24
Int. J. Computer Applications in Technology, Vol. 46, No. 1, 2013
Content management in a ubiquitous learning
environment
Débora Nice Ferrari Barbosa*
Feevale University,
BR-239, 2755, 93352-000, Novo Hamburgo, RS, Brazil
E-mail: deboranice@feevale.br
*Corresponding author
Jorge Luis Victória Barbosa
University of Vale do Rio dos Sinos,
Avenida Unisinos 950, 93022-000, São Leopoldo, RS, Brazil
E-mail: jbarbosa@unisinos.br
Patrícia Brandalise Scherer Bassani
Feevale University,
BR-239, 2755, 93352-000, Novo Hamburgo, RS, Brazil
E-mail: patriciab@feevale.br
João Rosa, Marcus Martins and Cássia Nino
University of Vale do Rio dos Sinos,
Avenida Unisinos 950, 93022-000, São Leopoldo, RS, Brazil
E-mail: jhr@unisinos.br
E-mail: mlewis@unisinos.br
E-mail: cnino@unisinos.br
Abstract: Currently, the mobility of users who carry mobile devices and access resources
through wireless networks brings up the need of providing uniform and immediate access to their
information. In this scenario, a new model of education called ubiquitous learning is being
explored. Therefore, the educational processes are related to the situation involving the learner
(i.e., they are context-aware), allowing the access to educational resources to be adapted
according to his/her profile and context. GlobalEdu is a computing environment that aims to
support ubiquitous learning, being aware of the context and mobility of the learners. This paper
presents the GlobalEdu content management model, as well as its model of interoperability
among repositories of learning objects that are used throughout the educational processes carried
in the system.
Keywords: ubiquitous computing; ubiquitous learning; learning objects; content learning model;
context-awareness learning.
Reference to this paper should be made as follows: Barbosa, D.N.F., Barbosa, J.L.V.,
Bassani, P.B.S., Rosa, J., Martins, M. and Nino, C. (2013) ‘Content management in a ubiquitous
learning environment’, Int. J. Computer Applications in Technology, Vol. 46, No. 1, pp.24–35.
Biographical notes: Débora Nice Ferrari Barbosa received her MS and PhD in Computer
Science from the Federal University of Rio Grande do Sul, Brazil, in 2001 and 2006,
respectively. She is a Professor at Feevale University, Novo Hamburgo, Brazil. Her research
interests include ubiquitous learning systems, distributed computing, multi-agent systems and
artificial intelligence. She is a member of the Brazilian Computer Society (SBC).
Jorge Luis Victória Barbosa received his MS and PhD in Computer Science from the Federal
University of Rio Grande do Sul (UFRGS), Brazil, in 1996 and 2002, respectively. Currently, he
is a Full Professor at the University of Vale do Rio dos Sinos (UNISINOS), São Leopoldo,
Brazil. Additionally, he is the Head of the Mobile Computing Laboratory (MobiLab/UNISINOS).
His research interests include mobile/ubiquitous computing, programming languages and
mobile/ubiquitous learning. He is also a member of the SBC.
Copyright © 2013 Inderscience Enterprises Ltd.
Content management in a ubiquitous learning environment
25
Patrícia Brandalise Scherer Bassani received her MS in Education from PUC-RS and PhD in
Computer Science Education from the Federal University of Rio Grande do Sul, Brazil, in 1999
and 2006, respectively. She is a Professor at Feevale University, Novo Hamburgo, Brazil. Her
research interests include education especially distance education technologies in education and
digital inclusion.
João Rosa received his BS in Computer Engineering at UNISINOS, São Leopoldo, Brazil.
Nowadays, he is a Masters student in Applied Computing at the same university and a
collaborator in research projects at Mobilab. His research interests include ubiquitous computing
and ubiquitous learning systems.
Marcus Martins received his MS in Computer Science at UNISINOS, São Leopoldo, Brazil.
Nowadays, he is a collaborator in research projects at Mobilab. His research interests include
ubiquitous computing and ubiquitous learning systems.
Cássia Nino received his MS in Computer Science at UNISINOS, São Leopoldo, Brazil.
Nowadays, he is a collaborator in research projects at Mobilab. His research interests include
ubiquitous computing and ubiquitous learning systems.
