the alter-nativa book for knowledge representation
TRANSCRIPT
I
The ALTER-NATIVA book for Knowledge Representation
João Sarraipa
Catarina Lucena
Ricardo Jardim Gonçalves
Universidade Nova de Lisboa
Silvia Baldiris
Ramon Fabregat
Universidad Nacional de Girona
Silvana Aciar
Universidad Nacional de San Juan
The ALTER-NATIVA book for Knowledge Representation
III
Acknowledgements
Authors have taken efforts in this project. However, it
would not have been possible without the kind support
and help of many other individuals and organizations of
the same project. We would like to extend our sincere
thanks to all of them.
We are highly indebted to CALE, CAM and CAC
communities for their contributions in the thesaurus
building.
We also would like to express our gratitude to
UNINOVA for its kind co-operation in producing and
publishing this booklet.
The research leading to these results has received
funding from the European Union under grant
agreement: ALTER-NATIVA Project
(DCIALA/19.09.01/10/21526/245-575/ALFA III (2010)
88).
The ALTER-NATIVA book for Knowledge Representation
V
Executive Summary
In general, formal knowledge representation enables
computers characterize relevant information related to
determined process elements and actors in a domain
for specific advanced reasoning. In the eLearning
domain, several mechanisms of knowledge
representation have been proposed, such as standards,
technological specifications and ontologies. Both
ontologies and specifications play an important role in
eLearning systems because they offer an explicit
conceptualisation allowing key concepts and terms
relevant to a given domain to be identified and defined
in a structure able to facilitate reasoning, use and
exchange knowledge between the components and
users of its systems and by that, to contribute to the
increase of its computational intelligence. In this paper
we introduce the importance of the knowledge
representation mechanisms to support the generation
of adaptable eLearning services for all.
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Table of contents
ACKNOWLEDGEMENTS ...................................................... III
EXECUTIVE SUMMARY ........................................................ V
LIST OF FIGURES .................................................................. X
LIST OF TABLES ................................................................ XIII
ACRONYMS LIST ................................................................ XV
1 INTRODUCTION .......................................................... 1
2 KNOWLEDGE MODELLING APPROACH FOLLOWED IN
ALTER-NATIVA .................................................................... 3
2.1 TERMINOLOGY .......................................................... 5
2.2 DOMAIN DICTIONARY ................................................. 5
2.3 GLOSSARY ................................................................ 6
2.4 TAXONOMY .............................................................. 7
2.5 THESAURUS .............................................................. 8
2.6 ONTOLOGY ............................................................. 10
2.7 KNOWLEDGE BASE ................................................... 11
3 ALTER-NATIVA’S KNOWLEDGE BASE ......................... 12
3.1 ONTOLOGY ............................................................. 14
3.2 THESAURUS ............................................................ 20
3.3 KNOWLEDGE BASE MANAGEMENT INTERFACE ................ 20
3.3.1 Create class on Webprotégé ........................... 24
3.3.2 Create Property on WebProtégé ..................... 25
3.3.3 Create Instance on WebProtégé ..................... 27
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4 THESAURUS OF ALTER-NATIVA PROJECT .................. 29
4.1 ALTER-NATIVA PROCESS FOLLOWED ......................... 30
4.2 THESAURUS INTERFACE ............................................. 34
4.2.1 Bot user ........................................................... 37
4.2.2 Administrator user .......................................... 38 4.2.2.1 Create a new concept.................................... 39 4.2.2.2 Edit concept .................................................. 41 4.2.2.3 Delete concept .............................................. 42
4.2.3 Bureaucratic user ............................................ 43
4.3 THESAURUS SYNCHRONIZATION .................................. 48
4.3.1 Delete concept ................................................ 49
4.3.2 Create concept ................................................ 50
4.3.3 Edit concept .................................................... 55
5 KB’S SERVICES OF THE PROJECT ................................ 57
5.1 KNOWLEDGE MANAGEMENT SERVICES ......................... 57
5.2 RECOMMENDATION SERVICES ..................................... 64
5.2.1 Recommendation of Users .............................. 65
5.2.2 Recommendation of VLOs .............................. 76
6 CONCLUSIONS .......................................................... 81
6.1 FUTURE WORK FEATURES .......................................... 82
7 REFERENCES ............................................................. 83
8 ANNEXES .................................................................. 86
8.1 EXCERPT OF LOM METADATA REPRESENTED IN ALTERNATIVA
KB 86
The ALTER-NATIVA book for Knowledge Representation
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8.2 EXCERPT OF DRD METADATA REPRESENTED IN ALTER-
NATIVA KB ........................................................................ 90
8.3 USER MODEL ........................................................... 92
8.4 WIKI TREE OF MATHEMATICS THESAURUS .................. 111
8.5 WIKI TREE OF LITERATURE THESAURUS ...................... 114
8.6 WIKI TREE OF TEACHING THESAURUS ........................ 116
8.7 WIKI TREE OF SCIENCE THESAURUS ........................... 117
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List of Figures
Figure 1 – KREs Relations in the taxis path to build
knowledge ...................................................................... 4
Figure 2 - Extract of a domain dictionary ....................... 6
Figure 3 – Example of Glossary ...................................... 9
Figure 4 - A part of the ALTER-NATIVA Knowledge Base
...................................................................................... 13
Figure 5- Knowledge base management interface ...... 21
Figure 6 - ALTER-NATIVA WebProtégé ......................... 23
Figure 7 - Create class option ....................................... 24
Figure 8 - Form to select a new class name ................. 24
Figure 9 - New class created ........................................ 25
Figure 10 - Create Property .......................................... 26
Figure 11 - New property form .................................... 26
Figure 12 - Create instance .......................................... 27
Figure 13 – New individual form .................................. 27
Figure 14 - Property value attribution ......................... 28
Figure 15 - Taxonomic structure illustration of the
ALTER-NATIVA Thesaurus............................................. 29
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Figure 16 - Thesaurus Building methodology [3] ........ 31
Figure 17 – Hierarchical representation of concepts ... 35
Figure 18 - Wiki front page options.............................. 36
Figure 19 - Wiki concept page example ....................... 38
Figure 20 – Steps to create a new concept .................. 41
Figure 21 – Steps to edit a concept .............................. 42
Figure 22 - Delete concept ........................................... 43
Figure 23 - Access the User Merge and Delete option. 44
Figure 24 - Delete user from database ......................... 46
Figure 25 – Change user rights ..................................... 47
Figure 26 - Synchronization architecture ..................... 48
Figure 27 - Delete concept with children associated ... 50
Figure 28 - Creation of a concept that points to an
existing master concept ............................................... 52
Figure 29 - Creation of a concept that points to a non-
existing master concept ............................................... 53
Figure 30 - The creates concept is referred as a master
concept ......................................................................... 54
Figure 31- Knowledge Management services .............. 59
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Figure 32 - Recommendation of services architecture 65
Figure 33 - Algorithm to obtain the most similar VLOs 80
The ALTER-NATIVA book for Knowledge Representation
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List of Tables
Table 1 - Support Tools description ............................. 17
Table 2 - Use case of concept creation ........................ 55
Table 3 - Summary of Knowledge Management services
...................................................................................... 61
Table 4 - Recommendation of services with similar
teaching experience ..................................................... 70
Table 5 - Recommendation of users with specific similar
profile characteristics ................................................... 72
Table 6 –Recommendation of users based on the
number of interactions ................................................ 74
Table 7 - Recommendation of users based on the
number of similar characteristics ................................. 74
Table 8 –Recommendation of users based on a
combination of number of interactions with common
profile users .................................................................. 75
Table 9 - Historical information associated to a VLO ... 76
Table 10 - Recommendation of VLO based on rating .. 77
Table 11 - Recommendation of VLO based on the
number of times consulted .......................................... 77
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Table 12 - Recommendation of the most similar VLO . 78
Table 13 - Combined recommendation of VLOs .......... 78
Table 14 - LOM metadata ............................................. 86
Table 15 - DRD metadata ............................................. 90
Table 16 - User Model General Profile ......................... 92
Table 17 - User model access to information
preferences .................................................................. 93
Table 18 - User Model ALTER-NATIVA Profile .............. 94
Table 19 - User Model Accessibility Profile ................ 103
Table 20 - User Model access preferences ................ 108
The ALTER-NATIVA book for Knowledge Representation
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Acronyms list
DB Data Base
DRD Digital resource Description
LOM Learning Object Metadata
KB Knowledge Base
KRE Knowledge Representation System
VLO Virtual Learning Object
1
1 Introduction
Currently is observed a great need for the development
or generation of services or mechanisms of adaptive
and intelligent E-learning content. E-learning is the use
of Internet technologies to enhance knowledge transfer
and performance in education and training. This
technologies offer learners control over content,
learning sequence, pace of learning, time, and often
media, allowing them to tailor their experiences to
meet their personal learning objectives [1].
Virtual education services should be accessible to
everyone (teachers and students). For that reason is
necessary to consider the specific needs of each user,
and consequently adapt the process to solve those
needs in a dynamic way. This can be done trough the
formal representation of knowledge that can be used
to support adaptive e-Learning services, even when it is
considered diversity characteristics.
This knowledge must be available and maintained by all
the involved community members on an e-learning
organization. In align to this, inside ALTER-NATIVA
community it was identified the need of organizing the
knowledge in such way that it could support the e-
learning infrastructures as described before. Thus it
was implemented the ALTER-NATIVA Knowledge Base
(KB) supported by web services and special graphic
The ALTER-NATIVA book for Knowledge Representation
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interfaces to facilitate the insertion, edition or
elimination of the knowledge necessary for the
adaptive e-Learning creation using the e-Learning
ALTER-NATIVA platform elements, such as Atutor,
Colabora and Repository.
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2 Knowledge Modelling approach
followed in ALTER-NATIVA
A Knowledge Representation Element (KRE) is an
element that facilitates the formal representation of
the knowledge in a specific domain. In the following
will be presented and explained some examples of
those elements: Dictionary; Glossary; Taxonomy;
Thesaurus; and KB.
The diagram of the Figure 1 represents the taxis path to
build knowledge of a specific domain. “Taxis” comes
from the Greek and means arrangement and to place in
order [2], which in this specific case represents a
specific arrangement, structured, of the lexicon to build
knowledge.
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Figure 1 – KREs Relations in the taxis path to build knowledge
In order to have a KB it is need to gather the knowledge
in a explicit way composed by, terminology, glossary,
thesaurus and ontologies supported by taxonomies,
domain dictionaries and human tacit knowledge. To
build a KB it is needed to build all the KRE presented in
Figure 1. First it starts to have a terminology to then
build a glossary followed by a thesaurus and finally the
ontology, which when populated becomes the KB in a
domain. The approach followed in ALTER-NATIVA is
based on MENTOR (methodology for enterprise
reference ontology development) [3]. Each one of
these components is explained in the following
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subsections. And latter on section 4.1 a more detailed
description of the knowledge gathering is described.
2.1 Terminology
Terminology is the study of terms and their use. Terms
are words that are used in specific contexts.
Terminology therefore denotes a more formal
discipline which systematically studies the labelling of
concepts particular to one or more concept fields or
domain of human activity, though research and analysis
of terms in context, for the purpose of documenting
and promoting correct usage [4].
2.2 Domain Dictionary
A dictionary is a book of alphabetically words in a
specific language, with definitions, etymologies,
pronunciations, and other information; or a book of
alphabetically listed words in one language with their
equivalents in another, also known as a lexicon.
A domain dictionary has been found to be one of the
most useful tools for a domain analysis. The dictionary
lessens a great deal of miscommunication by providing
users with information: 1) in a central location to look
for terms and abbreviations that are completely new;
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2) where definitions of terms are used differently or in
a very specific way within the domain [5]. Figure 2
illustrates an example of an extract of a domain
dictionary.
