=Paper=
{{Paper
|id=None
|storemode=property
|title=Google Wave Platform. Exploring the Settings for Personalized Learning
|pdfUrl=https://ceur-ws.org/Vol-638/ivanova_mupple10.pdf
|volume=Vol-638
}}
==Google Wave Platform. Exploring the Settings for Personalized Learning==
https://ceur-ws.org/Vol-638/ivanova_mupple10.pdf
Google Wave Platform: Exploring the Settings for
Personalized Learning
Malinka Ivanova1, Javed Alam2
1
Technical University - Sofia, College of Energetics and Electronics, Blvd. Kl. Ohridski 8,
Sofia 1000, Bulgaria
m_ivanova@tu-sofia.bg
2
Youngstown State University, College of Science,Technology, Engineering & Mathematics
Youngstown, Ohio 44555, USA
jalam1001@gmail.com
Abstract. The Google Wave is a communication, collaboration and rich media
document creation platform that is in focus of educators and researchers,
because of its capable to be harnessed for educational purposes. The paper
discusses characteristics of Google Wave those facilitate creation of
personalized learning spaces accessible to students anywhere and anytime.
They are examined with aim to support and enhance the knowledge receiving
during several engineering courses and students’ projects. The findings are
generalized in a model that is applied in practice. The paper also highlights
student experiences in using Google Wave in various learning situations.
Keywords: personalized learning, Google Wave, collaboration, networking,
real-time, on-demand
1 Introduction
A recent trend in developing innovative eLearning environments is to combine or
create mashups of existing software components, applications and services. Such an
approach increases possibilities for widening the set of learning scenarios and allows
high degree of personalization. Also, more attention is concentrated on architectures
for supporting personalized learning: through empowering the functionality of given
eLearning environment (integrated approach – e.g. Elgg) or using individual
applications (distributed approach – e.g. start pages, feed readers, wikis, blogs, etc.)
[1], [2], [3], [4]. From pedagogical point of view eLearning environments are
collaborative and non-collaborative depending upon the way knowledge is created
either through collaborative learning activities or through performing stand-alone
tasks. These environments are controlled, when educator or institution controls the
resources and learning paths and non-controlled, when learner self-arranges his/her
learning environment. In the blogosphere is started discussion about the difference
between personalized learning and personal learning. Personalized learning is
recognized as controlled and tailored approach where the educator keeps control over
subject area and directs students do the right learning content, while personal learning
is related to self-organized and life-long learners, e.g. non-controlled approach [5].
When the eLearning environment is well organized and flexible it can support a
range of different interactive learning approaches. It helps in enhancing the
personalized learning. However, it creates different, and more diverse, demands on
the design of eLearning space to support a range of learning activities, to facilitate
group learning approach, to maximize the use of shared spaces and knowledge.
The Google Wave platform emerged one year ago and has attracted the attention of
educators and researchers with its capability to support users to communicate and
collaborate more effectively on the web in form of waves [6], [7]. It also supports
wiki like collaborative media document creation. It is based upon a rich set of open
standard APIs that allow integration of extensions and robots within waves that
enhance the base functionality of the Waves and allow embedding of waves in other
web services.
The paper explores the characteristics of Google Wave for personalized learning
and they are examined with aim to facilitate and enhance the knowledge receiving
during several engineering courses and students’ projects. The findings are
generalized in a model that is applied in practice. Students’ opinions are gathered and
summarized.
2 Google Wave Personalized Learning Settings
Google Wave is designed as a real-time communication and collaboration platform
combining features of email, instant messaging, wikis, web chat, social networking,
and project management. Access from web browsers and mobile platforms (iPhone,
Android) is available [8]. This allows personal/personalized access to the Google
Wave from everywhere and on-demand. The Google Wave platform is extensible
through public APIs, gadgets and robots that allows flexible personal/personalized
content organization.
The proposed data model provides learning in waves with unique IDs. One wave
includes wavelets with unique IDs, each one with a participant list and with a set of
documents. A participant can be a user, a group or even a robot. Such data model is
suitable for knowledge organization in different waves, performing selective filtering
the waves, and creation of special waves according to student’s needs. Also,
personalized learning happens in collaboration with other learners, working together
in a group learning environment or on a project.