1
Introduction
The user who carries mobile devices has the possibility of
using the facilities of wireless technology, such as access
resources anywhere. However, to provide this scenario it is
necessary to offer uniform and immediate access to this
information. The ubiquitous computing (Abowd and
Mynatt, 2000; Satyanarayanan, 2001; Weiser, 1991) is a
computational model that aims to pro-actively serve the
needs of users, acting in an invisible way (background). The
goal is to provide a continuous integration between
technology and the environment, helping the user in his
daily tasks. In this model, the applications are available
regardless of place and time. The access to the network and
the computing environment is continuous, independent of
the device and the physical location of the user. From this
scenario, a new model of education called ubiquitous
learning (Barbosa et al., 2008; Ogata and Yano, 2009; Ogata
et al., 2010; Rogers et al., 2005; Yin et al., 2004, 2010) is
being explored. In this model, the mobility of learners and
the perception of the elements that are near them (context)
are part of the learning process and this process can occur
in a continuous, comprehensive and transparent way.
Therefore, these environments support learning processes
related to the situation involving the learner [context-aware
(Dey, 2001)], allowing learning resources to be accessed
according to the profile and the context in which learner is.
We have been investigating how mobile devices and
location technology could be used to improve learning. The
GlobalEdu project (Barbosa et al., 2005) considers four
elements and their interdependencies:
1
learners’ profiles and needs
2
the context surrounding the learners
3
the adopted educational paradigm
4
the possibilities and limitations of ubiquitous
technology.
The educational paradigm considered is interactionistconstructivist, which is strongly influenced by the work of
Piaget (1995). According to this reference, the subject in
action constructs a new knowledge during the interaction
with an object of knowledge. Learning is an internal process
involving the creation of a network of relations by
which the subject creates meaning about new information,
transforming it into knowledge. Therefore, a ubiquitous
learning application must support the integration among
learners and their context, allowing the access to
contextualised information and learning objects.
GlobalEdu uses two pedagogical strategies:
1
context-aware content distribution using learning
objects
2
stimulus to the interaction among learners.
So, GlobalEdu is a ubiquitous learning architecture that is
aware of the context and the mobility of the learner. In this
model of education, context awareness has a key role, since
it allows exposing to the learners aspects of their interest
that relate to where they are in the moment. The mobility
allows the system to act pro-actively in the various places
where the learners are. Because of this, one characteristic of
our architecture is to explore content (learning objects)
related to the context of the learner and his profile.
GlobalEdu adopts a distributed organisation, considering the
access to a global network. This network needs to support
wireless access, interconnected to a wired network that
provides the structure of services and equipment on a global
scale. This structure can interconnect GlobalEdu servers
scattered in different contexts. The model requires a
ubiquitous middleware. For this reason, the system is being
integrated to an environment that supports a ubiquitous
computing called ISAM (Augustin et al., 2004).
GlobalEdu has been tested at Unilasalle University in
order to support ubiquitous learning. We have created a
large-scale ubiquitous learning scenario based on GlobalEdu
and we used it to evaluate the systems functionality. In this
evaluation we involved learners of the university.
This paper is organised in seven sections. Section 2
discusses issues related to ubiquitous learning and learning
26
D.N.F. Barbosa et al.
objects. Section 3 presents previous work in the area of
ubiquitous technology used to create pedagogical
applications, and how it relates to our research. Section 4
details the GlobalEdu proposal. Section 5 presents the
content management educational module, which is the focus
of this paper. Section 6 describes the scenario in which the
module of content management was evaluated. Finally,
Section 7 describes a conclusion and indicates possible
future works.
2
Ubiquitous technology, ubiquitous learning and
learning objects
Location (Hightower and Borriello, 2001; Hightower et al.,
2006) is an important topic related to mobile computing
(Diaz et al., 2009; Satyanarayanan et al., 2009) and
ubiquitous computing (Abowd and Mynatt, 2000;
Satyanarayanan, 2001; Weiser, 1991). This research front
proposes the determination of the physical location of
mobile devices (for example, a room in a building, or a
specific address in a street).
Location technology is as useful as it can be continuous,
anytime, anywhere (Hightower et al., 2006). There are many
different ways to get location data in mobile computing
(Hightower and Borriello, 2001). Nowadays, new
alternatives to the use of satellites are appearing, like
integration between GPS and mobile telephony (FCC, 2011)
and positioning based on wireless antennas (Hightower
et al., 2006). Moreover, the proliferation of wireless
hotspots suggests that in the future this precision will grow,
providing sophisticated location-based services (Dey et al.,
2010). Location technologies can be used to explore nearby
opportunities [context-aware computing (Dey, 2001)].
Based on these studies, one can consider a medium term
scenario where society will be permeated with mobile
devices always connected to a communication network and
with available precise location data. This proliferation of
ubiquitous technology will significantly impact society in
several areas. Between these areas, one of the most
prominent ones is education [ubiquitous learning (Barbosa
et al., 2005, 2008; Ogata and Yano, 2009; Ogata et al.,
2010; Rogers et al., 2005; Yin et al., 2004, 2010)]. In this
scenario, new educational models should arise since
pedagogical resources would be accessible anytime,
anywhere.