Figure 2 - Extract of a domain dictionary
2.3 Glossary
Glossary is a list of specialized terms, mostly in
alphabetic order, that sometimes are unique to a
specific concept. Each term is composed by its
corresponding description. It includes descriptive
comments and explanatory notes, such as definitions,
synonyms, references, etc.
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A glossary can be used when communicating
information in order to unify knowledge sharing. A
glossary is understood as a set of terms and their
definitions, and is bound to the source document or
domain where these definitions are set Figure 3.
2.4 Taxonomy
It has become fashionable in certain circles to apply the
term in a wider, more general sense, where it may refer
to a classification of things or concepts, as well as to
the principles underlying such a classification [6].
A taxonomy is a classification system that categorizes
all the information in a class/subclass relationship,
representing a simple tree structure. At the top of this
structure is a single classification, the root node that
applies to all objects. The root node represents most
general category of all things that the domain is related
to. Nodes below this root are more specific
classifications that apply to subsets of the total set of
classified objects [6]. For any category, each
subcategory is a taxonomy.
Each child is a subset of the parent. The intersection of
each pair of children, in same level, is empty. Any path
The ALTER-NATIVA book for Knowledge Representation
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from the root to a leaf is called a branch. Since
taxonomies are transitive, child nodes aggregate
parents’ categories by heritage.
2.5 Thesaurus
A thesaurus is a structure that manages the
complexities of terminology and provides conceptual
relationships, ideally through an embedded
classification. A classification is a structure that
organizes concepts into a hierarchy, possibly in a
scheme of facets. A monolingual thesaurus has terms
from one language, a multilingual thesaurus from two
or more languages [7].
associated meanings about a domain in a semantic
related structure. A thesaurus is like taxonomy of
domain concepts composed by its reference meanings.
The thesaurus can be then represented by a set of
classes representing domain reference concepts with
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2.6 Ontology
Gruber stated in 1993 one of the most well known
description about what is an ontology: An ontology is a
formal, explicit specification of a shared
conceptualization [8]. Taking the example of the
taxonomy presented before, ontology is like the
enrichment of such structure, with properties and rules
that relates its concepts with the purpose of
representing a segment of the reality following the
view of a determined group.
Recently, it has been seen an explosion of interest in
ontologies as artefacts to represent human knowledge
and as critical components in knowledge management,
the Semantic Web, business-to-knowledge applications,
and several other application areas. Ontologies are now
being recognized as important components of
information systems and information processing. In the
areas of Knowledge representation and reasoning and
of conceptual modelling, it has long been recognised
that conceptualising a domain is a prerequisite for
understand the domain and processing information
about the domain, especially in the case of large, non-
trivial domains [9].
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2.7 Knowledge Base
Ontologies aggregate semantics, rules and
characteristics able to classify and represent a segment
of the reality. An ontology is the (unspecified)
conceptual system, which underlies a particular KB
[10]. By other words, ontologies provide some
structure for development of KBs, serving to define its
models [11]. When ontologies are associated with real
instances/individuals it becomes a KB. A KB composed
by ontologies and thesaurus structured by a similar
taxonomy that aggregates a glossary of terms in a
specific domain can represent such semantic organized
structure establishing in this way the lexicon of a
specific domain Figure 1 [12].
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3 ALTER-NATIVA’s Knowledge Base
The establishment of a KB for ALTERNATIVA arises from
the need to represent all the knowledge related with
the project. Its main objective is to facilitate knowledge
management, which the community members would
be able to use, but also actively participate in its
maintenance. By this, ALTER-NATIVA’s KB will be in a
constant updating, thus keeping alive. The ALTER-
NATIVA’s KB is split in two distinct parts: the
“Ontology” and the “Thesaurus” (Figure 4).
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ALTER-NATIVA Knowledge Base
Thesaurus
Thesaurus of
support tools
Thesaurus of
Areas
Ontology
Performance
Support tools
User profile
Virtual learning
objects (VLO)
Alternativa
technologies
Users
Metadata
Preferences
Recommendations
General profile
Accessibility profile
Alternativa profile
Participation
Performance scenarios
Participation in
performance scenario
DRD
LOM
Has DRD metadata
User to recommend
Had participation
Has keywords
VLO consulting
User interactivity
Interaction with user
Has LOM metadataHad consulted VLO
Has alternativa profileHas accessibility profile
Has general profile
Thesaurus of science
Thesaurus of mathematics
Thesaurus of literacture
Thesaurus of teaching
Has keywords
Relation of type:
Is a
Other type
Figure 4 - A part of the ALTER-NATIVA Knowledge Base
The Ontology is dedicated to represent the Knowledge
of the platform. It has three main objectives, the first is
to enable professors to establish cooperation’s through
COLABORA tool; the second is related to possibility to
create Virtual Learning Objects (VLOs), thus they need
to be saved and categorized using a common
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vocabulary understood by all the community; the third
is related to the searching of information namely VLOs
or users related to specific characteristics.
The Thesaurus is dedicated to represent the lexicon of
ALTER-NATIVA. Thus its main purpose is to have a set of
reference concepts and meanings about its domain. It
is from this set of concepts that VLO are characterized,
and is also using a specific wiki that the thesaurus is
updated enabling, as described before, to maintain this
community knowledge alive.
Consequently the further sectors of this chapter
present in detail these two KB main sectors (see Figure
4), the Ontology and the Thesaurus.
3.1 Ontology
An ontology provides a vocabulary that describes a
domain of interest and a specification of the meaning
of terms used in the vocabulary. By defining shared and
common domain theories, ontologies help both people
and machines to communicate concisely, supporting
the exchange of semantics and not only syntax [13].
Considering this definition is to conclude that, an
ontology can represent not only the different classes,
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but also their properties and relations in the scope of
the ALTER-NATIVA’s network. Therefore, it provides
support to the creation of virtual collaborative
communities and VLOs through recommendation
services, which uses user profiles and other information
as support learning tools or objectives to enhance
accessibility of trainees. It is also necessary to
understand how users and their profiles are related
with the Virtual learning Objects and what kind of tools
can be used to reduce the learning vulnerability
(diversity) of some users
The Ontology is composed by six main classes, where
the classes Users and Virtual Learning Objects are its
core, this because they are, directly or indirectly,
related to all the other classes (see Figure 4). The User
class represents all the users of the ALTER-NATIVA
platform, and the VLO class represents the Virtual
Learning Objects. In additional, all the
recommendations in the scope of the project are based
on the content of the information represented by these
both classes.
The User profile class is able to represents a user profile
characteristics. This is composed by three main profile
characteristic, namely: 1) General Profile; 2)
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Accessibility Profile; and 3) Alternativa Profile (Annexes
8.3). The General Profile contains the general
information related to a user, in particular to the
communities, which a user belongs and also its level of
studies accomplished. The Accessibility profile contains
the Information related to the disabilities of a user
(visual, hearing, physical and cognitive). By the last, the
Alternativa Profile that encompasses the information
about the teaching profiles, namely the specialization
area, the investigation groups, which a user was
involved, the level of knowledge when leading with
some disability, etc...
The Support Tools class is designed to represent the
support tools and its characteristics. One example of
the characteristics represented is shown in Table 1. As
can be observed, it also contains the information
related to the kind of users for which a support tool is
designed to. This class is connected to the Thesaurus
through keywords (Palabras Clave) of the supporting
tool description.
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Table 1 - Support Tools description
Camera Mouse (SG010)
Descripción: Permite controlar en
Windows el puntero del ratón
simplemente moviendo la cabeza, a
partir de la imagen tomada por una
webcam.
El primer paso consiste en calibrar
el programa, para que identifique
los movimientos de la cabeza, tras
lo cual el puntero responderá a
estos movimientos.
Para realizar los clics, sólo es
necesario dejar el puntero
relativamente quieto durante un
período de tiempo configurable.
También es posible hacer doble
clic.
Imagen
Ilustración 1 Configuración de
Camera Mouse
Autor/Fabricante/vendedor:
Boston College
URL: http://www.cameramouse.org
Área: Ciencias Lenguaje Matemáticas
Discapacidad: ☐ Auditiva
☐ Cognitiva
Física ☐ Visual
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Camera Mouse (SG010)
Vulnerabilidad: ☐ Étnica
Socio-Económica ☐ Violencia
Idioma: ☐No aplicable
Sólo
inglés
☐ Sólo
español
☐ Varios, incluido el
español
Sistema Operativo
Windows ☐Mac ☐GNU/Linux
☐Symbian
☐iPad ☐Android
☐Chrome ☐No Aplicable
Criterio del revisor
Palabras Clave: accesibilidad, diversidad, tecnología, emulador, ratón,
webcam
Recomendable
☐No recomendable
Notas adicionales:
La aplicación es fácil de instalar y de
configurar por el usuario. Al ser
software libre es apropiada para ser
integrada en el kit alternativa
The ALTER-NATIVA’s Technologies class is conceived to
represent the technologies of the platform. It
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aggregates the representation of the VLO metadata
with the user’s preferences that are registered when
users access the information, which further on makes
possible some recommendations. The subclass
metadata of the ALTER-NATIVA’s Technologies class
represents excerpts of the LOM (Learning Object
Metadata) and DRD (Digital resource Description)
chosen to be the metadata of each VLO in ALTER-
NATIVA (see Annexes 8.1). In the Recommendations
class are represented the interactions between users,
namely the activities that they share. It’s also
represented which are the VLOs that a specific user
consulted. Finally, the Preferences class has the
information related with the way how users prefer to
access to the information (see Table 20 of Annexes).
Finally, the Performance class represents all the
performance scenarios of the platform and the user’s
participations at these performance scenarios. This
information is represented accordingly with the
information represented in the first section of Table 18
at C in the annexes.
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3.2 Thesaurus
Thesaurus is like a taxonomy of domain concepts
composed by its reference meanings. In what concerns
the ALTER-NATIVA project, the Thesaurus contains
definitions that make possible a common
understanding about the disabilities that affect the
platform users, the different kinds of possible available
help and its characteristics. Thesaurus also contains
definitions to accomplish the understanding of VLO,
and then it gives a brief definition about his concepts
and sub-concepts.
The Thesaurus is related to the Ontology through
keywords used in tools guides and in metadata content
of VLOs. A better explanation of the Thesaurus is
presented with more detail in section 4.
3.3 Knowledge base management
Interface
The ALTER-NATIVA Knowledge Base can be managed in
two different ways: 1) by an ontology manager who can
directly edit the KB offline and upload the OWL file into
the repository folder using SSH (Secure Shell)
accordingly to the Webprotégé server specifications: 2)
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by various community users that can edit online the KB
trough an ontology editor web interface (Figure 5).
Ontology manager
KB repository
Webprótegé
ALTER-NATIVA Knowledge Base
Thesaurus
Thesaurus of
support tools
Thesaurus of
Areas
Ontology
Performance
Support tools
User profile
Virtual learning objects (VLO)
Alternativa technologies
Users
MetadataPreferences
Recommendations
General profile
Accessibility profileAlternativa profile
Participation
Performance scenarios
Participation in performance scenario
DRDLOM
Has DRD metadata
User to recommend
Had participation
Has keywords
VLO consultingUser interactivity
Interaction with user
Has LOM metadataHad consulted VLO
Has alternativa profileHas accessibility profile
Has general profile
Thesaurus of scienceThesaurus of mathematics
Thesaurus of literactureThesaurus of teaching
Has keywords
Relation of type:
Is a
Other type
Protégé
Apache TomcatSSH
Community Users
Figure 5- Knowledge base management interface
An ontology editor needs a graphical visualization of
ontologies. Such representation can be accomplished
by means of directed or nested graphs, topic maps or
other techniques. However it isn’t an easy operation to
accomplish, because ontologies are more than just a
hierarchy of concepts [14]. They are the sum of various
relations and attributes between classes and entities,
and in turn, these can have a wide number of instances,
so it can be difficult to represent or visualize ontologies
effectively.
