LEARNING OBJECT MANAGEMENT AND EVALUATION

Working with IMS Specifications and Metadata on AHKME LOM Tool

Hugo Rego, Tiago Moreira, Francísco García

University of Salamanca, Plaza de la Merced s/n,37008 Salamanca, Spain

Keywords: E-learning, Metadata, Learning Objects, Knowledge Management, IMS specifications.

Abstract: AHKME e-learning platform’s main aim is to provide a system with adaptive and knowledge management

abilities for students and teachers. This system is based on the IMS specifications representing information

through metadata, granting semantics to all contents in the platform, giving them meaning. In this platform,

metadata is used to satisfy requirements like reusability, interoperability and multipurpose. The system

provides authoring tools to define learning methods with adaptive characteristics, and tools to create courses

allowing users with different roles, promoting several types of collaborative and group learning. It is also

endowed with tools to retrieve, import and evaluate learning objects based on metadata, where students can

use quality educational contents fitting their characteristics, and teachers have the possibility of using

quality educational contents to structure their courses. The metadata management and evaluation play an

important role in order to get the best results in the teaching/learning process.

1 INTRODUCTION

In learning environments, information has to be

perceived and processed into knowledge. One of the

problems that have emerged from this

transformation was how to represent knowledge. So

standardization was indispensable.

Nowadays several organizations are working in

the standardization of metadata for educational

systems, in this way are developing standards and

specifications for that purpose. So to develop

AKHME platform we had to choose the most

adequate technological standards and specifications

in order to reach our objectives of multipurpose,

independence of the learning domain, reusability and

interoperability of resources and courses, since

several standards and specifications have been

developed to structure pedagogical contents and to

allow the characterization of a wide variety of

learning environments (Wiley, 2003).

Here we present AKHME (Adaptive

Hypermedia Knowledge Management E-learning

Platform), an open source platform that supports

both knowledge representation and knowledge

management based on metadata described by the

specifications. In this platform teachers have at their

disposal tools to create didactic materials and to

evaluate, import and retrieve quality educational

resources, and students can acquire knowledge

through quality learning objects, as well as through

the more appropriate learning technique based on

their characteristics, the learning activities available,

the instructional design, their learning style and the

learning objects characteristics.

The goals of AHKME and main contributions

are:

• The learning object management and evaluation

of quality, where we tried to introduce some

intelligence to these processes through intelligent

agents;

• The usage of the IMS specifications to

standardize all the resources of the platform;

• The usage of standards like XML, an open

source methodology both on programming

languages and databases technologies;

• The interaction of all subsystems through the

feedback between them allowing the platform to

adapt to the students and teachers characteristics

and to new contexts.

In this paper we’ll initially present an analysis of

current approaches to e-learning and a comparative

analysis of standards and specifications in order to

find the best to develop our system and then we’ll

describe the platform in order to give an overview

and to context the system, and we will focus on the

tools that provide the management and evaluation of

213

Rego H., Moreira T. and García F. (2006).

LEARNING OBJECT MANAGEMENT AND EVALUATION - Working with IMS Speciﬁcations and Metadata on AHKME LOM Tool.

In Proceedings of WEBIST 2006 - Second International Conference on Web Information Systems and Technologies - Society, e-Business and

e-Government / e-Learning, pages 213-220

DOI: 10.5220/0001246402130220

 SciTePress

learning objects through their metadata. Finally

we’ll present some conclusions and future work.

2 CURRENT APPROACHES

Nowadays, there are several solutions to support e-

learning, where most of them are content-centred

neglecting some important educational issues.

Before we started to develop our platform we

have done an analysis of reference commercial and

freeware/open-source current approaches to e-

learning platforms/systems, like Blackboard

(Blackboard, 2005), WebCT (WebCT, 2005),

IntraLearn (Intralearn, 2005), Angel (Angel, 2005),

Atutor (Atutor, 2005), Moodle (Moodle, 2005),

Sakai (Sakai, 2005) and DotLRN (DotLRN, 2005).