Barbosa et al. (2005) define ubiquitous learning as a
process that can occur anytime and anywhere and that is
adjustable, continuous and integrated with the learners’
daily activities. The essence of ubiquitous learning is to
realise which information is presented throughout the
learners’ daily tasks, in different forms and places, and to
link this data with the learners’ educational process.
Technologies that support ubiquitous learning should
provide these aspects through mechanisms that allow
knowing learners, contexts involving them, and how
learners relate to contexts.
Ubiquitous support provides the construction of learning
programmes related to dynamic information based on
learners’ physical context, allowing for links between
contexts and pedagogical goals. In this scenario, education
is dynamic and educational resources are distributed in
contexts.
We investigated which subset of functionalities is
needed to achieve the benefits of large-scale ubiquity. As
conclusion, we assumed that it is possible to develop
ubiquitous learning applications using ubiquitous computing
support. Therefore, it is also possible to implement
distributed, mobile, context-aware, adapted and follow-me
applications (Augustin et al., 2004). We considered that the
use of context-awareness (Dey, 2001) with ubiquitous
computing support enables the exploration of large-scale
ubiquitous learning.
The new class of context-aware systems opens prospects
for development of applications that explore the dynamic
nature and the mobility of users. The contextual information
comes from many sources, such as location sensors,
temperature sensors, users’ profiles and network monitors.
In addition, while supporting learning, context-awareness
allows relating explicit information of the learners (for
example, preferences and goals) with implicit information
of their physical location (for example, temperature and
people in the same location). For us, the daily context of the
user can be connected with the local context, joining current
information with educational objectives. In our work, local
context is the information about persons, relations, places
and resources in the specific location. Software agents can
understand this information.
Using ubiquitous learning support, applications can
proactively notify learners about events or resources of their
interests available in the context. In this scenario, it is
possible to look for learning objects according to the
learners’ contexts and profiles. Learning objects (LOM,
2011) are defined as any digital or non-digital resources that
can be used to support learning processes. These objects are
building blocks for constructing the context of learning. An
important aspect is the use of standards to catalogue the
objects, such as IEEE/LOM (2011). These standards aim at
facilitating exploration of issues related to accessibility,
interoperability, durability and flexibility. These aspects are
important in ubiquitous computing environments because
learners can access resources anywhere and with any
device.
3
Related works
Some projects are investigating the use of ubiquitous
computing to provide new learning perspectives.
Nonetheless, there are few proposals using learning objects
to represent pedagogical content. The integration between
contextualised user profiles and context technologies is the
key to ubiquitous learning environments. For instance, this
type of integration allows features like the distribution of
contextualised learning objects in a specific location and the
match of students with common interests within a learning
context. Therefore, we introduced into GlobalEdu the match
Content management in a ubiquitous learning environment
between context technology and user profiles. This match is
a central feature of GlobalEdu.
The technologies used to create ubiquitous learning
environments can be used to support specific applications.
For instance, JAPELAS (Yin et al., 2004) is a system
created with the goal of supporting learning of polite
expressions in Japanese. The students, using handheld PCs,
are assisted in the identification of the correct polite
expressions to be used in a particular context. JAPELAS
only allows the contact between two users. A new version
called JAPELAS2 (Yin et al., 2010) is oriented towards
supporting the interaction between many people, with a
collaborative/social approach. Both systems use location
technology and user profiles, but they represent a
specific application. In order to support several university
courses, a generic infrastructure should be available. This
infrastructure should provide applications that use location
technology aiming at supporting particular tasks. GlobalEdu
uses local information and learner profiles in a generic
approach, in order to explore pedagogical opportunities in a
context-aware environment. With GlobalEdu’s content
Management it’s possible to learn about any kind of content.
The ambient wood project (Rogers et al., 2005) is
dedicated to the design and building of pervasive
environments. WiFi and sensor-based technologies are
connected with a variety of mobile and standalone
computing devices. The proposal is that digital augmentation
offers a promising way for enhancing both indoor and
outdoor learning processes. GlobalEdu uses the social and
physical information to improve the learning process. With
ISAM integration GlobalEdu intends to explore both indoor
and outdoor applications.
Other approaches explore radio frequency identification
(RFID) technology to integrate the real world in the
pedagogical experience. TANGO (Ogata et al., 2010) allows
placement of RFID tags on real objects. The tags can be
detected when a learner visits an environment. A mobile
device can be used to interact with objects, in order to
improve the learner’s vocabulary through the questions and
answers previously registered in each object. Moreover,
Mobio threat (Segatto et al., 2008) is a pervasive game that
represents another pedagogical approach based on RFID
technology. In Mobio threat, RFID tags are implanted in
game objects, such as trees and rooms, to allow learners to
interact with these real objects using their mobile devices.
