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Create mobile content using a mobile-friendly knowledge management system:. The Athabasca University (AU) experience. Presentation. Introduction Mobile-friendly Knowledge Management System (MKMS) Mobile Device Automatic Detector Conclusion and Future work.
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Create mobile content using a mobile-friendly knowledge management system: The Athabasca University (AU) experience
Presentation • Introduction • Mobile-friendly Knowledge Management System (MKMS) • Mobile Device Automatic Detector • Conclusion and Future work
A Mobile-friendly Knowledge Management System Hongxing Geng
Outline • Introduction • Related work • Mobile-friendly Knowledge Management System (MKMS) • Conclusion and Future work
Introduction • What is a KMS? • What is a MKMS? • Why do we need a MKMS? • Existing KMSs have disadvantages • Knowledge sharing • Knowledge accessible anytime anywhere
Related work • Moodle (http://www.moodle.org) • Sakai (http://www.sakaiproject.org) • MOMO (http://mobilemoodle.org)
MKMS Design • Design principles • Web-based application • Simple • Multiple languages support • Extensible • Maintainable
MKMS System Architecture • Architecture • Knowledge Node Organization
MKMS Implementation • Prototype • PHP and Zend Framework • MySQL database • Multiple Language support (*.ini)
MKMSFeatures • Accessible through mobile devices • Two views: admin view and learners view • Management: create, delete, organize, and publish/unpublish, etc • Using metadata to describe knowledge entries
Conclusion and Future work • Conclusion • Manage and view content through mobile devices • Facilitate knowledge sharing • Describe entries using metadata • Future work • Authentication and Authorization • Quiz (multi-choice questions) • Searching capacity • OAI-compatible
Mobile Device Automatic Detector A component in Personalized and Adaptive M-learning Framework and Mobile Knowledge Management System Guangbing Yang
Problem statement • Capabilities of a mobile device decide what kind of the content it can display correctly and what context it can process properly • MKMS or other Mobile based LMS, like Personalized Adaptive m-learning System needs to know device capabilities before preparing and transporting the suitable learning contents to mobile clients
Our approach Our approach • design and develop a software API to detect the device information in details. Such information includes the device type, device type name (e.g. HTC, Samsung, iPhone, etc.), device OS, screen resolution, image type supported, etc. • establish a device profile repository to store mobile device specifications • generate device profile ontology and output RDFS or OWL • provide mobile profile retrieving services that can be consumed easily by other applications
System architecture System architecture • Service Oriented Architecture • XML format data exchanging between server and mobile client • XSL selection dependent on mobile device profile • Multi-language support • Multi-platform support
System architecture architecture
Experiment 4 Devices IPHONE Experimental
Experiment HTC Smartphone profile (sample) Experimental <rdf:RDF> <rdf:Description rdf:ID="Profile"> <prf:component> <rdf:Description rdf:ID="HardwarePlatform"> <rdf:type rdf:resource="http://www.openmobilealliance.org/tech/profiles/UAPROF/ccppschema-20021212#HardwarePlatform"/> <prf:Model>Polaris</prf:Model> <prf:Vendor>High Tech Computer Corporation</prf:Vendor> <prf:BitsPerPixel>16</prf:BitsPerPixel> <prf:ColorCapable>Yes</prf:ColorCapable> <prf:ScreenSize>240x320</prf:ScreenSize> <prf:ImageCapable>Yes</prf:ImageCapable> <prf:PixelAspectRatio>1x1</prf:PixelAspectRatio> <prf:ScreenSizeChar>16x36</prf:ScreenSizeChar> <prf:StandardFontProportional>Yes</prf:StandardFontProportional> <prf:SoundOutputCapable>Yes</prf:SoundOutputCapable> <prf:TextInputCapable>Yes</prf:TextInputCapable> <prf:VoiceInputCapable>Yes</prf:VoiceInputCapable> <prf:InputCharSet> <rdf:Bag> <rdf:li>US-ASCII</rdf:li> <rdf:li>UTF-8</rdf:li> <rdf:li>UTF-16</rdf:li> <rdf:li>ISO-10646-UCS-2</rdf:li> </rdf:Bag> </prf:InputCharSet>
Conclusion and further work Conclusion and further work • Described an approach of design and implementation of a mobile device detection adapter to lookup and generate the device profile • Based on the detailed information in the device profile, personalized adaptive m-Learning system or mobile knowledge management system can deliver or transport adaptive context and content to learners. • In next step, a service oriented architecture approach will be implemented into this adapter to provide more efficient and accurate device profile searching and retrieving services. video