1. Improving Learning Object Description Mechanisms to Support an Integrated Framework for Ubiquitous Learning Scenarios María Felisa Verdejo Carlos Celorrio Emilio Julio Lorenzo LTCS Group - UNED WMUTE 2006, Athens

2. Outline Introduction Enlace Project Ubiquity in Learning Processes Educational network infrastructure Metadata for Tools Objects Automatic Metadata Generation Integration by Tool Wrapping Conclusions

3. Introduction Mobile and ubiquitous technologies have demonstrated potential to enrich learning and teaching inside and outside the classroom. An increasingly number of experiences are being reported. However all these technologies are often a range of unintegrated options.

4. ENLACE Project Spanish National Research Project http://www.enlace.uned.es http://www.enlace.uned.es Explores the design of an innovative educational environment Technology seamlessly supporting the flow of learning activities in different contexts and settings

5. Enlace Project Students are engaged both in individual and collaborative activities compiling information analyzing and representing data building models to explain and predict behaviour exchanging and discussing their findings linking their view with real problems

6. Ubiquity in Learning Processes The learning workflow includes activities for a long term period (to be carried out either in sequence, parallel, or overlapping in time) in different scenarios (classroom, home, computer lab, field trips…) Ubiquitous context challenging the integration issue through the school curriculum location time social organization levels across devices interoperability connectivity

7. Ubiquity in Learning Processes Smooth flow throughout the scenarios of activities Users can create artefacts that will be reused in other tools, in other devices, or even different students in different contexts. Sustain seamless data and tool interoperability, through an educational network infrastructure a variety of mobile devices computer tools connectivity conditions

8. Educational network infrastructure The backbone of the technological infrastructure is a Learning Object Repository (LOR) a) a persistence mechanism for tools b) a web interface for accessing artefacts Metadata is a key factor

9. Outline Introduction Metadata for Tools Objects Automatic Metadata Generation Integration by Tool Wrapping Conclusions

10. Metadata for Tools Objects LOR as a service for external tools... 1. a declarative way for defining specific metadata. 2. mechanisms for automatic metadata generation GOAL: generalized framework for the external tools.

11. Metadata for Tools Objects A LO type in the repository defines the description for a class of LOs General Metadata Schema + other Tools Specific Metadata schemas the format of content (i.e. multimedia material, XML files, models following tool specific formats).

12. Metadata for Tools Objects Metadata items are grouped in Metadata Schemas. Each metadata item has a value type Text, for storing any kind of string text. Number, for integer or real numeric values, possibly delimited with maximum and minimum values. Predefined formats of interest, as for instance, date, time and position for storing GPS data. Vocabulary, for predefined set of values. Terms of an ontology

13. Metadata for Tools Objects The LOR provides mechanisms for defining new LO types for tools in a declarative way An example: Observation Card Object from CARDS tool

14. Outline Introduction Metadata for Tools Objects Automatic Metadata Generation The Method Extraction sources Conflict resolution criteria Integration by Tool Wrapping Conclusions

15. Automatic Metadata Generation Metadata is seen as a key feature for enhancing the search in digital repositories. How this metadata is created? 1) The author of the resource creates the metadata using editing tools 2) A professional cataloguer creates metadata (as librarians currently do) and 3) Methods for automatic generation of metadata are applied. We want a completely automatic metadata generation mechanism

16. The Method Automatic metadata generation process includes two steps: 1. Tool extraction of metadata field values. 2. Combining metadata field values.

17. Extraction sources LO types in the LOR includes information about how the metadata fields will be populated. Extraction sources for automatic metadata generation: 1) Tools own context 2) Default values 3) The object itself 4) The portal context 5) Inference from an ontology that models the different concepts underlying the metadata domains..

18. Conflict resolution criteria Defined at the moment of the LO type declaration. A list of ordered candidates. Tools metadata generated values has preference over the LORs generated ones.

19. Outline Introduction Metadata for Tools Objects Automatic Metadata Generation Integration by Tool Wrapping Conclusions

20. Integration by Tool Wrapping Many tools are not prepared for interoperating directly with the LORs web services interface. The idea for handling this problem is to use a mechanism allowing 1) to define an external metadata model suitable to describe potential outcomes from that tool 2) to wrap the non-compliant tool to produce a) appropriate metadata values from its output using the metadata model b) to generate input data to feed the tool from a selected LO.

21. Integration by Tool Wrapping CARDS is an authoring system for defining models for data collection and the metadata associated to these models. ModellingSpace is a collaborative modelling tool to create models to represent and understand natural phenomena, physics laws, trigonometric rules, etc. CARDS MODELING SPACE

22. Integration by Tool Wrapping An example of this flow in a topographic profiling activity.

23. Outline Introduction Metadata for Tools Objects Automatic Metadata Generation Integration by Tool Wrapping Conclusions

24. Storing and retrieving the products generated by students from different devices and tools Many diverse tools can be potentially integrated in the networking infrastructure, either by web services interoperability or by tool wrapping. The definition of an LO type allows to specify and implement a variety of automatic metadata generation methods to create a rich description of an artefact.

25. Conclusions Perspectives Scenario and activity design Pilot evaluation Broaden participation Tool integration Agent technology Configuration layer with functionality adaptation to dynamically deploy the required services customized for a certain learning scenario

26. Improving Learning Object Description Mechanisms to Support an Integrated Framework for Ubiquitous Learning Scenarios María Felisa Verdejo Carlos Celorrio Emilio Julio Lorenzo LTCS Group - UNED WMUTE 2006, Athens