6
Collaborative Filtering for Teaching in a Learning 3.0 Environment *JUHAIDA ABDUL AZIZ, *ROSSENI DIN, PARILAH M.SHAH, RASHIDAH RAHAMAT, SITI ZURAIDA MANAF & MOHAMED AMIN EMBI Faculty of Education Universiti Kebangsaan Malaysia 43600 Bangi, Selangor MALAYSIA (*[email protected] , *[email protected] ) Abstract: - Collaborative Filtering for teaching in a learning 3.0 environment is an approach in which teachers or learners who share the same interest could start collaboration easily as they have the same background. Through collaborative filtering, the system highly recommends other teachers or learners who have performed the same tasks in a large number of times to become good collaborator. For instance, this collaborative filtering is a significant tool when a learner searches for peer help to solve a problem. The system identifies the process by matching the learner’s actions and the other learners. Thus, opens up more opportunities for educators to practise diverse teaching styles that integrate wide dimension of technologies elements to suit the learners’ needs. In this paper, results from a preliminary study provide useful information to portray the early perception and readiness of the teachers towards Collaborative Filtering (CF) for teaching in a 3.0 learning environment. Finally, it enables teachers to better understand new technology and use it collaboratively to integrate technology into Malaysian education for learners’ benefit as well. Key-Words: - Collaborative filtering, Web technologies in education, semantic Web in education, teachers’ perceptions and readiness, teaching and learning in 3.0 environment 1 Introduction With the massive growth in the use of websites on social activities, it is a novel task to consider integrating the activities for the benefit of teaching and learning. Web services, namely wikis, blogs, discussion boards and social networking websites illustrate the current trend of diverse teaching style that uses the integration of collaborative exploration and information of academic environments. The recent research on collaborative filtering in teaching and learning has gained its steady momentum especially in web education. Lane and Yamashiro [1] in their findings on the survey done on assessing learning and scholarly technologies among selected universities in the United States, stated that despite high interest of students use of technologies for their personal lives, namely for communication and entertainment, they showed intention to learn to use the technologies for the sake of learning for instance, discussion boards, electronic homework submission, or even database searching tools initially in their courses. Faculty focus groups were considered to have a considerable desire to participate in collegial discussions on teaching technology and share information collaboratively with their colleagues. The possible educational benefits of social websites related to the teaching and learning in Web 3.0 underlying the Web 2.0 technologies have triggered the attention of the educators [2]. To date, Web 3.0 education triggers the new digital access to learning environment in which learner takes control and manages his/her own learning [3]. 2 What is Web 3.0 Teaching and Learning? The current trends and the future of learning with the Web education is moving towards a better, smarter, faster, richer and even more complex learning environment [4]. Learning virtually using the Internet and the websites is an active process in which Web 3.0 or known as Semantic Web serves as the personal assistance for teachers to determine whatever is desired and will delivered according to the preferred channel [5]. Web 3.0 technologies offer higher information of acquisition as they are equipped with smart intelligent agents that searchers the right content and subject matter to suit the users’ needs. In addition, 3.0 environment does correlate with successful, effective for teaching and learning. 2.1 What Is Collaborative Filtering (CF)? Recent Researches in E-Activities ISBN: 978-1-61804-048-0 83

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Collaborative Filtering for Teaching in a

Learning 3.0 Environment *JUHAIDA ABDUL AZIZ, *ROSSENI DIN, PARILAH M.SHAH, RASHIDAH RAHAMAT,

SITI ZURAIDA MANAF & MOHAMED AMIN EMBI

Faculty of Education

Universiti Kebangsaan Malaysia

43600 Bangi, Selangor

MALAYSIA

(*[email protected], *[email protected])

Abstract: - Collaborative Filtering for teaching in a learning 3.0 environment is an approach in which teachers

or learners who share the same interest could start collaboration easily as they have the same background.

Through collaborative filtering, the system highly recommends other teachers or learners who have performed

the same tasks in a large number of times to become good collaborator. For instance, this collaborative

filtering is a significant tool when a learner searches for peer help to solve a problem. The system identifies the

process by matching the learner’s actions and the other learners. Thus, opens up more opportunities for

educators to practise diverse teaching styles that integrate wide dimension of technologies elements to suit the

learners’ needs. In this paper, results from a preliminary study provide useful information to portray the early

perception and readiness of the teachers towards Collaborative Filtering (CF) for teaching in a 3.0 learning

environment. Finally, it enables teachers to better understand new technology and use it collaboratively to

integrate technology into Malaysian education for learners’ benefit as well.

