TOWARDS WEB 2.0 DRIVEN LEARNING ENVIRONMENTS

Mohamed Amine Chatti

, Daniel Dahl

, Matthias Jarke

and Gottfried Vossen

Informatik 5, RWTH Aachen University, Germany

Department of Information Systems, University of Muenster, Germany

Keywords: Web 2.0, E-Learning 2.0, Communities.

Abstract: Over the last decade, it has been widely argued that technology-enhanced learning could respond to the

needs of the new knowledge society and transform the way we learn. However, despite isolated

achievements, technology-enhanced learning has not really succeeded yet in revolutionizing our education

and learning processes. In fact, most current initiatives do not focus on the social aspect of learning and

learning content is still pushed to a pre-defined group of learners in closed environments. Recently, Web 2.0

concepts have started to open new doors for more effective learning and have the potential to overcome

many of the limitations of traditional learning models. In this paper we show in which way the community-

driven platform Learnr, under development at the University of Münster, puts crucial success factors for

future technology enhanced learning into practice, applying well known concepts like networking and social

tagging. As a consequence, a Web 2.0 perspective on learners, learning content and learning communities

can be derived.

1 INTRODUCTION

Peter Drucker argues that in the emerging economy,

knowledge is the primary resource for individuals

and for the economy overall; land, labor, and capital.

He further argues that improving knowledge worker

productivity is the greatest challenge of the 21

century (Drucker, 1994). In the new knowledge

society, similar to a knowledge worker, a learner is

a person who does not just consume knowledge

but who is also able to create it. Over the past few

years, the Web has been shifting from being a

medium in which information is transmitted and

consumed into a platform in which content is

created, shared, remixed, repurposed, and passed

along (Downes, 2005). We are entering a new phase

of Web evolution: the read-write Web, i.e., a new

generation of the Web where everyone can be a

consumer as well as a producer of knowledge in new

settings that place a significant value on

collaboration. Applied technologies, often

collectively termed Web 2.0 technologies (O´Reilly,

2005; Vossen and Hagemann, 2007), have been

opening new doors to the learner for more dynamic

and social learning. The new Web trends have

offered new means to connect people not only to

digital knowledge repositories but also to other

people, in order to share ideas, collaboratively create

new forms of dynamic learning content, get effective

support, and learn with and from peers.

Since learning is social, personal, distributed,

flexible, dynamic, and complex in nature, a

fundamental shift is needed towards a more

social, personalized, open, dynamic, emergent

and knowledge-pull model for learning, as

opposed to the one-size-fits-all, centralized,

static, top-down, and knowledge-push models of

traditional learning solutions (Chatti et al., 2007).

Web 2.0 concepts can lead the way to this new

generation of technology enhanced learning. To give

an example, teachers can use blogs instead of

mailing lists to keep in contact with their students;

instead of pushing information to the learners, blog

feeds of relevance can be subscribed to by the target

group, which in turn can be an open community.

Speaking of the social Web, the concept of tagging

and folksonomies (Vanderwal, 2005) offers a high

potential for learners to express their own

vocabulary in bottom-up built structures. Indeed, so

called tag clouds give a holistic view picking up

terms accumulated within a community in an

appropriate way.

The Web platform Learnr, under development and

prototypical in use at the University of Münster,

Germany, shows the way to a more learner-focused,

370

Amine Chatti M., Dahl D., Jarke M. and Vossen G. (2008).

TOWARDS WEB 2.0 DRIVEN LEARNING ENVIRONMENTS.

In Proceedings of the Fourth International Conference on Web Information Systems and Technologies, pages 370-375

DOI: 10.5220/0001519703700375

 SciTePress

Web 2.0 driven approach of technology enhanced

learning. Adopting concepts like networking and

social tagging in a desktop-like environment,

independent learning communities arise in a bottom-

up way; learning content is provided by the crowd

and accessed and annotated instantly in a Web

browser. Realizing the shift to a more social and

flexible model, Learnr gives a first outlook on what

future Web 2.0 driven learning might look like.