Our goal in studying these platforms was to identify

strong points and weaknesses, so we could try to

correct them with our platform. We have done an

analysis of several tools in these platforms where we

have considered several aspects like shown on table

Table 1: Analysis of e-learning platform.

Platforms

Comercial Open Source

Tools/Features

BB WebCT IntraLearn Angel ATutor Moodle Sakai .LRN

Technical Aspects

Interoperability/integration 9 9 9 9 9 9 9 9

Standards and specs compliance (1),

(2), (3)

(6), (1) (1), (2), (3),

(4), (5)

(1), (6) (1), (2)

(1) (6) (6)

Extensibility x x X x 9 9 9 9

Adaptation and Personalization

Interface Costum. and personaliz. 9 9 9 9 x 9 9 9

Choose Interface Language 9 9 9 9 9 9 x 9

Students previous knowledge x x X x x x x x

Courses and Resources adaptability x x X x x x x x

Administrative

Student Manage. / Monitor. tools 9 9 9 9 9 9 9 9

Database Access mechanisms x x 9 9 9 9 9 9

Produce reports 9 x 9 9 9 9 9 9

Admin. workflows quality & functio. 9 9 9 9 9 9 9 9

Tracking users 9 9 9 9 9 9 x x

Resources Management

Content Authoring and Editing 9 9 9 9 9 9 9 9

LOs and other types of content Mng. x 9 X x x x x x

Templates to aid on content creation x 9 9 9 9 9 9 9

LO Search and Indexation x x X x 9 x x x

File upload/download mechanisms 9 9 9 9 9 9 9 9

Evaluation of quality of resources x x X x x x x x

Learning Ôbjects Sharing/Reuse x x X x 9 x x x

Communication

Forum 9 9 9 9 9 9 9 9

Chat 9 9 9 9 9 9 9 x

Whiteboard 9 9 X 9 9 x x x

Email 9 9 9 9 9 9 9 9

Audio and Video Streaming x x X 9 x x x x

Evaluation

Self Assessments 9 9 9 9 9 9 9 9

Tests 9 9 9 9 9 9 9 9

Inquiries 9 9 9 x x 9 x x

Costs High High High High None None None None

Documentation 9 9 9 9 9 9 9 9

SCORM - (1); IMS - (2); AICC - (3); LRN - (4); Section 508 - (5); Some IMS Specifications - (6)

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Analysing table 1 we have found that the

majority of the e-learning platforms have good

administrative and communication tools, compliance

with standards like SCORM, AICC and some of the

IMS specifications. These platforms have high

implementation level and good documentation. On

the other hand we could notice that these platforms

have some problems regarding LO management,

sharing and reusability and in LO quality evaluation.

They also have some problems related to the

adaptation of resources to the students’

characteristics among others. From the comparison

of commercial and freeware/open-source platforms

we found that the commercial ones have more

difficulty in integrating with other systems and

supporting different kinds of pedagogies and of

course in terms of costs. So, in table 2 we resume

some strong points and weaknesses that we have

found.

These weaknesses are traduced in problems in

terms of interoperability of resources, reusability of

the resources, learning domain independence,

quality of learning resources and extensibility of the

platforms, what meets some of our goals already

presented before.

So, in order to solve these problems and from the

confrontation between commercial and open-

source/freeware platforms, we have decided to

develop an open source platform focused on issues

like adaptation, LO and Metadata Management and

evaluation.

Table 2: Strong points and weaknesses of e-learning

current approaches.

Strong Points Weaknesses

Communication Tools Resource management &

portability

Administrative &

Management Tools

Adaptability and

personalization

Compliance with standards Quality of resources

Implementation Level Development of new

components

Documentation Diversity of pedagogies

and applications

Possibility of hierarchical

organization

Costs (Comercial

Plataforms)

3 STANDARDS AND

SPECIFICATIONS

COMPARATIVE ANALYSIS

One of the biggest difficulties of e-learning systems

and platforms is in structuring content and

information using nowadays pedagogical models, so

they can reach a wider range of educational systems

and obtain a greater quality of teaching.

