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Application of Learning Styles Adaptivity in Mobile Learning Environments

Application of Learning Styles Adaptivity in Mobile

Learning Environments

Oleh : Kinshuk, Taiyu Lin

ABSTRACT

Availability of advanced mobile technologies, such as high bandwidth

infrastructure, wireless technologies, and handheld devices, have started to extend e

learning towards mobile learning !mlearning" !Sharples, #$$$"% &his phenomenon

fits well with the new paradigm 'anytime, anywhere computing( !Lehner and

)*se+abel, #$$#"% owever, the development of mlearning is still at rather early

stage and many issues have yet to be resolved% One of these issues is the potential of

individuali-ation of learning process for the learners%

&his paper explores how to improve learning process by adapting course

content presentation to student learning styles in multiplatform environments such

as ./ and .0A% A framewor+ has been developed to comprehensively model

student1s learning styles and present the appropriate sub2ect matter, including thecontent, format, media type, and so on, to suit individual student% &he wor+ is based

on the 3elderSilverman Learning Style &heory% &he framewor+ uses traditional

webbased intelligent tutorial architecture, with two additional components:

4learning style analysis module1 and 4access device analysis module1% &he learning

style analysis module ta+es care of modeling student learning style and

communicates with student model, whereas the access device analysis module

identifies the access device profile and provides the information to tutorial module%

&he tutorial module creates the suitable content, based on the student model

!including individual learning styles" and access device profile, and presents to the

student%

5ased on the framewor+, a prototype for the domain of .. programmingcourse has been developed% 6ith this system, students are able to learning ..

programming with course content that matches their own learning style and the

device used to access the content% A formative evaluation is planned to assess the

student satisfaction, learning efficiency, and effectiveness of the system while

providing various presentations of the same content to different users on different

devices%

INTRO!CTION

Availability of advanced mobile

technologies, such as high bandwidth

infrastructure, wireless technologies, and

handheld devices, have started to extend e

learning towards mobile learning !m

learning" !Sharples, #$$$"% &his

phenomenon fits well with the new paradigm

'anytime, anywhere computing( !Lehner

and )*se+abel, #$$#"% owever, the

development of mlearning is still at rather

early stage and many issues have yet to beresolved% One of these issues is the potential

of individuali-ation of learning process for

the learners%

7n past decades, researchers from

different disciplines have intended to define

and classify learning styles that help teacher

1


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)ama 8urnal% 9olume $ nomor $ &ahun #$;, $#;

to improve their individuali-ed teaching%

&here are many learning style theories used

today and the learning style theories have

been applied in educational environment

widely% 3or example, the &heory into

.ractice 0atabase !&7., #$$


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practical approach to establish the

dominant learning style of each

student%

o &he results of 7LS can be lin+ed

easily to adaptive environments

(.aredes and odrigue-, #$$#"%

o

7t is most appropriate and feasible to be implemented for hypermedia

courseware !/arver and oward,

???"%

&his theory categori-es an

individual1s preferred learning style by a

sliding scale of five dimensions: sensing-

intuitive, visual-verbal, inductive-deductive,

activereflective and sequential-global

!3elder and Silverman, ?BB 3elder, ??


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ExpertModule

StudentModel

Tutoring Module

Communication Mechanism

Server

Client

User Interface Module (PC or

InternetInternet

Learning styleanalysis

Access deiceanalysis


these styles, and there is respective course

material for each style% 6hen student first

time enter the system, the course content is

delivered to student randomly% &hen the

system monitors student1s learning process

and base on student1s evaluation to update

student1s learning styles !auditory, visual,tactile or a combination of them"% According

to student1s latest learning styles, the system

provides the suitable course content% &he

learning styles supported by the system are

not based on any educational learning style

theory, so its learning styles are more or less

li+e preference%

Adaptive /ourseware Environment

!A/E" !Specht and Oppermann, ??B"

provides certain mechanism to adapt to

student1s learning styles% 6hen a studentstarts to use a new courseware, the student