The remainder of this paper is structured as

follows: Section 2 stresses the deficiencies in current

technology-enhanced learning implementations and

discusses critical factors needed for the success of

future initiatives. Section 3 points out the potential

use of Web 2.0 concepts in learning environments.

Section 4 briefly surveys the Learnr system, a

learning environment build around those new

technologies that is described in more detail

elsewhere (Dahl and Vossen 2007). As a result, a

new Web 2.0 driven perspective on learners and

learning communities as well as learning content is

derived. Finally, Section 5 gives a summary of the

paper and outlines perspectives for future work.

2 PRESENT AND FUTURE OF

TECHNOLOGY-ENHANCED

LEARNING

Learning and knowledge can be viewed as two sides

of the same coin and are fundamentally social in

nature, as has been emphasized by many researchers

(Polanyi, 1967; Lave and Wenger, 1991; Nonaka

and Takeuchi, 1995; Siemens, 2006). Despite the

wide agreement that learning occurs within a social

context, current technology-enhanced learning

(TEL) efforts continue to put a heavy emphasis on

content delivery and technology. In fact, most TEL

content today is designed, authored, delivered, and

managed via centralized Virtual Learning

Environments (VLE) as statically packaged online

courses and modules without focusing on the social

aspects of learning. Examples include learning

management systems (LMS), learning content

management systems (LCMS), course management

systems (CMS), or content management systems

(CMS) such as CLIX, WebCT, Blackboard, Moodle,

ATutor, ILIAS, Plone, or Drupal (Baumgartner et

al., 2004; Kristöfl, 2005). Obviously, the

content/technology-centric model of learning has

failed to achieve performance improvement and

innovation. A major reason of the failure is

that

learning is more than static content, and technology

is only a secondary issue. Learning is basically about

people. This requires a change in focus from

technology-driven to people-driven models of

learning and would imply a shift from e-Learning to

“we-Learning,” a collaboration culture that could

foster knowledge networking and community

building. With technology as an enabler, the new

learning model is characterized by the combination

of formal and informal learning within a social

context. New social skills become increasingly

important for better performance and thus have to be

learned and continuously improved. Learn-what

referring to the high-quality learning resource that

has to be acquired has to be supplemented with

learn-who referring to the person or the entire

community with the required know-how that can

help achieving better results. Learn-who also

involves the ability to navigate and learn across

different communities.

In the future, people-driven implementations of

learning models need to be the norm rather than the

exception. Chatti et al. (2007) stress that a radical

revision of the traditional pedagogical principles and

policies imposed by formal educational institutions

is required. In the modern media and knowledge-

intensive era of collaboration culture, the one-size-

fits-all, centralized, static, top-down, and

knowledge-push models of traditional learning

initiatives need to be replaced with a more social,

personalized, open, dynamic, emergent, and

knowledge-pull model for learning. The authors

discuss seven critical factors needed for the success

of learning initiatives:

 Knowledge networking and community

building: TEL models need to recognize the

social aspect of learning and, as a consequence,

place strong emphasis on knowledge

networking and community building to

leverage, sustain, and share knowledge in a

collaborative way.

 Content-centric vs. user-centric: Recognizing

that learning and knowledge are personal,

approaches requires a move away from one-

size-fits-all content-centric models, and towards

a user-centric model that puts the learner at the

centre and gives her the control over the

learning experience.

 Centralized vs. distributed: TEL solutions need

to operate with a more decentralized and

socially open approach, based on small pieces

of learning content, loosely joined and

distributed control.

 Top-down vs. bottom-up: TEL solutions need to

follow an emergent bottom-up approach, driven

TOWARDS WEB 2.0 DRIVEN LEARNING ENVIRONMENTS

371

by the learner and based on sharing rather than

controlling.