Key-Words: - Collaborative filtering, Web technologies in education, semantic Web in education, teachers’

perceptions and readiness, teaching and learning in 3.0 environment

1 Introduction With the massive growth in the use of websites on

social activities, it is a novel task to consider

integrating the activities for the benefit of teaching

and learning. Web services, namely wikis, blogs,

discussion boards and social networking websites

illustrate the current trend of diverse teaching style

that uses the integration of collaborative

exploration and information of academic

environments. The recent research on collaborative

filtering in teaching and learning has gained its

steady momentum especially in web education.

Lane and Yamashiro [1] in their findings on the

survey done on assessing learning and scholarly

technologies among selected universities in the

United States, stated that despite high interest of

students use of technologies for their personal lives,

namely for communication and entertainment, they

showed intention to learn to use the technologies

for the sake of learning for instance, discussion

boards, electronic homework submission, or even

database searching tools initially in their courses.

Faculty focus groups were considered to have a

considerable desire to participate in collegial

discussions on teaching technology and share

information collaboratively with their colleagues.

The possible educational benefits of social websites

related to the teaching and learning in Web 3.0

underlying the Web 2.0 technologies have triggered

the attention of the educators [2]. To date, Web

3.0 education triggers the new digital access to

learning environment in which learner takes control

and manages his/her own learning [3].

2 What is Web 3.0 Teaching and

Learning? The current trends and the future of learning with

the Web education is moving towards a better,

smarter, faster, richer and even more complex

learning environment [4]. Learning virtually using

the Internet and the websites is an active process in

which Web 3.0 or known as Semantic Web serves

as the personal assistance for teachers to determine

whatever is desired and will delivered according to

the preferred channel [5]. Web 3.0 technologies

offer higher information of acquisition as they are

equipped with smart intelligent agents that

searchers the right content and subject matter to suit

the users’ needs. In addition, 3.0 environment does

correlate with successful, effective for teaching and

learning.

2.1 What Is Collaborative Filtering (CF)?

Recent Researches in E-Activities

ISBN: 978-1-61804-048-0 83

Collaborative Filtering (CF) is a novel approach

that relies on the prediction of the similarity of the

items used according to the users’ preferences [6].

People with similar taste tend to have similar

preferences. Hence, it can be a good indicator for

the item to be rated personally. Meanwhile, CF can

contribute to positive improvement in choosing the

right information as it takes into consideration of

what being preferred by others to predict

preferences. In Malaysia alone for example, a

moderator of a virtual discussion group like in The

University Kebangsaan Malaysia; Faculty of

Education Graduate Association deployed the

intelligent filter in sharing the information the

users desired. CF is coined as registered users

review books at the Amazon.com. Basically, the

mechanism embedded within the CF is a system in

which such preferences of a large group of people

are registered according to a similarity metric; a

subgroup of people is selected whose preferences

are similar to the preferences of the person who

seeks advice; an average of the preferences for that

subgroup is considerably weighted and

recommendation from the output results is taken

into account as the options to fulfil the preferences

of the users. This concept can be applied in social

filtering and the adaptive filtering as well [6][7].

2.2 The E-learning Recommender Systems

(ERS) To suit the users’ preferences and interests, the E-

learning Recommender System (ERS) provides

users with personalized suggestions by matching to

users’ profiles or groups. The systems require

“intelligent” interface to determine the interest of

the user and use the input to make suggestions

accordingly [6]. Others consider the system as

trying to propose to learners based on their previous

actions. Those recommendations of options could

be on any on-line activities or simply Web

resources [8].

2.3 Adaptive Hypermedia Systems (AHS)

The presentation and navigation assistance of the

systems are personalized according to users’ needs.

Bhosale [9] stated that a user model is coined to the

user requirements and a content model is utilized to

represent the content. User can select the most

appropriate content to be presented using a set of

algorithms while interacting to the Adaptive

Hypermedia System (AHS). To support,

Brusilovsky [10] claimed that the AHS is an

alternative to the traditional of “one-size-fits-all”

and the preferences and needs of the users are

taken into account throughout the process

administered.