Among these standards and specifications there

are some more focused on the design and structuring

of courses and others that try to enclose, in a general

way, all the process of teaching/learning. Among the

specifications that first emerged we have Sharable

Content Object Reference Model (SCORM) (Scorm,

2004), a project from Advanced Distributed

Learning (ADL), and the specification Educational

Modelling Language (EML) (Koper, 2003).

However these have some problems.

SCORM becomes more a standard integrator

than a standard by itself, what makes it dependent of

the other standards it integrates, besides it doesn’t

consider the evaluation and characterization of

students. EML is a specification that became

obsolete when the IMS (Instructional Management

Systems) Learning Design (LD) (IMS, 2004)

emerged, however it allows the building of the

learning experience based on learning activities,

being open to any other learning theories, including

aspects such as sequence of activities, users’ roles

and students’ characterization and evaluation. An

example of an EML application is HyCo (Hypertext

Composer), which is an authoring tool to create

contents (Garcia et .al, 2004). Finally we have the

IMS specifications that are used as a guide for

structuring contents, developed by the IMS

consortium (IMS, 2004), that began its activity with

the definition of specifications for instructional

structure, to become the standard it is today. It

includes specifications to structure the learning

process, the learning objects and their metadata, to

design units of learning and courses, to evaluate and

characterize the users, among others. The main

objective of these specifications is to be as general

as possible, so they can be applied to any process of

teaching/learning.

As we know the use of standards have become

very useful not just for the sake of saying that you

use a standard but because the use of a standard or

standards automatically makes everything you make

cross systems providing this way common

knowledge. The use of a standard helps to achieve

more stable systems, reduces the development and

maintenance time, allows backward compatibility

and validation, increases search engine success,

among many other know advantages.

Having detected the main problems of current e-

learning approaches, we’ve started to analyse several

aspects of several standards and specifications to

choose the one(s) that would best fit our needs, like

described on table 3.

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Table 3: Standards and specifications comparative

analysis.

Features IMS AICC SCORM Dublin

Core

Metadata

9 9

Learner Profile

Content

Packaging

9 9 9

Q&T

Interoperability

Content structure

9 9 9

Content

Communication

9 9

Learning Design

Simple

Sequencing

Accessibility

XML

9 9

Bindings

RDF

Implementation

handbooks

9 9

Learner

registration

We have analyzed the IMS Specifications, AICC

(AICC, 2005), SCORM and Dublin Core (Dublin

Core, 2005), regarding the following:

• Metadata - format to represent the metadata to

describe the learning resources;

• Learner Profile – format to record and manage

learning-related history, goals, and

accomplishments;

• Content Packaging – format to package courses

and resources so they can easily be transported to

other systems;

• Question & Test Interoperability - structure for

the representation of questions and test data and

their corresponding results reports;

• Data Repositories Interoperability – description

how to interact between data repositories;

• Content Structure – format to structure contents;

• Content communications – format to promote the

content communication;

• Learning Design – specifications for describing

the elements and structure of any unit of

learning;

• Simple Sequencing – format to represent

information needed to sequence learning

activities in a variety of ways;

• Accessibility – takes into account the issue of

accessibility;

• Bindings to XML and RDF – specifications to

describe the resources in XML or RDF;

• Implementation handbooks – information

available;

• Learner registration - format to register learner

related information.

From this analysis we’ve chosen the IMS

specifications, since they allow most of the aspects

we’ve analyzed and that we considered important to

reach our goals.

4 AHKME DESCRIPTION

AHKME is an e-learning platform that is divided in

four different subsystems: Learning Object Manager

and Learning Design subsystem, Knowledge

Management subsystem, Adaptive subsystem and

Visualization and Presentation subsystem. These

subsystems were structured this way taking into

account a certain line of reasoning, where first we

have the process of creation and management of

learning objects (LO), which is followed by the

process of course creation through the learning

design (LD). In parallel with these two processes the

Knowledge Management subsystem makes an

evaluation of the quality of the available learning

objects and courses. Then they pass through an

adaptive process based on the students’

characteristics to be presented to them, as we can see

on figure 1.