The real-time learning occurs through Wave’s technology known as “operational
transformations”. It allows immediately display of what student types within a wave
when he/she edits a collaborative document used simultaneously by several other
students. The editing operation is also send to the server to be ratified hoping that it
will be accepted by the server. The server stores all the course documents and all the
changes within the documents. It also displays the latest version of these documents.
In the end, each client is updated with the final version received from the server that is
the result of possibly many operational transformations.
For providing inter/intra-institutional or inter/intra-course personalized learning,
the Google Wave federation protocol can be used. It allows multiple wave providers
to share waves with each other through open source XMPP protocol. This is a good
opportunity to promote social interactions among students and educators from
different universities and training organizations as well as personal networking in the
context of teaching and learning.
A literature exploration about what is important for personalized learning, what
makes learning personalized is performed below and it is connected to Google Wave
characteristics to support the development of a model for learning personalization in
Google Wave.
Research shows that ensuring of flexible delivery of personalized learning is a main
factor guarantees students’ progression and widening participation according to [9].
Different solutions for personalized way of content delivery are presented in: [10]
where a system proposes personalized delivery of news, TV-on-demand, mobile
multimedia applications; [11] explores the evolution of the delivery of content to
distributed users in the point of view of a new level of interaction and personalization
providing of today’s Web sites; in [12] a model of dynamic content delivery
supporting a level of customization and content personalization is presented.
Other important factor recognized by managers, teachers and learners in supporting
the personalization agenda is content and knowledge presentation in multiple media
forms utilizing a wide range of technologies [13]. Technologies allow mashup media
content from different sources and easy embedding of components/widgets for
receiving students’ opinion, practicing basic-skills and assessment, practicing
independent work skills, creating to-do list, pretesting students' knowledge before
each unit, sharing the work of created lessons [14]. A wide variety of media content
presentation and knowledge presentation in different forms attract the attention to
learning not only of the excellent students, but also of excluded/disengaged giving
them alternative routes to access information and skills relevant to their needs and
interests [15].
The social nature of web and web applications is a fact that cannot be skipped. This
phenomenon offers opportunities for personalized learning receipting knowledge by
students in formal and informal situations and scenarios. Working on projects,
participating in forums and group activities are among more formal forms for
learning. Active personalized learning experience can be reached also through
informal conversation, reflexive dialogue and collaborative content generation,
enabling access to a wide raft of ideas and representations [16]. Community of
practices is other way for improvement of the knowledge of each participant through
communication and the possibility for learning through shared experiences, problems
and solutions, tools, methodologies [17].
Ubiquities access of web sites and systems is also influencing factor at receiving a
personalized learning on-demand. There are many examples at using of ubiquities and
mobile environments in the context of personalized learning, as well as solutions of
big companies like Motorola and HP. In the Motorola's report a model of Seamless
mobility ensuring personalization of user interaction, applications, services and
content is presented. It puts the user at the center of unique experiences remain
consistent and coherent across activities, devices, services, locations and networks
[18]. The HP service delivery platform has been designed to delivery of personalized,
content-rich services satisfying specific customer requirements [19].
As it is seen these explored four factors play influential role for personalized
learning organization. They are in scope when the characteristics for personalized
agenda in Google Wave are examined and when a model for personalized learning is
developed (Figure 1). Flexible delivery is ensuring by given delivery methods of
learning content and knowledge, technology is represented in support of the methods
for an array of learning resources presentation, learning scenarios are related to the
methods for knowledge reception and mobile access facilitates the methods for
receiving ubiquities/pervasive on-demand learning.