2.4 Recommendations for Teaching and

Learning in Malaysian Context In relation to the related literatures on the aspects of

the Web, the CF, the ERS and the AHS, some big

questions arise: Are these aspects fit into the

Malaysian educational context? Are the teachers

ready to implement these aspects in their teaching

approach? Wheeler [11] argued that some aspects

such as the users’ choice to accept or deny the use

of Web 3.0; the teachers’ willingness to accept the

technologies; the students’ readiness to be

autonomous learners and mind setting towards 3.0

learning environment as well as the success and

failure of Web 2.0, do need to be taken into

consideration. Again, Wheeler [12] pointed at the

pedagogical level saying that, Web Enhanced

Learning (WEL) and other technologies are the

indicators that have potential in enhancing

approaches to transform the quality of learning.

WEL enables students to participate directly, in

control and be responsible towards their own

learning processes. They are now more engaged

deeply and actively with their learning using WEL

tools collaboratively.

Malaysian educational system is exam-

oriented. Teachers put much emphasis for their

students to achieve highly in the national

examinations that they often use the chalk and talk

approach [13][14]. Textbooks and printed

materials would be the main instructional media

use since these are the materials which they

consider sufficient to enable the students to perform

with well. Malaysians need a fresh and new

philosophy in their approach to exams.

Nevertheless, the Malaysian Ministry of Education

is shifting to new paradigm to ensure the school-

based assessment is materialized in line with other

countries like the United States, Britain, Germany,

Japan and Finland [14].

Hence as a first step towards implementing

CF for teaching in a 3.0 learning environment, it is

better to have information about teachers’

perception on the matter. Teachers’ perception may

portray the early readiness towards CF for teaching in 3.0 learning environment. Thus, the purpose of

this preliminary study is to investigate the validity

and reliability of the items which aim to measure

the teachers’ readiness towards Web 3.0. The

objectives of the study are: (i) to identify

respondents’ perception and readiness to integrate

CF in the learning process, (ii) to identify reliability

of the CF instrument, (iii) to identify the person

Recent Researches in E-Activities

ISBN: 978-1-61804-048-0 84

mapping and (iv) item mapping of CF instrument.

In order to fulfil those objectives mentioned,

Rasch Measurement Model was employed with the

application of WINSTEPS to test the reliability of

the instrument and subsequently examined its

validity.

3 Research Methodology The preliminary study is based on the conceptual

framework illustrated (Fig 1). There are four

aspects investigated in the study.

3.1 Conceptual Framework The four aspects in the conceptual framework

investigated in the study (Fig.1) are:

(ii) Teacher context-awareness;

cognition; (iv) Teacher social skills. The

integrations of four learning theories and methods

are defined in every section respectively namely:

Minimalist Learning Theory (to study Web 3.0

technology), Collaborative Learning (to discover

teacher social skills), Situated Learning

investigate the teacher context-awareness) and

Multimodal Learning Theory (to study teacher

cognition). The final goal of the study

the intersections is generated as “

Filtering” (supported by Recommender system and

Hypermedia system) illustrated at the bottom of

Figure 1.

3.2 Pilot Survey The preliminary study is a survey conducted on 30

teachers from a local secondary

Cyberjaya, Malaysia. The respondents were

conveniently chosen and they

completed a set of questionnaire. The sample size is

ample and adequate in Rasch measurement model

in providing 95% confidence level on the analysis

and prediction of the data for the study

administered [19-22]. The survey consisted of a 5

point Likert scale of 25 items and 5 short answers

questions. The questionnaire consisted of two

sections. Section A is for demographic profile of

respondents and Section B is for the co

surveyed. Section B was designed based on three

constructs which are: (i) Context

perceptions and readiness of the respondents

towards the use of Web 2.0 technologies, (ii)

Multimodal learning skills; and (iii) Learning styl

Those constructs carried 8 items respectively

except for construct (iii) which carried 9 items

followed by 5 items in short answers questions.

of CF instrument.