Its main goal is to support learning about epidemics and
disease control. During the game, the players have to work
with pathological agents and chemical reactions. The
pedagogical contributions are centred in the areas of
chemistry and biology.
TANGO and Mobio threat use the same strategy to
improve the pedagogical experience, i.e., they integrated the
real world in the educational process using RFID
technology. Differently from GlobalEdu, both proposals
focus on specific pedagogical areas. GlobalEdu is a generic
ubiquitous learning model. Moreover, the integration
between GlobalEdu and ISAM is general enough to support
27
the interaction with real objects using RFIDs or any other
kind of technology.
Few projects in the area of ubiquitous learning use
learning objects to represent pedagogical content. JAPELAS
(Yin et al., 2004, 2010) was designed for a specific purpose,
and does not use learning objects. The ambient wood project
(Rogers et al., 2005) does not support learning objects. Its
focus is specifically on pervasive environments based on
digital augmentation. Yang (2006) proposes a peer-to-peer
access to content in a ubiquitous learning environment. The
proposal also does not specify how the content is going to
be represented. Unlike these works, GlobalEdu employs the
notion of learning objects and uses the content management
module to support a generic management of LOs.
Schmidt (2005) summarises the characteristics of
context-aware learning systems and presents a case study
that uses learning objects based on the SCORM (2011)
standard. GlobalEdu uses the LOM standard (LOM, 2011).
SeLeNe (Rigaux and Spyratos, 2010) and Elena (Simon
et al., 2002) also use the LOM standard, however, they do
not consider the adaptation of content according to the
learners’ current context, as GlobalEdu does. LOCAL
(Barbosa et al., 2007) uses the LOM standard and support
location-and-context-aware computing environments in a
small-scale ubiquitous learning model but GlobalEdu
aims to a large-scale management of content based on
interoperability among distributed repositories of learning
objects.
Previous publications of GlobalEdu describe the first
GlobalEdu architectural (Barbosa et al., 2005; Nino et al.,
2007). Considering the related works and the previous
publications we can emphasise, as main contribution of this
paper, the proposal of large-scale management of learning
content. This proposal is mainly based on interoperability
among distributed repositories of learning objects.
4
GlobalEdu
The GlobalEdu (Barbosa et al., 2005) uses profile, context
and profile learners data to find learning opportunities. It
can act in two ways:
1
sending learning objects (the focus of this paper)
2
stimulating interaction between learners.
It uses the learner profiles and content data to create bonds
between learners. There are two types of interaction:
1
Similar interests: the GlobalEdu finds learners with
similar interests in the same context and stimulates their
interaction. This approach can be used, for example, in
the creation of workgroups in a classroom or to study
about the same content (context-aware content
distribution using learning objects).
2
Complementary interests: the GlobalEdu finds learners
with complementary interests. For instance, a learner
who wishes to learn more about a particular subject is
28
D.N.F. Barbosa et al.
matched with a user who wishes to teach or who is an
expert on the subject.
GlobalEdu investigated how to expand the ISAM
architecture to learning domain. ISAM (Augustin et al.,
2004) considers that ‘the computer’ is the whole network.
The computing environment (data, device, code, service,
and resource) is spread in composed cells. Users can move
around, having both their applications and the virtual
environment following them.
The GlobalEdu architecture proposes a layered
organisation as Figure 1 shows.
Figure 1
GlobalEdu architecture
•
Information about context related to the learner’s
location and learning goals.
Figure 2 shows pedagogical agent’s architecture organisation.
The agent presents two basic types of activities: a cognitive
structure based on beliefs and a reactive structure based on
events. The beliefs, considered the knowledge of the
learner’s current state, are handled by the education
modules in the composition of the production rules being
this the formalism used by the pedagogical agent for
reasoning. Events constitute the stimuli necessary for the
reaction to the specific transformations that occur during
processing, characterised by the messages exchanged
internally by the agent.
Figure 2
Pedagogical agent’s architecture (see online version
for colours)
4.2 The system layer
4.1 The application layer
The application layer is represented by a pedagogical agent,
which follows the learners throughout the environment and
assists in their interactions with the system. The pedagogical
agent module runs on the mobile devices of the learners
assisting the educational process in the ubiquitous
environment. Pedagogical agent contains an interface to the
system layer and provides a ubiquitous vision through the
ISAM environment. The pedagogical agent characteristics
are the following:
•
•
•
The agent state migrates to the learner devices through
the ISAM services. This is an ISAM middleware
feature that allows an application running in a
disconnected mode. Because of this, the pedagogical
agent also controls disconnection operating normally,
despite some access restrictions to the GlobalEdu
system layer. So, ISAM guarantees that the pedagogical
agent follows learners providing some educational
process even when the learner is disconnected from the
GlobalEdu environment.
