designing and experiencing smart objects based learning scenarios: an approach combining ims ld,...

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Aroua Taamallah and Khemaja Maha.

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By  Aroua  Taamallah  and  Dr.  Maha  Khemaja        

   TEEM  2014,  Salamanca,  Spain,1-­‐3  Octobre  2014  

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§  Introduction ü Purpose ü  Internet of things ü e-Learning standards

§  State of the Art §  Challenges to overcome §  Proposal §  A Use case for validation §  Conclusions

     

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}  Our purpose is to use physical objects in learning processes

}  IoT and learning environments could be the enabling technologies

}  Internet of things and e-Learning are two different domains based on several different standards

}  Is it possible to combine IoT and e-Learning standards as IMS LD and xAPI?

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}  A paradigm introduced by Kevin Ashton in 1999 }  Related to ubiquitous computing }  Used to connect a physical objet to the Internet

                                                                                                               Figure 1: Internet of things    

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IMS Learning Design (IMS LD): }  is a specification developed by IMS GLC (IMS Global

Learning Consortium) in 2003 }  enables a formal description of learning processes.

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eXperience API (xAPI) }  is a specification that enables tracking of learning experiences }  It is based on an LRS (Learning Record Store)

ü  Is a repository ü  Allows to collect one’s learner data from any physical or digital

learning environment. ü Stores data in learning statements formats.

 

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Works   xAPI   IMS  LD   IdO   Applica6on  Domain   Smart  Objects   Interaction types with

objects [Gómez, et al.,

2013]        -­‐            -­‐          +   Experimentation

Laboratory

Tablet, PC, QR CODE and R F I D Ta g s , Mobile phones

Object - Object Human- object

[Chin, J., & Callaghan, V. 2013]

       -­‐            -­‐          +   Living Lab S e n s o r s , R F I D t a g s , Bozz-Board- Smart -Boxes

Human- object  

[Domingo, M.

C. ,2012]          -­‐            -­‐          +   School primary R F I D Embedded into books

Human- object  

[Borrego-Jaraba et al.,2013]        -­‐    Level A        +   University

Library RFID tags embedded into mobile phones

Human- object  

[Anasol et al.,2012]        -­‐   Level A        +   Mixed Reality

xReality objects Virtual objects, Buzz-board

Human- object

 

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}  There is a strong requirement to use standards that: ü  Support a range of pedagogical scenarios in a

formal way. ü  Adapt these scenarios based on learners’ tracked

experiences.  

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}  Three aspects: 1.  Extending the IMS LD with IoT 2.  Using xAPI specification to keep tracks of the learners’

experiences 3.  Adapting the learning scenarios based on historical information.

Heterogeneity of the standards prevent the combination

to take effect }  We need a unified and semantic language to overcome those

drawbacks }  Ontologies are considered as a promising solution

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}  Contains IMS LD specification’s main concepts, and their metadata ü  Describes formally, explicitly learning scenario.

           

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}  IMS LD extension provides three kinds of extensions : ü  Extending a learning environment with smart objects ü Extending learning objects with physical learning objects (PLO) ü Extending learner’s activities with physical activities : interaction

with physical objects

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}  IoT model illustrates the IMS LD extension which ü  includes smart objects into physical learning environment ü describes semantically the smart objects ’ profiles.

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}  xAPI model ü  provides xAPI specification concepts ü tracks learner’s learning experiences

                                                                                                                         

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 IoT  concepts     IMS  LD  concepts   xAPI  concepts  

Learner   Learner   Actor  

AcKvity   Verb  

Smart  Learning  Object   Learning  Object   Object  

Service   Service  

Outcome   Result  

Environment   Context  

Staff  

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}  Michael, a computer science student }  Proposed Unit Of Learning : Distinguishing between computer building blocks and understanding their functionalities }  Used components: ◦  Computer components (MotherBoard, RAM memory…) ◦  Mobile devices equipped with NFC modules ◦  Augmented objects with NFC tags

}  Learning activities: Touching IoT components, doing an evaluation task…

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}  Instantiation of IMS LD and IoT ontologies allows describing formally the scenario }  Contextual data is therefore captured

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}  Example 1: illustrates the list of subjects and objects related with has friend property :

}  It is used to express the relationship between smart objects

Example2: illustrates historical xAPI data

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}  Example3 : illustrates an adaptation rule : }  When Michael do not understand a component and its

functionalities, he sends a message using his Smartphone R1 to augmented objects.

}  Augmented objects send hyperlink for course explanation

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Our aim was to: }  1) use e-Learning standards with smart objects to design complex

learning scenarios }  2) keep track of the learner’s learning experience. }  We have used ontologies to: }  1)grant interoperability between standards }  2)provide context-aware activities to learners. We aim in the future to : }  extend our ontologies with additional rules related to context

awareness and adaptability. }  Experiment the proposal with an extended learning environment

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