Google Wave Platform
Delivery Content/ Knowledge receiving
knowledge
Collaboration Discussing
Real-time presentation
Links Group work Tracing Commenting
On-demand
Pictures
Networking Voting
Social way Well- Access
formatted
text Revising Sharing
Web-
Gadgets based
Multimedia Searching
Robots Integrated Ideas mapping Mobile
web pages
Fig. 1. Model for personalized learning in Google Wave
• Delivery methods. Learning instructions, content and knowledge can reach
students through the medium of integrated Google Wave’s rich text editor,
extensions, gadgets and robots. A wave can adopt any widgets specially created
for this purpose, but Wave gadgets are preferred, because the students can take
the advantages of the Wave’s live, multi-user environment. The Wave robots that
are designed as automated participants within a wave can talk with participants,
can provide information from outside sources, can monitor content within a
wave, can share social bookmarks, etc.
• Content/knowledge presentation. Every student has his/her favorite way/tools for
learning – learning through following links, through well-formatted text, through
multimedia/audio/video/images or embedded HTML code, some prefer to learn
by example, others by finding answers to questions, and others by solving
problems on their own. In a wave all of these variants are available and students
can personalize their learning using preferably media content. For this purpose
they have to add appropriate gadgets, robots or HTML code.
• Knowledge reception. Google Wave proposes several methods for knowledge
reception – by promoting collaborative work on projects, small groups’ problem
solving, allowing forming virtual learning network, facilitating learning by others
using Google Wave’s playback function, sharing, searching, real time video
conversations, mind mapping of ideas, discussion through active commenting,
and use of polling gadgets for voting to assess consensus development.
• Methods for ubiquities access. The platform of Google Wave is reachable any
time, from any location, serving the personalized learning on-demand, including
through mobile devices.
3 Students’ Experience
Google Wave personalized settings are utilized during several engineering courses
and students’ projects, where wave functionality helped students achieve required
learning outcomes. Their experience in using Google Wave is summarized in Table 1
and Table 2 below.
Table 1. Assessment survey responses from the students who will use Google Wave in the
future
Student’s opinion Learning methods
“Google Wave didn't interest me in the beginning because I didn't understand Communication
what it is for and what it could provide. After I knew that it combines the
benefits of emailing and chatting I was fascinated by this powerful tool.”
“Google Wave is very easy to learn and is a time saver for average people to Networking,
different companies it aloud people to work on the same thing in real time as collaboration
long as they have internet available.”
“Google Wave has been very helpful to my group. We are able to Group working,
communicate clearly at different times. Many of the gadgets are fun to interact through technology
with as well. I will definitely be using this in the future!”
“Google Wave was a complete new experience to me. The whole gadget and Learning experience
robots seems a little complicated at first.” through technology
“Google wave helps to revise past documents and conversations. Google wave Revising knowledge,
supports many number of gadgets and robots that can be used to search for knowledge gathering
information, plotting of the graphs, maps bar charts, etc.”
“In the beginning I didn't like Google wave at all. Then I started spending time Conversation and
on that and now I feel that it is fast way of communicating. My first Discussion
impression changed and now I spend few hours on it talking and discussions to
my friend.”
“Even if I were absent during my other partners were working, I can simply hit Knowledge tracking,
the playback button to see what actually happened during my absence. Google social networking
Wave is capable of serving both as a social networking tool and professional tool and professional
collaboration tool.” collaboration tool
“It definitely needs what they call it “a wave moment” to appreciate the Networking,
technology in which we accomplish something we couldn’t do with existing collaboration
tools. I really liked it because it lets me know who’s editing what and where,
where others attention is focused, an important feature when collaborating.”
“Whether it is for collaboration work among the group members or for sharing Collaboration,
data, news and problems, it has proved to be very significant. There are many Sharing
things that I am still learning and I should learn in order to use that tool fully.”
The survey results show that 65% of students will continue to use Google Wave in the
future, 20% of them are with answer “maybe” and 15% will not continue utilization
of the platform. What are the motivating drives of 65% of students to continue usage
of Google Wave for personalized learning? Several of them appreciate the possibility
for faster real-time communication, conversation and discussion for deeper learning
and clearing the problematic questions. Others like realized connections with peers,
experts and professionals and organization of expanded learning and professional
network via participation in several thematic waves. Deciding problems collaborating
and group working on projects in real-time and in technology-enhanced environment
attract students too. Many of them are excited from this new technology that offers
gaining information and knowledge through integration of gadgets and robots - at the
beginning they feel difficulty at usage of different environmental tools and services,
but when they understand and experiment with the technological opportunities they
are looking for other capacities.
