`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`DECLARATION OF GORDON MACPHERSON
`
`I, Gordon MacPherson, am over twenty-one (21) years of age. I have never been
`convicted of a felony, and I am fully competent to make this declaration. I declare the following
`to be true to the best of my knowledge, information and belief:
`
`1. I am Director Board Governance & IP Operations of The Institute of Electrical and
`Electronics Engineers, Incorporated (“IEEE”).
`
`2. IEEE is a neutral third party in this dispute.
`
`3. I am not being compensated for this declaration and IEEE is only being reimbursed
`for the cost of the article I am certifying.
`
`4. Among my responsibilities as Director Board Governance & IP Operations, I act as a
`custodian of certain records for IEEE.
`
`5. I make this declaration based on my personal knowledge and information contained
`in the business records of IEEE.
`
`6. As part of its ordinary course of business, IEEE publishes and makes available
`technical articles and standards. These publications are made available for public
`download through the IEEE digital library, IEEE Xplore.
`
`7. It is the regular practice of IEEE to publish articles and other writings including
`article abstracts and make them available to the public through IEEE Xplore. IEEE
`maintains copies of publications in the ordinary course of its regularly conducted
`activities.
`
`8. The article below has been attached as Exhibit A to this declaration:
`
`
`A. Sobah Abbas Petersen and Jan-Kristian Markiewicz, “PALLAS:
`Personalised Language Learning on Mobile Devices”, Fifth IEEE
`International Conference on Wireless, Mobile, and Ubiquitous Technology
`in Education (wmute 2008), March 23 – 26, 2008.
`
`
`
`
`
`9. I obtained a copy of Exhibit A through IEEE Xplore, where it is maintained in the
`ordinary course of IEEE’s business. Exhibit A is a true and correct copy of the
`Exhibit, as it existed on or about August 12, 2021.
`
`
`445 Hoes Lane Piscataway, NJ 08854
`
`DocuSign Envelope ID: 0C45B6AE-711E-4C85-82EC-7EC61C45E150
`
`Twitter Exhibit 1014
`Page 00001
`
`

`

`10. The article and abstract from IEEE Xplore show the date of publication. IEEE
`Xplore populates this information using the metadata associated with the publication.
`
`11. Sobah Abbas Petersen and Jan-Kristian Markiewicz, “PALLAS: Personalised
`Language Learning on Mobile Devices” was published in the Fifth IEEE
`International Conference on Wireless, Mobile, and Ubiquitous Technology in
`Education (wmute 2008). The Fifth IEEE International Conference on Wireless,
`Mobile, and Ubiquitous Technology in Education (wmute 2008) was held from
`March 23 – 26, 2008. Copies of this publication was made available no later than the
`last day of the conference. The article is currently available for public download
`from the IEEE digital library, IEEE Xplore.
`
`12. I hereby declare that all statements made herein of my own knowledge are true and
`that all statements made on information and belief are believed to be true, and further
`that these statements were made with the knowledge that willful false statements and
`the like are punishable by fine or imprisonment, or both, under 18 U.S.C. § 1001.
`
`I declare under penalty of perjury that the foregoing statements are true and correct.
`
`
`
`
`Executed on:
`
`
`
`
`
`
`
`
`
`
`DocuSign Envelope ID: 0C45B6AE-711E-4C85-82EC-7EC61C45E150
`
`8/13/2021
`
`Page 00002
`
`

`

`
`
`
`
`
`
`
`
`
`
`
`
`
`
`EXHIBIT A
`
`DocuSign Envelope ID: 0C45B6AE-711E-4C85-82EC-7EC61C45E150
`
`Page 00003
`
`

