From
the Editors …
Welcome to
the July 2010 issue of the Learning Technology newsletter.
Collaborative
learning attracts increasing interest worldwide: theoretical studies
demonstrate that collaboration can form the basis for effective learning;
technology can support numerous forms of collaboration; and learners engage in
collaborative activities in their everyday activities within the networked,
knowledge-based society. This issue introduces papers which describe how
technology can support collaboration with the aim of building more effective
learning environments.
Cohen, et
al., describe a peer-based learning network that has been set up to support
medical assistance in homecare settings. Jiang, et al., introduce a web-based
workspace (currently under development) which is designed to support student
teams in learning as well as the submission process of their distributed
assignments during a semester-long project. Rego demonstrates that a
combination of web 2.0 tools and a collaborative approach to learning can
assist target language acquisition among learners. Tambouris, et al.,
investigate the potential of Web2.0 technologies for supporting innovative
pedagogies such as Collaborative Learning and Problem-Based Learning (PBL), and
present a specific CSCL system. Lin, et al., propose a new group formation
approach for CSCL which is based on learners’ prior knowledge and is
implemented through particle swarm optimization. Tacke & Hobus describe a
case study of a free public wiki aiming to stimulate collaborative knowledge
production in a university setting. Finally, Verhaart discusses how wikis in
general and MediaWiki in particular can be used for teaching and learning
through case study examples.
The issue
also includes a section with regular articles (i.e. articles that are not related
to the special theme on collaborative learning). Caudill reviews and discusses
the evolution, current state and future trends of the online education industry
and market. Ikuta & Sculthorp present the intellectual and technical
infrastructure that has been developed and deployed for modeling accountability
and transparency in learning achievement in a specific university. Vignollet,
et al., describe a study which aims to investigate the commonalities and
differences between work flow management and learn flow management, in order to
help the two domains to capitalize and exchange results. McCarthy &
Scroggins describe the development of a SCORM-conformant learner model, which
aims to overcome the limitations of SCORM in relation to representing learner
information in a manner which is adequate for developing adaptive courses.
Kirkham discusses personal data security in lifelong learning. Finally, Veglis
describes a data visualization course for journalism students.
We
sincerely hope that this issue will help in keeping you abreast of the current
research and developments in Collaborative Learning through TEL as well as
advanced learning technologies in general. We also would like to take the
opportunity to invite you to contribute your own work on technology enhanced
learning (e.g., work in progress, project reports, case studies, and event
announcements) in this newsletter, if you are involved in research and/or
implementation of any aspect of advanced learning technologies. For more
details, please refer to the author guidelines at
http://www.ieeetclt.org/content/authors-guidelines.
Deadline for submission of articles: September
20, 2010
Special
theme of the next issue: Pervasive Learning and Usage of Sensors in
Technology Enhanced Learning
Articles
that are not in the area of the special theme are most welcome as well and will
be published in the regular article section!
Editors
Sabine Graf
Athabasca University, Canada
sabineg@athabascau.ca
Charalampos Karagiannidis
University of Thessaly, Greece
karagian@uth.gr
Special
Theme Section: Collaborative Learning Supported by Technology
With an
aging population, home healthcare solutions are becoming, by necessity, more
prevalent. Caregivers and patients alike face the challenge of making medical
decisions in dynamically changing environments, using whatever resources are
available in the home.
Our
research aims to provide important decision-making support in these scenarios
by leveraging the learning of peers through a social networking approach. In
particular, we propose that peer-based tutoring form the basis of the
information imparted to homecare caregivers and patients. Distinct from other
approaches to peer-based intelligent tutoring which assume an active social
network of information exchange in real-time (e.g. [3]), we propose a framework
that makes use of learning experienced by peers at several points in the past.
In essence, we seek to adopt an approach to learning that respects what McCalla
has referred to as the ecological approach [2]: enabling various learning
objects (texts, videos, book chapters) to be introduced to peers, based on the
past experiences of other, similar, students with these learning objects.
An example
scenario helps to motivate our research. Consider a diabetic patient,
attempting to manage his disease. Monitoring glucose levels becomes important
and the patient seeks resources which inform about how best to perform that
monitoring (with what frequency, using which methods, etc.). Distinct from an
approach of simply posting a query to a discussion group and receiving various
responses from peers (with varying degrees of reliability), one would treat
this problem as one of properly teaching the patient suitable information that
may be contained in a variety of online articles or instructional videos. We
assume a corpus of these learning objects exists and has been experienced by
other peers in the past. Pre- and post-testing of the learning achieved by
these peers is conducted (for example, through an exit quiz that results in a
level of understanding represented as a grade achieved, before and after the
interacting with the learning object). Then, each learning object has stored
with it the students who have experienced it, along with the benefit that each
students obtained (an increase, or decrease, in grade level achieved).
In
determining which learning object to display to a new student, we propose three
distinct methods. The first focuses on presenting to new students those
learning objects which produced the most benefit to like-minded peers, where
the similarity between students is determined on the basis of their overall
level of knowledge. This approach is motivated by collaborative filtering
techniques, as performed in recommender systems [1]. For example, those
learning objects which resulted in a weak understanding for other similar
patients would be avoided for the new student.
The second
proposal is to enable the peers to influence the determination of learning
objects which will be considered. While an initial corpus will be introduced,
once a peer has experienced learning, it will be possible to suggest, for
example, subdividing an existing, lengthy learning object into a smaller,
cogent element, which is strongly recommended to other students. Continuing
with the motivating scenario of informing homecare diabetic patients, there may
be a particular article in a book on managing diabetes which is of special
value. As with our algorithm for recommending learning objects, the
determination of which of these smaller articles to present to a peer will be
based on the learning that is experienced by others. The object would be added
to the corpus and then its overall benefit to peers can be tracked. It is
possible that for one population of (perhaps more advanced) students a more
targeted, succinct learning object would be preferable, while for another
population of students a learning object with additional explanations may be
preferable. In addition, one can manage the entire corpus by eventually
discarding learning objects that are not of use (garbage collection), resulting
in a refined and more valuable corpus on which the learning may proceed.
The final element
that we propose for peer-based home healthcare management is the introduction
of commentary, or annotations, to each of the learning objects in the corpus.
Again, in an effort to best represent the learning experienced by peers, one
allows each peer to leave behind comments on the learning object. Whether these
particular comments would be displayed to a new peer would be decided based on
the similarity of the peer who left them, but also on the inherent
trustworthiness of that peer (and her annotations), using methods from
multiagent trust modeling that we have explored in our previous research [4].
This particular representation of an agent's reputation combines both personal
reflection of the value of the agent and overall public perception of that
agent's reliability. In addition, the overall impression of the value of the
annotation (by all peers) can be integrated into our algorithm for determining
whether an annotation is shown.
In all, we
believe that home healthcare can be improved by enabling patients and
caregivers to learn on the basis of the past learning of their peers, through
judicious choice of material to present to the learners, which evolves over
time as the learning experiences of the peer group expand.
References
[1] Breese,
J. S., Heckerman, D., and Kadie, C. (1998). Empirical analysis of predictive
algorithms for collaborative filtering: 43-52.
[2] McCalla,
G. (2004). The ecological approach to the design of e-learning environments:
Purpose-based capture and use of information about learners. Journal of
Interactive Media in Education: Special Issue on the Educational Semantic Web,
7: 1-23.
[3] Vassileva,
J. (2008). Toward social learning environments. IEEE Trans. Learn. Technol.,
1(4): 199-214.