are as+ed for their learning strategies, such

as learning by example, reading texts, or

learning by doing% 5ased on the learning

model, the domain model and the

pedagogical model, the presentation

component selects appropriate learning units

and generates individual hypermedia

documents for student% 7n strict learning

style theory in education, its supporting

learning styles may be classified into student

preference%

&he 6ebbased system created by

.aredes and odrJgue- !#$$#" uses

3elderSilverman Learning Style &heory and

7ndex of Learning Styles to assess student1s

learning styles% &hen the assessment result is

used to automatically adapt 6ebbased

educational systems1 content seFuencing for

student% owever, the system only supports

two dimensions of four dimensions in the

3elderSilverman Learning Style &heory%

0ifferent systems have various ways

to collect student1s learning styles, such as

interview, Fuestionnaire, and monitor

student1s behaviour% owever, an important

point that has to be +ept in mind is to get a

useful student1s learning style actually is a

psychological test process that specially

designed, and not by a simple interview

!5rusilovs+y, #$$"%

All of these systems are ./ based systems%

&hey do not support the mobile

environments, which are emerging very fastand need to be further explored% &he aim of

the paper is to explore how to support

individual study in mobile environments%

T'E 'I"'%LE&EL ARC'ITECT!RE

O$ T'E S#STEM

&he highlevel architecture uses traditional

webbased intelligent tutorial architecture,

with two additional components: 4learning

style analysis module1 and 4access device

analysis module1% !figure"%

3igure : the high level architecture of the

prototype


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&he learning style analysis module ta+es

care of modeling student learning style and

communicates with student model, whereas

the access device analysis module identifies

the access device profile and provides the

information to tutorial module% &he tutorial

module creates the suitable content, based onthe student model !including individual

learning styles" and access device profile,

and presents to the student%

TO+AR T'E *ROTOT#*E

&his section discusses how toimplement the prototype based on the above

architecture%

Adaptation in mobile learning

environments

&he adaptation in mobile learning

environments implicates that it has to

consider the individual learner and theaccess device% 7n the prototype, the access

devices are ./ or .0A%

Adaptation to student1 learning styles:

&he framewor+ is able to adapt to individual

student learning style by providing a default

learning style adaptation and individual

learning style adaptation%

&he default learning style adaptation:

the system populates student learning style

with a default learning style if student selects

not to ta+e the learning style assessment

Table : default !references for mild

!references of learning st"le dimensions

process% 5ased on validation of

3elderSoloman1s 7ndex of Leaning Styles

that more students are active, sensing,

seFuential, and visual than reflective,

intuitive, verbal and global!9anKwanenberg, et al%, #$$ Kywno, #$$


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tutorial module% 5ased on the student1s

learning style and hisGher access device, the

system will present the course content

accordingly%

T,e control flo-s in t,e system

3rom the figure , the control flows

in the initial accessing the system are: a"

after a student logs into the system

successfully, it provides two options !default

learning style and ta+e the learning style

assessment" for the student% b" 7f the student

selects the default style, the system

populates the student learning style in

student model with the default style!activeGsensingGvisualGseFuential"%

Otherwise, the system provides the 7ndex of

Learning Style Fuestionnaire for the student%

After the student finishes the Fuestions and

submits the answers, the system analyses the

student1s learning style and populates hisGher

student model%

3rom then, the tutoring module will

combine the student1s leaning style

information and the information of access

device provided by access device analysis

module, and serve the student with course

content according to hisGher learning style

and access device%

Classification of st.dent learning styles

and t,eir implementation r.les

5ased on 3elderSilverman Learning

Style &heory, classification of student

learning styles and their implementation

rules are defined%

5ecause the system signs

corresponding default preferences for those

mild preferences of leaning style dimensions

and treats the moderate and strong

preference as the same, there are ; types of

combination of leaning style dimensions%

&hey are:

• activeGsensingGvisualGseFuential

• activeGsensingGvisualGglobal

• activeGsensingGverbalGseFuential

• activeGsensingGverbalGglobal

• activeGintuitiveGvisualGseFuential

• activeGintuitiveGvisualGglobal

• activeGintuitiveGverbalGseFuential

• activeGintuitiveGverbalGglobal

• reflectiveGsensingGvisualGseFuential

• reflectiveGsensingGvisualGglobal

• reflectiveGsensingGverbalGseFuential

• reflectiveGsensingGverbalGglobal

• reflectiveGintuitiveGvisualGseFuential

• reflectiveGintuitiveGvisualGglobal

• reflectiveGintuitiveGverbalGseFuential

• reflectiveGintuitiveGverbalGglobal

&hese different types of learning

styles are respectively implemented by the

combination of the following B elements%

&he implementation rules for each element

are discussed as follows%

Active: study in groups to discussing,

guess possible Fuestion and answer

them, find ways to do something with

learning concepts :