To implement the subsystems mentioned before

we have been developing Web applications using

HTML (Hypertext Markup Language) and CSS

(Cascade Style Sheets) for the Web pages’ design,

PHP (PHP: Hypertext Preprocessor) to run on server

side to make the manipulation of XML files,

Javascript to run on client side to implement

mechanisms in Web forms, pop-up windows and

.NET and C to implement several software agents.

Figure 1: AHKME’s structure.

These subsystems use XML as standard for file

storage. This standard has been widely used because

it allows the interchange of contents between

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different applications and platforms, facilitating the

publishing of contents (Bray et.al, 2004).

All the tools of the Learning object management

and Learning Design subsystem include a

mechanism that packages the generated information,

at the level of learning objects, courses as well as at

the level of the adapted courses.

Like said before we will now focus on the parts

of this system that provide the management and

evaluation of learning objects through their

metadata.

4.1 LOM and Learning Design

Subsystem

The Learning Object Management and Learning

Design Sub-system is mostly used by teachers. With

this sub-system we provided several features where

teachers can develop, search, retrieve, import and

analyze resources and also create courses.

We will now describe the tools and features of

this sub-system and how they are related with the

IMS specifications.

4.1.1 LO Manager

The Learning Objects Manager is a tool that allows

teachers to define and create metadata to describe

LOs. It uses the IMS Learning Resource Metadata

specification, which is based on the IEEE LOM

standard that allows the management and

representation of knowledge through LOs. The

architecture of this tool is described on figure 2.

This tool allows the user to edit LOs and

associate descriptive metadata to them.

Then all information is passed into a XML

manifest, that gathers all the XML files with their

metadata and all the resources used by a LO. By

this, it makes it easier to manage all the learning

contents, structuring all the information in XML

files, that can easily transport this structured

information, an also gives the possibility to the user

to create general metadata that can be associated

with any LO. Besides that, it still allows the creation

of packages with their manifests with the LOs and

their storage in a MySQL database, what enables the

management of these packages that will be used in

the design of. All the files and packages that are

imported or created in the platform pass through a

validation process with the schemas to check if

they’re in conformance with the IMS specifications,

and all the communication between tools and

databases is done based on the XML Document

Object Model (DOM).

The information packaging enables the creation

of packages of LOs and courses with their metadata,

so they can easily be transported and reused in other

systems, going towards reusability and

interoperability, using the IMS CP specification

(IMS, 2004).

The LOs are not static in the repositories, but they’re

in constant evaluation made by the knowledge

management sub-system that has tools that

communicate with this LO Manager. After the LOs'

evaluation, it may be needed to change the LO

cataloguing or the way that a LO is related with

other LOs, to get better LOs’ associations, in order

to obtain courses in a easier way taking into account

the content models that were more efficient. So, this

tool allows these changes that are reflected until the

creation of the content package, taking into account

the user’s wishes, granting a higher level of

flexibility.

Figure 2: LO Manager architecture.

The main advantage of using the IMS

specification for LOs is that through the association

of descriptive tags, we can better index them, find

them, use and reuse them.

4.1.1.1 LO Search Engine

The search of learning objects is a very important

task in order to reach reusability. The descriptive

metadata associated to the LOs becomes now more

important than ever, since the search is based on it.

The learning object’s search engine, provided by this

platform, is based on an intelligent agent that

receives as inputs the metadata elements from IMS

LRM for the search and retrieval of the LO.

When the teacher accesses the LO search engine,

he can choose from two different types of search –

simple or advanced. If the teacher chooses a simple

search the agent automatically presents the metadata

elements mostly used in searches for him to fill.

Otherwise if the teacher chooses an advanced

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search, the search engine allows the selection of

whatever elements he wants to search for.

Finally, the search engine, as result of the

elements selected, presents the LOs according to the

teacher’s search query with the respective quality

evaluation, attained by the LOs evaluation. From

this search results the teacher can choose the LOs

with more quality to integrate the courses he is

creating.

The LO search is based on an intelligent agent

that makes the search based on keywords but we aim

to base the search on ontologies to relate concepts

among them.