[4] Zhang,
J. and Cohen, R. (2007). Design of a mechanism for promoting honestyin
e-marketplaces. In AAAI: 1495-1500.
Robin Cohen
University of Waterloo
Waterloo, Ontario, Canada
rcohen@uwaterloo.ca
John Champaign
University of Waterloo
Waterloo, Ontario, Canada
john.champaign@gmail.com
The ability
to collaborate with other people is demanded in college students. Domains like
usability engineering require interdisciplinary knowledge and skills. Effective
collaboration and sharing of knowledge is the way to utilize all necessary
expertise. To prepare our students with required knowledge, we made a serial of
efforts in our usability engineering education in PennState University
(Ganoe,
Borge, Jiang, Carroll & Rosson, 2009).
We will
introduce a web-based workspace, under development, which is designed to
support students in learning and support their distributed assignments during
semester-long projects (Carroll, Borge, Ganoe & Jiang, 2010). The system
had its debut in the 2010 spring, serving a usability-engineering course
(http://ist413.ist.psu.edu).
Introducing collaborative competency into the
class
To harness
students with proper collaboration skills, we introduced collaborative competency (Borge, 2007) to the students. We adapted
its four collaborative capacities: communication, planning, critical
evaluation, and productivity (Borge & Carroll, 2010). Along with usability
engineering knowledge, we also gave students systematic training on collaboration.
For example, we gave student teams collaborative capacity guidelines to help
their semester-long projects, such as helping them to plan ahead and conduct
effective meetings.
Figure
1 - Four collaborative capacities
To support
the semester-long projects and collaboration, we started to envision a system
scaffolding this role. In the past, we have developed a system called BRIDGE
(Ganoe, Somervell, Neale, Isenhour, Carroll, Rosson and McCrickards, 2003). It
provides synchronous and asynchronous collaboration. BRIDGE hosts a large
variety of objects, from HTML to drawing objects, and to calendar. However, the
system is client-heavy with a Java client. The services are too advanced for
students without adequate collaboration experience.
The workspace
We began to
design and implement the workspace system in fall 2009. The high-level goal is
to create a lightweight, web-based space where students can practice usability
engineering knowledge and collaboration skills.
We
constructed a set of first-order requirements and designed affordances (table
1). First, students should be able to practice knowledge they learned, with
respect to the subject matters of the course. The system should provide support
for students to learn and for instructors to deliver the intended knowledge. Second, problem-solving skills require
teamwork, so students should be able to collaborate. Third, projects and assignments usually span more than one day and
need considerable coordination. Coordination and proper level scaffolding of it
is desired. Fourth, as we have found that the students sometimes show lack of
reflection on their own thinking and learning process, it will be very helpful
to aid their reflection throughout the activities. Fifth, the workspace should
be a place where information can be gathered and shared.
|
Requirement
|
Description
|
Affordance
|
|
Practice
knowledge
|
Apply
and discuss knowledge learned
|
Authoring,
Commenting tool
|
|
Collaboration
|
Use
collaborative technology and share information sharing
|
Shared
workspace and objects
|
|
Coordination
& team process
|
Supporting
team process
|
Meeting
agenda, to-do list
|
|
Reflection
& reasoning
|
Helping
students reflect on what they learn and team processes
|
Commenting
tool
|
|
Information
management
|
Gathering
and sharing information
|
Uploading
files, tagging
|
Table 1 - Summary of
requirements
The functions
exposed to the students are a set of digital objects: collaborative documents,
meeting agendas, a team to-do list, and file upload. Each team has a workspace.
The instructor and the team can access the workspace. A workspace is organized
as a tree of folders and objects. Students can create objects and upload
external files into a workspace.
In 2010
spring, 8 teams worked with clients in the USA. These clients displayed great diversity
(e.g., commercial companies, NGOs, research groups as well as ranging from
local to 3 time zones away). Students had deliverables every two weeks. 8 teams
created 3978 total objects.
Discussion
We found
that the workspace is useful and has potential in engineering education and
learning. We also observed issues regarding to the workspace use and
collaboration among students. Students are familiar with web 2.0 technology.
But they do not have enough knowledge for smooth and effective collaboration.
We saw instances where students do not reflect on learning activities enough,
and sometimes use concepts or instruments mechanically without adaption for
their current context. Students made different use of the workspace. For some
groups, they created and finished deliverables outside the workspace and then
uploaded them. For other groups, they had intensive chat and created
presentable objects within the workspace.
One effort we will undertake is to integrate different objects in the
workspace. This will include object type-conversion. The students will be able
to create a team to-do list from existing objects such as their meeting agendas
or to create to-do items from selected chat messages.
Another effort is to integrate and make more use of time information.
Many time-sensitive objects are supported, such as agenda items and to-dos. The
system will detect time information from objects and provide awareness to teams
(e.g., highlighting items due in the near future). We will plot group activity
on a timeline (Ganoe et al 2003). This information will allow teams and
instructors to monitor group activities. These improvements will help the
workspace better serve collaborative processes of the student teams.
Figure 2 - Workspace example
References
Borge, M. (2007). Regulating social
interactions: developing a functional theory of collaboration. Dissertation
Abstracts International, 241.
Borge, M., Carroll, J. (2010). Using
collaborative activity as a means to explore student performance and
understanding. Presented at the International Conference of The Learning
Sciences, Chicago, Il.
Carroll, J.M., Borge, M. Ganoe, C.H. &
Jiang, H. 2010. Distributed
collaborative homeworks: Learning activity management and technology support.
IEEE EDUCON 2010. (Madrid,
April 14-16). Pp. 1585-1594.
Ganoe, C.H., Somervell, J.P., Neale, D.C., Isenhour, P.L., Carroll, J.M.,
Rosson, M.B. & McCrickard, D.S. (2003). Classroom BRIDGE:
using collaborative public and desktop timelines to support activity awareness.
ACM UIST 2003. New York:
ACM, pages 21-30.
Ganoe, C., Borge, M.,
Jiang, H., Carroll, M., and Rosson,
MB. (2009) Usability Case Study
Learning Objects for Collaborative Authentic Education. Learning Technology
Newsletter, Volume 11 Issue 4 (http://www.ieeetclt.org/issues/october2009).
Hao Jiang
Pennsylvania State
University, USA
hjiang@ist.psu.edu
Craig H. Ganoe
Pennsylvania State University, USA
cganoe@ist.psu.edu
Marcela Borge
Pennsylvania State University, USA
mbs15@psu.edu
John M. Carroll
Pennsylvania State University, USA
jcarroll@ist.psu.edu
Ishita Ghosh
Pennsylvania State
University, USA
iug112@ist.psu.edu
Mary Beth Rosson
Pennsylvania State
University, USA
mrosson@ist.psu.edu
There is
growing interest in applying a socio-constructivist approach in language
education. Masaki Kobayashi conducted a study that examined language
socialization theory. Kobayashi cites Bernard Mohan, stating that language
socialisation “is a major source for learning about and expressing what one
must say, know, value, and do in order to participate in sociocultural
situations of society (Mohan, 1987, cited by Kobayashi). Simina and Hamel state
that when integrating a learner-centered, socio-constructivist approach within
a Computer Assisted Language Learning (CALL) environment, the potential for
successful acquisition of the target language is maximized (Simina, Hamel,
2005). This article attempts to demonstrate a collaborative approach combined
with web 2.0 tools can greatly aid target language acquisition among learners.
