PEDAGOGICAL FRAMEWORK TO IMPROVE THE QUALITY

OF LEARNING OBJECTS IN COLLABORATIVE

E-LEARNING SYSTEMS

Ali Alharbi, Frans Henskens and Michael Hannaford

School of Electrical Engineering and Computer Science, The University of Newcastle, Newcastle, Australia

Keywords:

Collaborative e-learning systems, Learning objects, Self-regulated learning, Learning style.

Abstract:

Learning objects are the building blocks of the learning resources in any e-learning system. In collaborative

e-learning systems, the learning objects are produced and consumed by different learners. Finding high-

quality learning objects that are related to a learner’s proﬁle is one of the major problems that may cause

e-learning systems to fail. This is especially true as the number of learning objects in the learning environment

increases. This paper presents a pedagogical framework to improve learners’ interactions with learning objects

in collaborative e-learning systems. The proposed framework is based on the theory of learning styles and the

cyclical model of self-regulated learning. By incorporating the experiences and contributions of different

learners with the available learning objects, the quality of the learning objects in the system can be increased.

Learners’ awareness of their preferred learning style can help them to ﬁnd appropriate learning objects. This

can be achieved by the help of the e-learning system that can generate a recommendation list of appropriate

learning objects based on the learner’s learning style.

1 INTRODUCTION

A collaborative e-learning system provides an envi-

ronment where people who share common interests

collaborate together by creating and sharing knowl-

edge to provide the opportunities for everybody to

learn (Wang et al., 2005).

The dominant education paradigm has shifted

from the traditional teacher-centred to one where the

student plays a more central role. This approach

is based on the constructivism theory of education

where the emphasis is placed on the learner to dis-

cover and construct knowledge through active par-

ticipation (Glasersfeld, 2009). Social Constructivism

(Pritchard and Woollard, 2010) is an extension of con-

structivism theory where the focus is placed on the

role the environment plays in helping the learner con-

struct knowledge. According to this theory, learn-

ing is a social process and, rather than only being

passively received or constructed by each individual

learner, knowledge is also the result of engaging in so-

cial activities. This view of learning is also related to

some contemporary theories of education such as So-

cial Cognitive Theory (SCT) (Bandura, 2001). SCT

views human behaviour as being inﬂuenced continu-

ously by the social and physical environment.

Learner-centred education paradigm places more

responsibilities on learners to control and regulate

their personal learning process in a collaborative so-

cial environment. In this new education paradigm, our

vision of the learning resources should be changed,

so that more emphasis is placed on learner-generated

resources, and in this case the learner is no longer a

passive consumer of knowledge but active as a con-

sumer and producer of knowledge and learning re-

sources (McLoughlin and Lee, 2010).

In e-learning systems, the building blocks of

learning resources are referred to as learning objects.

A learning object can be deﬁned as any digital re-

source that has a pedagogical objective and is in-

tended to be used and reused in different learning con-

texts (Sosteric and Hesemeier, 2002). Images, anima-

tions and simulations are all examples of learning ob-

jects. However, a learning object can also be an entire

web page that combines text, images, and other re-

sources to deliver a complete unit of learning.

In collaborative e-learning systems, learning ob-

jects are created to be shared and reused in different

contexts (Koohang, 2004). Having low-quality learn-

ing objects is one of the major problems that cause

353

Alharbi A., Henskens F. and Hannaford M..

PEDAGOGICAL FRAMEWORK TO IMPROVE THE QUALITY OF LEARNING OBJECTS IN COLLABORATIVE E-LEARNING SYSTEMS.

DOI: 10.5220/0003475803530358

In Proceedings of the 3rd International Conference on Computer Supported Education (CeLS-2011), pages 353-358

ISBN: 978-989-8425-50-8

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

e-learning systems to fail (Han et al., 2003). Another

problem is that it can be difﬁcult to ﬁnd learning ob-

jects related to a learner’s proﬁle (Shishehchi et al.,

2010). This is especially true as the number of learn-

ing objects in the learning environment increases.

This paper presents a pedagogical framework to

improve learners’ interactions with learning objects

in collaborative e-learning systems. The proposed

framework is based on the theory of learning styles

and the cyclical model of self-regulated learning. By

incorporating the experiences and contributions of

different learners with the available learning objects,

the quality of the learning objects in the system can

be increased. Learners’ awareness of their preferred

learning style can help them to ﬁnd appropriate learn-

ing objects. This can be achieved by the help of the

e-learning system that can generate a recommenda-

tion list of appropriate learning objects based on the

learner’s learning style.