The ontology visualization tool used was Webprotégé
which is a Collaborative Ontology Editor and Knowledge
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Acquisition Tool for the Web. WebProtégé includes a
set of predefined tabs, which contain the most popular
functionality in the protégé desktop editor [15]. For
example, the predefined Classes Tab enables users to
browse and edit the class hierarchy and the properties
of classes. The Properties Tab provides access to the
details of the properties in the ontology. The
Individuals Tab contains forms for acquiring instances
of classes [16]. Concluding, WebProtégé currently
supports the full-fledged editing of classes, properties
and individuals [16].
ALTER-NATIVA’s ontology was developed with Protégé
3.4.8, thus it uses OWL 1.0, RDF(S), and Frames
formats. That formats are supported by Webprotégé.
The Knowledge Base is available online at the URL
http://arale.udg.edu:8080/webprotege (Figure 6).
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Figure 6 - ALTER-NATIVA WebProtégé
ALTER-NATIVA’s KB can be edited through Webprotégé
by a logged in user. This user can create, delete or edit
classes, properties and individuals. The steps to take in
each on the mentioned actions are explained in more
detail in the following subsections. Although the user
can change the Thesaurus but he/she must be aware
that those changes will not be reflected in the wiki
thesaurus. That is because the synchronization from
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the ontology to the wiki is not implemented, it is only
implemented in the other way.
3.3.1 Create class on Webprotégé
To create a new class, the user must select the class
that will be the master (parent) of the new class
created and then press create, as is shown in Figure 7.
Figure 7 - Create class option
After that, will appear a form, so the user can choose
the name of the new class.
Figure 8 - Form to select a new class name
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Then, the new class will appear in the specified father
class with the chosen name (Figure 9).
Figure 9 - New class created
3.3.2 Create Property on WebProtégé
In order to create a new property, the user needs to
select the tab Properties and then select “create” from
the various available actions to take (Figure 10).
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Figure 10 - Create Property
Then will appear a form, where the user can enter the
name of the property and the property type to create
(Figure 11).
Figure 11 - New property form
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3.3.3 Create Instance on WebProtégé
A new individual is created through the selection of the
“create” option in the individuals tab (Figure 12).
Figure 12 - Create instance
As in the previous cases, it will appear a form where
the user can fill with the name of the instance to be
created (Figure 13)
Figure 13 – New individual form
The ALTER-NATIVA book for Knowledge Representation
28
After that, is possible to fill in the properties values to
that instance (Figure 14).
Figure 14 - Property value attribution
The ALTER-NATIVA book for Knowledge Representation
29
4 Thesaurus of ALTER-NATIVA
project
The ALTER-NATIVA Thesaurus represents the
information related to the concepts of four distinct
areas, namely Literature, Mathematics, Science and
Teaching. This information is composed by the
definition of each concept (keyword), the creation or
agreement date and the author/authors.
Mathematics
· Definition
· Creation data
· Author of the concept
Literature
· Definition
· Creation data
· Author of the concept
Teaching
· Definition
· Creation data
· Author of the concept
Science
· Definition
· Creation data
· Author of the concept
Areas
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Thesaurus
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Concept
· Definition
· Creation data
· Author of the concept
Figure 15 - Taxonomic structure illustration of the ALTER-NATIVA Thesaurus
The ALTER-NATIVA book for Knowledge Representation
30
4.1 ALTER-NATIVA process followed
The process followed for the thesaurus building has,
three steps: (1) terminology gathering; (2) glossary
building; and (3) thesaurus building (Figure 16). These
steps were defined based on the MENTOR, which
defines a set of workflows that also establishes a
thesaurus for the domain before starting the ontology
building [3].
The terminology gathering step (step 1) concerns the
process of collecting all relevant terms or concepts in a
specific domain previously defined. All the participants
in the process should give their inputs. There is no rule
from where the terms should come, since they are
related to the domain established. Concerning the
ALTER-NATIVA specific Thesaurus building case, was
asked to several professors of each area to collect
terms/concepts that may be used as keywords to
characterize Virtual Learning Objects that they think
they could intend to build in their future work.
All the concepts provided from contributors are
acceptable in this step, as nobody has authority at the
moment to erase another’s participant term. Thus, the
terms should be collected with reference to the
The ALTER-NATIVA book for Knowledge Representation
31
contributor, in order to enable each contributor to
provide term’s definitions during the next step.
No
Domain Defined
Domain related terms
collection
Annotations
attribution to the
terms
Terms revision
Agreement?
Taxonomic structure
definition
Terms classification
in the defined
structure
Agreement?
Yes
Thesaurus
Yes
Te
rmin
olo
gy
Ga
the
rin
gG
los
sa
ry
Bu
ild
ing
Th
es
au
rus
Bu
ildin
g
Figure 16 - Thesaurus Building methodology [3]
The Glossary building step builds a glossary in the
domain defined. It starts with annotations attribution
to the terms collected in the step before (Terminology
gathering). Then, each professor should provide the
The ALTER-NATIVA book for Knowledge Representation
32
annotations for his/her own terms. After having all the
terms provided with annotations, it proceeds to the
terms revision cycle to reach a reference definition. The
process for revision of terms can have four mismatches
cases:
· Existence of two syntactically different terms
with the same meaning description – the action
is to adopt one of the terms for being the
reference in such semantics meaning.
· Existence of two syntactical equal terms with
the same meaning description – the action is to
erase one of them.
· Existence of syntactically different terms with
two different meaning descriptions – no action
needed, both must be kept.
· Existence of two syntactically equal terms with
two different meaning descriptions – the action
is to consolidate all the provided descriptions
together in one of them and erase the other. In
such a case, a new term could be proposed to
the list if there is no agreement in the
conjunction of the input descriptions and if the
term to be born is not present in the
terminology list.
The ALTER-NATIVA book for Knowledge Representation
33
After a careful revision of all the terms with a successful
agreement in their meaning consolidation, the glossary
is defined from the terminology list in the domain
specified.
The thesaurus-building step is composed of a cycle
where the knowledge engineers and the domain
experts define a taxonomic structure from the glossary
terms, establishing some as thesaurus node terms (see
Figure 15). Afterwards, the other terms are classified
into semantic proper paths in the existent taxonomic
structure, into reaching the thesaurus leafs. If there is
an agreement in the structure and in the terms
classified, the thesaurus is defined. If not, the cycle
starts again.
The thesaurus tree developed for each area is, available
in the annexes:
1. Thesaurus of Mathematics : Annexes 8.4; 2. Thesaurus of Sciences : Annexes 8.7;
3. Thesaurus of Literature : Annexes 8.5;
4. Thesaurus of Teaching : Annexes 8.6;
The ALTER-NATIVA book for Knowledge Representation
34
4.2 Thesaurus Interface
Since a Thesaurus is like a taxonomy of domain
concepts composed by its reference meanings, it was
used Wikimedia1 as a front-end to enable
communication and knowledge gathering from the
ALTER-NATIVA professor’s community. Together with
the wiki extension CategoryTree2 it was possible to
represent a hierarchical representation of the concepts
used in taxonomies (see Figure 17).
1 MediaWiki is a free software open source wiki package
written in PHP, originally for use on Wikipedia. It is now also used by several other projects of the non-profit Wikimedia Foundation and by many other wikis, including this website, the home of MediaWiki. 2 The CategoryTree extension provides a dynamic view of the
wiki's category structure as a tree. It uses AJAX to load parts of the tree on demand. CategoryTree was originally written by Daniel Kinzler as an external tool, but was later integrated into the MediaWiki software with the help of Tim Starling.
The ALTER-NATIVA book for Knowledge Representation
35
Hierarchical representation of
Concepts
Figure 17 – Hierarchical representation of concepts
It was developed four different wiki Thesaurus that are
respectively available at:
5. Thesaurus of Mathematics : http://arale.udg.edu/alternativa/matematic
a/?title=P%C3%A1gina_principal
6. Thesaurus of Sciences :
http://arale.udg.edu/alternativa/ciencia/?title=P%C3%A1gina_principal
7. Thesaurus of Literature :
http://arale.udg.edu/alternativa/ciencia/?title=P%C3%A1gina_principal
8. Thesaurus of Teaching :
The ALTER-NATIVA book for Knowledge Representation
36
http://arale.udg.edu/alternativa/didatic
a/?title=P%C3%A1gina_principal
Through each one of the wiki Thesaurus main page is
possible to access the other wiki thesaurus, as can be
seen in (Figure 18).
Access to other wiki Thesaurus
Access to subject children
Figure 18 - Wiki front page options
The Thesaurus wiki was configured to have three kinds
of users:
1. Bot – Only consulting privileges;
2. Administrator – wiki knowledge administration.
3. Bureaucratic – User administration privileges.
The ALTER-NATIVA book for Knowledge Representation
37
Any user can create his own account in “crear una
cuenta” at the right top corner of the wiki. By default
its account will be of the bot kind. The process to
change it is explained in the 4.2.3 bureaucratic
subsection.
4.2.1 Bot user
For a common bot user of Thesaurus wiki (without
admin privileges), is only possible to consult
information, namely
1. He/she can navigate through hierarchical
structure of the concepts that compose the
thesaurus and, by clicking on [+], he/she is able
to access to a concept children (Figure 18);
2. In additional, he/she can see the concept
definition, creation date and authors of each
concept (Figure 19). In such concepts definition
pages the user can go directly to its master
(parent) or children concepts (Figure 19).
The ALTER-NATIVA book for Knowledge Representation
38
Figure 19 - Wiki concept page example
4.2.2 Administrator user
The Thesaurus wiki administrator is able to manage the
information represented in the Thesaurus. There are
three main actions that the administrator can do to
keep the thesaurus updated: 1) Create a new concept;
2) Edit a concept; and 3) Delete a concept. Firstly the
user needs to login with his credentials. The login is
available in “iniciar sesión” at the right top corner of
the wiki ( Figure 19).
The ALTER-NATIVA book for Knowledge Representation
39
4.2.2.1 Create a new concept
There is various ways of creating a new concept. In the
following it is presented the easier way to do that. The
user must follow three steps to create a new concept,
as is illustrated in Figure 20. At first, the user needs to
search for the name of the new concept. The user has
to write in the searching form “category:” followed by
the new concept name (e.g. “category: new concept”
(see step 1 of Figure 20)). It is a new concept, thus it
shouldn’t exist in the thesaurus. If it exists will appear a
window like the one presented in Figure 19 but related
to the inserted concept. Thus, in this case the user does
not need to create it. If he/she inserted a real new
concept name, it will appear in the page the “Search
Results” as presented in the second step of Figure 20.
In this case, the user only needs to click on “categoria:
new concept”. By the last, a user must fill the form
illustrated of the step 3 with the required information
and press save.
If it is not inserted correctly the word “category:” the
wiki creates a wiki page instead of a wiki category. In
this case, it is necessary to eliminate the created page
and insert the concept in the wiki again. To find the
page badly created, it is a matter to go to the concept
The ALTER-NATIVA book for Knowledge Representation
40
father page if inserted correctly and see its children
concepts. Thus, the following step is to access to it and
then delete it. For this, it is only a matter to follow the
instructions to delete a concept (see “delete a concept”
on section 4.2.2.3). However if the badly created page
didn’t receive a concept father, then this page should
be searched directly in the overall list of pages created
in the wiki. Finally, is a matter to access to it and then
delete it as explained before.