Bernd
Ruschoff discusses Technology Enhanced Language Learning (TELL) (Ruschoff,
1998). He states that “Education and teaching in the knowledge society can no
longer be reduced to “the act, process, or art of imparting knowledge and
skill” as Roget’s Thesaurus proposes, but learning must be recognised as an act
in which a learner plays the role of an active constructor of knowledge” (Ruschoff,
1998). The four essential skills of language learning are listening, speaking,
reading, and writing. PC Miller cites Phillips and Draper, who state that the
four language skills are “developed interdependently” to ensure learners become
competent communicators of the target language (Phillips & Draper, 1999,
cited by Miller). By taking a constructivist approach, using web 2.0 tools,
students can work together, improving their communicative competencies in these
four areas.
Richards
refers to an activity supported by technology as an “activity-reflection cycle”
(Richards, 2004) whereby the learner is engaged in “application and
interaction”. He concludes that technologies used in teaching and learning need
to “be grounded in activity as both process and structure.” (Richards, 2004)
Internet provides the language learner with a wealth of resources for applying
knowledge and interacting with others. Blogs, wikis, and social networks such
as Twitter and Facebook bring learners together to communicate through text,
improving their reading and writing skills. Voice and video chat tools such as
Skype and Google Voice Chat enable one-to-one interactions between both student
and teacher as well as between students, ensuring students feel comfortable
with practising their oral skills.
Thoms,
Liao, and Szutak (2005) conducted a study of university students collaborating
via on-line chat on a jigsaw activity using L1 (their native language) to move
along the activity to be completed in L2 (the target language). Brooks (1992)
was cited having discovered that when using L1 while interacting, “learners
strengthen their strategic competence” and promotes “inter-subjectivity” while
collaborating within a group (Brooks, 1992, cited by Thoms, Liao, & Szutak,
2005). They also found that activities involving collaboration effect L2
competency in grammatical skills.
Learners
can either collaborate synchronously (chat rooms, Skype) or asynchronously
(discussion board, Google Wave), having more flexibility in choosing how and when
to interact with others. Synchronous learning environments are beneficial when
wanting to practice language skills through conversation with other learners.
Asynchronous learning environments can be advantageous for language learners
from different parts of the world who cannot join live discussions due to time
zone differences. Asynchronous learning environments also are appealing to
learners wanting to carefully revise their written communication for grammar,
spelling, and accord prior to sending.
Language
Quests are web quests that help learners improve their language skills. The
European-based network site called “Language Quest” (http://lquest.net)
provides registered users with access to language web quests in various target
languages. Language quests can be particularly useful when teaching from a
project- or task-based approach, encouraging students to work collaboratively.
Virtual worlds such as SecondLife can serve as an effective space for
conducting a language quest. Howard Vickers found that virtual worlds offer
three forms of learning experiences: “social experiences, immersive experiences
and creative activities” (Vickers, 2010). Learners can collaborate with others
in a highly realistic environment through the target language whilst constructing
knowledge of language and culture.
Learners
who are engaged in a project-based learning approach will also find a wiki
useful as a tool for collaborating and drafting work on the internet with
peers. According to Bob Godwin-Jones, wikis can be defined as “intensely
collaborative” (Godwin-Jones, 2003). He elaborates that wikis are comprised of
an “open-editing system”, allowing multiple users to modify, add, or remove
content on any of the wiki's pages.
To
conclude, web 2.0 tools can be used successfully in a socio-constructivist and
communicative approach towards acquiring a new language. These tools give
learners increased flexibility in how and when they learn with others.
Asynchronous and synchronous learning provides learners with increased possibilities
to collaborate with learners across the globe. Use of written and verbal
communication can greatly aid learners in acquiring the target language.
References
Godwin-Jones, B. (2003). Blogs and Wikis:
Environments for On-line Collaboration. Language Learning & Technology.
Vol. 7, No. 2, pp. 12–16.
Kobayashi, M. (2006). Second Language
Socialization Through an Oral Project Presentation. In Beckett, G.H., &
Miller, P.C.(2006). Project-Based Second and Foreign Language Education: Past,
Present, and Future. Greenwich,
CT: Information Age Publishing
Inc.71-93.
Miller, P.C. (2006). Integrating Second
Language Standards Into Project-Based Instruction. In Beckett, G.H., &
Miller, P.C.(2006). Project-Based Second and Foreign Language Education: Past, Present,
and Future. Greenwich, CT: Information Age Publishing Inc. 225-240.
Richards, C. (2005). The Design of Effective
Supported Learning Activities: Exemplary Models, Changing Requirements, And New
Possibilities. Language Learning & Technology, 9(1), 60-79.
Ruschoff, B. (1998) New Technologies and
language learning: theoretical considerations and practical solutions. University of Essen, Germany.
Simina V. & Hamel, M.J. (2005). CASLA
through a social constructivist perspective: Web Quest in project-driven
language learning. ReCALL, 17 (2), 217-228.
Thoms, J., Liao, J., & Szustak, A. (2005).
The use of L1 in an L2 on-line chat activity. Canadian Modern Language Review,
62(1), 161-182.
Vickers, H. (2010). VirtualQuests:
Dialogic Language Learning with 3D Virtual Worlds. CORRELL: Computer Resources
for Language Learning 3, 75-81.
Bernadette Rego
University of British Columbia
Canada
regob@interchange.ubc.ca
Introduction
Latest
advances in ICT have started impacting also the field of education and
training. Social computing and Web2.0 technologies have brought vigorous
opportunities for learning and have realised a shift of the web’s role in
learning from an information carrier to a facilitator for the creation and
distribution of collective knowledge [1]. Technological advances have enhanced
the potential of collaborative learning and peer-learning, where students can
become more active participants and co-producers of knowledge, thereby allowing
for more horizontal educational structures and contexts.
The main
objective behind the work presented in this article is to investigate the
potential of Web2.0 technologies for supporting innovative pedagogies such as
collaborative learning and Problem-Based Learning (PBL) [2]. In this article we
present: (a) what PBL is and the implications in relation to course development
and (b) how Web2.0 technologies may be used in this context. The article
concludes with the presentation of a collaborative learning platform developed
to underpin our results and a short reference to further work.
PBL and Web2.0 in learning
Problem-based
learning is a student-centred pedagogy focusing on students’ active and often
collaborative production of knowledge through engaging with real world
problems/cases. Although there are differences in how PBL is carried out in
practice, one can also find some general traits; i.e. that problems are the
starting point for the learning process; that students should build on their
own experiences and learn through active engagement with real-world
problems/cases, which involve research and empirical activities often in
collaboration with peers. Numerous PBL scenarios may be developed for different
settings. However, the central aspect is how power is distributed between
teachers and students across three dimensions: the problem, the work process,
and the solution. Reflecting on these different aspects can support
teachers/course-designers in developing PBL practices which are congruent with
new learning practices and institutional demands.
Some of the
core concepts associated with Web2.0, such as collaboration, participation and
sharing, are well aligned with PBL. In our working context we find it useful to
distinguish between Web2.0 as a range of technologies (e.g. blogs, podcasts,
wikis) and Web2.0 as particular practices (e.g. blogging, podcasting,
collaborative writing). We emphasise this distinction because employing a
Web2.0 technology does not necessarily entail pedagogically innovative Web2.0
practices. For example, a teacher may create a blog and then use it only to
disseminate information to students, not allowing them to write or comment.
Therefore, Web2.0 learning is not only about using particular technologies, but
equally about the degree to which teachers adopt more student-centred,
participatory or collaborative practices.
