Thursday, March 01, 2007

Connections between working items in EUN, KUL and COSL

Visiting The Center for Open Sustainable Learning (COSL) in Utah State University last week was a very rewarding experience. People there are working on many interesting things regarding the support for the use of open content in education. I had already checked their website (http://cosl.usu.edu/) before going there, but of course it's nothing compared to sitting down with people, talking about my projects and their projects, and, little by little, creating understanding on complimentary approaches and ideas to collaborate (hopefully).

To get the big picture on where I stand between all the work done in European Schoonet (EUN), KULeuven (KUL) and COSL, I created a complicated looking image that hopefully helps me to put pieces of the puzzle together.

The image here on the left represent a rather generic lifecycle of a learning resource (this is the connected part of the image) and the greenish bubbles around it are working/research items that people in EUN, KULeuven and COSL work on. With a quick look it seems that all the institutes work in the same field - providing access to learning resources - however, each has its own focus and flavour to give.

Who and what?

KUL is focused on searchability of resources across different repositories (SQI, OAI-PHM) and emphasises the generation (ALOCOM, AMG) and collection of metadata (CAM), both to describe the resource (LOM) and its context of use (Contextualized Attention Metadata).

COSL works on making the content accessible (EduCommons CMS), but is also focuses on tools to support the use of content (MOCSL). Moreover, the relations of content and content, content and users, and users and users seem to have become more important (Didly, Oz). They are also working on a recommender system.

EUN has interest in making the content available (federated search, Minor) and using the social aspects for its retrieval, the main methods being social bookmarking and user annotations (MELT).

Let's take it step by step following the scenario

1. Repositories to make content available

This image depicts a rather typical scenario of learning resources which end up in a repository; first the resource is "created", then"described" (i.e. metadata added) and "approved" (e.g. QA) to be part of a repository's collection where it is "published".

EduCommons, a plone-based CMS created by COSL folks has been developed for this reason.

eduCommons is an OpenCourseWare management system designed specifically to support OpenCourseWare projects like USU OCW. eduCommons will help you develop and manage an open access collection of course materials.
Whereas in EUN MINOR was developed. It's an open source learning resources repository that allows users to manage learning resources and their metadata. Minor comes with a built-in connector to the EUN's Federation of Internet Resources for Education, which greatly facilitates the work of connecting to other repositories and querying their resources.

2. Make the content available for search

Both EUN and KUL has been active in making the resources and/or metadata that reside in distributed collections and repositories accessible. Both have greatly contributed to Simple Query Interface (SQI). EUN and KUL, for example, demonstrated a real-time interoperability between Learning Object Repositories last summer.

Apart from SQI, folks in KUL are also looking into harvesting metadata, which seems like a suitable and complimentary solution for SQI.

3. Accessing the resources

Once the resources are made available in a way or another, there are the users who "discover" them using various methods. This is an area where quite a lot of work in done in all 3 places.

In EUN and KUL, within the MELT-project, the focus is on creating Social information retrieval (SIR) techniques for flexible access to large-scale collections of content. Here we are interested in social bookmarking and tagging, as well as on other annotations like comments, ratings, etc. This work can also lead to an implementation of a recommender system for learning resources within the federation of repositories.

COSL has also been busy thinking of how to use people, and relations that people and content have, to create serendipitous ways to discover resources. Ozmozr (Oz) is, or will be, an identity and content aggregator that leverages the power of social collaborative filtering through tagging. Currently it looks somewhat messy, but try to see for the grand idea that lies behind.

There is also Srumdidilyumptio.us, just didly among friends, that allows users to express relationships, let them between people and people, people and content or content and content, i.e. any two resources accessible by URLs. Didly might not look that cool, but one should think of it rather as an API to make use of that information in another context, I was told.

These two tools/concepts pretty well demonstrate the thinking that COSL folks take forward. One could say that they aggregate s!#t out of everything, to illustrate the Web 2.o thinking. Moreover, COSL will be working on topping up these two "relations aggregators" with a recommender system. The difference to the work in EUN is that they are planning to recommend anything that people have input in Oz, whereas EUN is only talking about recommending learning resources.

More in the same area, novel ways to access resources, one of the PhD students in KUL is working on creating a better ranking system for resources, namely the LearnRank. This will use the Contextualised Attention Metadata framwork (CAM). Another one is busy with information visualization techniques for the same purpose. We are also interested in experimenting on the combo of information visualization and social bookmarking in the future.