`

`8/12/2021
`
`PALLAS: Personalised Language Learning on Mobile Devices | IEEE Conference Publication | IEEE Xplore
`
`IEEE.org
`
`IEEE Xplore
`
`IEEE-SA
`
`IEEE Spectrum
`
`More Sites
`
`SUBSCRIBE
`
`SUBSCRIBECart Create Account
`
`Personal Sign In 
`
`
`
`Browse  My Settings  Help 
`
`Institutional Sign In
`
`Institutional Sign In
`
`All
`
`
`
`
`
`ADVANCED SEARCH
`
`Conferences > Fifth IEEE International Conf... 
`
`PALLAS: Personalised Language Learning on Mobile Devices
`Publisher: IEEE
`
`Cite This
`
` PDF
`
`Sobah Abbas Petersen ; Jan-Kristian Markiewicz All Authors
`
`17
`Paper
`Citations
`
`320
`Full
`Text Views
`
`Abstract
`
`Document Sections
`
`1.
`
`Introduction
`
`2. Personalisation
`and context
`
`3. Scenario
`
`4. Design
`considerations
`
`5. PALLAS: System
`description
`
`Show Full Outline 
`
`Authors
`
`Figures
`
`References
`
`Citations
`
`Keywords
`
` 
`
`Alerts
`
`Manage Content Alerts
`
`Add to Citation Alerts
`
`Abstract:Mobile and ubiquitous learning facilitates language learners to continue their
`learning process outside the formal classroom, when and where they desire. While
`more and m... View more
`
` Metadata
`Abstract:
`Mobile and ubiquitous learning facilitates language learners to continue their learning
`process outside the formal classroom, when and where they desire. While more and
`more learning resources are accessible via a mobile device, there is a challenge in
`providing access to appropriate personalised learning resources. Personalisation and
`contextualisation are often used as synonyms. In our work, we distinguish between
`these two concepts and consider personalisation as a part of contextualisation. This
`paper describes the PALLAS system which enables real life language learning
`scenarios by providing personalised and contextualised access to learning resources
`via a mobile device. The dynamic and static parameters for contextualisation and
`personalisation of language learning resources are discussed.
`
`Published in: Fifth IEEE International Conference on Wireless, Mobile, and Ubiquitous
`Technology in Education (wmute 2008)
`
`https://ieeexplore.ieee.org/document/4489788
`
`1/3
`
` D
`
`ownl
`PDF
`
`Page 00004
`
`More
`Like
`This
`Intelligent Computer-Aided
`Instruction Modeling and a
`Method to Optimize Study
`Strategies for Parallel Robot
`Instruction
`IEEE Transactions on Education
`Published: 2013
`How to Improve the Quality and
`Effect of Computer Aided
`Instruction's Application in
`Classroom Teaching in Institutes
`of Higher Learning
`2010 Second International
`Workshop on Education
`Technology and Computer
`Science
`Published: 2010
`Show
`More
`

`

`8/12/2021
`
`Metrics
`
`More Like This
`
`PALLAS: Personalised Language Learning on Mobile Devices | IEEE Conference Publication | IEEE Xplore
`Date of Conference: 23-26 March 2008
`INSPEC Accession Number: 9940109
`
`Date Added to IEEE Xplore: 15 April 2008
`
`DOI: 10.1109/WMUTE.2008.17
`
` ISBN Information:
`
`Publisher: IEEE
`
`Conference Location: Beijing, China
`
` Contents
`
`1. Introduction
`The rapid growth of mobile and ubiquitous learning technologies have
`opened up new avenues and learning arenas for learners. Learners are
`now able to access learning material anytime, anywhere, while they are
`Sign in to Continue Reading
`out and about. While access to learning resources is improved
`significantly, additional challenges arise. Personalisation and
`contextualisation of learning resources have recently been the focus of
`several articles, e.g. [1], [2] and [3].
`
`Authors
`
`Figures
`
`References
`
`Citations
`
`Keywords
`
`Metrics
`
`
`
`
`
`
`
`
`
`
`
`
`
`IEEE Personal Account
`
`Purchase Details
`
`Profile Information
`
`Need Help?
`
`CHANGE USERNAME/PASSWORD
`
`PAYMENT OPTIONS
`
`COMMUNICATIONS PREFERENCES
`
`US & CANADA: +1 800 678 4333
`
`VIEW PURCHASED DOCUMENTS
`
`PROFESSION AND EDUCATION
`
`WORLDWIDE: +1 732 981 0060
`
`TECHNICAL INTERESTS
`
`CONTACT & SUPPORT
`
`Follow
`
`  
`
`About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting  | Sitemap | Privacy & Opting Out of Cookies
`A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
`
`© Copyright 2021 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
`
`IEEE Account
`
`Purchase Details
`
`Profile Information
`
`Need Help?
`
`» Change Username/Password
`» Update Address
`
`» Payment Options
`» Order History
`» View Purchased Documents
`
`» Communications Preferences
`» Profession and Education
`» Technical Interests
`
`» US & Canada: +1 800 678 4333
`» Worldwide: +1 732 981 0060
`» Contact & Support
`
`https://ieeexplore.ieee.org/document/4489788
`
`2/3
`
`Page 00005
`
`