Web2.0 collaborative learning
Therefore,
new tensions and challenges arise. Particularly questions concerning power
distribution between students and teachers become pertinent when combining
student-centred pedagogies and Web2.0 learning practices. We have mapped such
tensions across four central dimensions, which practitioners can use to reflect
on their design and values (Figure 1). This can provoke questions in relation
to who controls the learning process flow, e.g. should students be
self-directed learners, who decides which Web2.0 tools/practices to use, etc.?
Reflecting and deciding on such issues of control is increasingly important
when adopting student-centred pedagogies and Web2.0 practices, which are more
often employed in informal learning settings, in intra-organisational training
or for purely social purposes.
Figure 1 - Web2.0 learning tensions between teacher
and learner
Questions
similar to the aforementioned ones are to be addressed when designing Web2.0
learning environments; and different answers may be given depending on the
different learning settings and goals. For our Web2.0 learning platform we
targeted at enhanced collaboration opportunities and flexibility at the
teacher-learner continua. Consequently, the platform supports different models
of collaborative learning to be utilised in the different learning settings of
our pilots. The main aims while designing the learning platform are to:
·
provide
easy-to-use tools,
·
enable
and encourage collaboration,
·
organise
information in an easy and predictable way imposing minimal cognitive load on
users.
To address
these aims, we adopted the following approaches:
1.
Use
of popular Web2.0 tools, e.g. blog, wiki, forum.
2.
Integration
of existing standards, e.g. SCORM.
3.
Organisation
of resources, primarily based on tags.
4.
Hierarchical
division of spaces and content-filtering based on role, i.e. Class Desk, Group
Desk, My Desk.
5.
Back
office facility to support facilitator/teacher role.
6.
All
content can be commented on, rated, discussed and tagged to enable better
collaboration.
Application to a specific case
The
aforementioned learning approaches are particularly relevant to lifelong
training on multidisciplinary topics, such as Enterprise Architecture (EA),
which is gaining increased recognition worldwide. EA is a topic in need of deep
and diverse background competencies (technical, business,
organisation-specific) that are often acquired within the organisational context.
EA is therefore suitable to be taught in a collaborative organisational context
utilising PBL approaches. Consequently, EA is the topic selected for piloting
the presented work within the context of the EA Training 2.0 project. So far,
the first pilot for undergraduate students is completed in Greece; pilots in Germany,
Austria and Poland follow,
targeting postgraduate students, private and public sector employees
respectively. All pilots utilise the presented Web2.0 platform although
according to different learning approaches; University pilots are closer to the
traditional lecturing model with the platform as a supporting tool, the public
sector pilot is offered completely online, and the private sector pilot
utilises both elearning and mentoring practices.
Acknowledgement
The work
reported is part of the EA Training 2.0 project (www.eatraining.eu) which is co-funded by
the European Commission under the Lifelong Learning Programme.
Figure 2 - Platform home page
References
Maloney Edward J. (2007) "What Web 2.0 Can
Teach Us About Learning". The Chronicle of Higher Education. http://chronicle.com/article/What-Web-20-Can-Teach-Us/8332,
accessed 21 June 2010
Glud, L. N., Buus, L., Ryberg, T.,
Georgsen, M., & Davidsen, J. (2010) "Contributing to a Learning
Methodology for Web 2.0 Learning – Identifying Central Tensions in Educational
Use of Web 2.0 Technologies". In L. Dirckinck-Holmfeld, V. Hodgson, C.
Jones, M. de Laat, D. McConnell, & T. Ryberg (Eds.), Proceedings of the 7th
International Conference on Networked Learning, Networked Learning
(pp.934-942). Aalborg
Efthimios Tambouris
University of Macedonia, Greece
tambouris@uom.gr
Eleni Panopoulou
University of Macedonia, Greece
epanopou@uom.gr
Konstantinos Tarabanis
University of Macedonia, Greece
kat@uom.gr
Thomas Ryberg
Aalborg University, Denmark
ryberg@hum.aau.dk
Lillian Buus
Aalborg University, Denmark
lillian@hum.aau.dk
Vassilios Peristeras
Digital Enterprise
Research Institute
Galway, Ireland
Greek National
Centre for Public Administration and Local Government
Athens, Greece
vassilios.peristeras@deri.org
Introduction
Collaborative
learning is based on sociological and psychological approaches that emphasize
how students can learn together and develop interpersonal relationships via
interaction with peers [5]. However, one obstacle to achieving this is the
difficulty instructors face in placing students into appropriate groups to make
the best use of collaborative learning. In very small classes, it is easy for
instructors to form groups; however, there are often many students in a
computer-supported collaborative learning environment, making group formation
is a time-consuming process.
Several
studies have demonstrated that criteria for group formation affect the learning
performance and social behavior of students [1], [7]. In this study, students’
prior knowledge level is used as the criterion for forming collaborative
learning groups. Prior knowledge is an essential framework for learning new
knowledge since it affects learners who interpret, organize, assimilate, and
absorb new instructions [6]. Several studies have found that learners achieve
better learning comprehension and performance when they have better prior
knowledge in the learning context [2], [4].
This study
models the group formation problem based on students’ prior knowledge level and
applies particle swarm optimization (PSO) to address the optimization problem
[3].
Particle swarm optimization for group formation
problem
To form
collaborative learning groups, two grouping criteria are designed based on the
prior knowledge level of students. Generally, the prior knowledge levels of
students for each topic can be measured by an assessment. The formal definition
of the first grouping criterion is:
where f1 uses the prior knowledge
levels of n students for k topics to measure the average
difference of prior knowledge levels for k
topics within each group. Lxjl
represents the prior knowledge level of the lth
topic of the xth
participating student in the jth
group 1≤ j ≤ r
. pjx is the xth
participating student in the jth
group. n is the number of
participating students, r is the
number of groups, and k is the number
of topics. The formal definition of the second grouping criterion is:
where f2 uses the prior knowledge
levels of n students for k topics to measure the average
difference of prior knowledge levels for k topics between r groups. The other variables are as defined above.
Furthermore,
the encoding rule of PSO is modified to Py=[p11 p12…p1n p21…p2n…pjn… prn], where Py
is the yth particle, and
the particle uses r × n bits to represent that a group can be
formed from the n participating
students. Based on these, the formal definition of the fitness function for the
PSO is:
The fitness
function is to find an optimal solution that will maximize the difference of
the prior knowledge level between members in each group and minimize the
difference of the prior knowledge level between groups.
Additionally,
a logistic transformation, sigmoid function S(‧), is
used as the velocity function to update the position of each particle.
The sigmoid
function is used as a probability scale with a range of [0.0, 1.0] to determine
which particle bits have a value of 1.
The
proposed approach has the following six steps.
Step 1. Generation of initial swarm.
Initially,
the approach adopted random-selection strategy to decide who (which) students
(bits) are selected and set the state to value 1 in each particle.
Step 2. Fitness evaluation of particles.
The
approach measures the quality of each particle based on the fitness function
and then administers the next step to guarantee the quality of each particle.
Step 3. Determining the best fitness values
of individual and global particles.
Each
particle compares the present fitness value with the individual best value
obtained in the past generations to determine which one is better. If the
present value is better, the individual best value will be replaced by the
present one and vice versa. Additionally, the global best value is found among
all particles in the swarm.
Step 4. Updating the position of each
particle.
The
updating of the velocities and particle positions is based on the velocity
function of the PSO.
Step 5. Determination of termination.
This step
is to determine whether this procedure can be terminated, and if not then it
goes back to the second step in phase 2 and repeats these steps until
termination can be achieved.
Step 6. Group formation result generation.
This step
is to show the group formation results to instructors. If the instructors are
unsatisfied with the results, then they can require the PSO to form groups
again.