4. Support the decision making

Next step in discovering resources is to make the decision upon the piece of content. Usually users are exposed to a list of search results (sortable sometimes, ranked or not) or a list of recommendations. There are different ways the system can support users at this point.

EUN and COSL are both interested in user relevance judgments (AnnoRate; use of ratings and evaluations in EUN) and other annotations such as pedagogical comments, to help users to choose the content. EUN has also implemented personal collections of learning resources, so users could see in how many other collections the resource has been added in, to help them to judge its relevance.

After choosing the resource, users in EUN can add it to their favourites collection (bookmark) or choose to "obtain" the resource, its metadata or uri from the repository. Ozmozr, a COSL tool, allows users to bookmark items too, and to share them with other users. Additionally, at the same time, users can also save these bookmarks to their delicous account, for example.

It's good to make here a remark that CAM framework can be used to collect all kinds of user attention when interacting with a repository, for example, to save the search history, what items have been looked at or obtained, etc. This can be fed in again to help the discovery of resources, like is the case of LearnRank.

5. Re-using and re-purposing the content, content collaboration


Once the items have been obtained, there are the users, teachers or learners, who modify, "re-purpose", sequence or rip the resource to make it suitable for their needs.

In this sub-area ,some complimentary approaches have been taken too. Within an EUN-lead project a plone-based collaborative platform called LeMill has been developed by UIAH. LeMill is a web community for finding, authoring and sharing open and free learning resources.

In COSL some tools are under construction to support the use and re-use. Send2Wiki plug-in allows a user to send a webpage to a wiki and modify it there. It will automatically check on the CC licence and bring that info along. User can then modify the page in the wiki as they wish, for example to make a translation of it (hope to pilot this in EUN), or if it's from WikiPedia, modify the content to make it more suitable for K-12, for example (now some researchers in COSL say that Wikipedia is rather graduate level reading, thus the need for different versions).

Make a Path will help users in putting pieces of resource together for a coherent learning path. This tool is like creating your own music playlists. Once the users are using it (I hope EUN will pilot this, for example), some interesting patterns will most like start appearing. One possible way to take this forward to help sequence learning resources could be case based reasoning, like Claudio did for generating music play lists. Additionally, The INSTRUCTIONAL ARCHITECT allows teachers to find, use and share learning resources from the National Science Digital Library (NSDL) and the Web in order to create engaging and interactive educational web pages.

Moreover, there is research interest to better understand the collaboration aspects and communication patterns around content, how people work on it, share it, ask questions, help others, etc. In LeMill the collaboration aspect is important, one of the developers is currently conducting his PhD research (UIAH) on collaborative authoring of learning resources. Whereas in COSL, there is interest in looking into Yahoo! Answers, as well as there was some early work around supporting the users of MIT OpenCourseware.

I think KUL ALOCOM framework and AGM could be used here to make sure that a) the smallest possible pieces of content are saved in the repository, too, b) the correct metadata is sucked from the context. Also, CAM could be used to better track users interaction modes and patterns, etc.


6. Actual use of content and its evaluation


After ripping and mashing the content, it it usually "integrated" (e.g. using CMS, etc) to teaching and learning practices (pedagogical methods). "Use" of the learning resource takes place in its own context. Here, the CAM framework becomes useful to know more about how the resources have been used, in what context (e.g. entered by a university prof to a course, all this metadata can be sucked with the help of AGM and CAM).

Following the use, the users are given possibilities to evaluate or rate the content. The challenge here for a federation of repositories is that different repositories use different ways to rate and evaluate the content (different scale, different criteria (ped, technical, suitability in classroom,..), thus interoperability becomes cumbersome and there might be something lost in semantics (EUN). A rating service on a top of repositories like AnnoRate overcomes such hurdles.

To shortly summarise:


Everyone is interested in adding metadata, any kinds of it (LOM, attention, annotations, relations (bookmarks, sequence, ...), to the system












and using it for better retrieval of resources, and the new thing, to connect people.
















"We use people to find content. We use content to find people. Information seeking behavior and social network analysis go hand in hand." Peter Morville (2004)
The really interesting part of a folksonomy is not the content item being described, and not the tags that describe the item, but the person doing the tagging. by Greenchameleon

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