`

`8/12/2021
`
`PALLAS: Personalised Language Learning on Mobile Devices | IEEE Conference Publication | IEEE Xplore
`
`About IEEE Xplore Contact Us
`
`|
`
`
`
`|
`
`Help
`
`
`
`|
`
`Accessibility
`
`
`
`|
`
`Terms of Use
`
`
`
`|
`
`Nondiscrimination Policy
`
`
`
`|
`
`Sitemap
`
`
`
`|
`
`Privacy & Opting Out of Cookies
`
`A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
`© Copyright 2021 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
`
`https://ieeexplore.ieee.org/document/4489788
`
`3/3
`
`Page 00006
`
`

`

`
`
`
`
`Fifth IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in EducationFifth IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in EducationFifth IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in Education
`
`PALLAS: Personalised Language Learning on
`Mobile Devices
`
`
`
`Sobah Abbas Petersen
`NTNU, Trondheim, Norway.
`Email: sap@idi.ntnu.no
`
`
`
`Abstract
`
`
`Mobile and ubiquitous learning facilitates language
`learners to continue their learning process outside
`the formal classroom, when and where they desire.
`While more and more
`learning resources are
`accessible via a mobile device, there is a challenge in
`providing access
`to appropriate personalised
`learning
`resources.
`Personalisation
`and
`contextualisation are often used as synonyms. In our
`work, we distinguish between these two concepts and
`consider
`personalisation
`as
`a
`part
`of
`contextualisation. This paper describes the PALLAS
`system which enables real life language learning
`scenarios
`by
`providing
`personalised
`and
`contextualised access to learning resources via a
`mobile device. The dynamic and static parameters for
`contextualisation and personalisation of language
`learning resources are discussed.
`
`
`1. Introduction
`
`
`The rapid growth of mobile and ubiquitous learning
`technologies have opened up new avenues and
`learning arenas for learners. Learners are now able to
`access learning material anytime, anywhere, while
`they are out and about. While access to learning
`resources
`is
`improved
`significantly, additional
`challenges
`arise.
`Personalisation
`and
`contextualisation of learning resources have recently
`been the focus of several articles, e.g. [1], [2] and [3].
`Personalisation of learning systems is an effort
`towards making education more learner-centred. The
`essence of this is that it is the system that conforms to
`the learner rather than the learner to the system [4].
`Personalisation
`in education
`is considered very
`broadly where
`the
`learner can create
`learning
`experiences in diverse locations, collaborate with
`experts in the areas of personal interests, track and
`review their own learning across the diverse sites and
`
`Jan-Kristian Markiewicz
`NTNU, Trondheim, Norway.
`Email: janmark@microsoft.com
`
`
`
`
`learning stages and access learning resources in the
`form and media relevant to their language skills,
`abilities and personal preferences. Personalisation is
`not only about new ways of distributing learning
`resources, but also about finding ways to understand
`the skills, resources and interests of the learner
`outside the classroom.
`The term mobile learning has become popular to
`denote learning that is conducted while the learner is
`on the go or when the learner is mobile [5]. Mobile
`learners often have varied learning backgrounds and
`levels and thus mobile learning systems should be
`adaptable [6]. Thus, we believe that personalisation is
`crucial for mobile learning. Mobile learning also
`involves providing access to learning resources and
`providing learning support for the mobile learner,
`using diverse technologies such as mobile, ubiquitous
`or embedded devices. Learning via such technologies
`is not intended to replace classroom learning; rather
`such
`technologies,
`if
`leveraged properly, can
`complement and add value to existing learning
`models, [7], such as the socio-constructivist approach
`to learning [8].
`Language
`learning has been an area where
`technology, in particular mobile technology in recent
`times, has been popular. Use of mobile technology
`for learning English as a foreign language has been
`popular. Initially, mobile-based language learning
`services focused on providing instant help in either
`obtaining the meaning of a word [9] or help in
`pronouncing a word. Little or no emphasis was given
`to providing personalised learning. More recently,
`improved support has been provided by partial
`personalised
`learning
`such
`as
`supporting
`pronunciation of specific sounds for specific user
`groups, e.g. [10].
`In this paper, we describe a prototype system,
`PALLAS, which provides support to a mobile
`language learner by providing personalised and
`contextualised access to learning resources. The main
`focus of this paper is on the personalisation of
`
`
`
`0-7695-3108-3/08 $25.00 © 2008 IEEE0-7695-3108-3/08 $25.00 © 2008 IEEE0-7695-3108-3/08 $25.00 © 2008 IEEE
`
`
`DOI 10.1109/WMUTE.2008.17DOI 10.1109/WMUTE.2008.17DOI 10.1109/WMUTE.2008.17
`
`
`
`
`
`525252
`
`Authorized licensed use limited to: IEEE Publications Operations Staff. Downloaded on August 12,2021 at 13:10:25 UTC from IEEE Xplore. Restrictions apply.
`
`Page 00007
`
`