Conclusion
This study
applied PSO to model a group formation problem. The approach allows educators
to form collaborative learning groups based on the prior knowledge level of
each student. Educators can thus design appropriate assignments to promote a
high level of learning and interaction within a group. A series of experiments
will be conducted in the future to evaluate the efficacy of the approach.
Acknowledgements
This work
was supported in part by the National Science Council (NSC), Taiwan, ROC, under
grants NSC 98-2631-S-006-001, NSC 97-2511-S-006-001-MY3, and NSC
98-2631-S-024-001.
References
[1]
Beane,
W. E. & Lemke, E. A. (1971). Group variables influencing the transfer of
conceptual behavior. Journal of
Educational Psychology, 62(3), 215-218.
[2]
Jong,
T. D. & Joolingen, W. R. V. (1998). Scientific Discovery Learning with Computer
Simulations of Conceptual Domains. Review of Educational Research, 68(2),
179-201.
[3]
Kennedy,
J. & Eberhart, R.C. (1995). Particle swarm optimization, In Proceedings of the IEEE international
conference on neural networks (pp. 1942–1948). Perth,
Australia: IEEE Service
Center.
[4]
Moreno, R. (2004). Decreasing
Cognitive Load for Novice Students: Effects of Explanatory versus Corrective
Feedback in Discovery-Based Multimedia. Instructional Science, 32(1-2),
99-113.
[5]
Stahl,
G. (2005). Group cognition in computer-assisted collaborative learning. Journal
of Computer Assisted Learning, 21(2), 79-90.
[6]
Yates, G. & Chandler, M. (1994). Prior Knowledge. SET: Research
Information for Teachers, 2, Item 6.
[7]
Zurita,
G., Nussbaum, M., & Salinas,
R. (2005). Dynamic grouping in collaborative learning supported by wireless
handhelds. Journal of Educational Technology & Society, 8(3),
149-161 [Special Issue on Authoring of Adaptive Hypermedia].
Yen-Ting Lin
National
Cheng Kung University, Taiwan
ricky014@gmail.com
Yi-Chun Lin
National
Cheng Kung University, Taiwan
jellyplum@gmail.com
Yueh-Min Huang
National
Cheng Kung University, Taiwan
huang@mail.ncku.edu.tw
Introduction
Knowledge
production is a core process in modern society and economy. Gibbons et al. [1] describe
two different modes of knowledge production. While mode 1 clearly separates the
scientific sphere from the other societal spheres, mode 2 emphasizes the
importance of these being intertwined. According to mode 2, multiple
connections between scientists and practitioners are a major source for
creating knowledge. Consequently, learning can generally be considered to be a
“process of creating networks” [2]. These establish
·
intra-disciplinary
linkages between scientists (same domain)
·
inter-disciplinary
linkages between scientists (different domains), and
·
trans-disciplinary
linkages between scientists and practitioners.
Learning
networks facilitate the integration and recombination of knowledge which form
the basis for knowledge creation.
Description
Our goal is
to incorporate this notion of learning in academic seminars using a free public
wiki [3], see http://de.wikiversity.org/wiki/Kurs:Teams_SoSe10. Students from
different fields are prompted to write their papers in groups of up to four
persons, thus fostering the intra- and inter-disciplinary exchange of ideas in
teams. Furthermore, we explicitly encourage outsiders to give hints regarding
literature or, at best, to discuss the subject and to produce new ideas by
introducing their expertise or practical experience.
Concurrently,
we offer a course which deals with basic knowledge and methods related to the
process of writing scientific papers. Students taking part in the seminar
described above are encouraged to attend this course, as well as other students
preparing a term paper, bachelor or master thesis. We invite them to present
the current status of their work, e.g. the structure of their paper or the
outline of their argumentation. This will then be discussed and reviewed by the
other students always trying to develop and apply the basic rules of scientific
work. In this integrative learning context, the wiki has proved to be a very
helpful tool making the preliminary work results of a student accessible for
the others. This allows them to give feedback and to make suggestions for
improvement, on-line as well as off-line (during the course).
Discussion
Even
without participation from outside the university, groups of students can
benefit from using a wiki since they do not have to worry about spreading
updates of the text or about backups of previous versions. In addition, they
can acquaint themselves with working in Web 2.0. If outsiders join in, they can
enrich the papers by supporting new perspectives and real-life relevance. In
our first run, external input was scarce but appreciated by the students.
Furthermore, this outside involvement can motivate them because they realize
that others are interested in their efforts and that they do not only write for
their tutors. Those, in turn, gain the option not only to review the final
paper but the whole process of creation within the wiki. If they notice severe
problems, they can intervene at an early stage.
Additionally,
seminar students can benefit from the discussions and recommendations given by
participants of the course about scientific work as explained above. In return,
the latter obtain "training material" that they can apply the
scientific principles to which are taught in their course. This is a
substantial advantage since our experience from previous courses shows that
most students from conventional seminars were not prepared to deliver insight
into their work, either because they were not willing to do so or simply
because they did not bring their papers to the course.
One of the
counter-arguments against using a wiki might be that students and tutors must
learn its special syntax if no graphical user interface is featured. In fact,
this did not occur to be a problem. Although only three of the thirteen
participants of our seminar stated that they had been actively working with
wikis before, a very brief introduction was sufficient: the students were able
to learn the markup language autodidactically and the majority thinks wikis are
useful for collaboratively writing papers.
One more
critical issue may be the expenditure of time for tutors, if they want to
monitor the students' activity within the wiki. Essentially, it seems unlikely
that someone can keep track of all changes made and know the status of all
papers at all times, but the tutor can flexibly peek at the theses when his
schedule allows to, and he can use the wiki to only display the differences
between two particular versions to show the progress made since the previous
review.
The most
critical issue to keep in mind may be plagiarism which can happen either way,
in a wiki or on paper. Considering the former, it is very likely that there is
a larger inhibition threshold: who would like to be caught cheating in public?
Additionally, revealing misbehavior would be easier because the data are stored
digitally for further processing. In a nutshell: during our reviews, we did not
detect any plagiarism.
Finally,
one may fear that the papers will lack the personal contributions of the
students since others are invited to discuss with them and to give suggestions.
But, ultimately, someone has to write the theses and if someone else did, you
would not be worse off than with a printed version - quite the contrary, with a
wiki, tutors have more means for discovering fraud.
Conclusion
Public seminars
cannot only deepen knowledge related to specific fields but also foster skills
required in information society, e.g. communicating with others and working in
teams. Public wikis are not only adequate tools for collaborating more
efficiently but also for involving a wide range of different people - always
allowing outsiders, ideally practitioners, to participate in joint knowledge
construction.
References
[1] Gibbons,
M.; Limoges,
C.; Nowotny, H.; Schwartzman, S.; Scott, P.; Trow, M.: The new production of
knowledge. Sage, London,
2009.
[2] Siemens,
G.: Knowing Knowledge. lulu.com, Winnipeg,
2006.
[3] Spannagel,
C.; Schimpf, F.: Öffentliche Seminare im Web 2.0. In (Schwill, A.; Apostolopoulos, N.; eds.): Lernen
im Digitalen Zeitalter – Workshop-Band: Dokumentation der Pre-Conference zur
DeLFI2009. Logos, Berlin, 2009; pp. 13-20.