In step 3 of Figure 20, the master concept (Concepto
Padre) of the form must be filled with a concept that
already exists in the Thesaurus tree. If the master
concept is filled incorrectly, the new concept will be
“lost” in the wiki. The admin can recover from this
situation searching this specific page, directly in the
overall list of pages created in the wiki. Then the user
should access to it, to then edit the concept and fill the
master concept with a valid name.
The ALTER-NATIVA book for Knowledge Representation
41
2
1
3
Figure 20 – Steps to create a new concept
4.2.2.2 Edit concept
The user can edit an existing concept of the Thesaurus
by pressing “Edit” in the corresponding page of the
concept to be edited (step 1 of Figure 21). Then will
appear a Form where the user can change the master
concept (Concepto Padre), the concept definition,
creation date and authors (step 2 of Figure 21).
As in the create concept section, if the master concept
is not filled correctly, the concept will be lost in the
The ALTER-NATIVA book for Knowledge Representation
42
wiki. In this case it is necessary to do the procedure
also presented in the mentioned subsection to recover
that situation.
1
2
Figure 21 – Steps to edit a concept
4.2.2.3 Delete concept
The user needs to press “Delete” in the concept
corresponding page to delete it (Figure 22) and then
confirm this action. If the eliminated concept has
children concepts, those concepts will be lost in the
wiki. They will be positioned at the root of the
Thesaurus. Thus they could be “moved” from there
The ALTER-NATIVA book for Knowledge Representation
43
simply by editing the master (parent) concept form of
those concepts.
1
2
Figure 22 - Delete concept
4.2.3 Bureaucratic user
The bureaucratic user can execute two different
actions: 1) Delete a user from the user database; and 2)
Promote a user to admin.
Delete a user from DB
The user elimination from the Data Base (DB) is
possible thanks to the installation of the wiki extension
The ALTER-NATIVA book for Knowledge Representation
44
“User Merge and Delete”3. After the installation of that
extension, in the wiki Special Pages appears the option
“User Merge and Delete”. The steps to access the
mentioned option are illustrated on Figure 23.
2
1
Figure 23 - Access the User Merge and Delete option
The bureaucratic user can delete another existing user
of the wiki by pressing “Merge and delete users” in the
Users and rights section of the special pages (see Figure
23 and Figure 24). Then will appear a Form where the
user can fill with the name of the user to delete (Old
3 User Merge and Delete extension allows wiki users with
the user merge permission (Bureaucrat by default) to merge one Wiki user's account with another Wiki user's account. (http://www.mediawiki.org/wiki/Extension:User_Merge_and_Delete)
The ALTER-NATIVA book for Knowledge Representation
45
user) and select the check point who says “Delete old
user” (step 2 of Figure 21).
Promote a user to admin
The bureaucratic user can manage the wiki privacy by
editing the users’ rights. This user can change another
user’s rights by pressing “User rights management” in
the “Users and rights” section of the special pages.
Then will appear a form to fill with the name of the
user whose rights will be changed. By the last, it is
necessary to fill the check box with the group where
the user will belong (step 2 of Figure 25).
The ALTER-NATIVA book for Knowledge Representation
48
4.3 Thesaurus Synchronization
A general overview of the Thesaurus synchronization
architecture is shown in Figure 26. This architecture is
composed of four main components:
· The Thesaurus Wiki where the knowledge of
the professor’s community is gathered;
· The Thesaurus Wiki Data Base (DB) that
contains all the contents/concepts of the
Thesaurus Wiki and means of detecting any
changes that may occur;
· The ALTER-NATIVA KB Knowledge that contains
the ontology and also the Thesaurus;
· The Synchronization module, that serves as a
user interface to the synchronization process
between the wiki and the ALTER-NATIVA KB.
Thesaurus wiki
Wiki DBALTER-
NATIVA KB
Synchronization
module
JDBCProtegé
OWL API
Update changes
Figure 26 - Synchronization architecture
The ALTER-NATIVA book for Knowledge Representation
49
This architecture uses the wiki DB to detect any
changes that have occurred in the wiki since it was last
run and then updates the Knowledge base’s Thesaurus
accordingly. In the previous section was explained the
different action that an Admin user can execute in the
wiki Thesaurus. In this section will be explained how
the synchronization module handles these changes to
have a correct representation of the wiki knowledge
updated in the entire platform. At the following
subsections are explained in detail the three actions,
which represent the mentioned changes: 1) delete
concept; 2) create concept; and 3) edit concept.
4.3.1 Delete concept
The elimination of a concept directly affects the
structure of the Thesaurus tree. If the deleted concept
that have children associated, is just removed from the
Thesaurus tree. But if the deleted concept had children
associated it is necessary to take some actions to
reflect the wiki status. In this case, the children are
positioned in the Knowledge Base Thesaurus root. in
Figure 27 is illustrated the initial and final status of the
Thesaurus tree after the deletion of a concept with
children. As can be seen, the action is related to the
deletion of the “Concept b”, which in the initial
The ALTER-NATIVA book for Knowledge Representation
50
thesaurus tree had the children “Concept c” and
“Concept b”. In the final state is possible to see that
these concepts are shifted to the root (Thing).
Initial Thesaurus Tree
Concept b
· Master concept: Thesaurus
Concept deleted
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Final Thesaurus Tree
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Figure 27 - Delete concept with children associated
4.3.2 Create concept
As the delete concept action, the creation of a concept
will directly affect the structure of the Thesaurus tree.
So it is necessary to rearrange the three to handle the
The ALTER-NATIVA book for Knowledge Representation
51
three special cases that will be explained at the
following.
The Figure 28 illustrates the case where the inserted
concepts referrers another existing concept as a master
concept. As can be seen, the concept to insert in the
Thesaurus points at the concept “Concept b” as is
master concept. Since the “Concept b” exists in the
initial state of the thesaurus tree, the action to take is
to insert the “Concept h” has child of “Concept b”.
The Figure 29 illustrates the case where the inserted
concepts referrers a non- existing concept as a master
concept. As can be seen, the concept to insert in the
Thesaurus points at the concept “Concept z” as is
master concept. Since the “Concept z” does not exist in
the initial state of the thesaurus tree, the action to take
is to insert the “Concept h” has child of “Thing”, that
means, place the new concept in the root.
The ALTER-NATIVA book for Knowledge Representation
52
Initial Thesaurus Tree
Concept h
· Master concept: Concept b
New concept inserted
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Final Thesaurus Tree
Concept h
· Master concept: Concept b
Figure 28 - Creation of a concept that points to an existing master concept
The ALTER-NATIVA book for Knowledge Representation
53
Initial Thesaurus Tree
Concept h
· Master concept: Concept z
New concept inserted
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Final Thesaurus Tree
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Concept h
· Master concept: Concept z
Figure 29 - Creation of a concept that points to a non-existing master concept
It is also possible to occur the case where the inserted
concept is referred as master concept by some of the
concepts placed in the root. Figure 30 illustrates the
mentioned case. As can be seen the “Concept y” is
pointed as master concept of “Concept f”. When the
new concept is inserted in the tree, “concept f” will be
placed bellow it.
The ALTER-NATIVA book for Knowledge Representation
54
Initial Thesaurus Tree
Concept y
· Master concept: Concept b
New concept inserted
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Concept f
· Master concept: Concept y
Thing
·
Concept g
· Master concept: Concept x
Thesaurus
· Thing
Concept a
· Master concept: Thesaurus
Concept b
· Master concept: Thesaurus
Concept c
· Master concept: Concept b
Concept d
· Master concept: Concept b
Concept e
· Master concept: Thesaurus
Final Thesaurus Tree
Concept y
· Master concept: Concept b
Figure 30 - The creates concept is referred as a master concept
Figure 30 also illustrates that some of the mentioned
atomic cases can occur simultaneously. Table 2
contains a summary explanation of all the possible
conjugations of the mentioned atomic situations and
which are the steps to execute by the synchronization
module.
The ALTER-NATIVA book for Knowledge Representation
55
Table 2 - Use case of concept creation
Inserted master concept exists?
Any concept in the "Thing" who
reference the new concept as master
Action
Yes Yes · Put new concept below the class referred as master concept.
· Put the class tree of the concepts that are in the class Thing and refer the new concept as master concept below them.
No · Put new concept below the concept referred as master concept.
No Yes · Put new concept below the class Thing.
· Put the class tree of the concepts that are in the class Thing and refer the new concept as master concept below them.
No · Put new concept below the class Thing.
4.3.3 Edit concept
When a concept is edited, if the master concept field of
the form (see Figure 21) is not changed, it is only
necessary to save (update) the new information in the
Knowledge Base Thesaurus. If the master concept is
changed, may occur two situations: 1) the new master
concept does not exist in the Thesaurus tree, so is
necessary to execute the steps illustrated on Figure 29;
The ALTER-NATIVA book for Knowledge Representation
56
or 2) the new master concept exists in the tree and is
necessary to execute the steps illustrated on Figure 28.
The ALTER-NATIVA book for Knowledge Representation
57
5 KB’s services of the Project
The Implemented Web Services are responsible for
giving worldwide users the mechanism of Knowledge
Management and reasoning trough the Web (those
Web Services can be accessed on
http://arale.udg.edu:8080/axis2/services/listServices).
This services use JENA libraries, a java API for OWL, to
edit and query the Knowledge Base. The available
services are divided in two groups: Knowledge
Management services and Recommendation services. A
better description of those will be given in the following
subsections.
5.1 Knowledge Management services
Knowledge Management services are essentially
divided in two groups (see Figure 31): 1) Knowledge
Editing services, the ones related to the knowledge
edition; 2) Knowledge Query services, that are the ones
related to the knowledge consultation.
All these services are related to the VLO, VLO
consulted, User Model (profiles), Performance
scenarios, Thesaurus and users interactions.
59
Knowledge Management Services
· User Model creation
· User Model edition
· User Model elimination
Virtual Learning Objects
· VLO creation
· VLO edition
· VLO elimination
Knowledge Editing services
· LOM metadata edition
· DRD metadata edition
· LOM metadata creation
· DRD metadata creation
· ALTER-NATIVA profile creation
· General profile creation
· Accessibility profile creation
· ALTER-NATIVA profile edition
· General profile edition
· Accessibility profile edition
User Model
· Interactivite activity creation
· Interactive activity edition
· Interactive activity elimination
· Set activity name
· Set user collection
· Edit activity name
· Add user to activity
· Delete user from activity
VLOs consulted
· Add consulting information
· Edit consulting information
· VLO consulting Elimination
Users' interactions
· Performance scenario creation
· Performance scenario edition
· Performance scenario
elimination
· Add participation in scenario
· Edit participacion in scenario
· Elimination os participation in
scenario
Performance scenarios
· Set rating of VLO
· Set usuario who consulted the
VLO
· Edit VLO rating
· Increment number of times
Virtual Learning Objects
· Return of all VLOs’ identifiers
· Return of VLO metadata
Knowledge Query services
· Return LOM metadata
· Return DRD metadata
User Model
· User Interactivite activity
consulting· Consult activity
· Consult users’s collection
VLOs consulted
· User consulting information
Users' interactions
· Performance scenario
consulting
· User participation in scenario
consulting
Performance scenarios
· Rating over VLO consulted
· Number of times consulted
· Return of all users’ identifiers
· Return of users profiles· Return ALTER-NATIVA profile
· Return General profile
· Return Accessibility profile
· Return Thesaurus
ThesaurusThesaurus
· Return Mathematics Thesaurus
· Return Science Thesaurus
· Return Literature Thesaurus
· Return Teaching Thesaurus
· Thesaurus synchronization
· Synchronize Mathematics
Thesaurus
· Synchronize Science Thesaurus
· Synchronize Literature
Thesaurus
· SynchronizeTeaching
Thesaurus
Colabora RepositorioWeb ThesaurusATutor
Platform elements
Figure 31- Knowledge Management services
60
The user interactions and the VLO consulted are a kind
of log of the system which then are mainly used to
perform recommendations. Figure 31 also presents
how the Knowledge Management are responsible by
the integration of the ALTER-NATIVA KB with the other
elements of the platform. The blue colour represents
the connection between the platform element ATutor
and the Knowledge Base of the project. As can be
observed, the blue colour helps to clarify the services
that ATutor uses to enable its own access to insert/edit
and consult the information related with the VLOs and
keywords (those are provided from the Thesaurus).