A learner can then use different learning strategies

which can contribute to increase the quality of learn-

ing objects by providing different notes, comments,

summaries, examples, ratings or reﬂections associ-

ated with the same learning object.

This paper is organized as follows. Section 2

presents the theoretical background of this paper by

deﬁning and discussing the concepts of self-regulated

learning and learning styles. Section 3 presents the

proposed pedagogical framework for improving the

learning process in the collaborative e-learning sys-

tems based on the self-regulated learning and the

learning styles. Section 4 discusses some implications

of the proposed pedagogical framework on searching

and recommending of learning objects that are related

to different learning styles. Finally, section 5 presents

conclusions and proposals for future work.

2 THEORETICAL BACKGROUND

2.1 Self-Regulated Learning

Self-regulated learning (SRL), an educational ap-

proach inﬂuenced by the constructivism and social

views of learning, is an important area of research

in education and psychology. Self-regulated learning

can be deﬁned as “ self-generated thoughts, feelings

and actions that are planned and cyclically adapted

to the attainment of personal goals” (Zimmerman,

2000).

Basically, self-regulated learning refers to the

ability of the learners to understand and control

their learning process and environment. To achieve

this, learners have to specify their goals, select and

use appropriate strategies, and monitor their learn-

ing progress towards achieving their goals (Schunk,

1996). Students with the ability to self-regulate their

learning can have high academic achievement with

less effort (Pintrich, 2000).

Despite the fact that there are a variety of

self-regulated learning models, these models are

all similar to Zimmerman’s Cyclical Model of

Self-Regulated Learning. Zimmerman (Zimmer-

man, 2000) developed a model that represents self-

regulated learning as a process of three cyclical

phases (Figure 1): (1) forethought, (2) performance,

and (3) self-reﬂection.

Figure 1: SRL Cyclical Model.

Forethought phase involves processes that oc-

cur before learning including goal settings, previous

knowledge activation and strategic planning. Goal

setting is the process of determining the outcomes of

the learning task. Strategic planning involves the se-

lection of strategies and resources required for per-

forming the task and time planning.

Performance phase involves processes that oc-

cur during learning. This includes cognitive learn-

ing strategies students use to deal with the learning

material. Rehearsal, elaboration, organizational and

critical thinking strategies are examples of cognitive

strategies that have been reported to have positive im-

pact on the academic performance of students (Pin-

trich and De Groot, 1990). Rehearsal strategies are

the basic methods used by the learner to keep the in-

formation in the working memory, and involve strate-

gies such as note taking and repeating the learning

material. Elaboration strategies are methods used by

the learner to keep the information in the long-term

memory, and involve methods such as summarizing,

paraphrasing, relating new information to the exist-

ing knowledge of the learner and using examples and

analogies. Organizational strategies are methods used

by learners to link the important ideas of the learn-

ing materials such as creating concept maps. Re-

hearsal strategies are example of surface level pro-

cessing strategies which focus on memorizing of facts

and information retrieval, while elaboration and orga-

nizational strategies are deep level processing strate-

gies which focus on understanding the relationship

between learning material (Zusho et al., 2003).

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354

The performance phase involves also metacogni-

tive strategies the learners may use to monitor their

progress such as self-recording and self-questioning.

Self-recording is a technique used by learners to

record each learning activity and its results. Self-

questioning or testing is a strategy used by the learn-

ers to assess their understanding of the learning ma-

terial by performing a test to evaluate performance

against a predeﬁned goal or standard. During this

phase, the learner can use resource management

strategies such as searching for suitable learning re-

sources and seek help from other learners in the learn-

ing environment.

The phase of self-reﬂection involves processes

that follow the learning task including the learners’

perceptions of their performance and experience with

the learning material.

The self-regulated learning phases are cyclical;

feedback from previous phase is used to adjust the

next phase (Zimmerman, 2000).

2.2 Learning Style

Learning is a process whereby individuals acquire

new knowledge. Research indicated that students tend

to gather and process information in different ways.

