself. In no case are they close to developing anything like a strategic or service level implementation. This is as it should be, however, given the stage the Learning Registry itself is at.

Others who showed an early interest, for instance, The Open University’s LabSpace and LearningSpace platforms; JISC TechDIS; and the Health, E-Learning and Media (HELM) team at Nottingham University (distinct from the Xerte / Xenith team at Nottingham who have an OER Rapid Innovation project), have not been able to make resource available to work with JLeRN as it is too experimental and not part of their core work. Their participation in our events and discussions has been valuable and much appreciated, however. And Terry McAndrew at TechDIS is working up an accessibility use case which will be published here on the blog.

Interest in the Learning Registry outwith the educational technology sector

There are other JISC communities outwith educational technology that have shown an interest in JLeRN and the Learning Registry, the most prominent being those involved in content, discovery and activity data. Joy Palmer, a Senior Manager at Mimas with a number of interests and projects in these areas, has been keeping her own watching brief on the progress of JLeRN. Joy and Amber Thomas made sure that JLeRN was represented at JISC Content and Discovery Cross-Programmes Meeting in April 2012, where a number of useful conversations were had. Amber Thomas has also noted that the research data management community has similar issues to solve. JLeRN has commissioned a report looking at how the Learning Registry might benefit these wider areas: see David Kay’s JLeRN blog post initiating discussion around this. His final report will also be published here on the blog.

Strategic interest and expectations management

Broadly speaking, discussions within the HE community in the UK and abroad, as reported informally by various JLeRN, Mimas, CETIS and JISC folk, have indicated that those who recognise the gaps in paradata provision are interested in the Learning Registry at a strategic level, but this invariably raises an accompanying problem of expectations management. In describing the problem area the Learning Registry is aimed at, and the innovative approach being taken, it can be easy to latch onto this work as the next big thing that will solve all problems, without recognising that there is (a) a lot of work to be done, and (b) that work would require a well-supported infrastructure, both technically and in terms of communities, shared vocabularies, and so on.

Understanding and using the Learning Registry: Pgogy tools for searching and submitting

I started with the Learning Registry as part of Plugfest 1, which was just over a year ago in Washington D.C. (see my CETIS blog post reporting on it here).

Stuff about Pat Lockley’s tools noted here, plus other thoughts and projects of his, are available on his Pgogy website

Part of the thing I think people don’t get with the Learning Registry, is that as the Internet became the Web, then the Web became a series of distinction destinations – Facebook, Google, Twitter, etc. So although the Learning Registry exists – it doesn’t have a front page, or a “Tweet this” button, but it exists like HTTP exists – you can build using the Learning Registry, but you might never see it.

So that is poorly explained, but that is an innate part of the problem – and it’s a problem I sought to rectify at the first Plugfest. If I can’t take people to the Learning Registry, then I should take the Learning Registry to people. How? …

A Chrome tool: the Learning Registry enhancing Google searching

Google is the biggest store of links in the world (I shy away from the ‘R’ word), and so it is where people go to search. Some of the links returned via a Google search will also be links stored in a Learning Registry node – so you can, via one of my Learning Registry tools, check to see if it knows anything about a website.

So you can do a Google search, click on a button, and really quickly (the Learning Registry technology is state of the art) you can see which pages the Learning Registry knows about. Sometimes this knowledge will be just keywords, authors and descriptions, but could also be educational levels and the type of interactivity supported by the page.

You can download the Chrome plugin here – and watch a short demo video below showing you how it works.

Note on trying this from Sarah Currier: Once you’ve installed this in Chrome, you can try it out by running any search in Jorum – nearly all of Jorum’s OERs have metadata in the JLeRN node. So you should see lots of small crosses (+) to click on next to your search results. If you want to try it in Google search, try a search for something you know is in Jorum – here’s an idea in case you want a quick win: “SEA and good governance” governmentality – look for the little cross in your Google search results against a Jorum DSpace result, and note that the same resource appears in the search results in other repositories but without the cross as they don’t publish to the JLeRN node. If they all published to the nide, along with usage data (paradata) ab out that resource, you’d be able to use one of the other tools to look at *all* the paradata for this resource, even when accessed in different places.