In order to fulfil those objectives mentioned,

odel was employed with the

application of WINSTEPS to test the reliability of

and subsequently examined its’

The preliminary study is based on the conceptual

). There are four

conceptual framework

investigated in the study (Fig.1) are: (i) Web 3.0;

awareness; (iii) Teacher

Teacher social skills. The

integrations of four learning theories and methods

are defined in every section respectively namely:

heory (to study Web 3.0

earning (to discover

earning Theory (to

awareness) and

heory (to study teacher

cognition). The final goal of the study from all of

as “Collaborative

ecommender system and

illustrated at the bottom of

conducted on 30

teachers from a local secondary school in

Cyberjaya, Malaysia. The respondents were

conveniently chosen and they anonymously

completed a set of questionnaire. The sample size is

ample and adequate in Rasch measurement model

in providing 95% confidence level on the analysis

data for the study

The survey consisted of a 5-

point Likert scale of 25 items and 5 short answers

questions. The questionnaire consisted of two

sections. Section A is for demographic profile of

respondents and Section B is for the constructs

surveyed. Section B was designed based on three

which are: (i) Context-awareness;

perceptions and readiness of the respondents

towards the use of Web 2.0 technologies, (ii)

and (iii) Learning style.

Those constructs carried 8 items respectively

carried 9 items

followed by 5 items in short answers questions.

These constructs were analyzed using WINSTEPS

for Rasch Measurement Model.

Fig. 1: Conceptual framework

4 Results & DiscussionsThe survey was done using

consisting of 25 questions

responses and 5 short answers

A, responses were yielded from the demographics

profiling of respondents’

3.0 technologies. The demographics showed a

relatively equal distribu

selected sample of 26 female respondents which

was equivalent to 80 percent of the total

involved in the survey

consisted of male respondents.

respondents did not have significant impact on the

findings gathered. Most

aged from 21 to 40 years old (

remaining respondents were aged above

old. For the Internet usage

technologies, thirteen of the respondents

used the Internet daily. Nine

(30%) use it weekly while the rest

respondents (10%) used it once in a while and

of them (16.7%) used it only when necessary.

Section B, investigated

readiness of the teachers o

approach. From the finding

mutually agreed that active

activities motivated them in collaborative teaching

and learning environment.

inquired on their usage and

social networking sites, such as

wikis, blog, podcast and others.

respondents agreed to have

and considered themselves

perception and readiness of

the Internet devices. Half of the respondents

Web 3.0 technology: minimalist learning

theory

Teacher social skills : collaborative

learning

Teacher contextawareness:

learning theory

Teacher cognition: multimodal

learning theory

COLLABORATIVE FILTERING: Recommender System &

Hypermedia system

These constructs were analyzed using WINSTEPS

Rasch Measurement Model.

: Conceptual framework

& Discussions The survey was done using a set of questionnaire

consisting of 25 questions of 5-point Likert scaled

short answers questions. In section

yielded from the demographics

experience in using Web

The demographics showed a non-

relatively equal distribution of conveniently

f 26 female respondents which

percent of the total 30 teachers

involved in the survey; while the remainder

consisted of male respondents. The gender of the

not have significant impact on the

Most of the respondents were

years old (66.7%), while the

remaining respondents were aged above 40 years

nternet usage of the Web 2.0

of the respondents (43.3%)

nternet daily. Nine of the respondents

while the rest, i.e. three of the

respondents (10%) used it once in a while and five

of them (16.7%) used it only when necessary.

on the perceptions and

readiness of the teachers on the collaborative

approach. From the findings, the respondents

mutually agreed that active participation in group

them in collaborative teaching

and learning environment. Respondents were also

usage and participation in the

such as discussion boards,

ikis, blog, podcast and others. Most of the

have been involved actively

themselves to have positive

of the learning style with

Half of the respondents were

Web 3.0 technology: minimalist learning

theory

Teacher social skills collaborative

learning

Teacher context-awareness: situated

learning theory

Teacher cognition: multimodal

learning theory

COLLABORATIVE FILTERING: Recommender System &

Hypermedia system

Recent Researches in E-Activities

ISBN: 978-1-61804-048-0 85

considered skilful in manoeuvring

technologies in their teaching experience.

their future perception of learning with

devices, the majority of the respondents

agreed (40%) and agreed (60%) to be

interested to learn the devices in the future.

implied that the collaborative approach with the

Web technologies do have positive impact in their

teaching and learning and capable to improve their

assessment and sense of competiveness

education as well.