These differences are known as learning styles. Many

deﬁnitions can be found in the literature for the term

learning style. The learning style can be deﬁned

as “a particular way in which an individual learns”

(Pritchard, 2009). Shaw and Marlow (Shaw and Mar-

low, 1999) describe the learning style as “a distinctive

and habitual manner of acquiring knowledge, skills

or attitudes through study or experience”. One of the

most comprehensive deﬁnition of the learning style is

the one provided by Keefe (Keefe, 1988) who deﬁned

learning style as “ the characteristic cognitive, affec-

tive and psychological behaviors that serve as relativ-

ity stable indicators of how learners perceive, interact

with and respond to the learning environment”.

Learning styles can be identiﬁed using different

learning style models. Felder and Silverman (Felder

and Silverman, 1988; Felder and Spurlin, 2005) de-

veloped a model to identify students’ learning styles

especially in science and engineering education. This

model consists of four dimensions:

2.2.1 Sensing/Intuitive

This dimension describes the type of information an

individual preferentially perceives. Sensing learners

prefer concrete contents and facts and oriented toward

the details whereas intuitive learners prefer abstract

concept, theories and mathematical formulas and dis-

like details. Sensing learners tend to solve problems

using well-established methods and dislike complica-

tions. Intuitive learners like innovations, new ideas of

solving problems and dislike repetition.

2.2.2 Visual/Verbal

This dimension describes the channel through which

the learner most effectively perceives information.

Visual learners prefer learning through visual medium

such as pictures, charts and diagrams whereas verbal

learners prefer spoken or written materials and expla-

nations.

2.2.3 Active/Reﬂective

This dimension describes how the learner processes

information. Active learners prefer learning in groups

and they tend to try things out whereas reﬂective

learners prefer working alone and think about how

things work before try them.

2.2.4 Sequential/Global

This dimension describes how the learner progresses

towards understanding the information. Sequential

learners prefer following a logical, step by step linear

approach whereas global learners prefer absorbing the

learning materials randomly in big jumps without fol-

lowing step by step approach until grasping the full

picture.

3 PROPOSED PEDAGOGICAL

FRAMEWORK FOR

COLLABORATIVE

E-LEARNING SYSTEMS

The framework proposed in this paper is to en-

hance the educational effectiveness of the collabora-

tive learning environment based on the cyclical model

of self-regulated learning and learning style that are

well-grounded in the educational theories. The self-

regulated learning cyclical model (section 2.1) is ap-

plied to provide an alternative and effective design for

collaborative learning environment. The new peda-

gogical framework takes into consideration the learn-

ing styles of learners before involving in any learning

activity within the learning environment. The pro-

posed framework consists of the following compo-

nents (Figure 2):

PEDAGOGICAL FRAMEWORK TO IMPROVE THE QUALITY OF LEARNING OBJECTS IN COLLABORATIVE

E-LEARNING SYSTEMS

355

Figure 2: Pedagogical Framework for Collaborative e-

Learning Systems.

3.1 Learning Styles Identiﬁcation

This component is responsible for identifying learn-

ers’ learning styles based on Felder-Silverman learn-

ing style model. An instrument known as Index of

Learning Style (ILS) (Felder and Spurlin, 2005) can

be used to achieve that. Felder-Silverman model de-

scribes the learner’s preferences based on four di-

mensions: Sensing-Intuitive, Visual-Verbal, Active-

Reﬂective and Sequential-Global. Based on the re-

sult, a learner’s proﬁle will be created to contain in-

formation about his/her learning styles. This module

is responsible for increasing learners’ awareness of

their learning styles by providing guidelines to help

them to better utilize the strengths of their learning

styles. Also, this can help the collaborative e-learning

system to recommend suitable learning objects for the

learners based on their learning styles. The following

are sample of the guidelines that can be given to the

learners based on their learning styles:

1. Sensing Learners:

• Find real world examples to link the content of

the learning object with the real word.

• Focus on the learning objects that contain facts

and procedures.

• Find learning objects that contain experiments

results.

2. Intuitive Learners:

• Read the summaries written by other learners.

• Find learning objects that contain innovative

ideas of applying the concepts.

• Find learning objects that use theories and

mathematical formulas.

3. Visual Learners:

• Focus on learning objects that use visualization

(e.g., pictures, diagrams, animations, etc.).

• Draw concept maps to link key points in the

learning objects.