Sharing of opinion, experience, resources and tracking these such as in daily journal
allow students to back so many times as they need to analyze and understand concepts
and theory.
The technology like Google Wave supports the conversational aspect of personalized
learning allowing: questions asking participating in discussions, seeking help or
advise on a project, sharing of learning documents and other media relevant to the
course topic, creating a learning network, following peers and educators with same
interests, reflecting on proposed learning.
Table 2. Assessment survey responses from the students who have doubts and who will not use
Google Wave in the future
Student’s opinion Student’s decision
“I think this is a pointless networking tool much like Facebook and MySpace. Not use in the future
Quite frankly, I believe it was a waste of my time.”
“I started a wave and have used it briefly. I don't really enjoy it that much. I Not use in the future
don't even text. I doubt I will ever use this in my daily life.”
“I don't know, I think the possibilities for this are great for communication. I Not use in the future
just don't see it feasible.”
“Although Google wave seemed to be confusing in initial days, eventually it Maybe, will use in
has somehow become familiar to use nowadays. Whether it is for collaboration the future
work among the group members or for sharing data, news, views and
problems, it has proved to be very significant. There are many things that I am
still learning and I should learn in order to use that tool fully.”
“In the beginning I didn't like Google wave at all. I found it little bit confusing Maybe, will use in
and it didn't work on IE. Then I started spending time on that and now I feel the future
that it is fast way of communicating. My first impression changed and now I
spend few hours on it talking and discussions to my friend. Some problems
like it gets slow when we have more/ large waves trouble me sometime.”
“I feel that Google Wave is not brief enough for professional work and also Maybe, will use in
complicated for entertainment. However, it is useful to communicate.” the future
“Google Wave was a complete new experience to me. The whole gadget and Maybe, will use in
robots seems a little complicated at first. I guess it is just like anything else the future
when you do something over and over it gets a little easier. I just don't know
when I would actually use this format. I guess I could try and used it with my
colleagues, but the problem is they also have to learn how to use it. You just
don't see Google Wave catching on like Facebook and MySpace.”
The students that answer with “maybe, I will use it in the future” are 20% and their
uncertainty derives from the imperfections of the technology such as incompatibility
with different web browsers, slow loading at big waves, time for studying tools, ect.
Another reason is related to their doubts about usefulness of this technology to reach
effectiveness in their future professional career. However, these students admit the
benefits of Google Wave for learning and communication in the contexts of
engineering courses that they participate.
15% of students are categorically that they will not use Google Wave platform in
the future. They consider participation in social networks as wasted time. Also, the
wasted time is needed time for technology studying. They suppose that such
technology is unfeasible for usage in daily and professional life.
Several opinions of students who are not sure and who will not use Goggle Wave
platform in the future are presented in Table 2.
4 Conclusion
Google Wave is not specifically designed to support teaching and learning activities,
but it has the desired features that can be used to support personalized and directed
learning environments. This paper demonstrates that Google Wave technology can be
successfully used to assists learning according to student’ needs and learning goals of
given engineering courses. Different learning methods during the semester are
utilized, including collaborative learning in groups, working on students’ projects via
sharing, discussing and revising.
The Google Wave platform is flexible and extensible allowing extensive
personalization and customization as needed to tailor the need of eLearning
environment. Its use was well liked and accepted by the students.
A model for personalized learning is created and it leads to basic understanding of
the main factors impacting the personalized learning, its social aspects, and to
students’ assessment of eLearning technology - what they like, prefers and utilize in
practice that possesses features for learning facilitation in the context of personalized
learning needs.
This exploration is worthwhile despite the decision of Google team to not continue
development of Google Wave further as a standalone product. They are in the process
of incorporating the technology developed for Google Wave in other Google projects
that can find use in PLE. Also, the technology is available in the form of open source
and can be used for free in different educational contexts.