A bar chart illustrates the percentage of the

respondents in their use of the

approach in their teaching (Fig.2).

that there were nineteen respondents

agreed practicing the collaborative approach in

their teaching. This is the highest degree of

agreement in utilizing the method intended for the

study. Four respondents (20%) strongly

follow the same course. In contrast, there were

respondents (13%) who disagreed

collaborative approach in their teaching and only

one respondent strongly disagreed employing this

approach. This was the lowest degree of

disagreement towards practicing the collaborative

approach in the teaching education.

Fig.2: Respondents’ Use of CF in Teaching

As shown in Table 1, the findings revealed

item reliability index was 0.75 with a separation

index of 1.72. After discussion with expert

decided to be acceptable since this is a pilot part of

the work. In relation, reliability of item

interpreted on a 0 to 1 scale the same way as

Cronbach’s alpha is interpreted [17][

reliability index indicated the replicability of item

placements used in the study conducted if ever

these same items were to be given

respondents from purposive samplings

the same way. Thus, if the reliability of item shows

high index measurement, it can be inferred that the

items used in the study have generated a line of

13%

64%

20%

3%

manoeuvring the Web

technologies in their teaching experience. As for

their future perception of learning with ubiquities

devices, the majority of the respondents strongly

%) to be involved and

devices in the future. They

implied that the collaborative approach with the

eb technologies do have positive impact in their

capable to improve their

assessment and sense of competiveness in

the percentage of the

collaborative

It was found

that there were nineteen respondents (64%) who

the collaborative approach in

This is the highest degree of

agreement in utilizing the method intended for the

strongly agreed to

there were six

practicing the

collaborative approach in their teaching and only

employing this

was the lowest degree of

the collaborative

in Teaching

As shown in Table 1, the findings revealed that the

with a separation

experts, it was

since this is a pilot part of

eliability of item can be

interpreted on a 0 to 1 scale the same way as

[18]. The item

the replicability of item

placements used in the study conducted if ever

these same items were to be given to other

purposive samplings that behave

the same way. Thus, if the reliability of item shows

high index measurement, it can be inferred that the

items used in the study have generated a line of

inquiry in which some of the items are cons

more difficult and some of them are relatively

easier. Hence, consistency of the inference is much

to be expected in the findings from the study

conducted [17].