Paradata: information about how learning resources are used

As well as this information to describe webpages (in this case, metadata about learning resources), increasingly Learning Registry nodes are storing what is called paradata, which is information on how a resource is used. Imagine the same Google search as above, but this time you can see how popular resources are. So what would normally just be a page, now becomes a page used by 500 teachers in your subject area. Once a resource becomes used (and as long as someone tells the Learning Registry about it) other people can find this data and pick out the resources most suited to their needs.

So paradata, another great mystery to explain? Not really, it’s like seeing how often a book is cited, a link linked or a tweet retweeted. All that is different is the data on reuse is in a slightly different format, and is shared outside of the silos where it lives right now.

How can you share paradata for your resources? Well a lot of people use Google Analytics data, and a page visit (one that Google Analytics tracks) is paradata, it just needs some tweaks before it can become data in a Learning Registry node. How can you do this? …

Pliny: submit your Google Analytics data to the Learning Registry

You can use Pliny, another tool developed by me, to share your Google Analytics paradata. Pliny uses Oauth to sign you into Google Analytics. It then accesses your analytics data, and submits it to the Learning Registry for you (currently the tool at the above link submits to the JLeRN Alpha Node). It does all the hard work for you, all you need to do is click your mouse a few times.

You can watch the short demo video below to see how Pliny works:

Ramanathan: submit metadata from your RSS feed to the Learning Registry

So we’ve looked at the benefits of the Learning Registry for teachers in terms of finding appropriate resources; how can people contribute? Well, Pliny allows paradata to be submitted, and you could use another tool I developed – Ramanathan – to take an RSS feed and use it to submit the metadata in a feed into a Learning Registry node.

You can watch a short demo video below to see how Ramanathan works:

In the same way that there isn’t a place to go to search for teachers, how do cataloguers work with such a decentralised model? Both Pliny and Ramanathan help data to be submitted, but there isn’t as of yet an easy tool to remotely manage metadata on your resources in a Learning Registry node. If you use either of these tools, you will be given permanent links to your documents on the Learning Registry node – but this is only to see – not to delete or revise.

Learning Registry Browser: find Learning Registry paradata for a web page

I’ve developed a second browser plugin for Chrome – the Learning Registry Browser – which will tell you if the page you are on has data in the Learning Registry, show you the documents that have been submitted, and when they where submitted. Remember that as people might be using your resources, there may be documents not submitted by you; this is one of the benefits of the Learning Registry – to track others’ use of your resources outside of your own silo.

You can watch this brief demo video to see how it works (and see the note above in red, which will give you a sample search to try):

I appreciate this is lots of new things, but I hope that you think you’ll find these tools helpful and are encouraged and hopefully curious enough to consider submitting data to the Learning Registry.

JLeRN node upgraded

The node was previously running version 0.23.5 of the LR code but is now running version 0.23.7.  Version 0.23.6 was a major release and 0.23.7 was a minor release.

The release notes for version 0.23.6 state the following:

• Data Services NEW
  • The extract API is included and enabled in this distribution. The Extract API brings a “batteries included” interface for tailoring data extraction and query to suit more narrow and varied use case needs without high resource requirements.
  • Data Service views are NOT installed by default. Node administrators can install any or all of the 3 standards alignment focused data services using python CouchApp. This is done to prevent unneeded consumption of disk space for data services not utilized.
  • Interactive documentation explaining Data Services and how to roll your own for your use case.
• Resource Data Distribution refactoring CHANGED
  • Distribute has been significantly refactored to reduce the need for 2x storage for documents. New distribute uses 2 DB’s, incoming and resourcedata. New _tainted documents can be distributed to incoming, and node may impose an internal policy for untainting documents before moving into resource_data. All harvest services still operate against resource_data.
  • More compatible with Learning Registry 0.23 specification. Document Types of resource_data are distributed, not resource_data_distributable.
  • Upgrade will require some minor configuration changes to NGINX to change or expose incoming endpoint.
  • IMPORTANT Legacy nodes can distribute to a 0.23.6 by adjusting service documents to use the incoming endpoint. Legacy cannot be the destination for a 0.23.6 server.
• Subscription for Distribute NEW
  • You may now visit http://%5Bnode address]/register, enter the URL of your node (use https if SSL required to access).
• Support for CouchDB 1.2.0 NEW
  • This is a highly recommended upgrade. Significantly improves the storage and resource utilization, as well paves path for features planned for future releases.
• Many Bug fixes

I have not yet installed the Data Services views (pertaining to standards alignment) but if anybody wants them please tell me.

Next steps:
1. Test the new Extract API
2. Test distributing data between nodes

I’ll report back with the test results.

JLeRN at Dev8eD next week: will you be there?

The JLeRN team (myself and developer Nick Syrotiuk) are working with CETIS to bring you some juicy sessions on the Learning Registry at Dev8eD: “A free event for building, sharing and learning cool stuff in education! Tuesday 29th – Wednesday 30th May 2012, Birmingham, UK.”

We are very interested in talking and hacking with people working on JISC and other OER projects, including the Rapid Innovation projects we already know about, and anyone else interested in “capturing conversations around OERs” and paradata. If you haven’t already signed up to Dev8eD and you want to spend some quality time with JLeRN, this is a great opportunity to do so!

We are planning:

1. A Lightning Talk on Day 1 from Nick to update you on what’s new at JLeRN;
2. A workshop / panel session on Day 1 for those working in this area to share what their projects are doing and identify common requirements or useful ways in which JLeRN and CETIS can help;
3. A training session / hack session on Day 2 so that Nick can give you direct support with whatever you are working on with JLeRN or the Learning Registry.

If you are planning to come we would really like to hear from you to see how many projects will have something to talk about at the workshop / panel session on Day 1. Comment here or email me at sarah [dot] currier [at] manchester.ac.uk

I’d also like to hear if you have any further ideas about how we can best use our time at Dev8eD with you.

Node Explorer

We now have a prototype of a tiny app you can use to explore things on our node.  Our app is based on some work, called LR statistics, previously done by the LR developers in the U.S.  If you wanted to, you could clone the app and adapt it to explore any LR node.  The source code is available in our JLerN Github repository.

The app is here:
http://jlern.iriscouch.com/resource_data/_design/explorer/start.html

This version of the app runs on CouchDB in a cloud.  (It literally took seconds to create a CouchDB instance, hosted by Iris Couch.)  Once the prototype was ready, we replicated our resource data from the JLeRN Alpha node to the cloud and pushed the app there also.  The app is just another JSON document stored in CouchDB.

Tonight the document count is 15955.  This will not change if new documents are published to the JLeRN Alpha node.  Having said that, live updates could probably be implemented but this would require further testing.  [28 May: We have now implemented live updates.  With respect to IE 8 & 9, the app works as expected but the status information might say the node is down when it is actually up.  This has to do with your browser’s security settings.  In your Internet Options, (1) allow “jlern.iriscouch.com” as a trusted site; (2) lower your security levels for that zone to Medium-Low; and (3) answer “yes” to the security question when you start the app.  Or contact us.]

We could further develop the Node Explorer in any number of ways.  Please do let us know what you think would be useful.

Dunking your Cake into a tasty source of data

APIs make it easier for developers to interact with web applications and systems. To understand the capabilities of the Learning Registry, and how Jorum could potentially use and benefit from the it, I decided to create a CakePHP Datasource for the Learning Registry API. My framework of choice is CakePHP. CakePHP is designed for rapid development, and is ideal for prototyping web applications.