The orange colour represents the connection between
the platform element Repositorio and the necessary
services to be able to upload the metadata information
of the VLOs into the Knowledge base.
The red colour represents which services the platform
element Colabora can use to manage the information
related to the users and their profiles. Is also
represented in red colour the services to manage the
interactions between the users and their participations
in performance scenarios.
The red colour connects the Web Thesaurus with the
service responsible by its the synchronization with the
Knowledge Base
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61
A summary list of all Knowledge Management services
and a brief description can be consulted on Table 3. The
First column of the table consists in a direct relation
with the explanation made for the Figure 31. The
second column represents the name of the Web service
group that can be consulted on the URL:
http://arale.udg.edu:8080/axis2/services/listServices.
Table 3 - Summary of Knowledge Management services
Knowledge Management service
Service Group
Service name Service description
Thesaurus
synchro synchro
This service makes the synchronization between the wiki Thesaurus and the Knowledge Base
User Model
Modelo_Usuario
create_Usuario
Creates a User and the associated profiles (ALTER-NATIVA; General and Accessibility)
delete_Usuario
Deletes a User and the associated profiles (ALTER-NATIVA; General and Accessibility)
Id_todos_usuarios Returns the identifiers of all the user in the Knowledge Base
delete_perfil_alternativa
Deletes the ALTER-NATIVA's profile of a user
delete_perfil_general
Deletes the General profile of a user
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delete_perfil_accesibilidade_a_tecnologia_de_interaccion_y_comunicacion
Delete the Accessibility profile of a user
Virtual Learning Objects
OVAs_Servicios
get_OVA_by_id
Gets the metadata of a VLO giving the VLO's identifier as input (accordingly with Table 14 and Table 15 )
upload_OVA_by_id
Uploads the metadata of a VLO giving the VLO's identifier and the metadata as input (accordingly with Table 14 and Table 15 )
get_OVAs_Ids Returns the identifiers of all the VLOs in the Knowledge Base
create_OVA Creates a VLO and the metadata associated
delete_OVA_by_id Deletes a VLO and the metadata associated
Performance
scenarios
Escenario
get_all_escenarios Returns the identifiers of all the Performance scenarios
create_escenario Creates a performance scenario
upload_escenario_desempeno
Uploads the information of a Performance scenario (accordingly with desempeño of Table 18)
Get_escenario
Gets the information of a performance scenarios given by a unique identifier (accordingly with desempeño of Table 18)
Thesaurus of
Mathematics
Thesaurus
create_tree_matematicas
Returns the Thesaurus of Mathematics concepts tree
create_tree_ciencias
Returns the Thesaurus of Sciences concepts tree
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create_tree_didaticas
Returns the Thesaurus of Teaching concepts tree
create_tree_lenguaje
Returns the Thesaurus of Literature concepts tree
User Model
Perfil_General
Upload_perfil_general
Uploads the General profile information related to a user given by a unique identifier (see Table 16)
Get_perfil_general
Gets the general profile information related to a user given by a unique identifier (see Table 16)
create_perfil_general
Creates a General profile for a user given by a unique identifier
User Model
Preferences
Upload_preferencias
Upload a user access preferences (see Table 20)
Create_preferencias
Create a user access preferences
Get_preferencias Get a user access preferences (see Table 20)
Delete_preferences Delete a user access preferences
User Model
Perfil_alternativa
Upload_perfil_alternativa
Upload a user ALTER-NATIVA's profile (accordingly with Table 18)
insercion_de_escenario_de_desempeno
Add a user participation in a performance scenario (accordingly with Table 18)
delete_participacion_por_id_usuario_y_nombre_escenario
Delete a user participation in a performance scenario
create_perfil_alternativa
Create an ALTER-NATIVA profile to a user
get_perfil_alternativa
Get a user ALTER-NATIVA profile (accordingly with Table 18)
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User Model
Perfil_de_accesibilidad
Upload_Perfil_accesibilidad
Upload a user accessibility (see Table 19)
Create_Perfil_accesibilidad
Create a user accessibility profile
Get_Perfil_accesibilidad
Delete a user accessibility profile (see Table 19)
5.2 Recommendation services
The recommendation services have as goal the support
in searching VLOs, which could be related to various
characteristics as for specific necessities (diversity) of
the trainees. It also has the goal to help on searching
professors related to specific profiles or teaching
experiences. The recommendations are essentially
done based on the User Model (profile), VLOs
metadata, historical information of the consulted VLO
by a user and users’ interactions. This information will
feed the ontology and make possible the
recommendation of items based on some existing
patterns (see Figure 32).
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UserVLO
Recommended items
Ontology
User
Interactions
Consulted
VLO
User
ModelVLO
Recommendation Services
Similar teaching experience
Recommendation of Users
Specific similar profile
characteristics
Number of interactions
Number of common
characteristics
Combination of number of interactions with common
profile users
Recommendation of VLOs
Similar VLOs (keywords)
More used VLOs
VLOs with higher rating
Combined recommendation of
VLOs
Recommendation System
Figure 32 - Recommendation of services architecture
In additional, the output of the recommender system
will be a user to interact or a VLO to consult,
respectively in the scope of Colabora or ATutor (Figure
32).
5.2.1 Recommendation of Users
Recommendation of users concerns the automatic
presentation of users to interact based on: 1) similar
teaching experience; 2) a specific similar profile
characteristics; 3) number of interactions between two
determined users; 4) number of common profile
characteristics between two users; and also 5) a
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combination of number of interactions with common
profile users.
When the recommendations deal with more than one
characteristic, the process of choosing the most
appropriated item is by calculating the one that has
more similarities to the set of chosen target
characteristics. Thus it was developed a function to be
used in such process, which calculates the strength of
each item with potential to be recommended. A
pseudocode example of a function that calculates the
item with “strength” in relation to a set of
characteristics is presented in the following.
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List_strength{
User_identifier;
Strength;
}
Function: Get users with similar expertise at creating
Input: User_identifier, maximum number of users
Begin
List_aux = Get list of users with the
same expertise creating
learning objects;
List_strength = [List; ones(0:
List_aux.size-1)];
List_aux = Get list of users with the
same expertise creating
didactical sequences;
List_strength =
List_aggregation(List_stren
gth, List_aux);
List_aux = Get list of users with the
same expertise creating
didactical sequences;
List_strength =
List_aggregation(List_stren
gth, List_aux);
List_strength =
Order_DESC(List_strength.st
rength);
End
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Output: List_strength(0: maximum number of users – 1);
End
Function: List_aggregation
Input: List_strength, List_aux
Begin
For i=0 to List aux.size() -1
If
(List_strength.User_identifier.contains(List_aux(i))
List_strength.strength =
List_strength.strength +1;
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Else
List_strength.Add(user_i
dentifier=List_aux(i);
strength = 1);
strength=1);
EndIf
EndFor
End
Output: List_strength;
End
The first user recommendation is based on users
teaching experience similarities. In Table 4 are
presented the services of recommendation of users
based on similar characteristics, together with a brief
description and the identification of the inputs and
outputs of the services.
There are two services from the following list, which
are in the gray lines that represent the aggregation of
the three previous services (in white lines). The
characteristics handled by these services are related to
the user profiles mainly presented at annexes 8.3
(Table 18).
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Table 4 - Recommendation of services with similar teaching experience
WEB SERVICE
DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the users with experience in the same kind of disabilities which the user has experience to teach
Usuarios_que_tienem_mesma_Experiencia_en_su_trabajo_docente
User identifier
Serialized ArrayList of users
Returns the users with experience in the same level of education which the user has experience to teach
Usuarios_que_tienem_mesma_Experiencia_docente
User identifier
Serialized ArrayList of users
Returns the users with the same expertise creating learning objects
Usuarios_que_tienem_mesma_experticia_en_Creacion_de_Objetos_de_Aprendizaje
User identifier
Serialized ArrayList of users
Returns the users with the same expertise creating
Usuarios_que_tienem_mesma_experticia_en_Creacion_de_Secuencias_didaticas
User identifier
Serialized ArrayList of users
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didactical sequences
Returns the users with the same expertise creating didactical unities
Usuarios_que_tienem_mesma_experticia_en_Creacion_de_unidades_didaticas
User identifier
Serialized ArrayList of users
Returns the users with the most similar expertise creating learning objects, didactical sequences and didactical unities.
Usuarios_con_mesma_experticia
User identifier; maximum number of users
Serialized ArrayList of users
Returns the users with the same expertise with virtual scenarios
Usuarios_que_tienem_mesmo_manejo_de_escenarios_virtuales
User identifier
Serialized ArrayList of users
Returns the users with the same expertise with digital networks
Usuarios_que_tienem_mesmo_manejo_de_escenarios_redes_digitales
User identifier
Serialized ArrayList of users
Returns the users with the same expertise with
Usuarios_que_tienem_mesmo_manejo_de_escenarios_presenciales
User identifier
Serialized ArrayList of users
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classroom scenarios
Returns the users with the most similar expertise with virtual scenarios, digital networks and classroom scenarios
Usuarios_con_manejo_de_escenarios_mas_similares
User identifier
Serialized ArrayList of users
Other type of user recommendations is done based on
a specific similar profile characteristic mainly related to
professors’ formation. This recommendation is done by
searching for other users with some profile
characteristics based on the User Model profile defined
in ALTER-NATIVA and that is represented on Annexes
8.3. In Table 5 are described the Web Services of
recommendation developed concerning some specific
users’ profile characteristics.
Table 5 - Recommendation of users with specific similar profile characteristics
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the users Usuarios_que_tiene User Serialized
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with the same level of knowledge about the theories of sciences professors formation
m_mesmo_Grado_de_conocimiento_de_Las_teorias_sobre_la_formacion_de_profesores_de_ciencias
identifier ArrayList of users
Returns the users with the same level of knowledge about the theories of literatures professors formation
Usuarios_que_tienem_mesmo_Grado_de_conocimiento_de_Las_teorias_sobre_la_formacion_de_profesores_de_lenguaje
User identifier
Serialized ArrayList of users
Returns the users with the same level of knowledge about the theories of mathematics professors formation
Usuarios_que_tienem_mesmo_Grado_de_conocimiento_de_Las_teorias_sobre_la_formacion_de_profesores_de_matematicas
User identifier
Serialized ArrayList of users
Returns the users with the same development area
Usuarios_que_Pertenecem_a_mesmo_Camo_o_area_de_desarrollo
User identifier
Serialized ArrayList of users
Returns the users of the same virtual community
Usuarios_que_Pertenecem_a_mesma_comunidad_virtual
User identifier
Serialized ArrayList of users
The recommendation of users can also be done based
on the number of times that a user interacts with
another one. The Web Service is presented in the
following table.
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Table 6 –Recommendation of users based on the number of interactions
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the users with the higher number of interactions with one given user
return_usuarios_con_mas_interacciones
User identifier
Serialized ArrayList of users
The recommendation of users based on the number of
common profile characteristics has as goal to return the
user with the most similar profile comparatively to
another user. For that, is made a search of a user with
the higher number of similar profile characteristics
from the entire User Model (see Annexes 8.3). The
characteristics taken into account are the specialization
field, professional development field, first and second
languages. The Web services is presented in the
following table.