Table 1: Summary Statistics and Item Reliability

Figure 3 shows output analysis from WINSTEPS

that illustrates the four levels of the agreement and

disagreement of the respondents in the study. The

presentation of the data shows both figures of the

distribution of respondents along the logit scale on

the right side and the sample of items on the left

side. The relative distribution of the

Fig. 3: Wright Person

-----------------------------------------------

ITEM - MAP - PERSON

<rare>|<more>

1 +

|

T|

X |T

X | r23 2 2 1 1 1 1

1 1

XX |S r10 2 2 1 1 1 2

1 1

XX S| r20 2 3 1 3 1 2

1 3 r28 2 3 1 3 1 4

XX | r11 2 2 1 1 1 2

1 1 r14 1 4 1 4 1 1

r5 2 5 1 4 1 1

1 1

X |M r12 1 3 1 3 1 1

1 1 r2 2 4 1 5 1 1

r21 2 3 1 3 1 2

1 2 r24 2 5 1 5 1 3

r6 2 2 1 1 1 1

X | r4 2 3 1 3 1 4

0 X M+ r1 2 2 1 1 1 4

1 2 r16 2 2 1 1 1 4

r27 2 2 1 1 1 2

1 2 r3 1 4 1 5 1 1

XXX |S

XXXXX | r17 2 4 1 5 1 4

XX |

XX S|T r8 2 2 1 1 1 2

| r7 2 3 1 2 1 1

|

XX | r18 2 4 1 5 1 3

T|

|

-1 +

3%

inquiry in which some of the items are considered

more difficult and some of them are relatively

easier. Hence, consistency of the inference is much

to be expected in the findings from the study

Table 1: Summary Statistics and Item Reliability

Figure 3 shows output analysis from WINSTEPS

that illustrates the four levels of the agreement and

disagreement of the respondents in the study. The

ation of the data shows both figures of the

distribution of respondents along the logit scale on

the right side and the sample of items on the left

side. The relative distribution of the respondents

Fig. 3: Wright Person-Item

-----------------------------------------------

2 2 1 1 1 1 r30 1 2 1 1

2 2 1 1 1 2 r26 1 5 1 5

2 3 1 3 1 2 r25 2 5 1 5

2 2 1 1 1 2 r13 1 3 1 3

2 5 1 4 1 1 r9 2 2 1 1

1 3 1 3 1 1 r19 2 3 1 3

2 3 1 3 1 2 r22 2 2 1 1

2 2 1 1 1 1

2 3 1 3 1 4

2 2 1 1 1 4 r15 2 4 1 5

2 2 1 1 1 2 r29 2 3 1 3

2 4 1 5 1 4

2 2 1 1 1 2

2 3 1 2 1 1

2 4 1 5 1 3

6 Respondents disagreed to

practice the collaborative

approach in teaching.

19 Respondents agreed and practiced the

collaborative approach in teaching.

4 Respondents strongly agreed

and practiced the collaborative

approach in teaching.

1 Respondents strongly disagreed to

practice the collaborative approach in

teaching.

Recent Researches in E-Activities

ISBN: 978-1-61804-048-0 86

<frequ>|<less>

who practiced collaborative teaching hanged

considerably and can be detected between the logit

scale of 0 and 1. In other words, nineteen of the

respondents/ teachers (64%) agreed to practice

collaborative approach in their teaching. Four

respondents were detected along logit scale 1 in

which they strongly agreed to practice the

collaborative approach in their teaching. Contrary

to that, seven respondents were detected to hang

along logit scale of 0 and -1 in which 6 of them

disagreed and one strongly disagreed to practice the

collaborative approach in their teaching

respectively. Hence, it can be concluded that 23

out of 30 teachers in the pilot study conducted had

given mutual agreement on the collaborative

approach in their teaching and learning

environment that contributed to their positive

perceptions and readiness on the usage of Web 3.0

technologies of the ubiquitous devices in future.

Figure 4 illustrates the 25 items of the

instrument used for collaborative approach in the

study. Those respondents that practiced the highest

degree of collaborative approach in their teaching

were shown on the top left side of the item map that

can be captured along the logit scale of 0 and 1.

Fig.4: Item Map

Item Map

INPUT: 30 PERSON 25 ITEM MEASURED: 30

PERSON 25 ITEM 116 CATS WINSTEPS 3.69.1.11

------------------------------------------

PERSON - MAP - ITEM

<more>|<rare>

1 +

|

|T

T| P2

XX | LS1

XX S| IS6 IS8

XXX |S IS4 P4

XXXXX | IS1 IS11

XXXXXXX M| P5

X | IS7

0 XXXXXX +M P7

S| IS12 LS2 LS4

X | IS10 LS3 LS5 P1

P8

| IS3 IS5

X T|S IS9 P3

X |

|

X | IS2 P6

|T

|

-1 +

<less>|<frequ>

Meanwhile, the top right side of the item map

represented the difficult items used in the

questionnaire that measured the construct of

collaborative approach in teaching that strongly

agreed by the respondents. On the contrary, the

easy items to measure the disagreement of using

collaborative approach in teaching was revealed at

the bottom right side of the item map. The lowest

degree of collaborative approach used was shown

at the side mentioned hanged along the logit scale

of 0 and -1. The 2 M detected on the logit scale

indicated the mean index of the respondents (on the

left side) and the items (on the right side)

respectively which hanged along between logit

scale of 0 and 1.

6 Conclusion The primary objective for this study was to increase

the awareness of various Internet-based resources

for educators/ teachers. From the findings, it was

possible to say that teachers perceived an increase

in the awareness of such resources and showed

positive perceptions of the pedagogical benefits of

Web 3.0 technologies in teaching and learning. Yet,

it was difficult to assert that this activity was more

beneficial than others in accomplishing this goal.