So far, I’ve created the READ parts of the LR Datasource. The LR Datasource abstracts the connection requirements and the intricacies of the API and helps connect Cake developers directly to the LR, allowing them to simply “plug-in” to a node and use the data obtained directly in their developments.

Recently, I have been working on the Jorum Dashboard; a web application that will provide an up to date, accessible window to statistical data about Jorum resources. The dashboard is written in CakePHP and I have been able to plug the LR Datasource directly into the application, giving me access to LR nodes (including the JLeRN nodes).

With the READ capabilities of the Datasource I can access paradata about resources and display that information within the Jorum Dashboard.

In the future I’d like to develop the Dashboard so that it submits the DSpace stats about resources, collects further usage data about resources from other sources including Topsy, Twitter, Google, Klout, and posts this paradata to a Learning Registry node.

You can find this and other CakePHP Datasources that I am working on at the following Git repository: https://github.com/cookiescrumbs/Datasource

What next…?

We have been looking at options to further work related to the JLeRN node and paradata, basically to create a sample interface. Javascript will be used mainly for the front-end, though it is all in primary stages. With all the data we have currently in our JLeRN node, it would be good to have a way to explore it and use it through a web client. Currently it is not fully clear what we might end up with, but some basic wireframes for the web pages are considered. Next we will look at the sharing and synchronising of learning resources across the Alpha node on Ubuntu OS and the Beta node on Windows 2008 OS.

Keep watching this space on more progress.

Update on the JLeRN Experiment Paradata Challenge at Dev8D

Just a wee update on the results of the JLeRN Experiment Paradata Challenge at Dev8D 2012. The whole team put a lot of effort into the challenge, especially Bharti Gupta, who set up the pre-conference surgery, ran an introductory session at Dev8D, and really got involved in discussing the Learning Registry with developers and following up after the conference finished. A big thanks also to Steven Cook from Jorum who accompanied Bharti to Dev8D, and helped a lot with supporting the challenge.

So: after a lot of interest we had two entries, both in the form of use case ideas around using paradata about books. We (the JLeRN team and the judging panel) decided not to award any prizes as the ideas just weren’t quite developed enough in relation to the Learning Registry, but we did feel these were use cases worth keeping an eye on.

We really want to emphasise that the lack of prizes is not a reflection on the work we know the two entrants put in, in terms of getting their heads around the Learning Registry. It still takes a fairly big push of effort and thought to dig into this stuff, and we were asking developers to do this a bit too quickly, and in their own time. And, it has to be said, without the incentive of a big cash prize at the end! Thank you very much for participating Vani and Neeta!

Ultimately, we came up with the challenge idea as a way of publicising the JLeRN Experiment and more broadly the Learning Registry. We’re not too disappointed at not being able to award any prizes, because the whole experience sparked a fair amount of interest in what we’re doing, and discussion on Twitter and elsewhere. It also highlighted some of the requirements developers identified around supporting their engagement in the Learning Registry. It was genuinely a valuable exercise for the project.

We’d like to thank the Dev8D team, especially Mahendra Mahey, for their help in thinking through and setting up the challenge. I’d emphasise however, that any decisions we made (such as the nature of the prizes on offer) that may have contributed to people not entering, were entirely our own decision!

We’ve had an interesting discussion within the judging panel for the challenge (including folk involved in organising hackdays and other developer events) about where the community is currently at with developer challenges, so hopefully we’ve contributed to that as well. We’re grateful to them for their support throughout.

We’ll be releasing an interim report and a plan for the next 5 months of JLeRN work very soon. Lessons learned from running the challenge, as well as from the hackday, the CETIS Conference, and our other activities, will feed into these, so watch the blog for a post!

And there will be some other very good news coming soon too about some funded projects who will be working with JLeRN over the next 7-8 months, and some small bits of cash we may be offering for mini-tasks. Watch this space …