4. Verbal Learners:

• Find descriptions for diagrams and other visual

learning material.

• Focus on learning objects that contains audio

learning resources.

• Write summary for the learning object in your

own words.

5. Active Learners:

• Find learning objects that contain simulations.

• Discuss the content of the leaning object with

other learners.

6. Reﬂective Learners:

• Read the comments and reﬂections written by

other learners about their experience using the

learning object.

• Think of possible questions or applications of

the content of the learning object.

7. Sequential Learners:

• Look at the outline of the content of the learn-

ing object.

• Use concept map to see how the key points in

the learning object linked to each others.

8. Global Learners:

• Take overview of the learning object before go-

ing into the details.

• Link the content of the learning object with

something you already know.

3.2 Collaborative Learning Cyclical

Process

This is the main component of the pedagogical frame-

work in which the learners participate in the learn-

ing process by interacting with learning objects. To

increase the educational effectiveness of the learn-

ing process, this paper applies the cyclical model of

self-regulated learning. The model consists of three

phases: forethought, performance and self-reﬂection

as described in section 2.1.

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356

3.2.1 Forethought (Planning and Activation)

Before engaging in learning activity, learner has to set

goals and plan for their time using tools that should

be provided by the e-learning environment. Choosing

suitable learning objects is very important task that

need to be done in this phase. This can be achieved by

the help of the information gathered from the interac-

tion of other learners with learning objects. Also, the

e-learning system can recommend suitable learning

objects based on the result of the learning style iden-

tiﬁcation in the previous phase. After that, the learner

should assess their previous knowledge required to

understand the content of the learning object. To

achieve that, learning objects have to be associated

with extra information on the prerequisite knowledge

required before using the learning objects.

3.2.2 Performance (Action)

In this phase, the learner starts the learning task by

using different cognitive and metacognitive learning

strategies as discussed in section 2.1. The learner can

perform a number of actions on the learning object:

• Note taking and commenting.

• Paraphrasing and summarizing.

• Providing real world examples of applying the

concept.

• Outlining and creating concepts maps for the con-

tent of the learning object.

• Rating and tagging the learning object.

In this phase, learners also use metacognitive strate-

gies such as self-testing to check their understanding

of the concepts covered by the learning object. This

can be achieved by providing assessment questions

associated with the learning object.

3.2.3 Reﬂection Phase

This phase involves the processes that occur after

completing the learning task. In the proposed frame-

work, the e-learning system should allow learners

to write reﬂections on their experience in using the

learning objects and whether the learning goals have

been achieved or not. Learners’ reﬂections on their

experience of using the learning object will be associ-

ated with the learning object and can help other learn-

ers to choose suitable learning objects and plan for

their learning process.

Figure 3: Extension of the Learning Object.

4 IMPLICATIONS OF THE

PROPOSED FRAMEWORK:

SEARCHING AND

RECOMMENDING OF

SUITABLE LEARNING

OBJECTS

In the proposed framework, learners follow cyclical

model to consume the knowledge provided by the

learning objects in the collaborative e-learning sys-

tem. According to this, learners with different learn-

ing styles interact with the learning objects by follow-

ing a number of strategies which will result in pro-

viding different notes, comments, summaries, exam-

ples, ratings and reﬂections associated with the same

learning object and generated by learners with differ-

ent learning styles (Figure 3). In this case, the learner

is not only a consumer of the knowledge but also a

producer. This can increase the quality of the learn-

ing objects to be compatible with different learning

styles.

Searching and recommending of learning objects

can be improved as a result of applying the proposed

framework. The experience of a learner in using spe-

ciﬁc learning objects can help other learners to ﬁnd

suitable learning objects for them based on the collab-

orative comments, ratings and reﬂections provided by

learners with different learning styles. Also, appro-

priate tags can be used to index the learning objects

to match different learning styles. For examples, for

PEDAGOGICAL FRAMEWORK TO IMPROVE THE QUALITY OF LEARNING OBJECTS IN COLLABORATIVE

E-LEARNING SYSTEMS

357

sensing learners, appropriate tags can be fact, experi-

ment, real world example, while for intuitive learners,

the tags can be innovative idea, mathematical formula

and theory. For Visual learners, the appropriate tags

can be image, diagram, and simulation while for ver-

bal learners, explanation and audio. For sequential

learners, appropriate tags such as outline can be used

while for global learner, overview is one of the sug-

gested tags that can be used. Recommendation sys-

tems can be integrated to the collaborative e-learning

environment to provide learners with suitable learning

objects based on their learning styles and the interac-

tion of other learners with learning objects.