Communication between learner and educational
modules obtaining information of the environment.
Accessing control of the learning objects. It helps the
learner with the search and presents the learning object
according to context information and learner’s model.
Educational modules and support modules compose the
system layer. They provide support for execution of the
pedagogical agent in the ubiquitous environment.
Furthermore, they enable the identification and the
adaptation of resources according to the learners’ profiles
and contexts. The educational modules and the support
modules are heavyweight execution units, thus they are
executed on the network servers. Otherwise, the
pedagogical agent component is a lightweight execution
unit, thus it can be executed on the learners’ mobile devices.
Both pedagogical agent and system layer use ISAM
middleware services for communication (Figure 3). So, the
GlobalEdu components use ISAM feature for all services
that need ubiquitous support.
Figure 3
GlobalEdu and ISAM communication (see online
version for colours)
Content management in a ubiquitous learning environment
4.2.1 Educational modules
The educational modules are responsible for performing
functions related to the contexts and the content
management. They also are responsible for manipulating the
learners’ model. GlobalEdu has the following educational
modules: profile management, content management and
context management.
4.2.1.1
Profile management educational module
When learners move around contexts their learning models
can change. The profile management educational module
generates the learners’ model, which is represented by a
metadata. This stores information about each learner, and
provides this information to the other subsystems. The
profiles can be used to customise the user’s learning.
In the scope of ubiquitous learning, profiles allow the
exploration of resources based on the characteristics of the
learners and the contexts in which they interact. The profile
learner metadata uses some categories of the PAPI (2011)
and LIP (2011) standard and the learning styles (Felder and
Silverman, 1998). The metadata also supports trails (Levis
et al., 2008). It is due to:
1
Flexibility: the standards was designed in order to be
freely extended since its components are optional an
can be redefined if needed.
2
Modularity: each profile field and/or section can be
handled separately, allowing for part of the profile to be
stored in the personal assistant, while another part is
tied to each context visited by the user.
The PAPI categories used are the following:
1
Personal information – stores basic user data, such as
name, address, phone number and e-mail.
2
preferences – helps the model to customise the user
experience, storing configuration data related to the
preferred media type (audio, video and/or text). If the
learner has some type of physical disability GlobalEdu
can provide content in different formats.
3
Relations – stores data that specifies relations with
other users in the same context (for example, ‘student’,
‘teacher’ or ‘researcher’).
4
Security – stores credentials (names and passwords) to
allow different access levels in specific contexts.
The LIP categories used are the following:
1
Goal – follows the knowledge areas defined in the
ACM Computing Classification System (ACM, 2011),
having a general knowledge area (for example, ‘Math’)
and a specific interest topic (for example, ‘group
theory’). The specific areas are then classified
according to the learner’s goals (for example, ‘to learn’
or ‘to teach’).
2
29
Competency – refers to proposed goals and evaluations
conducted in a context.
The learning styles are based on the proposal of Felder and
Silverman (1998). A trail contains the history of the
learners’ actions in the ubiquitous environment storing
information related to locations, devices, applications, and
contexts accessed. Therefore, it is possible to know any
change in the learners’ models. The learners’ metadata also
has information of relations that is generated as a learner
meets other learners in the ubiquitous environment. This
presupposes the existence of other learners with the same
goals, competencies and preferences.
4.2.1.2
Context management educational module
The context management educational module manages the
learners’ contexts monitoring any change in the contexts
where the learners are. The learners’ contexts are composed
of social context and physical context. So, this service
perceives changes of context elements in the different
locations where the learner is. His/her social context and
physical context compose the learner context.
The social context has the information about location
context and presence of other pedagogical agents in the
currently context. Location context is the information about
people (name, e-mail, commitments, and role), events (type,
description, and location) and resources (name, type,
description, and commitments) related to a specific location.
The presence of other personal agents presupposes the
existence of other learners with the same goals,
competencies and preferences, so the learner may access
those learners for contact or not. This information can also
be used for the creation of learner groups in the same
context.
The physical context represents the resources accessed
by the learner, such as network, locations and devices. We
consider that the ubiquitous computational environment
monitors physical context elements. Besides, any element
state changes are informed to the context management
educational module.
Management context in GlobalEdu is the capacity to
know how to locate the learner in an environment (cell) that
he/she is currently, to identify a learner in the corresponding
context and to provide interest information adapted to the
device. In the same way, each location is modelled as a
geographic region and has information about location
context. This information is stored in a repository (location
context repositories) in each geographic region (see
Figure 4), represented as XML metadata. So, for GlobalEdu,
cells compose the ubiquitous environment and these have
different contexts. For example, a university can be
considered a cell and their buildings, different contexts.