• .roviding discussion area

• eminding student to guess several possible

Fuestions

eflective: thin+ about Fuietly before

going ahead stop periodically to review


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what have been learning, writing

summaries :

• &hin+ before going ahead

• Stop periodically to review what

have been learning

• 6riting summaries

Sensing: facts, example following by

the exposition, handon wor+, practical

material :

• Example first and following by the

exposition

• andon wor+, such as practicing in

the applying environment

7ntuitive/ abstract, concept, theory,

exposition before example :

• Exposition first and following by the

example

• More concept and abstract

9isual: picture, graphs, diagram, flow

chart, schematics, demonstration,

concepts map, color notes, slides with

multimedia :

• More picture, graphs, diagram

• Animation demonstration

• /olor important concepts

9erbal: text, and audio

• text

• Audio

SeFuential: Step by step logically to

present material, outline the material in

order :

• Step by step to present material

• /onstrict lin+s

Dlobal: Large picture before detail, large

2ump, context of the sub2ect :

• Dive big picture of the course

• .rovide all the lin+s

; types of learning styles and their

corresponding implementation rules have

been finali-ed% 7n the next section, the design

and implementation of the prototype are

presented in details%

&he classification of student learning

styles and their implementation rules

reFuested for implementing the 3elder and

Silverman learning style theory have been

identified and discussed% 7n the following

section, the prototype that implements the

3elder and Silverman learning style theory is

discussed%

Implementation of t,e prototype

&he prototype uses the ..

programming tutorials material as course

content% Students1 profiles including the

learning style are stored in a MySL

database% &he prototype is developed by

using ML technologies, .., Apache web

server%

&o dynamically identify the access

device, a simple http header string

identification techniFue is used% Since the

.0A is limited at the si-e of screen and the

resource, it is not capable of displaying

multimedia as rich as ./% &herefore, two

sets of course content are developed for ./

based and .0A based%

&he figure # is the page that student

can select the default learning style or ta+ingthe leaning style assessment from ./s% 7f the

student selects the course area directly, the

system will populate the student model with

the default learning style and bring the

student to the course content according to

the learning style%

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Figure : a screens#ot t#at student can select

to go straig#t to course or ta$e t#e

assessment

&he figure < is a lesson for the

learning style

activeGsensingGvisualGseFuential% 7t provides

the example at the begging of the lesson !if the lesson has example"%

Student can enter the group discussion area

anytime through the menu H discussion area%

&he lesson is presented step by step with few

lin+s that student can 2ump% According to the

visual, the lesson is presented with picture

and highlighting the important concepts%

Figure %: a screens#ot of a lesson for leaning

st"le active&sensing&visual&sequential

CONCL!SION

7n this paper, we presented a

mechanism to fully model student1s learning

styles and fully adapt the course content to

individual learning style, based on the

3elderSilverman learning style theory, and

the access device% A prototype for ..

programming course was developed to

demonstrate the mechanism% Students can

perform study with course content that

nicely match their own learning style and

their access devices !./ or .0A"% 5yadapting the course content to the student1s

individual learning style and access device,

we expect students are able to learning more

efficiently and more effectively%

)ext step, we are going to conduct an

evaluation on the prototype to assess the

learning efficiency and effectiveness of this

system%

RE$ERENCES

5riggs, >% /% and Myers, 7% 5% !?@@"%

'"ers-riggs T"!e ndicator , .alo

Alto, /A: /onsulting .sychologist

.ress, 7nc%

5rusilovs+y, .% !#$$"% *da!tive#"!ermedia. Nser Modeling and Nser

Adapted 7nteraction, &en Iear

Anniversary 7ssue !Alfred >obsa,

ed%" !G#", B@$

/arver, /% A%, oward, % A% and Lane, 6% 0

!???"% +n#ancing tudent earning


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T#roug# "!ermedia Course/are

and ncor!oration of tudent

earning t"les, 7EEE &ransactions

on Education, vol% C#, no% , ???,

pp% olb, 0% 3ry, % !?@="% &owards an

applied theory of experiential

learning, in T#eories of grou!

!rocesses, ed% /%L% /opper London:

8ohn 6iley,


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