 Knowledge-push vs. knowledge-pull:

Recognizing that learning and knowledge are

dynamic and flexible in nature, TEL approaches

require a shift in emphasis from a knowledge-

push to a knowledge-pull model.

 Adoption: For TEL approaches to be adopted,

their systems need to be both simple and useful.

 Knowledge sharing culture and trust: A bottom-

up approach and distributed control build a base

for successful knowledge sharing and trust.

Encouraging people to build their personal

social networks and join communities based on

their needs helps to ensure trust and motivates

them to share.

Recognizing the social aspect of learning, several

TEL initiatives, such as Elgg, Moodle, CLIX, Plone,

and Drupal are starting to integrate social modules

into their solutions (Bryant, 2006). However, these

initiatives still employ centrally managed systems

that are driven by the needs of the institution and

consequently often not adopted by the learners.

Dalsgaard (2006) points out that a common idea

behind current systems is that different tools, e.g.,

discussion forums, chat, file sharing, video

conferences, shared whiteboards, and e-portfolios

are integrated in a single system which offers all

necessary tools to run and manage a learning course.

All learning activities and materials in a course are

organized and managed by and within the system.

To meet the requirements discussed above, we

would, however, need new learning models that take

a small-pieces, loosely joined approach

characterized by the freeform use of a set of learner-

controlled tools and the bottom-up creation of

learning communities.

3 WEB 2.0 MEETS TEL

We are entering a new generation of user-centric,

open, dynamic Web, with peer production, sharing,

collaboration, distributed content, and decentralized

authority in the foreground. This new Web

generation is often termed “Web 2.0.” The people-

driven approach to learning can be implemented

around Web 2.0 concepts. The rise of Web 2.0

technologies with more support for collaboration

and networking provides new opportunities to

overcome many of the failings of traditional TEL

solutions. Recently, researchers have been focusing

on how to incorporate the new Web trends into the

learning process and how to harness and apply Web

2.0 concepts to create new learning experiences and

learn across communities. E-Learning via Web 2.0

technologies has been referred to as E-Learning 2.0

(Downes, 2005). Harnessing collective intelligence

has become the driving force behind Web 2.0 and

social software, also called social media, has

emerged as a key component of the new Web. In a

learning context, social software have become a

means to connect people not only to digital

knowledge repositories but also to other people, in

order to share ideas, collaboratively create new

forms of dynamic learning content, get effective

support, and learn with and from peers. Rapidly

evolving examples of social software include wikis,

blogs, RSS, pod/vodcasting, and social

tagging/folksonomies. Social software is, however,

not restricted to these technologies.

Social software has the potential to change the

way we learn. For example, instead of generating

lexical entries in Wikipedia, learners could

collaboratively create learning content (learner-

generated content) in an open environment.

Networking as it can be found in OpenBC/Xing with

a business background also makes sense in the

context of learning (open learning networks).

Similar to tagging photos in Flickr or videos in

Youtube, learning content in form of slideshows or

exercises could be annotated in a similar way. The

concept of blogging could abandon mailing lists

which are explicitly created by teachers; instead,

teachers as well as learners simply blog their topics

of interest, and anybody who is interested subscribes

to the corresponding RSS feed to keep herself or

himself up-to-date.

Moreover, social software supports a bottom-up

building of communities and networks. Wikis,

Blogs, social tagging and folksonomies are good

examples of bottom-up social software in action.

Wikis provide an opportunity for social interaction.

Around blogs, a social knowledge network from

people with similar practices or interests can be

created and even enlarged by comments, trackbacks,

and blogrolls. Social tagging and folksonomies also

provide a powerful way to foster community

building as users share, organize, discover, and look

for what others have tagged and find people with the

same – or similar – interests (Chatti et al., 2006;

Dahl and Vossen, 2007). Especially the latter

concept builds a base of the TEL platform presented

in the following section.