`

`learning resources that is provided to a mobile
`language
`learner.
`In our work, we consider
`personalisation of learning resources of as a part of
`contextualisation
`and
`distinguish
`between
`personalisation and contextualisation. Personalisation
`of resources is considered as providing content to the
`learner according to the learner’s needs and interests
`and presenting it to the learner rather than the learner
`having to look for it. The PALLAS system described
`in this paper considers dynamic and static parameters
`for personalisation where the dynamic parameters are
`updated automatically by the system and the static
`parameters are provided by the learner.
`Mobile Language learning is illustrated using a
`scenario, which is also used to evaluate the system.
`The rest of this paper is structured as follows: Section
`2 discusses personalisation and context and how other
`authors have used these concepts; Section 3 describes
`a mobile language learning scenario; Section 4
`discusses the design considerations for PALLAS and
`how personalisation and contextualisation is done in
`PALLAS; Section 5 provides an overview of the
`PALLAS prototype system; Section 6 outlines the
`current status of the work and provides a brief
`scenario-based evaluation of the current system;
`Section 7 describes the related work and Section 8
`concludes the paper and discusses our plans for the
`future.
`
`2. Personalisation and context
`
`
`Personalisation of learning systems is often based
`on making them context-aware, where the definition
`of context has varied from the location of the learner
`[11] and [12] to learner’s leisure time and individual
`abilities [2]. According to Dey [13], context is
`defined as any information that can be used to
`characterise
`the situation of an entity. Thus,
`information that is required to provide personalised
`learning resources to a language learner can also be
`considered as a part of the context of the learner. We
`subscribe to the notion that context is built up of a
`number of aspects as proposed by Kofod-Petersen et
`al. [14]. In their taxonomy, they have identified task
`context which captures the user’s activities and goals;
`social context which describes the user’s relationships
`and roles; personal context which encompasses the
`mental and physical properties of the user; spatio-
`temporal context which represents concepts such as
`time and location and environmental context which
`deals with the surroundings and the entities present. A
`framework for the context of a mobile learner in an
`ambient intelligent environment is proposed in [15].
`
`In the mobile learning domain, context is viewed
`as dynamic, as being continually constructed through
`negotiation between communicating partners and the
`interplay of activities and artefacts [1]. Unlike the
`context for traditional learning, the context for mobile
`learning evolves according to the interactions of the
`learner. Earlier work on context in educational
`systems considered the interaction of the learner with
`the system only [16] and not with other learners or
`people that can support her learning process. Factors
`that have to be taken into account in personalisation
`for a mobile learner, in addition to the learner’s
`individual profile, include the evolution of the
`behaviour of the learner, the variables affecting the
`learning such as the social aspects and the uncertainty
`of the domain or the learning environment such as
`something happening unexpectedly [17].
`In [2], personalisation is considered as similar to
`context awareness where the context of a language
`learner is defined as the learner’s location, learning
`time, e.g. around Christmas time, learning abilities
`and leisure time. In their application, the learner’s
`location is considered the most important parameter.
`A broader view of personalisation is considered in
`[3], where a multi-modal approach was proposed for
`personalisation of ubiquitous learning applications. A
`user model describes the learner’s personal data such
`as name, gender and address and the learner’s
`interests and experiences; a usage model describes
`the learner’s usage behaviour; an application model
`describes information about the application and an
`environment model describes the learner’s location or
`physical context, the device type and hardware and
`software aspects.
`
`3. Scenario
`
`Mina is a student in Trondheim attending a
`beginner’s class in French. One day, on her way home
`from school, she passes the farmers’ market. She
`doesn’t know the French names for vegetables, so she
`takes her Smartphone and starts the language learning
`application PALLAS. She selects French and enters
`the keyword “grønnsaker”. Mina is presented with a
`short
`text
`in French describing
`the different
`vegetables. The difficulty level of the text is based on
`Mina’s profile in the language learning application,
`which has been built automatically based on her
`previous interactions with it. After she has finished
`reading the short text, she looks at the glossary
`connected to the text. The glossary contains the
`French names and pictures of the different vegetables.
`When she has finished reading through the glossary,
`
`Authorized licensed use limited to: IEEE Publications Operations Staff. Downloaded on August 12,2021 at 13:10:25 UTC from IEEE Xplore. Restrictions apply.
`
`535353
`
`Page 00008
`
`