The access to the environment by the learner is done
with an authentication, and the context management
educational module notices this event. With a new learner’s
entrance in the environment the social context changed. In
this case, the service takes two actions:
30
D.N.F. Barbosa et al.
1
notifies other learners in the corresponding context
(location context)
2
sends to the new learner adapted information about that
context that the learner is currently.
A comparison is accomplished with the learner’s profile in
order to define learners with the same goals, competencies
and preferences whose information the learner may access
for contact or not.
For the adaptation process, there is a relationship
between context management educational module and the
others elements of the GlobalEdu architecture. With this, the
learner can ask explicitly information about the social
context that he/she is in or still to extend the research for
other contexts. For example, the search for learning objects
becomes more productive if done in several different
contexts.
The content management educational module is
responsible for managing the learning objects according to
the learners’ models. Section 5 describes, in details, this
component.
4.2.2 Support modules
The support modules assist the execution of the educational
modules and the pedagogical agent and manage aspects of
communication, adaptation of interfaces to devices, users’
access, and persistence. The support modules act as
interfaces between the educational modules and the ISAM
environment (Augustin et al., 2004). The support modules
use the migration and the physical mobility support of the
ISAM environment to manage the mobility of the
pedagogical agents among devices. In addition, the support
modules manage the messages interchange among the
educational modules, the pedagogical agents and the ISAM
environment.
The ubiquitous environment is composed of cells, each cell
with different contexts (see Figure 4). For example, a
University can be considered a cell and its buildings
different contexts.
The runtime layer is represented by a middleware that
supports the execution of educational applications,
providing the necessary elements for the system. These
elements are: perception of elements of the contexts,
migration of code and mechanisms for communication.
5
In GlobalEdu the content management educational module
(content management, for short) is responsible for the
learning objects management, identifying and providing
these objects according to the learners’ profiles and the
limitations of their physical context (for example, devices
and networks bandwidth).
The objects are categorised by the IEEE/LOM (2011).
They are managed according to a network of distributed
repositories of learning objects. These repositories are
integrated through a middleware to provide a unified view
of the objects. Therefore, learners have access, anywhere, to
all objects that are within the GlobalEdu network in a
transparent and personalised way. The interaction of the
learners with the content management EM is made through
the pedagogical agent.
5.1 The content management educational module
Among the tasks of the content management, this work
specifically focuses on the following:
•
4.3 The runtime layer
The runtime layer monitors elements of the physical
context. Each location is modelled as a geographic region
and has information of context. The context data is stored in
a repository and is represented by a metadata in the XML
format.
Figure 4
Content management in GlobalEdu
•
A ubiquitous environment of GlobalEdu (see online
version for colours)
•
Metadata management – all content in GlobalEdu is
stored in repositories called content repositories. The
content is represented in XML, according to the LOM
standard. The metadata management controls the
insertion, deletion and modification of the learning
objects. Each location in GlobalEdu can provide its
own content repository.
Content selection – the selection of a specific content to
present to a learner considers three requirements. The
first is the content related to the pedagogical strategy,
which must be in accordance with the learners’
preferred style of learning, as specified in their profile.
The second analyses whether the target content is
related to any of the learners’ goals. The third considers
the learners’ physical context, so that they receive
content adapted to the device and the network
bandwidth.
Content discovery – the learners, using the pedagogical
agent, can request information of the learning objects
available in the environment. This query can be made
according to learners’ profiles (mediated by the system)
or via keywords (free search). Figure 5 shows the use
case diagram of the basic functions of the content
management.
Content management in a ubiquitous learning environment
Figure 5
The content management functions
31
3
Exchanges list of repositories and enables the
repositories to update their local views of the
network, requesting the list of the remote
repositories. The list contains the identifier, the
address of access and the current state of the
repositories. Periodically, each repository updates
its list, consulting other repositories. The frequency
of the list exchange is a configuration parameter of
the system.
5.2 The content management educational module
architecture
The architecture of the content management educational
module is service-oriented. Figure 6 shows the components
of each content management educational module server in
the GlobalEdu network (see Figure 4).
The actors involved are the following:
•
•
•
•
Figure 6
The content management architecture
administrator – represents the user who can add, edit
and delete learning objects
context manager – characterises the context
management EM
pedagogical agent – represents the pedagogical agent
content repository – illustrates the content repositories.
Each repository is aware of all registered repositories in the
GlobalEdu network. The repositories are responsible for
forwarding queries made by learners, thus enabling the
learners to have a single vision of all objects. The operations
are the following:
•
•
•
Manages learning objects – represents the operations of
content management in each repository. The supported
operations are the following: add, delete and update
learning objects.