Nevertheless, teachers, educators or any

laymen who have interest in technology, need to be

involved in the buzz of digital and education. It is

high time to have rich conversation, conduct active

teaching and learning research, but the

collaborative intelligent filtering need to play as the

significant role to ensure technology 3.0 won’t do

any harm to the users. Through this, it is hoped that

the Malaysian National Philosophy could be

materialised. Thus, as teachers or educators

progress, they need to discuss and scrutinise their

own practices, and make explicit their pedagogies

that can meet the current demands. Apart from that,

with the reliability index of 0.75 found for the items

measured, though it is adequate, it is strongly

suggested for this questionnaire to be improvised in

order to be used for more data of larger number of

respondents for future study.

References:

Difficult items = Item measures

collaborative approach in

teaching that strongly agreed

by the respondents.

Respondents

/ teachers

who

practiced

collaborative

teaching.

Respondents

/ teachers

who used the

least

collaborative

approach in

teaching.

Easy items= Item measures

collaborative approach in

teaching that strongly

disagreed by the respondents.

Recent Researches in E-Activities

ISBN: 978-1-61804-048-0 87

[1] Cara Lane and Greg Yamashiro,

Learning and ScholarlyTechnologies:

Lessons from an Institutional

EDUCAUSE Quarterly, vol. 31, no. 3

(July–September 2008)

http://www.educause.edu/EDUCAUSE+Qu

arterly/EDUCAUSEquarterlyMagazineVol

um/AssessingLearningandScholarlyT/1630

98

[2] Jason T. Abbitt.(2007). Exploring the

Educational Possibilities for a User

Driven Social Content System in an

Undergraduate Course. Merlot Journal of

Online Learning, Vol.3, No.4, Dec2007.

Accessed on 23 June 2011.

[3] Derek Keats. (2007).Information &

Communication Services, The University of

the Western Cape,P. Bag X17, Bellville

7535, [email protected].

[4] Smith, M.K (2011).Teaching in the Web

3.0World.April4,2011 Posted

in News, semantic, Technology

http://taxodiary.com/2011/04/teaching

the-web-3-0- world/

[5] Bingham, T. (2011). ASTD (the American

Society for Training & Development) and

their article, “Better, Smarter, Faster : Web

3.0 and the Future of Learning

http://www.astd.org/TD/Archives/2011/Apr

/Free/Apr11_Better+Smarter+Faster.htm

[6] Kangas, S. (2002). Collaborative filtering

and recommendation systems.VTT

Information Technology.Findland.

http://www.vtt.fi/inf/julkaisut/muut/2002/c

ollaborativefiltering.pdf

[7] Shardanand U. and Maes (1995),

information filtering: Algorithms for

automating "word of mouth"

of CHI'95 -- Human Factors in Computing

Systems, 210-217

[8] Osmar R. Zaíane, (2002)."

Recommender Agent for e Learning

Systems," icce, pp.55, 2002.International

Conference on Computers in Education

(ICCE'02).

[9] Bhosale, D. (2006). Alco Zone: An

Adaptive Hypermedia Based Personalized

Alcohol Education. Blacksburg, Virginia.

[10] Brusilovsky, P. (2001) “Adaptive

Hypermedia”, User Modelling and User

Adapted Interaction, Vol.11, pp. 87

[11] Wheeler, S. (2009).Learning with

edgeless

Cara Lane and Greg Yamashiro, Assessing

ScholarlyTechnologies:

Lessons from an Institutional Survey, in

vol. 31, no. 3

http://www.educause.edu/EDUCAUSE+Qu

arterly/EDUCAUSEquarterlyMagazineVol

um/AssessingLearningandScholarlyT/1630

Exploring the

Educational Possibilities for a User-

Driven Social Content System in an

Merlot Journal of

Online Learning, Vol.3, No.4, Dec2007.

Information &

The University of

the Western Cape,P. Bag X17, Bellville

Teaching in the Web

Posted

Technology.

http://taxodiary.com/2011/04/teaching-in-

ASTD (the American

Society for Training & Development) and

Better, Smarter, Faster : Web

3.0 and the Future of Learning.”

http://www.astd.org/TD/Archives/2011/Apr

/Free/Apr11_Better+Smarter+Faster.htm

[6] Kangas, S. (2002). Collaborative filtering

and recommendation systems.VTT

Information Technology.Findland.

http://www.vtt.fi/inf/julkaisut/muut/2002/c

Shardanand U. and Maes (1995), Social

information filtering: Algorithms for

", Proceedings

Human Factors in Computing

Osmar R. Zaíane, (2002)."Building a

Recommender Agent for e Learning

," icce, pp.55, 2002.International

Conference on Computers in Education

, D. (2006). Alco Zone: An

Adaptive Hypermedia Based Personalized

Alcohol Education. Blacksburg, Virginia.