4.1.1.2 Metadata Automation Process

The insertion of metadata can be a complex and

time-wasting process, because it has several

categories and in them several elements and items.

So, in our platform we provide an automation of

this process, to facilitate the insertion of metadata,

and to describe the LO’s through the most adequate

metadata elements. This way we can optimize the

LO’s search, retrieval and reusability and facilitate

the user’s task reducing the time of development of

learning objects.

4.2 Knowledge Management

Sub-System

The main objective of this system is to assure quality

to the information inside the platform through the

evaluation of LOs and courses, in order to get the

best courses and the best resources to reach to the

best learning/teaching process.

To evaluate LOs we’re developing two different

tools. One the tools allows teachers and experts to

analyze, change and evaluate LOs through a Web

application based on evaluation model that will be

described next. The other tool is an intelligent agent

that automatically evaluates LOs basing its final

evaluation on previous evaluations of other learning

objects.

We will now describe how the learning object

evaluation is processed and the knowledge model to

import external learning objects.

4.2.1 LO Evaluation

The quality of the learning resources is becoming an

aspect with great importance on e-learning

environments, since when e-learning systems first

emerged there was a massive production of

resources without taking into account their quality.

Resources were developed without measure, where

features like reusability were discarded. Nowadays

the scenery is changing and there are already several

criteria and aspects to consider in order to evaluate

the quality of a learning resource.

Vargo, et.al states that a systematic evaluation of

learning objects must become a valued practice if

the promise of ubiquitous, high quality Web-based

education is to become a reality (Vargo et.al, 2003).

Here we present a feature of our platform to

evaluate the quality of LOs based on metadata.

To archive an optimal evaluation of LOs, it’s

necessary to consider quality criteria from different

kind of categories, for this reason the following

criteria with the respective weight for the evaluation

of learning objects were proposed:

Psychopedagogical category (30%), contains

pedagogical criteria that can evaluate, for example,

if the LO has the capacity to motivate the student for

learning; Didactic-curricular category (30%), this

criteria can evaluate if the LO helps to archive the

unit of learning objectives, etc; Technical-aesthetic

category (20%) tries to evaluate the legibility of the

LO, the colours used, etc.; Functional Category

(20%), tries to evaluate its accessibility among other

aspects to guarantee that the LO doesn’t obstruct the

learning process. The final evaluation value is the

sum of all the classifications attributed to each

category multiplied by their weight. The

classification of the categories has the following

rating scale: 0 = not present; 1 = Very low; 2 = Low;

3 = Medium; 4= High; 5=Very High (Morales et al,

2004).

With these quality evaluation criteria defined,

we’re developing two different tools to evaluate the

quality of LOs. One of the tools allows teachers and

experts to analyze, change and evaluate LOs through

a Web application based on the evaluation model

mentioned before. This is a collaborative tool in

which experts and teachers analyse the LOs and give

an individual evaluation to the LO, then they gather

in a sort of on-line forum to reach to the final

evaluation of the LO (Morales et.al, 2004).

The other tool is an intelligent agent that

automatically evaluates LOs basing its final

evaluation on previous evaluations of other learning

objects. A schematic representation of the agent is

presented on figure 3.

In order to evaluate the LO, the agent starts to

import the LO to evaluate and other LOs already

evaluated. Then he applies data mining techniques

(decision trees) to the educational characteristics of

the LO defined in the IMS LRM specification in

order to calculus the final evaluation of the LO.

In order to use the learning objects evaluation

defined before we have made a correspondence

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between the educational characteristics defined on

the IEEE LOM standard and the aspects described in

the evaluation model (IEEE LOM, 2002).

For now we have just considered the educational

category because it has almost all the information

about the technical and educational aspects of LOs

we have considered important to evaluate LOs.

Figure 3: Agent schematic representation.

After the calculus of the final evaluation of the

object, the agent stores this information in an

auxiliary database made for this purpose and also

inserts it in the annotation element described by the

IMS LRM specification.

With these two tools the learning objects are

constantly being availed of their quality, playing an

important role in the reusability of the learning

objects for different contexts.

