Social tagging of educational resources potentially offers new ways for:
1.1) better manage their digital learning resources that reside in different repositories and platforms, and
1.2) discover and access new resources from different contexts (e.g. different language, educational system) through tags and other users.
2.1) get third party metadata on learning resources (either the ones that already reside on their repository, or the possible new ones to be added to collections,
2.2) create affinities (e.g. link structure) between separate pieces of resources (either on their own repository, or the ones that reside on other repositories on the federation or on the Web) that were not cross-referenced before.
In the MELT project so far, we have only been able to see the peak of these potentials emerging. We list issues that we see important for future work in the field, for the clarity, we only list one of the main issues for each topic:
- 1.1 To fully support users in their knowledge management task on digital learning resources, the bookmarks (including title, url and tags) should be exportable in standard Webfeed formats. This would allow users to access and manage their MELT resources as part of their other resources collections, whereas now users need to be logged on to the MELT portal to do this.
- 1.2 Pivotal browsing of social bookmarks takes advantage of the affinities between the user, resource and tags. In the MELT context, more metadata could also be added to support pivotal browsing, such as the country of the user, interest topics; resource metadata such as multilingual indexing keywords. This would allow novel ways to access resources that other users have already discovered within the federation, and thus build on users’ social interactions and co-construction of knowledge.
- 2.1 Tags by end-users on the MELT portal have been shown to be of good quality as additional metadata descriptors of resources. We have enumerated possibilities of metadata ecology that the use of multilingual Thesaurus can offer to a federation such as LRE. Apart from working on ways to automatically generate LOM from tags, we urge on using the hierarchical structure and multilingual features to leverage user-generated tags.
- 2.2 Why not do Google for learning resources? Using PageRank-like algorithms on a learning resource repository or federation has been impossible for a number of reasons, the most important is the lack of a link-structure that cross-references resources. Tags, creating underlying connections between seemingly random pieces of content in different languages, on repositories in different countries and other platforms on the Web, rely on humans’ subjective idea of its importance for a given information seeking task. Using this new, emerging link-structure with tags as “anchor texts” offers totally new ways to “organise the world's learning resources and make them universally accessible and useful”. A new tag line could be “From teachers to teachers”.