Oliver Tacke
Technische Universität Braunschweig, Germany
o.tacke@tu-braunschweig.de
Björn Hobus
Technische Universität Braunschweig, Germany
b.hobus@tu-braunschweig.de
Introduction
Internet
based Wikis provide a ubiquitous way for teaching and learning content to be
created managed and distributed. Content can be created by a lead person (such
as a Lecturer), and can be added to, and amended by both the creator and
learners based on their research or prior knowledge.
MediaWiki
is the software used by Wikipedia, the largest encyclopedia in existence
(Gabrilovich & Markovitch, 2007), and has been adopted by two significant
collaborative Learning content repositories: WikiEducator (http://www.wikieducator.org) and
WikiVersity (http://www.wikiversity.org).
For the
research being conducted the overall research question is “Can a wiki be used
to effectively deliver content in a blended learning environment?” This is the
part of a major action research project spanning many years, and this cycle
considers the use of wikis as a delivery tool in the virtualMe framework. For
more detail please refer to Verhaart (2008; 2009).
From an
educator’s perspective, are there examples of how WikiMedia can be used to
facilitate both teaching and learning, and what technology is required to allow
the content to be presented? The overall purpose of this paper is to generate
interest in sourcing good exemplars that will form a resource for those wishing
to use wikis for learning.
MediaWiki in Teaching and Learning
In order to
investigate how wikis (and in particular MediaWiki) can be applied, MediaWiki
has been used in a blended teaching and learning environment. So as not to be
constrained by the limitations of existing systems (such as wikiEducator &
WikiVersity), a MediaWiki has been privately hosted at http://www.virtualmv.com/wiki. This has
allowed for research into what additions could be added enhancing learning
based content.
In a
blended learning situation, multiple pedagogies can be employed. At the 2010
DEANZ Conference, in Wellington,
New Zealand,
Terry Anderson described three generations of distance education pedagogy.
These included: behaviourist/cognitive, constructivist and connectivist. (Anderson, 2010), where:
behaviourist/cognitive includes, self paced and individual study (and in a
blended environment instructivist; constructivist, working in groups; and
connectivist, using networks and collectives. For a blended environment,
multiple strategies are used to engage students, with different pedagogies
suiting different situations. Therefore, in order to be useful in a blended
teaching and learning environment ideally multiple pedagogies should be
supported.
Content presentation and technology support for
learning
Developing
learning content and materials in MediaWiki has two lenses: The first involves
the way in which the content is to be delivered to learners, and the second
what technology is required. The MediaWiki case study being explored centres on
content in the Multimedia, and Internet domains for undergraduate students. At
this stage, several learning paradigms have been prototyped and used in
teaching situations and include:
·
Presentation
– Content is presented either as a lecture or as supporting material.
·
Video
Tutorials.
·
Activity
- Content presented where students are expected to do a task.
·
Research/Referencing
– where content is set out in a way that exemplifies good citing and
referencing.
·
Question
and Answering: Providing the ability for either providing “hidden” answers, or
quizzes, such as multi-choice tests that can be marked by the computer.
·
Discussion–
where students can collaborate using social media such as Twitter or discussion
threads.
·
Enhanced
content – displaying computer source code with significant features (such as key-words)
highlighted.
·
Connected
media – Using external media (may be shared collaboratively – like Google
docs).
·
Interactive
– where learners interact with the content – in the protype enter some HTML
code and it is displayed on the wiki page. This would also include Flash based
or JavaScript tutorials.
Many of
these are illustrated in Figure 1.
Figure 1 - Sample wiki page
showing Twitter feed, Google Docs, Wiki links, Referencing and discussion
thread
In order to
facilitate these situations, MediaWiki has been extended. From the case study
five ways to extend MediaWiki were identified:
1.
Adding
JavaScript that would be loaded with every page.
2.
Developing
Templates that would automate functionality such as providing pedagogical
templates (for objectives, questions, etc.), and referencing.
3.
Adding
full (PHP) extensions to Mediawiki.
4.
Adding
Widget extensions to Media Wiki .
5.
Using
tools external to MediaWiki, such as Mark Russinovich’s Zoom-it (Russinovich,
2009).
Wiki grids
Two wiki
grids have been constructed to help this research. The first
“MediaWiki:Teaching and Learning Examples” and the second “MediaWiki:Extending
for Teaching and Learning”, both can be accessed via http://www.virtualmv.com/wiki/index.php?title=Research:Wiki.
In the
first case examples are mainly taken from the research wiki (virtualMVwiki),
though it is hoped that over time this will include more examples from the
publically generated wikis (WikiVersity and WikiEducator). An excerpt from the
grid is shown in Table 1.
Table 1 - Table of teaching and
learning examples
The second table
identifies the extensions to MediaWiki to enable the learning material to be
constructed. An excerpt from the grid is shown in Table 2.
|
Type
|
Description
|
virtualMV-wiki
|
Wiki-Educator
|
Wiki-versity
|
Wiki-pedia
|
|
js:CT
|
Collapsible Tables: Gives the ability to hide the
body of a table.
|
Y 1
|
Y 1
|
?
|
?
|
|
tm:FR
|
Footnote reference: Provides a citable reference for
the page and creates a zotero (COinS) record
|
Y$
|
N
|
N
|
N
|
|
ex:DIS
|
Discussion: allows discussion threads to be
added to each page, and via Special:RecentComments see a full list of
comments
|
Y list
|
?
|
?
|
?
|
|
wi:GD
|
Google docs: Displays a google document (e.g
Presentation).
|
Y 1
|
N
|
?
|
?
|
|
ot:ZIT
|
ZoomIt (Russinovich,
2009)[2]: Allows you to zoom
into a page and annotate when presenting.
|
.
|
.
|
.
|
.
|
|
|
|
|
|
|
|
Table 2 - Table of teaching and
learning extensions
Results/Benefits
The actual case
study has been evolving since July 2008 and has been deployed in a blended
teaching environment. From a lecturer view the wiki has proved a suitable tool
for delivering a wide variety of content in different modes (lecture,
practical, etc.), and feedback from students has been very positive. Formal
research into student perceptions and experiences is to be conducted.
Ongoing, Future work
and Conclusion
The work
presented into using MediaWiki in teaching and learning is ongoing and many
research paths are presenting themselves. It is hoped that this paper will
encourage readers to look into the MediaWiki based teaching and learning
systems and find good exemplars for others to base teaching content on. Indeed
readers are invited to participate in this research and contribute to the
wikipages identified.
References
Anderson, T. (2010) Three Generations of
Distance Education Pedagogy [PowerPoint]. Retrieved May 2, 2010 from
http://cider.athabascau.ca/CIDERSessions/ sessionarchive/
Gabrilovich, E. & Markovitch, S. (2007)
Computing Semantic Relatedness using Wikipedia-based Explicit Semantic
Analysis., International Joint Conference on Artificial Intelligence, Hyderabad, India,
January 6-12. pp 1606-1611
Russinovich, M. (2009). ZoomIt v.1. In Microsoft TechNet. Retrieved June 6,
2010 from http://technet.microsoft.com/en-us/sysinternals/bb897434.aspx
Verhaart, M. (2008). The virtualMe: A
knowledge acquisition framework. Unpublished PhD thesis. Massey University,
Palmerston North, New Zealand., Retrieved from
http://muir.massey.ac.nz/handle/10179/851
Verhaart, M. (2009). Personal Web
based knowledge management: The virtualMe framework. VDM Verlag.ISBN:
978-3-639-16525-8
Michael Verhaart
Eastern Institute
of Technology
Hawke’s Bay, New Zealand
mverhaart@eit.ac.nz
Regular Articles Section
Over the
past decade online education has experienced an incredible, meteoric rise as a
product and an industry. Correspondence education has existed for generations
but online education as its own entity is much younger. While there may be
different arguments as to when online education really began one milestone is
the formation of the first accredited online university, cited by the United
States Distance Learning Association as Jones International
University in 1993. Using
this date, today in 2010 online education is only 17 years old; yet it is
highly visible to academics in new online initiatives and to the general public
through pervasive advertisements from for-profit online education providers.