5 AHKME LOM VS SIMILAR

TOOLS

We have also done an analysis of some key features

of metadata tools confronting the learning object

metadata tool of AHKME with some other similar

learning object metadata tools. To make this analysis

we have defined a set of tasks like the ones

described on table 4 and tested if the different tools

supported them.

The Advanced Distributed Learning (ADL)

Sharable Content Object Reference Model

(SCORM) Metadata Generator (ADL SCORM,

2005) is an application for creating XML metadata

files based on SCORM specification and provides

data validation. The resource description tool of

EUN, created by Lund University in Sweden, is an

HTML page where the user can fill a number of

fields that represent the EUN (EUN, 2005) proposed

specification of educational metadata. Reggie

metadata editor (Reggie, 2005) supports a number of

metadata educational specifications where the user

has to complete the required fields and to select the

metadata format required from a list of technologies

available (Resource Description Format, HTML).

The LOM Editor (Lom Editor, 2005) is an

application for creation and modification of XML

metadata files based on a previous version of LOM

v1.4. The Alfanet (Alfanet, 2005) has an authoring

tool that is based on the standards of the IMS Global

Learning Consortium. So, AHKME LOM provides

some additional features regarding the packaging of

LO metadata and their evaluation. Although,

AHKME is the only tool that allows these features,

Alfanet also packages information but only at the

level of courses.

Table 4: Comparative analysis between AHKME LOM

tool and similar tools.

Tartsk

Alfanet

LOM

Editor

ADL

SCORM

Reggie

AHKME

LOM

EUN

Creation of new

metadata files

9 9 9 9 9 9

Modification of data in

metadata files

9 9 9

Support any

educational metadata

standard, specification

9 9

Modification of

structure of metadata

files

Validation in terms of

data values

9 9 9 9

Validation of structure

of metadata

9 9

Support of the XML

9 9 9 9

Packaging of LOs

metadata

Evaluation of LOs

metadata

LO Search and

Indexation

Allow metadata

document

management

The analysed tools can provide functionalities

for meeting specific requirements like XML

validation and support, and creation of metadata

files, lacking some important points like:

• Lack of educational orientation, by not providing

a list of available educational metadata;

• Require that the person who edits metadata must

know XML;

• Lack on functionalities regarding the user’s

needs to characterize several learning

environments;

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• They do not provide management of the

resources.

So, AHKME LOM distinguishes itself from the

others by introducing an abstraction level to the user

from the technical aspects in terms of the XML

language and is more focused on the user needs, by

facilitating the metadata annotation of the LO

through a metadata automation process and the

search and retrieval of the LO, for the user to reuse

the LO in another scenarios. Because of AHKME’s

LO quality evaluation, the user may choose the best

LOs that best fit his educational scenario.

6 CONCLUSIONS

In this article we’ve presented how the platform

AHKME uses the IMS specifications and metadata

for learning resource management and evaluation.

The IMS specifications, which use the

combination of potentialities of metadata and XML,

are excellent to represent knowledge.

Through knowledge management the platform

allows a continuous evaluation of contents, granting

quality to all the existing resources in the platform

for teachers and students to use.

The presented platform uses knowledge

representation and knowledge management as two

processes that work simultaneously to grant success

to the process of teaching/learning.

The main contributions of AHKME are the

learning object management and evaluation of

quality, where we tried to introduce some

intelligence to these processes through intelligent

agents; the usage of the IMS specifications to

standardize all the resources of the platform in order

to reach interoperability and compatibility of its

learning components, and the interaction of all

subsystems through the feedback between them

allowing the platform to adapt to the students and

teachers characteristics and to new contexts. So, it’s

very important to have the resources well

catalogued, available, and with quality so we can

create quality courses. Meanwhile, we should take

into account that quality courses don’t just depend

on quality resources, but mainly in the design of

activities to reach determined learning objectives.

Being a multi-purpose platform it can be applied

to several kinds of matters, students, and learning

strategies, in both training and educational

environments.

ACKNOWLEDGEMENTS

This work has been partly financed by Ministry of

Education and Science as well as FEDER

KEOPS project (TSI2005-00960).

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