Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object...

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ED-Media 2005 presentation about how to capture learning objects from LMSs, automatically generate LOM metadata for them and store them in a LOR

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Frameworks for the Automatic Indexation of Learning Management

Systems Content into Learning Object Repositories

Xavier Ochoa, ESPOL, EcuadorKris Cardinaels, KULeuven, BelgiumMichael Meire, KULeuven, Belgium

Erik Duval, KULeuven, ARIADNE, Belgium

Summary

Why to do it?How to do it?How we do itWhat to do next?

Why to do it? Short answer:

There is not other feasible way solve the “chicken and egg” problem of critical mass in LORs.

Why to do it? While the amount of electronic learning

material is growing exponentially the amount of Learning Objects in LORs is growing linearly only.

Major LORs have a comparable number of Learning Objects as a Mid-sized LMS

MERLOT SMETE ARIADNE SIDWEB

# of LOs 11000 11000 5000 6000

Why to do it? There are two options with human

generated metadata1. Each teacher generates the metadata for

their own LOs 2. There is a group of “indexers” in charge to

index available LOs

These approaches had not worked and we did not even considered that LO metadata is NOT DEAD, but must grow and change with time and usage.

Why to do it?

The metadata information automatically generated could not be as good as the one manually generated by the teacher but…

Metadata does not need to be perfect, just good enough to enable sharing.

(Duval et al, 2004)

Why to do it? There is a broad spectrum of “not-perfect”

but “extremely useful” applications that rely on automatic generated metadata. Google Citeseer Ask Jeeves Spam filters

The question must not be IF we should create automatically generated metadata from LOs in LMSs, but HOW!!

How to do it? This work proposes two orthogonal

frameworks that could facilitate the analysis, design and implementation of Automatic Indexers for LMS content.

One of them focuses on the methodology needed to pass from a LMS to a LOR, while the other focuses on the technological aspect of the Automatic Metadata Generation.

Methodological Framework1. Definition of objectives and policies2. Inventory of already available Information3. Selection of metadata fields and values4. Classification of Learning Objects in different

Levels5. Mapping available information to different

elements in the standard6. Extraction and Conversion of information to

metadata field values7. Sharing and Cross-validation of metadata of

related LOs

Methodological Framework5. Mapping available information to

different elements in the standard We take every field described in our

metadata specification and tried to find the information available to fill them.

Example: Metadata Field: Pedagogical Context Level: Course Available Information:

Type of institution, department, area, level in the curriculum, prerequisites and following courses, level of actual registered students.

Methodological Framework6. Extraction and Conversion of information to

metadata field values • A class inherited from LMSContextIndexer is

implemented. Example

Fixed values: the institution is an University Easy text parsing from web pages or documents or

extracted from Database Looking up information of students in the directory

This is an University course of Computer Engineering that is focus on 2nd year students that have knowledge of Calculus and Linear Algebra and could be used for Data Structures and Programming Languages.

Methodological Framework7. Sharing and Cross-validation of metadata of

related LOs Sharing information among different levels

(Some information is easy to extract at certain levels)

Link related LOs between them Relationships are created to explicitly declare

the hierarchy in the metadata instances

Technological Framework: AMG AMG framework = Automatic Metadata

Generation framework, that easily allows: development and addition of new LO Automatic Indexers metadata creation according to different standards

The idea is that there are different “things” that can help to automatically create metadata different “sources” of metadata, like: The content of the LO itself The context where the LO is published The usage of the LO by teachers and students

Technological Framework: AMG

http://ariadne.cs.kuleuven.ac.be/amg

Technological Framework: AMG

Technological Framework: AMG For each application that wants to do automatic

metadata generation: some of the existing indexers can be used

e.g. the object-based indexers, that allow to extract information from common file types (pdf, ppt, …)

the structure of the AMG framework can be used to add new indexers

“plug in” new indexers Currently implemented indexers:

Toledo-Blackboard (KULeuven’s LMS) SIDWeb (ESPOL’s LMS) OpenCourse Ware (MIT) AACE Digital Library

http://ariadne.cs.kuleuven.ac.be/amg

How we do it We are implementing the framework steps

to automatically index Learning Objects present in Toledo (KULeuven) and SIDWeb (ESPOL) LMSs.

Both could be considered as fair examples of current LMSs: easy web publishing, user tracking, course structure, etc.

Toledo is the name for the Blackboard configuration at KULeuven, SIDWeb is an in-house implementation.

How we do it The first four steps of the Methodological

Framework are followed. Then we design and prototype the

mapping, extraction and conversion of available information in metadata values

The actual Indexer is created in the Technical Framework

The created metadata is improved using the relation between LOs.

Lesson Learned

Do it as simple as possible, but not simpler.

Conclusions Automatic Indexation of already published

content is necessary if we want to reach a critical mass in LORs (bootstrapping)

We do not need a perfect solution, just one good enough to enable sharing

Automatic Indexation of LMS’s content is possible with available (and simple) technology

The frameworks presented enable the easy creation of LMS Automatic Indexers (less than 1 man/month)

The metadata generated seems to be useful

What to do next? Generate a robust implementation Evaluate generated metadata First mass generation of metadata from an

existing LMS and its use in an existing LOR Spread and Improve the Frameworks!!!

Are you Interested???

Thanks!Questions, Suggestions?

More info:xavier@cti.espol.edu.ec

{krisc, michael, erikd}@cs.kuleuven.ac.be

http://ariadne.cs.kuleuven.ac.be/amg

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