Adaptive

User Modelling and User-

Vol.11, pp. 87-110.

2009).Learning with ‘e’: The

University?

http://stevewheeler.blogspot.com/2009/06/e

dgeless-university.html

[12] Wheeler S. (2010). Teacher resistance to

new technologies:

Enhanced Learning can be overcome. In

G. Trentin and M. Repetto (Eds) Faculty

Training for Web

York, NY: Nova Science.

[13]

http://blog.thestar.com.my/permalink.asp?i

d=6291.Accessed

26June2011.

[14]

http://pgoh13.com/exam_revamp.html

essed on 26June2011.

[15] Malone, T., Grant, K., Turbak, F., Brobst,

S., & Cohen, M. (1987). Intelligent

information sharing systems.

Communications of the ACM,

[16] Linacre, J. M. (2006). WINS

measurement computer

Winsteps.com.

[17] Bond, T.G. & Fox, C.M. 2007.

The Rasch Model: Fundamental

Measurement in the Human Sciences.

Lawrence Erlbaum Associates

[18] Rosseni Din. 2010. Development

andValidation of an Integrated Meaningful

hybrid e- Training (I

science: Theoretical

Design and Development Approach

Universiti Kebangsaan Malaysia.

[19] J.M.Linacre, “Sample size and item

calibaration stability,”

Transcations, vol.7, p.328, 1994.

[20] I.I. Zoubir, “Bootstrap method in signal

processing, “IEEE Signal Processing

Magazine, vol.24, pp. 7

[21] K.E.Agho, “The Bootstrap method of Rasch

conditional item difficulty estimation,”

Rasch Measurement Transction

2005.

[22] Z.Sohaimi, A.A.Azrilah, “Online

Information Satisfation: a Rasch Model

Measurement of Information Managment

Experience within the Malaysian

Agricultural Extension Services, in

Fifth Internationl Joint Co

IMS and IDC.

http://stevewheeler.blogspot.com/2009/06/e

university.html.

Wheeler S. (2010). Teacher resistance to

new technologies: How barriers to Web

Enhanced Learning can be overcome. In

G. Trentin and M. Repetto (Eds) Faculty

Enhanced Learning. New

York, NY: Nova Science.

http://blog.thestar.com.my/permalink.asp?i

on

http://pgoh13.com/exam_revamp.html.Acc

essed on 26June2011.

Malone, T., Grant, K., Turbak, F., Brobst,

S., & Cohen, M. (1987). Intelligent

information sharing systems.

Communications of the ACM, 30(5).

Linacre, J. M. (2006). WINSTEPS: Rasch

measurement computer program. Chicago:

Bond, T.G. & Fox, C.M. 2007. Applying

The Rasch Model: Fundamental

Measurement in the Human Sciences. N.J:

Lawrence Erlbaum Associates Publishers.

Rosseni Din. 2010. Development

of an Integrated Meaningful

Training (I-Met) for Computer

science: Theoretical-Empirical Based

Design and Development Approach:

Universiti Kebangsaan Malaysia.

J.M.Linacre, “Sample size and item

calibaration stability,” Rasch Measurement

, vol.7, p.328, 1994.

I.I. Zoubir, “Bootstrap method in signal

IEEE Signal Processing

vol.24, pp. 7-8, July 2007.

K.E.Agho, “The Bootstrap method of Rasch

conditional item difficulty estimation,”

sch Measurement Transction, vol.19,

Z.Sohaimi, A.A.Azrilah, “Online

Information Satisfation: a Rasch Model

Measurement of Information Managment

Experience within the Malaysian

Agricultural Extension Services, in 2009

Fifth Internationl Joint Conference on INC,

Recent Researches in E-Activities

ISBN: 978-1-61804-048-0 88