5 CONCLUSIONS AND FUTURE

WORK

This paper presented a pedagogical framework based

on the learning styles and the self-regulated learn-

ing to improve the quality of the learning objects in

collaborative e-learning systems.The proposed frame-

work can also help learners to ﬁnd suitable learning

objects compatible with their learning styles. This

work will continue by conducting empirical studies

involving students using a collaborative e-learning

system based on the proposed pedagogical frame-

work. These empirical studies will help to evaluate

the educational effectiveness of the proposed frame-

work.

REFERENCES

Bandura, A. (2001). Social cognitive theory: an agentic

perspective. Annual review of psychology, 52:1.

Felder, R. and Silverman, L. (1988). Learning and teaching

styles in engineering education. Engineering educa-

tion, 78(7):674–681.

Felder, R. and Spurlin, J. (2005). Applications, reliability

and validity of the index of learning styles. Interna-

tional Journal of Engineering Education, 21(1):103–

112.

Glasersfeld, E. (2009). Ampliﬁcation of a Constructivist

Perspective. Issues in Education, 3(2):203–209.

Han, K., Kumar, V., and Nesbit, J. (2003). Rating learning

object quality with bayesian belief networks. In World

Conference on E-Learning in Corp., Govt., Health., &

Higher, volume 1, pages 1598–1601.

Keefe, J. (1988). Proﬁling and Utilizing Learning Style.

NASSP Learning Style Series. Publication Sales, Na-

tional Association of Secondary School Principals,

1904 Association Drive, Reston, VA.

Koohang, A. (2004). Creating learning objects in collabora-

tive e-learning settings. Issues in Information Systems,

4(2):584–590.

McLoughlin, C. and Lee, M. (2010). Personalised and self

regulated learning in the Web 2.0 era: International

exemplars of innovative pedagogy using social soft-

ware. Australasian Journal of Educational Technol-

ogy, 26(1):28–43.

Pintrich, P. (2000). Multiple goals, multiple pathways: The

role of goal orientation in learning and achievement.

Journal of Educational Psychology, 92(3):544.

Pintrich, P. and De Groot, E. (1990). Motivational and

self-regulated learning components of classroom aca-

demic performance. Journal of educational psychol-

ogy, 82(1):33–40.

Pritchard, A. (2009). Ways of learning: learning theories

and learning styles in the classroom. David Fulton

Publish.

Pritchard, A. and Woollard, J. (2010). Psychology for the

classroom: Constructivism and social learning. Psy-

chology for the Classroom.

Schunk, D. (1996). Goal and self-evaluative inﬂuences dur-

ing children’s cognitive skill learning. American Edu-

cational Research Journal, pages 359–382.

Shaw, G. and Marlow, N. (1999). The role of student learn-

ing styles, gender, attitudes and perceptions on infor-

mation and communication technology assisted learn-

ing. Computers & Education, 33(4):223–234.

Shishehchi, S., Banihashem, S., and Zin, N. (2010). A

proposed semantic recommendation system for e-

learning: A rule and ontology based e-learning rec-

ommendation system. In Information Technology (IT-

Sim), 2010 International Symposium in, volume 1,

pages 1–5. IEEE.

Sosteric, M. and Hesemeier, S. (2002). When is a Learn-

ing Object not an Object: A ﬁrst step towards a theory

of learning objects. The International Review of Re-

search in Open and Distance Learning, 3(2).

Wang, J., Sun, Y., Fan, Z., and Liu, Y. (2005). A collabora-

tive E-learning system based on multi-agent. Internet

and Network Economics, pages 455–463.

Zimmerman, B. (2000). Attaining self-regulation: A social

cognitive perspective. Handbook of self-regulation,

13:39.

Zusho, A., Pintrich, P., and Coppola, B. (2003). Skill and

will: the role of motivation and cognition in the learn-

ing of college chemistry. International Journal of Sci-

ence Education, 25(9):1081–1094.

CSEDU 2011 - 3rd International Conference on Computer Supported Education

358