Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object Repositories Xavier Ochoa, ESPOL, Ecuador Kris Cardinaels, KULeuven, Belgium Michael Meire, KULeuven, Belgium Erik Duval, KULeuven, ARIADNE, Belgium

Summary Why to do it? How to do it? How we do it What to do next?

Why to do it?

How to do it?

How we do it

What 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.

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  6000  5000  11000  11000 # of LOs SIDWEB ARIADNE SMETE MERLOT

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

Why to do it? There are two options with human generated metadata Each teacher generates the metadata for their own LOs 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.

There are two options with human generated metadata

Each teacher generates the metadata for their own LOs

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)

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!!

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.

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 Framework Definition of objectives and policies Inventory of already available Information Selection of metadata fields and values Classification of Learning Objects in different Levels Mapping available information to different elements in the standard Extraction and Conversion of information to metadata field values Sharing and Cross-validation of metadata of related LOs

Definition of objectives and policies

Inventory of already available Information

Selection of metadata fields and values

Classification of Learning Objects in different Levels

Mapping available information to different elements in the standard

Extraction and Conversion of information to metadata field values

Sharing and Cross-validation of metadata of related LOs

Methodological Framework 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.

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 Framework 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 .

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 Framework 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

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

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

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.

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.

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.

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

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???

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: [email_address] {krisc, michael, erikd}@cs.kuleuven.ac.be http://ariadne.cs.kuleuven.ac.be/amg