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The 5R Adaptation Framework for Location-Based Mobile Learning Systems

Kinshuk, PhDAssociate Dean, Faculty of Science & Technology

Professor, School of Computing and Information SystemsNSERC/iCORE/Xerox/Markin Industrial Research Chair for Adaptivity and

Personalization in Informatics

Athabasca University, Canadakinshuk@ieee.org

http://kinshuk.athabascau.ca

(jointly with Qing Tan, Xiaokun Zhang and Rory McGreal)

Overall research direction

• Individualised learning in increasingly global educational environment

• Bridging the gap among different types of learners

• Support for:

• Mobile and life-long learners

• Just-in-time and on-demand learning

• Context adaptationSlide 2

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Vision

~ Learning omnipresent and highly contextual ~

So how do we do it?

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Adaptivity in ubiquitous learning

Extensive modelling of learner’s actions, interactions, “mood”, trends of

preferences, skill & knowledge levels, implicit and explicit changes in skill &

knowledge levels

Real-time monitoring of learner’s location, technology use, and change of situational

aspects

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Learner awareness

Personalization of learning experience through the dynamic learner modeling

• Performance based model

• Cognitive trait model

• Learning styles

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Dynamic learner modelingMining of historical and real

time data for real-time adaptivity

• Learning activities• Learning style• Interests & knowledge• Problem solving activities• Learning object/activity usage• Social activities• Learner location• Location related activities

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Technology awareness

Personalization of learning experience through the identification of technological functionality

• Identifying various device functionality

• Dynamically optimize the content to suit the functionality

Display capability, Audio and video capability, Multi-language capability, Memory, Bandwidth,

Operation platform

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Location awareness

Personalization of learning experience through the use of location modeling

• Location based optimal grouping

• Location based adaptation of learning content

• Location based collaborative creation of authentic content

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Location based technologies

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Location aware dynamic grouping

A

B

C D

E

F

G

T = t1 T = t2

t1 != t2!=t3

T = t3

Location Grouping

Mobile Learner’s AddressMobile Learner’s Cellular DataMobile Learner’s GPS CoordinatesMobile Learner’s Other Location Info

Mobile Virtual Campus

Mobile Learner’s Learning ProfileMobile Learner’s Learning StyleMobile Learner’s Learning Interests

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Location based content creation

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Real-life physical objects

Personalization of learning experience as per surrounding environment

Public databases of POIs

QR CodesWi-Fi & Bluetooth Access Point identification

Active and Passive RFIDs

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Surrounding context

Personalization of learning experience through the use of surrounding context

• Identifying specific context-aware knowledge structure among different domains

• Identify the learning objective(s) that the learner is really interested in

• Propose learning activities to the learner

• Lead the learner around the learning environment

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5R Adaptation Framework

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Introduction of framework

• A conceptual framework for the implementation of Adaptive Mobile Learning systems.

• An ontology model of the framework in which the factors of Learner, Location, Time, and Mobile Device are considered in generating Personalized Learning Contents

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Presenting or generating personalized learning contents and instructions dynamically

Learning environment and mobile device

The context of learning process and instruction

Appropriately identifying characters of particular learner.

Dynamic Contents

Mobile Device

Context Aware

Learner Identification

Challenge of facilitating mobile learning and ensuring learners’ performance:

Introduction of framework (cont. 1)

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Introduction of framework (cont. 2)

The challenge facing the development of location-based adaptive learning applications is the ability to deal with these contexts from Learning Perspective.

One of the key strategies is to:•identify and normalize context information based on efficient context-aware data fusion.•semantic-based context constraints using composable ontology models.

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Introduction of framework (cont. 3)

The Ontology-based approach:•Uses predefined metadata models of the learning contents, learner models, context information of the learning activities, and mobile device, etc.

•Retrieve structured and unstructured learning materials and generate personalized, just-in-time, and location-aware learning contents or adaptive “filter” that directs mobile learner to access right contents.

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Introduction of framework (cont. 4)

The First approach:•To create semantic learning contents manually.

The Second approach:•To take advantage of pre-existing learning objects.•To develop shareable ontologies, publishing learning objects standard, and reward mobile service system to make the learning objects widely accessible.

Our Research Aim:To conduct bottom-up development of the ontology for the personalized learning objectives, learning context information and proposed 5R constraint information.

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Introduction of framework (cont. 5)

The Third approach:•To develop software and knowledge retrieval mechanism that automatically identifies appropriate learning components and extracts structural knowledge from unstructured learning contents.

•Learning contents are pre-developed and stored in the learning contents repository of the learning management system.

Our Research Aim:To build and manipulate adaptive “filter” to direct just-in-time retrieval paths during the mobile learning processes.

5R Adaptation Framework

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• The Right Time: Factors: the Date-Time and the Learning Progress

Alberta Legislature:Open: 09:00 AMClose: 04:30 PM

Device Date Time:03:25 PM

Timing Match!Show Contents!

5R Adaptation Framework

• The Right Location: The learner’s current geographic location

GPS Coordination Match!Show Contents!

5R Adaptation Framework

• The Right Device:

HD Video Contents

Audio Contents

Text Contents

Web Page Contents

Flash VideoContents

5R Adaptation Framework

LOA1

LOP2LOH3 Take

Picture

ScreenShot

BackHome

Design Manner of Legislature Building

LO A1

Take Picture

ScreenShot

BackHome

5R Adaptation Framework

• The Right Contents: Learning objects, learning activities, and leaning instruction

• The Right Learner:

Physical Education

Practical English

Art

Computer Science

Mathematics

5R Adaptation Framework

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Implementation of framework

The First layer:•Consists of “Location”, “Time”, “Learner”, “Device”, and “Learning Contents”, respectively representing the five adaptation inputs.

The Second layer:•Further description of information or data of each adaptation input.•The ontology scheme, namely, the relationships among the adaptation inputs, which illustrates why the inputs need to be described and how the inputs are interconnected.

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Framework ontology schema

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Framework application scenario: Concept

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Framework application scenario: Field tripLocation-based mobile fieldtrip applications at a zoo

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Framework application scenario: Field tripLocation-based mobile fieldtrip applications using visualized interaction with dynamic geospatial data

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5R adaptation features in the fieldtrip scenario

Location-based experiment Lab interface and visualized interaction

on mobile devices.

Adaptive learning content retrieval constrained by the location and

ongoing fieldtrip activities.

Visualized fieldtrip plan, real-time activity collaboration and

monitoring during the fieltrip

FieldtripFieldtripScenarioScenario

Dynamic annotation or blog on the visualized semantic physical object model.

Real-time sharing experience between students and others who are in the field or in remote areas

via visualized virtual interaction interface.

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Framework application scenario: RFID Classroom

System Screenshot: User Login

System Screenshot: Learning Object - Round Exicter @ Location code 80

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Framework application scenario: RFID Classroom

System Screenshot: Learning Object - Rectangular Exicter @ Location code 3F

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Mobile and ubiquitouseducational environment

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Thank you!