Searches for learning objects – represents the searches
for learning objects in the GlobalEdu repositories. In
the filtering process of the searches, objects whose
format matches the physical context (device and
network) receive higher priority. The available searches
are the following:
1 Queries guided by profiles, which consider the
description of the learning objects matched with
the learners’ style of learning and goals.
2 Queries guided by keywords, which enable
learners to search for objects based on keywords,
allowing them to look for the objects that are not
strictly related with their declared goals.
Manages the repository registry – contains three basic
operations:
1 Registers repository advertises the existence of a
new content repository in the GlobalEdu network.
2 Shutdowns repository advertises that a repository is
leaving the network for maintenance or repairs.
The architecture of the content management is based on a
network of interconnected servers. The components of the
architecture are the following:
•
•
•
•
Content manager server – represents each repository
server in the GlobalEdu network. Each server is
independent of the others and they can run even
disconnected from the GlobalEdu network. While it is
offline, the queries of objects are processed in the local
repository.
Content manager repository – represents the
persistence of the learning objects. Different
implementations can be provided, whereas the
implementation to be used is defined in the repository
configuration file. The default implementation of the
content management repository is based on the JCR
API (Java Content Repository), which is provided by
the Apache Jackrabbit Project (2011).
Descriptors list – maintains interconnected the
repositories in the network keeping a list of the
repositories known by each server.
Listeners – enables operations to be connected to the
server life-cycle.
32
•
•
D.N.F. Barbosa et al.
Service executor – maintains compatibility among
different devices. The service executor packs and
transports parameters between the client node and the
node hosting the service implementation, as well as any
result in the opposite direction. Currently, it is possible
to invoke remote services either through sockets or web
services.
objects and can be changed at any time either by the learner
or automatically by GlobalEdu.
Figure 7
U-inContext interface, (a) PDA Zaurus SL-5600
interface (b) desktop interface (see online version
for colours)
Services – represents the services provided by the
content management. These services are divided into
two groups:
1 the former is responsible for providing the
integration and interoperability among repositories
in the network
2 the component is responsible for the
implementation of these services is the list of the
repositories.
The latter group is responsible for exporting functions
related to the handling of the learning objects. These
services can include, remove, update and find an object
in the repository.
6
Evaluation scenario
The prototype of the content management educational
module was integrated with the remaining modules of the
GlobalEdu architecture. Currently, the system has the
pedagogical agent and the context management educational
module prototype. The pedagogical agent was implemented
with the U-inContext application (Nino et al., 2007).
Basically, this is a simplified version of the pedagogical
agent that relates social context with learner using his/her
position and the learner profile. The platform used by
implementation is Java in the J2SE and J2ME versions. To
provide content information to the learner the content
management educational module communicates with
U-inContext and ISAM environment. All these elements are
executing in the same GlobalEdu server (see Figure 4).
Aspects related to the learner’s profile use the PeLeP system
(Levis et al., 2008).
The U-inContext application performs a subset of the
functionalities originally conceived by the GlobalEdu
model. The U-inContext has a graphical user interface
which is adapted to the device in use (for instance, PDA,
smarthphone or desktop). Figure 7 shows the U-inContext
Interface (as can be seen in figures, the interfaces are in
Portuguese) for PDA Zaurus SL-5600 [Figure 7(a)] and
desktop [Figure 7(b)]. This figure shows that when the
learner starts the pedagogical agent is possible to select his
visual mode. When learners access the environment they
can choose to be invisible to other learners, available to
other learners or unavailable. In the last case, the learner
does not receive context information of the GlobalEdu.
In the U-inContext application the learners can insert
profile information about their interests and competences.
This information is used for the distribution of the learning
(a)
(b)
After starting the U-InContext the learner receives the social
context information (people, events and resources). For
GlobalEdu a learning object is a resource. Thus, learning
objects available to the learner’s context are reported in
resource interface item (‘Recursos’ in Portuguese). Figure 8
presents a learner’s context information. In addition, the
learners can search for specific objects. The list of learning
objects is presented on the ‘My Information’ (‘Minhas
Informações’ in Portuguese) menu and they are filtered
according to the learners’ current context. Using this
interface learners also can access a list of the learning
objects available in the GlobalEdu network [button ‘Busca’
in the Figure 8(b)]. To access a learning object, the learners
Content management in a ubiquitous learning environment
can select a resource item [‘Recursos’ in Portuguese in the
Figure 8(a) or Figure 8(b)].
Figure 8
Learner’s context information, (a) PDA interface
(b) desktop interface (see online version for colours)
(a)
33
to the services available in the GlobalEdu network. When
the learners entered the university the system detected them
and considering their profiles, sent learning objects
information to their devices. The learners moved around the
contexts of the university. Each visited context had different
content information available.