References
1. Harmelen, V., Metcalfe, M., Randall, D.: The Manchaster PLE Project. JISC Emerge
Benefits Realisation, Report, (2009),
http://reports.jiscemerge.org.uk/Benefits-Realisation/View-category.html
2. Taraghi, B., Ebner, M., Schaffert, S.: Personal Learning Environments for Higher
Education: A Mashup Based Widget Concept. Proceedings of the Second International
Workshop on Mashup Personal Learning Environments (MUPPLE09), (2009), http://ceur-
ws.org/Vol-506/
3. Ivanova, M.: Use of Start Pages for Building a Mashup Personal Learning Environment to
Support Self-Organized Learners. Serdica Journal of Computing, vol. 3, pp. 227–238,
(2009)
4. Hammond, J.: Social networking with Elgg at Alton Convent. Posted on December 5th,
(2008), http://opensourceschools.org.uk/social-networking-elgg-alton-convent.html
5. Drexler, W.: Personalized vs. Personal learning, teach Web blog, 5 August, (2010),
http://teachweb2.blogspot.com/2010/08/personal-vs-personalized-learning.html
6. Higher Education in a Web 2.0 World. Report of Committee of Inquiry into the Changing
Learner Experience, UK, March, (2009),
http://www.jisc.ac.uk/media/documents/publications/heweb20rptv1.pdf
7. Google Wave has great potential for education,
http://www.eschoolnews.com/2009/06/08/google-wave-has-great-potential-for-education/
8. Trapani, G., Pash, A.: The Complete Guide to Google Wave,
http://completewaveguide.com/
9. Enhancing Learner Progression through Personalized Learning Environments. Final
report, (2009),
http://www.jisc.ac.uk/whatwedo/programmes/elearningcapital/xinstit1/elp2.aspx
10. Steiger, O., Ebrahimi, T., Sanjuan, D.: MPEG-based personalized content delivery. IEEE
International Conference on Image Processing, ICIP'03, vol. 3, pp. 45-48, Barcelona,
Spain, September 14-17, (2003),
http://infoscience.epfl.ch/record/86993/files/Steiger2003_287.pdf
11. Akamai Technologies, Inc., Report, Web 2.0 is Here-Is Your Web Infrastructure Ready?,
http://prod-www-web01.akamai.com/dl/whitepapers/Akamai_Web_2.0_Whitepaper.pdf
12. Eric Severson Dynamic Content Delivery using DITA, White paper, (2007)
http://www.marklogic-news.com/images/MarkLogic_Flatirons_07_Using_DITA.pdf
13. Banyard, P., Underwood, J.: Understanding the learning space. eLearning Papers, Nº 9,
ISSN 1887-1542, July (2008),
http://www.elearningeuropa.info/files/media/media15970.pdf
14. Grace Rubenstein Ten Tips for Personalized Learning via Technology, (2010)
http://www.edutopia.org/stw-differentiated-instruction-ten-key-lessons
15. Green, H., Facer, K., Rudd, T.: Personalization and Digital Technologies. Future lab
report, http://www.maximise-ict.co.uk/Personalisation_Report.pdf
16. McLoughlin, C., Lee M.: Personalized and self regulated learning in the Web 2.0 era:
International exemplars of innovative pedagogy using social software. Australasian
Journal of Educational Technology, 26(1), pp. 28-43, (2010)
17. Gannon-Leary, P., Fontainha, E.: Communities of Practice and virtual learning
communities: benefits, barriers and success factors. eLearning Papers, Nº 5, September,
ISSN 1887-1542, (2007), http://www.elearningeuropa.info/files/media/media13563.pdf
18. Motorola Seamless Mobility: Services and Solutions to Connect Devices, Networks and
Environments, (2005),
http://www.motorola.com/networkoperators/pdfs/Seamless_Mobility_Brochure.pdf
19. HP Service Delivery Platform, White paper, (2007),
http://hp.telecomtv.com/mobileworld08/collateral/Service_Delivery_Platform_Mash-
up/SDP.pdf