Yahoo
Finance lists the market cap, the current trading value of stocks, for the
training and education industry at US$36 billion at the time of this writing.
While the industry does include some companies that do not operate online and
others that operate both online and on-ground much of this $36 billion is made
up of online education programs. Appollo Group, who owns the University of
Phoenix, has a market cap of US$7.8 billion, Strayer Education US$3.4 billion,
Education Management Corporation that includes Argosy University US$3 billion,
and Grand Canyon University with US$1.12 billion. These figures represent only
the publicly traded for-profit online education providers and as such do not reflect
the full value of the industry that also includes privately held for-profit and
both public and private non-profit providers.
The
billions of dollars of value in the online education market can help to clarify
the magnitude of what is involved in working in this industry. The very rise of
the industry, the speed and relative ease with which so many providers have
become successful, makes the job of succeeding in online education appear much
easier than it actually is in today’s environment. Industries operate on a life
cycle, a series of four stages through which most companies and industries
progress. The life cycle stage in which companies are operating can be
indicative of an organization’s strategic environment.
These four
stages are introduction, growth, maturity, and decline (Lake,
2003). Briefly, the introduction stage is a new product that is finding its way
into the market and is often purchased only by early adopters. The growth phase
is a period during which the product finds broad acceptance and many new
providers enter the market and find success. In the maturity stage demand and
sales of the product may continue to grow, but competition among competitors
increases and successful providers begin to establish dominance in the market.
In decline, consumers stop purchasing the product and providers exit the
market.
Online
education today has entered the early maturity stage. In this stage online
education can certainly continue to expand, and many more students may pursue
online education opportunities, but the competitive market for providers of
online education will see substantial change. There are several key facts that
indicate this shift in life-cycle stage.
One of the
key indicators of a mature stage in the life cycle is the establishment of
dominant providers in the marketplace. Online education is experiencing this
shift today, with 75% of online courses currently being offered by just 1/3 of
online providers (Allen & Seaman, 2007). Mayadas, Bourne, and Bosch (2009)
further explain that the majority of online enrollments are in traditional
institutions and those enrollments are leveling off. The growing dominance of a
minority percentage of providers and slowing growth in new enrollments will
change the competitive environment in online education. Contrast these findings
of 2007 and 2009 with the market in 1998, when Hanna explained that online
education demand exceeded supply and that the rapidly developing market saw
many new entrants trying to find the correct practices. In just a decade the
market has changed from very open to more controlled.
Going
forward participants in the online education industry will likely see increased
competition and also increased barriers to entry for new competitors. The
details of these changes will be seen as the industry moves forward, but what
is important for everyone involved in online education to recognize is that
change is coming. Competition among online providers will drive changes in the
way online education operates, perhaps driving new initiatives for quality of
online programs, perhaps driving cost competition that makes education more
affordable, or in the most unfortunate circumstance perhaps driving quality
down to make the system faster and easier.
The
ultimate direction of these changes will be driven by multiple forces. Consumer
demand, what students want and are willing to accept, will be one major force.
Online providers, both administrators and faculty, will be another. As
participants in the process faculty members and those responsible for the
administration of programs will need to be aware of these pending changes to
the market and plan for how individual programs will respond. In such a dynamic
environment the successful programs will most likely be the most proactive.
Regardless
of what happens, or how it happens, online education remains a powerful force
in the educational world and is likely to continue growing in both size and
influence. What it ultimately becomes is up to everyone involved in the
process. Entering this maturity stage in the product life cycle everyone
involved in online education will soon see changes. Plan, project, and be
proactive.
References
Allen, I. and
Seaman, J. (2007). Online Nation: Five Years of Growth in Online Learning. Needham, MA.
Sloan Consortium.
Hanna, D. (1998). Higher Education in an Era of
Digital Competition: Emerging Organizational Models. Journal of Asynchronous
Learning Networks. 2(1). pp 66-95.
Lake, L. (2003). Product Life Cycle.
Retrieved February 8, 2010, from: http://marketing.about.com/od/marketingglossary/g/prodlifedef.htm.
Mayadas, A., Bourne, J., and
Bacsich, P. (2009). Online Education Today. Science 2. 323 (5910). DOI:
10.1126/science.1168874.
Jason G. Caudill
Carson-Newman College
Jefferson City, TN, USA
jason.caudill@gmail.com
As the
drive for accountability in higher education continues, it is essential to
establish an assessment system that produces high-quality, valid measures of
learner achievement that are transparent to learners, faculty, and external
stakeholders (Skeele, Carr, Martinelli, & Sardone, 2007). Providing this
type of assessment system through a collaborative model has introduced the need
for a defined intellectual infrastructure, and a sound technological system
endorsed by internal stakeholders at Capella. In response to the challenges
posed by seeking full participation in generating this model, several tools
have been developed to support the intellectual and technological
infrastructure of the assessment system.
Description of Innovations and Implementation
Through the
collaboration of faculty and staff, and their use of intellectual tools,
including Frame of Reference, Moderation
Sessions, and Misalignment Taxonomy,
along with the technological tools generated from additional collaboration, it
is expected that an assessment system that includes the integral pieces of
quality, validity, and transparency will be available for the purposes of
accurate measurement of learner achievement and program effectiveness.
Frame of Reference
To ensure
that assessments are aligned with the stated program outcomes of the
curriculum, faculty chairs are building an explicit model for each of their
programs’ outcome statements, referred to as a Frame of Reference, as shown in
Figure 1. A Frame of Reference represents the faculty’s collective
understanding of the program outcomes and expectations for learner performance.
This includes results from the discipline’s learning science, professional
standards, case studies, learner exemplars, professional standards, anecdotal
stories, published reflections from professionals, and important speeches. This
work is inspired by the National Research Council’s recommendation to base
educational assessments and educational reports upon cognitive models of
learning (Pellegrino, J., Chudowsky, N., & Glaser, R, 2001).
The first
use of the Frame of Reference has been to align assessments in capstone courses
with program outcomes. For each capstone course, a faculty member and an
assessment specialist monitored the Frame of Reference development and
incorporated this work into the design of the assessments. Because the Frame of
Reference is also intended to improve internal and external reporting on
learner program outcome achievement, the Frame of Reference was incorporated
into a rubric design that included criteria aligning with program outcomes and
scaled levels of performance.
Moderation Session
Establishing common
outcome performance expectations throughout the faculty is essential to
building assessments that lead to reliable and valid judgments about a degree
program’s effectiveness. A Moderation Session is a synchronous meeting in which
faculty collectively assesses a
representative learner’s demonstration of the program outcomes, share their
assessments with one another, and discuss points of consensus and disagreement
about performance expectations, as shown in Figure 2.
Figure 1 - Frame of Reference
The goal of
the Moderation Session is to reveal differences in performance expectations and
resolve these differences in order to increase the reliability of the
assessments. In most circumstances, one-hour Moderation Sessions have been
conducted with faculty chairs, subject matter experts, and capstone instructors
within Adobe Connect online meeting rooms. Faculty conducted their assessments
using a draft rubric prepared by the subject matter expert and assessment
specialist. The moderation session facilitator collected assessment data using
poll questions, in which faculty indicated the degree to which each criterion
in the rubric had been demonstrated by the learner. The facilitator then
sequentially revealed the poll results for the criteria that demonstrated the
least consistency.