`

`Mina selects the “Glossary test” option. This starts a
`test based on the glossary words. When Mina
`accesses PALLAS via her desktop computer later that
`day, she is notified that she should practice more on
`the vegetable glossary.
`One day while passing by the art gallery, her
`location-aware Smartphone starts to beep. Mina sees
`a notification from PALLAS telling her that the art
`gallery has a French art exhibition. She visits the
`exhibition which also allows her to get in contact with
`some French people that she could practice her
`French with. Whenever Mina has problems
`understanding a French word, she queries PALLAS’
`built-in dictionary.
`
`4. Design considerations
`
`In this section we consider the general design
`considerations for systems that support language
`learning
`and
`how
`personalisation
`and
`contextualisation is supported in PALLAS.
`
`4.1 General
`
`language
`for
`There are several approaches
`teaching and learning, [18], and guidelines for the
`designing of teaching systems and resources have
`been around for many years, e.g. [19]. Guidelines are
`proposed for personalised learning resources such as
`the learning material to be appropriate for the age of
`the learner, to fit the language level of the learner,
`that the system provides enough time for the learner
`and that feedback should be provided to the learner
`responses.
`For the mobile learner, as the learning becomes
`more
`personalised
`and
`contextualised,
`the
`technological challenges
`in designing
`learning
`support is bigger. The devices that support the learner
`are more personalised. Sharples et al. identified some
`of the design issues for such learning support in [20]
`and [21]. Such
`technologies should be highly
`portable, unobtrusive, available and must adapt to the
`learner’s needs and context. Unlike the design of
`computer-based teaching systems, there are other
`implications in using mobile devices. Some of these
`are discussed in [22]. When the learner is mobile, she
`may have small time slots to engage in learning and
`thus would
`like
`to conduct “small chunks of
`learning”. So, it’s important to keep track of the
`learning process for any learner so that the learner
`can start from where she left the previous time.
`
`
`
`4.2 Personalisation in PALLAS
`
`between
`distinguish
`our work, we
`In
`contextualisation and personalisation, where we
`consider
`personalisation
`as
`a
`part
`of
`contextualisation. In PALLAS, contextualisation is
`achieved using
`the profile of
`the
`learner and
`environmental parameters. The
`learner’s profile
`contains information such as the learner’s age, skill
`level, native language, interests and courses taken.
`Environmental parameters include location, time and
`day and the mobile device that is used by the learner.
`An overview of these parameters is provided in
`Figure 1, where a symbol is shown to the right of the
`parameter to indicate the dynamic parameters; i.e. the
`ones that are updated automatically. The parameters
`that are not dynamic such as the age of the learner are
`updated manually by the learner. This supports two
`ways of adaptability by the system; by using some
`knowledge about the learner in a system controlled
`way and by using knowledge provided by the learner
`manually [6].
`
`
`
`Figure 1. Dynamic personalisation and
`contextualisation parameters in PALLAS
`
`An overview of personalisation parameters that
`we have found in the literature and the ones that are
`supported in PALLAS are provided in Table 1. In
`addition to the parameters that we have found in the
`literature, PALLAS also considers the learner’s native
`language as this can be important in determining the
`appropriate learning material presented. For example,
`a beginner may prefer to receive an explanation of a
`word in her native language rather than the target
`language. Since interactions with other people play an
`important role
`in
`language
`learning and
`these
`interactions influence the context of the learner [1],
`we have included a learner’s user groups or the
`communities
`that she may
`interact with as a
`personalisation parameter. This parameter is essential
`
`545454
`
`Authorized licensed use limited to: IEEE Publications Operations Staff. Downloaded on August 12,2021 at 13:10:25 UTC from IEEE Xplore. Restrictions apply.
`
`Page 00009
`
`