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4 LEARNR: WEB 2.0 DRIVEN

LEARNING

At present, teachers as well as learners are supported

by a number of electronic platforms enabling a

combination of traditional on-site and distance

learning. For example, teachers at the University of

Münster use Web applications for distributing

slideshows of lectures or additional literature and

online systems to offer exercises with a high degree

of automatic reviewing. Even computer-based

exams are held in computer pools. In contrast, the

actual process of learning, which is characterized by

a summarization and recapitulation of information in

the phase of intensive learning (e.g., prior to exams),

is not supported to a higher degree yet; therefore, the

pen-and-paper way, working with prints of digital

learning content, is still the first and only choice.

Personal comments are added on post-its, relevant

paragraphs are highlighted with text-markers and

additional artefacts like file-cards or summaries are

created. This is where Learnr comes in.

4.1 Central Features of Learnr

The primary goal of the Web platform Learnr is an

adoption of the traditional concepts for intensive

learning to the digital world. On the one hand, based

on the electronic representation of information an

effective search (e.g., keyword search in slides or

summaries) can be offered. Virtual artefacts like

file-cards for recapitulation and notes can be

exchanged easily and revised collaboratively.

Offering a 24/7 (24 hours, 7 days a week) Web

application, the learning content along with the

personal additions can be accessed anytime and

anywhere: from the computer pool of the university,

the home office, the Internet café or even the hotel

lobby on vacation. On the other hand, the process of

learning achieves a social focus as learners publish

personal information to a learning community,

which is characterized by discussion, exchange and

evaluation of the learners´ knowledge.

Figure 1 gives an impression of the main Learnr

work panel. Centred, learners can browse instantly

through learning content in the form of slides,

secondary literature or exercises. Virtual text

markers help to highlight the personally relevant

parts (1). Additionally, notes can be added just like

post-its (2). Applying the concept of tagging, single

slides can be marked and classified (3) which results

in a structure, respectively a tag cloud, reflecting the

learners’vocabulary.

Figure 1: Annotating Learning Content.

The process of learning described so far is individual

and isolated from other learners. With the adoption

of networking as known from social software

applications like MySpace or Facebook learners can

affiliate in so called learning communities. Being

part of these communities, summaries and file-cards

are exchanged, notes are discussed, comments are

rated and last but not least tagging becomes a social

activity.

4.2 Evaluation of the Seven Success

Factors for Future TEL Initiatives

Analyzing Learnr with respect to the critical success

factors listed in Section 2 we can claim that a

promising new TEL generation has already started.

In the following section the criterions are brought

into relation with their realization in Learnr, as the

seven factors are broken down into a 2-dimensional

view: a user- and a content-perspective.

4.2.1 User-Perspective

In Learnr users actively build learning communities.

This means, learners decide whom to learn and to

share knowledge with (Knowledge Networking and

Community Building). In contrast to classical top-

down approaches, where learning groups are defined

by teachers within organisational boundaries (like

universities or even single university lectures),

learners from different universities, schools or

companies can affiliate (see Figure 2). Private

education in sense of lifelong learning participates as

well. The different opinions are expressed with

annotations, tags and within discussions.

Learnr facilitates the concept of self-guided learning

(User-centralization). With the learner being the

centre of the system, he or she decides which

content to consume, which person to learn with and

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373

at which time to do so. Basically, every learner can

provide learning content, as long as the respective

property rights are respected. The process of

learning, making knowledge in the form of

annotations or tags explicit, firstly is executed in a

private workspace; the learner decides when to

publish certain information like summaries or file-

cards for the learning community (knowledge

export) respectively when to access knowledge

residing within the community (knowledge import).

Learning content is no longer imposed by the

corresponding teachers upon the learners at a given

time. Rather learners search for new or further

information navigating through a tag cloud, using

the fulltext search or communicating with their

community (knowledge pull).

Figure 2: User-Perspective in Learnr.

