The document discusses the idea of creating reusable and interoperable annotations for learning resources by capturing structured user feedback from various contexts. It presents scenarios illustrating the challenge of extracting useful feedback across different platforms and suggests a conceptual model that incorporates existing frameworks and pilot projects. The authors emphasize the importance of metadata, user context, and the need for consistent identification of resources to enhance recommendations and social navigation in educational environments.

1. What if annotations were
reusable: a preliminary
discussion
- ICWL 2009 -
Nikos Manouselis, Greek Research & Technology Network
Riina Vuorikari, European Schoolnet

2. Outline
• Problem statement
• A possible solution: a conceptual model
and pilot
• Further discussion points

3. Problem scenario 1
The same learning resource, that’s
metadata has been federated, is tagged
on different portals: LeMill, LRE, and
Koolielu

4. Problem scenario 2

5. Problem scenario 2
The same movie is found and rated in
three different application contexts: a
movie recommender system, an e-
commerce site, and an educational portal

6. Problem description
• Implicit and explicit feedback is hard to
acquire (e.g. LRE)
– Ratio: search-bookmark 5.5:1
– Ration: play-bookmark 3.2:1
– Ratio: play-rate 2.7:1
• This feedback is needed to better guide users
(e.g. recommendations, social navigation)
• Social information can make users more
efficient! (Vuorikari and Koper, 2009)

7. An idea!
A structured way to represent
different types of user feedback
from
different contexts
could prove of particular value.

8. Hypothetical questions?
• Can we represent and store user
feedback in a structured, interoperable
and reusable format?
• Is it safe to assume that the user
feedback can be used in another
application domain, e.g. a new
recommender system in a different
application context?

9. Capturing user feedback
To be reusable, the user feedback should
• be in a structured and interoperable
format
• reflect the annotation scheme (e.g. tag,
rating, multi-rating)
• incorporate some information about the
context in which it has been collected

10. model

11. Capturing user feedback
Different frameworks exist:
• Contextualized Attention Metadata
Framework
• Attention Profiling Markup Language (APML)
• User Labor Markup Language (ULML)
• Microformat, e.g. Google support
Vuorikari, R. & Berendt, B. (2009). Study on contexts in tracking
usage and attention metadata in multilingual technology enhanced
learning.

12. Capturing user feedback (e.g.CAM)

13. Capturing user feedback
(example of microformats)

14. Pilot in Organic.Edunet
• A registry of annotation schemes for
learning resources
• To store annotation schemes, ratings
and tags from different environments on
learning resources
• To be used to create better services for
users (e.g. recommendation, social
navigation)

15. Pilot in Organic.Edunet

16. Conceptual work in Aspect
• IMS LODE Information for Learning
Object Exchange (ILOX)
– different facets:
• for LOM,
• for folksonomies,
• annotations
• ratings
• ...

17. Lots of issues...
• How to identify the same item in many
different contexts (no persistent IDs)?
• Is it necessary to encode the information
about the user who annotated?
– Tags are interesting BECAUSE of (user,item,tag)
triple
• Do users really find an annotation from
another context useful?
• ...

18. thanks! for your attention
comments?
questions?
http://aspect-project.org/
http://lreforschools.eun.org
www.organic-edunet.eu