Table 7 - Recommendation of users based on the number of similar characteristics
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the users with the most similar
get_usuarios_similares User identifier
Serialized ArrayList
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characteristics from specialization field, professional development field, first and second languajes
of users
By the last, a recommendation service based on the
combination of number of interactions with common
profile users is presented. This is an aggregation of the
two previous presented services. This service is
presented in the following table.
Table 8 –Recommendation of users based on a combination of number of interactions with common profile users
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the users with the higher strength based on the most similar characteristics from specialization field, professional development field, first
get_usuarios_similares
User identifier
Serialized ArrayList of users
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and second languages and number of interactions with another user.
5.2.2 Recommendation of VLOs
The services of recommendation of VLOs are divided in
four groups, the recommendation based on: 1) higher
rating; 2) most used; 3) number of similarities with
other VLOs consulted by the user; and 4) combination
of the previous properties.
To automatically recommend VLO is necessary to have
a historical representation of the consulted VLO.
Historical information is represented by a table (Table
9), which has the VLO and the user identifier, the
number of times the user consulted the VLO and its
associated rating (1- Good or 0 - Bad).
Table 9 - Historical information associated to a VLO
VLO identifier User identifier Number of times consulted Rating
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The recommendation of VLO based on the rating (Table
10) and the number of times consulted (Table 11) can
be done directly through the previous table.
Table 10 - Recommendation of VLO based on rating
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the VLO with the higher rating
return_OVAs_mas_gustadas User identifier
Serialized ArrayList of VLO
Table 11 - Recommendation of VLO based on the number of times consulted
WEB SERVICE
DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the most consulted VLO.
return_usuarios_con_mas_interacciones
User identifier
Serialized ArrayList of VLO
The recommendation of similar VLOs is done by
searching the ones that have the higher number of
keywords in common with other that the user
consulted before (see Table 12).
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Table 12 - Recommendation of the most similar VLO
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns most similar VLOs Ovas_similares User identifier
Serialized ArrayList of VLO
The combined recommendation of VLOs is done based
on all the previous described recommendation services
for VLO. This service is presented in the following table,
and its algorithm steps are illustrated in Figure 33.
Table 13 - Combined recommendation of VLOs
WEB SERVICE DESCRIPTION
SERVICE NAME INPUT OUTPUT
Returns the VLO with the higher strength based on the number of times consulted, rating and number of similarities
Recomendacion_OVAs User identifier
Serialized ArrayList of VLO
In the top left of Figure 33, it is shown how the
algorithm starts, which is by collecting the identifiers of
all the VLO consulted by a user. Then, are collected the
keywords of those VLOs (top right). After this, as can be
observed in the middle left of the figure, it is generated
a new table without the VLO consulted by the user. It is
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79
used to collect the VLO with equal keywords to be then
counted the number of keywords in common. Finally,
the recommendation result is represented by the
bottom table, which presents the VLO with common
keywords, ordered by the high number of keywords in
common.
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80
User identifier VLO identifier
1 1
1 3
2 1
VLO identifier Keywords
1Keyword 1
keyword 4
2
Keyword 1
Keyword 2
Keyword 3
3 Keyword 5
4Keyword 4
Keyword 5
5Keyword 8
Keyword 3
6Keyword 6
Keyword 5
7
Keyword 1
Keyword 4
Keyword 5
VLO identifier Keywords
2
Keyword 1
Keyword 2
Keyword 3
4Keyword 4
Keyword 5
5Keyword 8
Keyword 3
6Keyword 6
Keyword 5
7
Keyword 1
Keyword 4
Keyword 5
VLO identifierNumber of
similar keywords
7 3
4 2
2 1
6 1
Figure 33 - Algorithm to obtain the most similar VLOs
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6 Conclusions
In this document report it is presented the KB
developed to represent the ALTER-NATIVA’s
knowledge. It includes all the metadata needed to
characterize the various e-learning elements (e.g.
courses) and users. This document also describes this
KB related services, which make possible the
Knowledge edition and query, as also the generation of
recommendations for users and VLO.
In additional it is also shown the Wiki Thesaurus and its
functionalities to represent the lexicon of the ALTER-
NATIVA’s community. This wiki Thesaurus has as goal
the: 1) Classification of the e-learning elements; 2)
representation of concepts and reference descriptions;
and enables 3) the constant update of the lexicon
information by the community. This lexicon is reflected
in the ALTER-NATIVA’s KB due to a synchronization
service. Such process enables a harmonization of the
related community e-learning elements
characterization but also the knowledge handled by the
developed ALTER-NATIVA platform.
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6.1 Future Work features
As a future work, it is intended to provide some further
developments and respectively instructions to support
other Thesaurus area inclusion in the platform. This can
be done through the installation of a Wikimedia with
the same features of the wikis described in this
document. It is also necessary to create a new
ramification of the Thesaurus new area in the KB, and
then add to the synchronization service the necessary
access to the related owl file and wiki.
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7 References
[1] J. G. Ruiz, M. J. Mintzer, and R. M. Leipzig, “The impact of E-learning in medical education.,” Academic medicine : journal of the Association of American Medical Colleges, vol. 81, no. 3, pp. 207–212, 2006.
[2] “taxis @ www.thefreedictionary.com.” .
[3] J. Sarraipa, R. Jardim-Gonçalves, and A. Steiger-Garção, “MENTOR: an enabler for interoperable intelligent systems.,” Int. J. General Systems, vol. 39, no. 5, pp. 557–573, 2010.
[4] “Terminology @ en.wikipedia.org.” [Online]. Available: http://en.wikipedia.org/wiki/Terminology#Typology.
[5] R. Jardim-Goncalves, J. Sarraipa, C. Agostinho, and H. Panetto, “Knowledge framework for intelligent manufacturing systems,” J. Intell. Manuf., vol. 22, no. 5, pp. 725–735, 2011.
[6] “Taxonomy @ en.wikipedia.org.” [Online]. Available: http://en.wikipedia.org/wiki/Taxonomy.
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[7] D. Soergel, Thesauri and ontologies in digital libraries: tutorial. dsoergel.com, 2002.
[8] T. R. Gruber, “A translation approach to portable ontology specifications,” Knowl. Acquis., vol. 5, no. 2, pp. 199–220, 1993.
[9] D. Estival, C. Nowak, and A. Zschorn, “Towards ontology-based natural language processing,” in Proceeedings of the Workshop on NLP and XML (NLPXML-2004): RDF/RDFS and OWL in Language Technology, 2004, pp. 59–66.
[10] N. Guarino and P. Giaretta, “Ontologies and Knowledge Bases: Towards a Terminological Clarification,” Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, pp. 25–32, 1995.
[11] D. E. O’Leary, “Using AI in knowledge management: knowledge bases and ontologies,” Intelligent Systems and their Applications, IEEE, vol. 13, no. 3, pp. 34–39, 1998.
[12] J. Sarraipa, J. Silva, R. Jardim-Goncalves, and A. Monteiro, “MENTOR—A methodology for enterprise reference ontology development,” 4th International IEEE Conference on Intelligent Systems, pp. 6-32 – 6-40, 2008.
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[13] A. Maedche and S. Staab, “Ontology Learning for the Semantic Web,” IEEE Intelligent Systems, vol. 16, no. 2, pp. 72–79, 2001.
[14] J. Psarras, “‘ Envisioning , Supporting and Promoting Future Internet Enterprise Systems Research through Scientific Collaboration ’ EISB Models & Tools Report,” 2009.
[15] N. F. Noy, M. Sintek, S. Decker, M. Crubézy, R. W. Fergerson, and M. A. Musen, “Creating Semantic Web Contents with Protégé-2000,” 2000.
[16] T. Tudorache, C. Nyulas, N. F. Noy, and M. A. Musen, “WebProtégé : A Collaborative Ontology Editor and Knowledge Acquisition Tool for the Web,” vol. 165, pp. 1–11, 2011.
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8 Annexes
8.1 Excerpt of LOM metadata
represented in Alternativa KB Table 14 - LOM metadata
LOM MRSchema
Atributo name (elementNames.xsd)
1. General general
Identificador identifier
Catálogo catalog
Entrada entry
Título title
Idioma language
Descripción description
Palabra Clave keyword
Cobertura coverage
Estructura structure
Nivel de agregación aggregationLevel
2. Ciclo de vida lifeCycle
Versión version
Estado status
Contribución contribute
Tipo role
Entidad entity
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Fecha date
3. Meta-metadatos metaMetadata
Identificador identifier
Catálogo catalog
Entrada entry
Contribución contribute
Tipo role
Entidad entity
Fecha date
Esquema deMetadatos metadataSchema
Idioma language
4. Técnica technical
Formato format
Tamaño size
Localización location
Requisitos requirement
AgregadorOR orComposite
--Tipo type
--Nombre name
--Versión Mínima minimumVersion
--Versión Máxima maximumVersion
Pautas deInstalación installationRemarks
OtrosRequisitos de Plataforma otherPlatformRequirements
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Duración duration
5. Uso educativo educational
Tipo de interactividad interactivityType
Tipo deRecurso Educativo learningResourceType
Nivel de interactividad interactivityLevel
Densidad semántica semanticDensity
Destinatario intendedEndUserRole
Contexto [Nivel educativo] context
Rango Típicode Edad typicalAgeRange
Dificultad difficulty
Tiempo Típico de Aprendizaje typicalLearningTime
Descripción description
Idioma language
6. Derechos rights
Coste cost
Derechos deAutor y otras Restricciones copyrightAndOtherRestrictions
Descripción description
7. Relación [con otros recursos] relation
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Tipo [naturaleza de la relación con el recurso principal] kind
Recurso [recurso principal al que se refiere esta relación] resource
Identificador identifier
--Catálogo catalog
--Entrada entry
--Descripción description
8. Anotación annotation
Entidad entity
Fecha date
Descripción description
9. Clasificación classification
Propósito purpose
RutaTaxonómica taxonPath
Fuente source
Taxón taxon
--Identificador identifier
--Entrada entry
Descripción description
Palabras clave keyword
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8.2 Excerpt of DRD metadata
represented in ALTER-NATIVA KB Table 15 - DRD metadata
DRD type
Atributo
6.1.