`

`to support a collaborative and mobile language
`learner [15]. Other courses that are taken by the
`learner are also considered as this may provide
`additional information about the learner and may help
`in determining the people that may be able to help in
`the learning process. This could also be used to
`determine
`appropriate
`activities
`for
`language
`learning. For example, if the learner is studying
`French and architecture, activities that relate to the
`buildings in the vicinity could be suggested to the
`learner. The weather is considered as PALLAS is
`aimed to be used outside of the classroom and may
`help in suggesting appropriate activities for the
`learner.
`
`Table 1. Overview of personalisation and
`contextualisation parameters
`
`
`Personalisation Parameters in
`Literature
`
`Learner’s skills, learning ability
`Learner’s name, age
`Learner’s gender
`Learner’s address
`Experience
`Interests
`Stereotype
`Device, Hardware, Software
`Location
`Access logs
`Activity Logs
`Time
`Leisure Time
`
`
`
`Personalisation
`Parameters
`in
`PALLAS
`X
`X
`
`
`X
`X
`
`X
`X
`X
`X
`X
`X
`
`The PALLAS system is designed to provide
`active personalisation where personalisation is an
`ongoing process. Two assumptions have been made
`in order make
`it easier
`to
`support active
`personalisation:
`i)
`although
`the
`learner’s
`personalisation data, most important of which is the
`skills level changes over time, it seldom changes
`drastically within a short amount of time; ii) PALLAS
`is a substantial source of the learner’s language
`learning. The PALLAS system is based on a central
`server architecture and the learner’s personalisation
`data or profile is stored on the server. The learner’s
`skill level is automatically updated every time the
`learner completes an exercise and the learning content
`delivered to a learner at any time is matched against
`the learner’s current personal data. As mobile learners
`engage in small chunks of learning and are likely to
`do this often, it is important that the personalisation
`data is updated after every time and the more
`
`regularly the learner accesses PALLAS, (assumption
`ii), the more likely it is that the personalisation data is
`accurate.
`
`5. PALLAS: System description
`
`
`This section provides an overview of
`PALLAS system.
`
`5.1 System overview
`
`
`the
`
`
`
`
`
`Figure 2. PALLAS system overview
`
`
`The PALLAS system is based on a central server
`architecture, see Figure 2. The PALLAS Server is the
`main hub of communication, content storage and
`content distribution. The main server components are
`the Web Server, which can host web pages and web
`services, the Database Server, for data storage, and
`the Application Server which is used to run scheduled
`tasks such as importing content from the publishing
`houses’ Content Management Systems. PALLAS
`supports different ways of creating and accessing
`learning content. A description of the learning content
`and how this is created and composed are beyond the
`scope of this paper.
`The Map Provider gives access to map data which
`is useful for PALLAS’ context needs. Maps are
`among other things used to make it easy to add
`
`555555
`
`Authorized licensed use limited to: IEEE Publications Operations Staff. Downloaded on August 12,2021 at 13:10:25 UTC from IEEE Xplore. Restrictions apply.
`
`Page 00010
`
`