The implementing platform consisted of mobile nodes
comprising notebooks and PDAs Sharp Zaurus SL-5600.
The test was conducted with a sample consisting of six
professionals of the computing field and other areas. We
presented the purpose of the work and the basic operation of
the prototype. Subsequently, the individuals, using the
pedagogical agent, registered their data and were invited to
use the prototype for one day. At the end of the experiment,
the learners were asked to answer an evaluation survey.
The test was conducted in a specific building at
Unilasalle University (geographic region). In this building,
we have mapped two contexts: the hall and the computer
science lab (location context).
The learning objects information (metadata) was
inserted into GlobalEdu server. We used simple classroom
learning objects, such as presentations (in PPT format) and
documents (in PDF format). Evaluating the GlobalEdu
context-aware feature was important for us. So, we did not
contemplate the search by keyword in evaluation. We only
contemplated the search according to context-aware and
learner’s profile.
Even knowing that the number of individuals involved
in the experiment was small (six individuals), analysing the
results we can note that GlobalEdu is a good tool for
interacting with learning objects in a context-aware
environment. Figure 9 summarises the individuals’
perceptions regarding the system adequacy for learning any
kind of content and the system uses as an assisting tool in
classrooms. The results indicate a good acceptance of the
individuals about the evaluated items. The persons
classified, in general, the system as good or excellent for
aiding in the learning process.
Figure 9
Aspects of analysis in the evaluation (see online
version for colours)
(b)
We present a scenario that involves some aspects of
GlobalEdu system. The objective is to evaluate the selection
of learning objects according to learners’ profiles or to
explicit keywords. In this case, we decide that the
experiment aims at evaluating the context-aware filtering of
learning objects, accessing the learning object information
hosted in remote repositories and using GlobalEdu as an
tool in the classroom.
The case study was conducted at the Unilasalle
University. This university was considered as a cell, which
is composed of different contexts. The devices of the
learners received an instance of the U-inContext application.
The learners, carrying different types of devices, had access
The users noted that the system would be helpful to the
daily use. An interesting comment made by a user,
regarding the capacity of the system in assisting the learning
process, was the following: “I think that in the future this
system will replace the distance-learning systems used in
institutions”. The perception of this individual is that the
system could be used to access all information currently
available in the distance-learning system of the university.
34
7
D.N.F. Barbosa et al.
Conclusions
Studying the elements that involve the learner in a virtual
world is a task approached in virtual environments research,
particularly in distance education. Considering a ubiquitous
learning, this perception transcends the virtual and reaches
the real world of the learner. Thus, one of the main
problems in this research is the perception of the context in
which the learner is. This influences the learner’s profile
and the educational content that he handles.
So, in the field of education, ubiquitous computing has
been proving itself as a useful tool, facilitating the
interaction between learners and computer systems’
infrastructures and resources. This is done through the
mapping of the learners’ location and profiles in a
large-scale environment. In this paper, we discussed how
ubiquitous computing technologies could be useful in this
new scenario. The following general conclusions can be
underlined:
1
it is possible to develop content management in a
ubiquitous learning system using ubiquitous computing
support
2
ubiquitous technologies stimulate the use of mobile
devices as learning tools
3
user profiles and context-awareness allow to address
personalised content according to different contexts
4
advances in this area will allow new approaches to
manage content in educational ubiquitous
environments.
This paper presented the content management educational
model proposed for the GlobalEdu as well as its model of
interoperability among repositories of learning objects
handled during the educational process. The development of
the system provided a single view of all objects available on
the GlobalEdu network, providing to the user learning
objects according to his/her profile and context. The results
of the experiments show that GlobalEdu can be used in a
specific classroom-learning situation and in generic learning
object manipulation. Through a pre-evaluation of the system
developed, it was possible to realise the efficiency of the
system and the satisfaction of the users during their use.
Specific conclusions about the proposed model can be
highlighted:
1
GlobalEdu contains basic modules to support
large-scale ubiquitous learning.
2
The profile learner, the content information and the
context-awareness, by providing location data, is a key
component of the contextualisation process. Therefore,
improvements to these technologies will benefit
GlobalEdu as a whole (and the learner experience as
well).
3
The prototype and initial results attest the usefulness of
the model.
GlobalEdu is an initial proposal. As future work, we intend
to extend the content management educational module,
providing extensions to work with other standards of
learning objects, such as the SCORM (2011). The work
presented is not too distant, whereas it is possible to create
converters to import and to export learning objects in
various formats, without changing the operation of the
system core. New applications (for example, distance
education applications) could be created to access the
GlobalEdu network of learning objects. Finally, we intend
to analyse the GlobalEdu performance and acceptance with
a larger number of individuals.
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