Access For All Digital Resource Description
access mode statement
DRD
control flexibility
ISO_AFA_VOCAB
has control flexibility statement
ISO_AFA_VOCAB
control_flexibility_vocabulary = state ( full_keyboard_control, full_mouse_control )
display transformability
( font_size, font_face, foreground_colour, background_colour, cursor_presentation, highlight_presentation, layout, structure_presentation )
has display transformability statement
colour coding ecore:Eboolean
Hazard ISO_AFA_VOCAB
hazard_vocabulary = state ( flashing, sound, olfactory, motion_simulation )
has adaptation
ISO_AFA_VOCAB
has part ISO_AFA_VOC
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AB
is adaptation DRD
is display transformability statement of
ISO_AFA_VOCAB
is control flexibility statement of
ISO_AFA_VOCAB
is part of ISO_AFA_VOCAB
adaptation statement
DRD
support tool ISO_AFA_VOCAB
support_tool_vocabulary = state ( dictionary, calculator, note_taking, peer_interaction, abacus, thesaurus, spell_checker, homophone_checker, mind_mapping_software, outline_tool )
6.2. Access Mode Statement
original access mode
ISO_AFA_VOCAB
access_mode_vocabulary = state ( visual, textual, auditory, tactile, olfactory )
access mode usage
ISO_AFA_VOCAB
access_mode_usage_vocabulary = state ( informative, ornamental )
6.4. Adaptation Statement
adaptation type
ISO_AFA_VOCAB
adaptation_type_vocabulary = state ( audio_representation, visual_representation, text_representation, tactile_representation, caption, audio_description, Braille, digital_talking_book, electronic_book )
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original access mode
ISO_AFA_VOCAB
access_mode_vocabulary = state ( visual, textual, auditory, tactile, olfactory )
Extent ISO_AFA_VOCAB
extent_vocabulary = state ( part, all )
representation form
ISO_AFA_VOCAB
representation_form_vocabulary = state ( enhanced, verbatim, real-time, transcript, alternative text, long description, sign language, image-based, symbolic, recorded, synthesized, haptic )
language ISO_AFA_VOCAB
reading rate ecore:Eint
education level
ecore:Estring
6.3. Is Adaptation
is adaptation of
ISO_AFA_VOCAB
Extent ISO_AFA_VOCAB
extent_vocabulary = state ( part, all )
8.3 User model Table 16 - User Model General Profile
A. PERFIL GENERAL Possible values
Pertenece alguna comunidad
Area Matematicas, Ciencias, Lenguaje
Nivel de Estudios alcanzado
Primaria, Secundaria, Tecnica-Tecnológica, Universitaria, Pos-gradual
Nivel de conocimiento en accesibilidad Web Experto, Principiante
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Nivel de conocimiento en tecnologias asistivas Experto, Principiante
Aplicacion de TIC
Capacidad de diferenciar navegadores y de identificar ventajas para el trabajo didáctico
Alta, media, baja
Conocimiento de programas básicos para el trabajo académico:
Alta, media, baja
Conocimiento y capacidad de búsqueda y de comparación y de selección de opciones de procesadores de textos.
Alta, media, baja
Capacidad de acceder en la web a sitios para el trabajo académico
Alta, media, baja
Table 17 - User model access to information preferences
B. Preferencias para el acceso a la información
Dieciseis combinaciones de Felder con su puntuación
Entrada
Verbal [1,11]
Visual [1,11]
Procesamiento
Activo [1,11]
Reflexivo [1,11]
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Entendimiento
Global [1,11]
Secuencial [1,11]
Percepción
Intuitivo [1,11]
Sensitivo [1,11]
Table 18 - User Model ALTER-NATIVA Profile
C. Perfil ALTER-NATIVA Possible values
DESEMPEÑO
Escenarios de desempeño
Ministerios de Educación, Secretarías de educación, Institutos asesores en educación, Universidades, Colegios, Normales, Instituciones no gubernamentales, otro
Participaciones en el escenario de desempeño
Estudiantes en proceos de formación, Funcionarios gubernamentales o no gubernamentales, Formadores de profesores y Funcionarios Directivos, coordinadores o diseñadores de programas o currículos, Dirección, Administración, Coordinación, Planeación, Docencia, Investigación , formación.
Tipo de escenario Gubernamental, no gubernamental
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Nombre del escenario
Cargo que desempeña en el escenario
Ministro, Secretario de educación, Director de departamento, asesor, funcionario, Rector, Vicerector, Decano, Director de programa, coordinador de programa, profesor, estudiante
Tipo de dedicación en el escenario Tiempo completo, medio tiempo, tiempo parcial
ESPECIALIZACIÓN EN EDUCACIÓN
Perfil General
Campo o área de desarrollo profesional en educación
Administrativa, Educación, Tecnología, Educación en ciencias, Educación en lenguaje, Educación en Ciencias
Campo de especialización
Educación , Tecnología, Educación mat, Educación Leng. Educación Ciencias Educación y tecnología, Educación mat y tecnología, Educación Leng y tecnología, Educación Ciencias y tecnología
Nivel de especialización principiante, novato, experto
Manejo de Poblacion diversa Si
En el manejo de escenarios Manejo
Virtuales
Presenciales
Redes digitales
Manejo de recursos tecnologicos en el aula
Alta
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Computador
Pantallas digitales
Video Bin
equipo y software de acceso a la información para discapacidad visual
Experticia en la creación de unidades didácticas
Alta, media, baja
Experticia en la creación de secuencias didácticas Alta, media, baja
Experticia en Creación de Objetos de Aprendizaje Alta, media, baja
Trabajos previos en comunidades de práctica ambientes colaborativos … innovaciones grupales
Si, NO
Conocimiento o interés por conocer herramientas Tic como editores, procesos de diseño de blogs, diseño de páginas web, para el diseño didáctico.
Alta, media, baja
Conocimiento y uso de páginas y sitios web para el trabajo interactivo en educación: con textos, con testimonios, con fotografías y videos, con materiales multimedia.
Alta, media, baja
Ha participado en:
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Proyectos de innovación curricular en el área de (matemáticas, ciencias y leanguaje) Si, NO
Proyectos de innovación curricular en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO
Proyectos de investigación en el aula en el área de (matemáticas, ciencias y leanguaje)
Si, NO
Proyectos de investigación en el aula en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO
Proyectos de incorporación de tecnologías digitales en el área de (matemáticas, ciencias y leanguaje) Si, NO
Proyectos de incorporación de tecnologías digitales en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO
Proyectos relacionados con la inclusión educativa en el área de (matemáticas, ciencias y leanguaje) Si, NO
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Proyectos relacionados con la inclusión educativa en formación de profesores de (matemáticas, ciencias y leanguaje) Si, NO
Grado de conocimiento de:
Las teorías sobre la formación de profesores de (matemáticas, ciencias y lenguaje)
Alta, media, baja
Las bases teóricas de la didáctica de las (matemáticas, ciencias y leanguaje)
Alta, media, baja
Las teorías sobre la incorporación de la tecnología en las aulas de formación de profesores de (matemáticas, ciencias y leanguaje)
Alta, media, baja
Manejo práctico de las TIC Alta, media, baja
Uso educativo de las TIC Alta, media, baja
De las siguientes poblaciones, indique con cual (es) ha tenido experiencia en su trabajo docente:
Ciegos Si, NO
Sordos Si, NO
Población vulnerable económicamente Si, NO
Indígenas en educación multilingüe Si, NO
Indígenas en educación en lengua materna Si, NO
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Ha participado en:
Redes de colaboración docente Si, NO
Redes virtuales de colaboración docente Si, NO
Grupos de trabajo docente y de trabajo académico en general
Si, NO
Grupos de investigación en educación matemática, en el campo de la pedagogía y la didáctica del lenguaje y la comunicación o educación en ciencias)
Si, NO
Trabajo en equipo, en colaboración y producción conjunta de propuestas didácticas
Si, NO
Tiene experiencia en
Elaboración y presentación de ponencias en eventos especializados de (matemática, ciencias o del lenguaje y la comunicación)
Alta, media, baja
Produce artículos y materiales relacionados con la pedagogía y la didáctica de (matemática, ciencias o del lenguaje y la comunicación)
Alta, media, baja
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Elaboración de textos escolares para (matemática, ciencias o lenguaje)
Alta, media, baja
Elaboración de textos para la formación de profesores de (matemática, ciencias o lenguaje)
Alta, media, baja
Su experiencia docente es fundamentalmente con
Escolares de la educación primaria Alta, media, baja
Escolares de la educación secundaria Alta, media, baja
Estudiantes para profesor de (matemática, ciencias o lenguaje) Alta, media, baja
Perfil CAC
El docente de las facultades de ciencia:
Entiende la ciencia como una actividad cultural
SI - NO
Entiende el conocimiento como provisional
SI - NO
Reconoce la importancia de la experimentación
SI - NO
Interpreta modelos de fenómenos complejos
SI - NO
Aplica diversas habilidades del pensamiento
SI - NO
Usa aritmética y álgebra básica SI - NO
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Experticia de un docente en un con dispositivos didáctico Alta, media, baja
Tipos de dispositivos en ciencias diagramas de ciclos, redes de conceptos, diagramas jerárquizados
Experticia de un docente en: Alta, media, baja
Instrumentos para resolver diagramas Alta, media, baja
Reconocimiento de conceptos Alta, media, baja
Reconocimeinto de las relaciones causa-efecto Alta, media, baja
Argumentación Alta, media, baja
Aplicación de modelos Alta, media, baja
Reconstrucción de modelos Alta, media, baja
Aplicación a nuevas situaciones Alta, media, baja
El docente de ciencias reconoce el papel de la ciencia en la sociedad
Alto, medio, bajo
Reconoce las repercusiones de la ciencia en la vida humana
Alto, medio, bajo
Reconoce la importancia de los vínculos con el desarrollo tecnológico
Alto, medio, bajo
Reconoce la importancia de la alfabetización científica de la sociedad
Alto, medio, bajo
Perfil CALE
Epistemología del lenguaje y la comunicación Alto, medio, bajo
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Referentes Curriculares del Lenguaje y Comunicación Alto, medio, bajo
Teorías de la adquisición y el desarrollo de las lenguas en contextos diversos Alto, medio, bajo
Conocimiento de entornos semióticos y comunicativos Alto, medio, bajo
Diversidad, educación y lenguaje Alto, medio, bajo
Enfoques teóricos y políticos de la diversidad Alto, medio, bajo
Poblaciones diversas y acceso educativo en lenguaje. Alto, medio, bajo
Mediaciones para la experiencia del lenguaje Alto, medio, bajo
Dominio de fuentes bibliográficas del área del lenguaje Alto, medio, bajo
Observación de las diferencias en el desarrollo del lenguaje Alto, medio, bajo
Diversidades en el acceso a la lectura Alto, medio, bajo
Dispositivos didácticos y lenguaje Alto, medio, bajo
Fundamentos teóricos y metodológicos de dispositivos didácticos
Alto, medio, bajo
Dispositivos didácticos y desarrollo del lenguaje Alto, medio, bajo
Criterios para seleccionar dispositivos para el desarrollo del lenguaje
Alto, medio, bajo
TIC para el desarrollo de lenguaje Alto, medio, bajo
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Análisis curricular y didáctico para el desarrollo del lenguaje Alto, medio, bajo
Capacidad crítica en el uso de TIC y lenguaje Alto, medio, bajo
Tic y campos estructurantes del área de lenguaje Alto, medio, bajo
Aspectos técnicos, semióticos y culturales de las TIC Alto, medio, bajo
TIC, otras tecnologías y desarrollo del lenguaje en diversidad. Alto, medio, bajo
Perfil CAM
Experiencias curriculares para la formación matemática y didáctica
experiencia= 0-1 años, 2-5, 6 - 10, de 11 en adelantes
Experiencias en la formación de una didáctica de la didáctica de las matemáticas de educadores matemáticas
experiencia= 0-1 años, 2-5, 6 - 10, de 11 en adelantes
Experiencias en ambientes de aprendizaje interculturales y pluritecnológicos en la educación matemáticas.
experiencia= 0-1 años, 2-5, 6 - 10, de 11 en adelantes
Table 19 - User Model Accessibility Profile
D. PERFIL DE ACCESIBILIDAD A TECNOLOGIA DE INTERACCIÓN Y COMUNICACIÓN.
Possible values
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CONDICIÓN SENSORIAL(percepción, (**** operación y comprensión de la información) ****
ATENCIÓN
Rendimiento cognitivo Muy bajo
Bajo
Medio
Alto
Muy alto
Capacidad de Reconocimiento de emociones Si
No
Capacidad para Regular emociones Emociones positivas o neutro
Emociones negativas
Capacidad para manejar la conducta Si
No
Trastorno por deficit de Atención e Hiperactividad (TDAH)
Si TDAH + alteraciones emocionales
Si TDAH
No TDAH
AUDICIÓN
NIVEL DE AUDICIÓN Hipoacusia leve o ligera
Hipoacusia media o moderada
Hipoacusia severa
Hipoacusia profunda o sordera
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Cofosis o anacusia
Momento de perdida de la audición Prelocutivo
Poslocutivo
Manejo de ayudas Auditiva
Si ¿Cúal? • Ninguna • Prótesis auditivas • Sistema de amplificación • Implante coclear
No
Forma de Comunicación Oral
Escrita
Visogestual
Situación de comunicación Bilingüe
Monolingüe
Dominio de una lengua Lengua oral (auditivo vocal
Lengua de señas
Nivel de dominio de dicha lengua (esta pregunta dependerá de la anterior)
Excelente, Bueno, Aceptable, Insuficiente
Dominio de la Lengua Escrita Excelente, Bueno, Aceptable, Insuficiente
acompañamiento de un intérprete de lengua de señas para
• Ninguna situación • Interacciones cara a cara con personas oyentes • La lectura de textos escritos
Miembro de alguna asociación de Sordos • Si • No
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Formación academica Integracion /Inclución
Colegios especialezados para sordos
VISIÓN
Tipo de limitación visual
Parcial **** no reconocemos (INCI) este nivel de limitación, reconocemos Total y baja visión ****
Total
Baja vision
**** con qué fin se hace esta clasificación? **** Congénita
**** con qué fin se hace esta clasificación? **** Adquirida
**** con qué fin se hace esta clasificación? **** Súbita
**** con qué fin se hace esta clasificación? **** Gradual
Manejo de ayuda Visuales Si ¿Cuál?