`

`location context to content. The reason why the Map
`Provider interfaces through the server instead of
`directly to the different clients is that it makes the use
`of maps transparent to the client application. This
`makes it possible, for example, to change to a
`different provider without changing any code in the
`client applications. The SMS Service Provider
`facilitates SMS responses to users. Finally, the server
`uses different Third Party Lookup Services
`to
`automatically add context information to content, e.g.
`a Google Search [23], to find the address of a point of
`interest.
`The main user groups for PALLAS are language
`learners,
`language
`teachers
`and
`system
`administrators. The main roles of the teachers are to
`manage their students learning activities and to
`provide language learning content. The PALLAS
`system administrators are responsible for performing
`administrative tasks which include giving teachers’
`access to PALLAS and configuring the server’s
`content import module settings. This functionality can
`be provided through a web site on the PALLAS
`server or a client application that uses the PALLAS
`Web Services. The system administrators and
`teachers can perform their tasks using a PC with a
`web browser or the client application.
`Learners have a variety of ways to use PALLAS.
`They can use a descktop PC to log onto a learner
`portal web site on the PALLAS server or they can use
`mobile devices such as mobile phones and PDAs.
`The learner’s profile is updated every time whichever
`device the learner uses to access the PALALS system.
`The mobile devices can use PALLAS in a number of
`ways: they can run a custom client application that
`provides all the functionality, they can use a mobile
`web browser as a thin client or they can query the
`system via SMS. If the learner is using a mobile
`device with the PALLAS mobile client application
`installed, they could use a GPS unit to automatically
`obtain location information.
`PALLAS
`is
`implemented using Microsoft
`Windows technology and the .NET development
`platform. The mobile device that was used to test the
`application was a Qtek 8310 smartphone [24],
`running the Windows Mobile 5.0 OS. The technical
`details of PALLAS are available from [25].
`
`5.2 Mobile smart client
`
`
`The Mobile smart client performs the functions
`such
`as
`display
`of
`content,
`caching
`and
`synchronisation of data. It is responsible for the
`presentation of the data. The main components of it
`
`are the context engine and the adaptivity engine
`which make the PALLAS mobile client context-
`sensitive and adaptive
`to
`the user and
`the
`environment, see Figure 3.
`
`
`
`
`
`Figure 3. Mobile smart client architecture
`
`
`The context engine runs monitoring services to
`keep track of the context data and updates the learner
`profile and the other dynamic parameters shown in
`Figure 1. It also contains context history services that
`allow storage and retrieval of previous context and
`personalisation data. The adaptivity engine supports
`the presentation of appropriate content to the learner
`and the presentation tier uses the content retriever in
`the adaptivity engine for this. The context engine also
`provides events that other modules can subscribe to.
`For example, the adaptivity engine subscribes to
`several events of the context engine for adapting the
`GUI or the profile of the user. A synchronisation
`engine is used to conduct communication with the
`PALLAS server. It provides transparent access to the
`content, profile and result data and transfers cache
`and synchronises data between the server and the
`mobile client.
`The mobile client also has local storage where
`data that is downloaded when a network connection is
`
`565656
`
`Authorized licensed use limited to: IEEE Publications Operations Staff. Downloaded on August 12,2021 at 13:10:25 UTC from IEEE Xplore. Restrictions apply.
`
`Page 00011
`
`

`

`available can be cached. If the learner queries
`PALLAS while a network connection is unavailable,
`then the locally stored content is presented.
`
`5.3 Mobile client for learners
`
`
`The mobile smart client allows learners to access
`language learning content anytime and anywhere, via
`a mobile device. Figure 4 shows the main window of
`the PALLAS mobile client. The learner is able to
`select the activity that she wants to perform such as
`perform a query, do some tests or exercises or access
`the dictionary service. An activity can be selected by
`using the joystick on the phone or by pressing the
`corresponding number, e.g. 6 for the dictionary
`service. A context bar is displayed on the top of the
`window, which displays the current learner. The
`symbol to the right indicates if the mobile device is
`online or offline (note that the device is online in the
`figure) and the symbol to the left indicates if the
`current location is known (note that the location is
`unknown in the figure).
`The learner is able to update her profile manually
`using the mobile client, see Figure 5. The menu
`shows the other activities that can be performed using
`the mobile client.
`
`
`
`Figure 4. Mobile client: activities for the
`learner
`
`
`
`
`
`
`
`The mobile client also displays triggers that are
`fired based on the context information. For example,
`the learner is in the vicinity of an exhibition that fits
`the profile of the learner, see Figure 6. The symbols
`on the top right corner of the display indicate that the
`device is offline and that the location is known. Note
`that context triggers can fire although the device is
`offline as PALLAS has cached content stored locally
`on the device.
`
`
`
`
`
`
`Figure 6. Mobile client: context trigger
`
`
`6. Current status and evaluation
`
`PALLAS was developed as a prototype system
`and the specifications for the system were determined
`by analysing mobile language learning scenarios such
`as the one described in Section 3. A scenario-based
`evaluation of the functionalities of PALLAS has been
`conducted and an overview of this is provided below:
`• Learners have their own profiles to keep track of
`their progress,