According to Chatti et al. (2007), future learning

platforms need to offer a perceived usefulness and

an ease of use (Adoption, Acceptance). Utilizing the

social focus in Learnr, learners find additional,

valuable information: Explicit annotations of the

community, the learning focus of other learners (for

example, so called “hot slides” hold a high number

of tags, notes and discussions) or the exchange of

knowledge (summaries, file-cards). Furthermore, the

single learners’ own contribution achieves some

quality assurance as the community reads and rates

the published notes and summaries. The ease of use

is offered as the RIA-concept (Rich Internet

Applications) is followed: On the one hand, Learnr

can be accessed via ordinary Web browsers (no

installation required), on the other hand the

extensive use of AJAX enables a desktop-like

usability (rare page reloads, instant search results).

In comparison to classical TEL platforms, a general

shift from top-down to bottom-up learning can be

identified (Bottom-Up Learning). As the previously

explained aspects already showed, in the first line

learners gain a new degree of liberty instead of

formerly experienced force: learning groups

naturally evolve “from below” instead of being

defined “from above” and distributed content is

pulled from a wide range on demand instead of

being pushed by a single teacher. In general, the role

of teachers shifts to a learning process

advisor/facilitator. Offering the networking concepts

described above a learning community characterized

by trust and liberty can evolve (Knowledge Sharing

Culture). As learners follow the same objective, e.g.,

to pass an exam, further content is studied and

evaluated and explicit knowledge is shared.

4.2.2 Content-Perspective

Learnr brings together learning content from varying

organisations like universities, companies, or

secondary schools. The concept of user-generated

content (e.g., learners creating slides using their own

vocabulary) is supported as well. In the end learners

decide which content to work with. Indeed,

slideshows presented by the teacher who performs

the final exam might achieve the highest priority, but

related, more detailed distributed information is

available via a tag cloud, for example.

Figure 3: Content-Perspective in Learnr.

Utilizing the concept of deep tagging (Arrington,

2006), not only entire slideshows are labelled with

notes and tags, but also small sub units like single

slides are annotated. In this way small learning units

provided by different authors are brought into

relation and can be accessed by learners easily (see

Figure 3, Decentralisation of Content).

5 CONCLUSIONS AND FUTURE

WORK

In this paper at first deficiencies in present and

success factors for future TEL models were

illustrated. The potential of social concepts known

from Web 2.0 applications was pointed out for the

context of TEL. The platform Learnr, developed and

prototypical in use at the University of Münster, is

based on concepts like social tagging and

networking and therefore offers its users a new

perspective of Web 2.0 driven learning.

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Learnr already implements the key elements of the

crucial factors introduced by Chatti et al. (2007), but

a consequent continuation of their approaches might

enable additional potentials. For example, the

system still focuses on courses and learning content,

via which new learners can be found. In the sense of

user centralization it is desirable to look for new

learning partners directly based on a not yet defined

search interface: according to already known social

software applications like OpenBC/Xing learners

and their knowledge domains should be the key

factors. In result, the individually best fitting

learning partner could be found more easily.

Regarding learning content existing TEL

repositories could be coupled loosely, for example

based on Web Services so that on-demand access to

a broad range of resources could be offered. Finally,

we could speak of a real decentralization of content,

as currently different content and sources are

supported, but the single artefacts still need to be

uploaded into Learnr. Moreover, already existing

social networks should be importable to the system;

unfortunately, this currently lacks due to missing

interfaces to popular social software applications.

Even a new generation of external, content-

independent tagging service would make sense:

learners could not only tag learning content, but also

learning partners, relationships, discussions, emails,

and so on. These approaches already tend into the

research field of personal learning environments

(Wilson et al., 2007).

ACKNOWLEDGEMENTS

This work is supported in part by the EU Network of

Excellence PROLEARN (http://www.prolearn-

project.org) and the BMBF funded cHL Hybrid

Project (http://elearning.uni-muenster.de).

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