No
Mediaciones en el aprendizaje Braille
Abaco
Lector de pantalla ¿Cuál?
Calculadoras parlantes
Sistemas de
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reconocimiento de textos en tinta
Uso de libros hablados
textos convertidos en audio con voz artificial (sintetizada)
Móviles adaptados con lector de pantalla
insuficiencia motora de origen cerebral
Tipo de limitación Hemiplejía
Paraplejía
Cuadriplejía
Hipotonía
Grado de la disfunción Espastica
Atetosica
Ataxica
Momento en que se presenta la limitación Congénita
Adquirida
Manejo de ayudas Auditiva Si ¿Cúal?
No
CONDICIÓN LINGÜÍSTICA
Primera Lengua (L1) Español
Quechua
Aymara
Miskito
Zapoteco
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Mixteco
Lengua de Señas Colombiana
Lengua de Señas Méxicana
Lengua de Señas Nicaraguence
Segunda Lengua (L2) Español
Castellano Escrito
Quechua
Aymara
Miskito
Zapoteco
Mixteco
Nivel de conocimiento del Español Marco Europeo de clasificación
Nivel de conocimiento de la Primera Lengua (L1) Marco Europeo de clasificación
Otras lenguas Marco Europeo de clasificación
CONDICIÓN SOCIO-ECONOMICA
Fuentes de Ingreso Formal e Informal
Situación económica Pobreza y Pobreza Extrema
Table 20 - User Model access preferences
E. PREFERENCIAS DE ACCESO
Possible values
Text Settings
font face Serif, Sans Serif, Monospaced, Cursive, Fantasy
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font size (1.5X) , (2X), (2.5X), (3X)
foreground color Blanco, Negro, Rojo, Amarillo, Azul, Verde, Gris, Gris claro, Gris Oscuro, Rosa, Cyan, Magenta
background color Blanco, Negro, Rojo, Amarillo, Azul, Verde, Gris, Gris claro, Gris Oscuro, Rosa, Cyan, Magenta
highlight color Blanco, Negro, Rojo, Amarillo, Azul, Verde, Gris, Gris claro, Gris Oscuro, Rosa, Cyan, Magenta
Alternativas al contenido
Alternatives to text
use alternative to text yes, no
preferred alternative Audio, Visual, Sign Language
append to replace original content
Append, Replace
preferred language English - English, Spanish - Español
Alternatives to audio
use alternative to audio yes, no
preferred alternative Text, Visual, Sign Language
append to replace original content
Append, Replace
preferred language English - English, Spanish - Español
Alternatives to visual
use alternative to visual yes, no
preferred alternative Text, Audio, Sign Language
append to replace original content
Append, Replace
preferred language English - English, Spanish - Español
Ayudas al estudiante
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Learner tools
Learner tools Dictionary, Thesauros, Encyclopedia, Atlas, Note, Taking, Calculator, Abacus
Navigations
Show page Table of Contents yes, no
Show Next/Previous Navigation Buttons
yes, no
Show Breadcrumb Link Navigation
yes, no
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8.4 Wiki Tree of Mathematics Thesaurus
[−] Matemáticas
[−] Cantidad [−] Conceptos numéricos
[×] Funciones [×] Relaciones [×] Sistema de numeración [×] Sistemas numéricos [×] Sucesiones y series numéricas [×] Variable numérica
[−] Habilidades numéricas [×] Cálculo numérico [×] Estimación numérica [×] Identificación de patrones numéricos [×] Manejo de información numérica [×] Modelación numérica/algebraica
[−] Instrumentos para el aprendizaje numérico [×] Artefactos artísticos y de uso social [×] Calendarios [×] Juegos para el pensamiento numérico [×] Software para el pensamiento numérico [×] Ábaco
[−] Procesos numéricos [×] Aproximar numéricamente [×] Clasificar [×] Contar [×] Formulación y solución de ecuaciones [×] Operar [×] Ordenar
[−] Forma [−] Concepto geométrico
[×] Elementos y objetos de las geometrías [×] Espacios geométricos [×] Geometrías
[−] Habilidades geométricas [×] Diseñar geométricamente [×] Localización espacial [×] Orientación espacial
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[×] Uso de instrumentos para hacer geometría y razonar geométricamente [×] Visualización geométrica
[−] Instrumentos para el aprendizaje geométrico [×] Herramientas de trazo y construcción [×] Juego de geometría [×] Rompecabezas [×] Software para la geometría
[−] Procesos geométricos [×] Construir y trazar geométricamente [×] Operar geométricamente [×] Representación geométrica [×] Transformar geométricamente
[−] Magnitud [−] Conceptos relativos a la magnitud
[×] Magnitudes [×] Sistemas de unidades de medida [×] Unidades de medida no convencionales [×] Unidades de medidas convencionales
[−] Habilidades para la medición [×] Aplicación de algoritmos y fórmulas métricas [×] Componer y descomponer en la medición [×] Deducir fórmulas [×] Estimación de medidas [×] Relacionar magnitudes [×] Uso de instrumentos
[−] Instrumentos para el aprendizaje de la medición [×] Instrumentos de medición [×] Objetos informales para medir [×] Recipientes [×] Retículas
[−] Proceso de la medición [×] Comparación de magnitudes [×] Conversión de unidades [×] Medir [×] Operar con unidades de sistemas de unidades de
medidas [−] Procesos matemáticos transversales
[−] Jugar [×] Instrumentos de los juegos [×] Las reglas de los juegos
[−] Modelar
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[×] Construcción de modelos [×] Identificación de patrones [×] Predicción [×] Sistemas cotidianos y fenómenos físicos
[−] Razonar [×] Argumentar [×] Conjeturar [×] Probar y demonstar [×] Razonamientos abductivos [×] Razonamientos deductivos [×] Razonamientos inductivos
[−] Representar [×] Conversión de representaciones [×] Instrumentos para las representaciones [×] Sistemas de representación [×] Tratamiento de representaciones
[−] Resolver problemas [×] Estrategias para representar problemas [×] Estrategias para resolver problemas [×] Problemas y tipos
[×] Tecnologías y solución de problemas
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8.5 Wiki Tree of Literature Thesaurus
[−] Lenguaje [−] Dimensiones de análisis del lenguaje [×] Dimensión afectiva [×] Dimensión cognitiva [×] Dimensión social [−] Experiencia discursiva [−] Escriturabilidad y lecturabilidad [−] Aprendizaje de la escritura [−] Escritura alfabética [×] Procesos cognitivos de la escritura [×] Procesos perceptuales del signo escrito [−] Procesos socioculturales de la escritura [×] Diversidad textual/Géneros de la escritura [−] Aprendizaje de otros sistemas de representación gráfica [−] Sistemas no verbales [−] Sistemas autónomos [×] Icónicos [×] Simbólicos [×] Sistemas de signos paralingüísticos [−] Experiencia Narrativa [−] Género Discursivo [−] Formas Textuales [×] Macroestructura narrativa [×] Microestructura [×] Superestructura narrativa [−] Géneros por esfera social [×] Género artístico [×] Género científico [−] Hecho estético [−] Expresión estética [−] Forma y contenido [−] Literatura [×] Metonimia Sinécdoque [×] Metáfora Símil [×] Música [×] Pintura [−] Pensamiento narrativo [−] Narratividad [−] Acción narrativa
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[×] Actores personajes [×] Organización espacio/temporal [×] Conciencia narrativa [−] Oralidad/Lenguas orales y de señas [−] Procesos de apropiación lingüística [−] Adquisición de la lengua oral y de señas [×] Escuchar [×] Funciones del lenguaje [×] Hablar/Señar [×] Procesos cognitivos de la oralidad [×] Procesos de percepción oral y visogestual [×] Procesos metacognitivos [−] Desarrollo de las lenguas [−] Pragmática de las lenguas [−] Prácticas discursivas y situación social [×] Contextos de uso [−] Semiótica de las lenguas [×] Bilinguismo en la población sorda [×] Bilingüismo en la población indígena [×] L1 L2 L3 ... [×] Monolingüismo [×] Plurilingüismo [×] Silabario [×] Sistemas Braille
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8.6 Wiki Tree of Teaching Thesaurus
[−] Didáticas
[−] Conceptos didáticos [×] Contrato didáctico [×] Didáctica general y específica [×] Disopsitivos didácticos [×] Dispositivos didácticos [×] Secuencias didácticas [×] Situaciones didácticas [×] Unidades didácticas
[−] Habilidades didáticas [×] Reconocimiento de trayectorias de aprendizaje en estudiantes [×] Reflexión didáctica [×] Uso de recursos de aprendizaje de los estudiantes [×] Valoración de procesos de estudiantes
[−] Intrumentos didáticos [×] Ambientes de aprendizaje [×] Objetos virtuales de aprendizaje [×] Tecnologías de la Información y la comunicació TIC [×] Tecnológias ancestrales
[−] Procesos didáticos [×] Aprender [×] Diseñar dispositivos didáctico [×] Enseñar [×] Evaluar dispositivos didácticos [×] Gestionar dispositivos didácticos
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8.7 Wiki Tree of Science Thesaurus
[−] Ciencias
[−] Ambiente [−] Interacciones
[×] Interacciones ambientales [−] Interacciones físico
[−] Fuerza [×] Fuerza de gravedad [×] Fuerza de roce [−] Fuerza normal
[×] Massa [×] Fuerza Tensión
[×] Movimento [×] Seres inanimados [×] Seres muertos [−] Seres vivos
[−] Funciones Vitales [×] Alimentación [×] Crecimiento [×] Nutrición [×] Reproducción [×] Respiración
[−] Sistemas Vitales [×] Sistema Circulatorio [×] Sistema Digestivo [×] Sistema reproductor
[−] Cambio químico [−] Reacciones químicas
[−] Cambio de color [−] Ecuación química
[−] Moléculas [−] Colisiones
[×] Cinética química [−] Átomos
[×] Enlaces químicos [×] Formación de precipitados
[−] Sustancias químicas [×] Intercambio de calor [×] Producción de gases [−] Propiedades químicas
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[−] Productos [−] Conservación de la energía
[×] Energia [−] Reactantes
[−] Conservación de la materia [−] Materia
[×] Estequiometría