Misalignment Taxonomy
As an
outcomes-based institution, Capella needs a consistent, transparent method for
directly connecting a learner’s coursework to the development of skills and competencies
that they will be able to use in their future careers. To achieve this
transparency, all assessment instruments and scoring guide criteria must be
aligned to the stated course competencies in each course, and align with the
respective specialization and program outcomes.
Defining
alignment is a necessary part of employing a consistent, transparent method for
connecting coursework to career. Capella faculty leadership is mindful of the
risks to such definitions and wishes to be clear that the intent is not to
institute a formulaic process that might restrict faculty members’ articulation
of assessment needs. As such, the work has focused primarily on some of the
ways that criteria can be misaligned, and leaves the establishment of alignment
within the control of faculty leadership and their subject matter experts.
Figure 2 - Moderation Session
Alignment Tool
Raters use
information in the Alignment Tool, as shown in Appendix C, to judge each
assessment criterions’ relationship to each course competency. Specifically,
raters, who consist of a faculty chair, a subject matter expert, and an
assessment specialist, use course competency and assessment instrument
information to apply the Misalignment Taxonomy to the assessment criteria. The
raters work independently, thus inter-rater reliability is established. Upon
completion of the raters’ work, a report is generated that shows raters’
judgments of assessment criteria alignment to course competencies. Raters use
the report to discuss judgment discrepancies and make final alignment
judgments. The goal of using the Alignment Tool is to establish a collaborative
process that, while maintaining the faculty chair and faculty’s ownership of
the curriculum.
Conclusion
In response
to the call for accountability and transparency in learning achievement,
Capella has developed a system based on an intellectual and technological
infrastructure founded upon the collaborative efforts of faculty leadership,
subject matter experts, and assessment personnel. The intellectual
infrastructure has provided a basis for which technological tools can be
further used to validate evidence of learner performance. Providing quality
measures of learner performance on program outcomes that can be reported to
both internal and external stakeholders addresses the need for transparency and
accountability in higher education, and demonstrates how a shared purpose
around the use of technical tools can promote confidence in reporting as well
as generate information for program improvement.
Figure 3 - Alignment tool
References
Pellegrino, J., Chudowsky, N., & Glaser, R.
(2001). Knowing what students know: The
science and design of educational assessment. Washington,
DC: National
Academy Press.
Skeele, R. W., Carr, V. B., Martinelli, J., & Sardone,
N. B. (2007). A multifaceted tool for student, course, and program assessment. Proceedings of the IADIS International
eLearning Conference, Lisbon,
Portugal.
Juanita Ikuta
Capella University, USA
juanita.ikuta@capella.edu
Stacy Sculthorp
Capella University, USA
stacy.sculthorp@capella.edu
The Business Process Management (BPM) [1]
field and the Learning Design field (LD)
[2] share some objectives: to give methods, languages and tools that allow end
users to better manage their "business processes" either in an
industrial or in an educational context. However, these fields do not share
their results. The study described in this paper tries to analyse the
commonalities and differences of the existing approaches with the ambition to
help the two domains capitalizing results from one to another. Indeed, few
approaches in the LDM field are reusing tools from BPM/Workflow, like Marino
& al in [3]. In our level of knowledge, no BPM/Workflow approach has ever
tried to reuse results from LDM field.
A
comparison of these two fields could be necessary to foster fruitful exchanges
between them. We share intuitions with others like Marino [3] on commonalities
and differences, although no tangible proofs to these intuitions have been
given in any study.
A
collaborative study has been initiated, grouping researchers from both fields.
In this paper, first of all, the methodology of this study is described, then
the first results obtained by the comparison of the approaches on a common case
study are given and, finally, the conclusion presents the next steps of this
study. The main points considered to be compared are: the objectives, the types
of activities, the life-cycles of the resulting applications, the types of
expected results, the observation/supervision facilities and, from a technical
point a view, the proposed architectures.
The first
step of the proposed methodology consists of the study of a common situation
and the comparison of the ways to handle it using BPM solutions on the one
hand, and LD solutions on the other hand. The chosen situation is the so-called
"Planet-Game" case study [4], proposed in 2006 in a workshop at ICALT.
Then,
rather than studying only the modelling dimension, we pushed the study up to
the implementation on professional workflow management systems of the learning
design example (see a proposed BPMN model in Figure 1; existing implementations
with LD approaches are described in [4]).
Figure 1 - Implementation of the planet game process
on a WMFS
In both
domains, the main idea is shared: the
model of the "activity" is the model of the "application",
each domain proposing several modelling languages to build the
"descriptive model" of the activity. This model is the result of the
first stage of the life cycle which allows having the application which will
support the aimed activity.
This life-cycle in both domains is based on
four main steps:
·
In
BPM: 1) Design/Model 2) Configure/Deploy 3) Enact/Execute 4) Monitor
·
In
LD: 1) Design 2) Initialize/Operationalize 3) Enact/Execute 4) Monitor
Although
the vocabulary could vary a little, even in the same field, these four steps
are quite similar, in both fields. Generally the "theoretical"
life-cycle is cyclic, including an Evaluation phase consisting in evaluating a
particular execution, to determine possible improvements. The model is adapted
if necessary, taking into account what occurred during the previous execution.
Considering the design phase, both domains propose graphical languages as notation languages to build a
"descriptive model" that will be transformed/translated in an executable (codified) model. The deploy phase in BPM will be
considered from a different perspective than the LD initialize/operationalize
one. In BPM, deploying is done with an integration and performance perspective
whereas the LD one is mostly concerned with the ability to execute the process.
Regarding
the differences, it first appears that the most important difference between a
learning process and a business process is that the latter is goal oriented and
the former is process oriented. In one case, it is important that the business
goal is achieved (the expected object is produced), in the other, it is
important that the process is executed entirely and the goal (Enhancing the
effectivity of learning, learner's creativity, learner's success, etc.) is
embedded in the execution.
Then, one
of the most important difficulties regarding the set-up of a learning scenario
on a BPM system was user management. In BPM an activity is assigned to one user
which is a problem to model group e-learning activities.
The third most important issue with
BPM tools, when compared with LD ones, is that they are not part of a system
providing a set of resources suitable for cooperative activities (e.g. forums,
chat, document sharing). The integration with the environment is not
straightforward but it leaves open a wide range of possibilities as BPMS are
designed with enterprise integration in mind, providing, in most of them, a lot
of integration support with the outer world.
Mainly,
this first step of this study allows to better understand each other and to
obtain first results in terms of the differences and commonalities between two
domains: the BPM and the LD. Implementing the example helped us to go beyond
the simple model to model comparison and to identify conceptual differences
that are most of the time left as implicit in both fields. Follow-ups would be
to try to implement business process on Learning Design Systems to transform
models from one BPM language to one LD language, and vice-versa, using the
model driven engineering methods and tools in order to leverage each
environment facilities, based on the result of the first step.
References
[1] Object
Management Group / Business Process Management Initiative, http://www.bpmn.org/
[2] Koper,
R. and Manderveld, Jocelyn (2004). Educational modelling language: modelling
reusable, interoperable, rich and personalised units of learnings, British
Journal of Educational Technology, Vol 35 No 5 2004, 537-551
[3] O.
Marino, R. Casallas, J. Villalobos, D. Correal, J. Contamines, "Bridging
the Gap between E-learning Modeling and Delivery through the Transformation of
Learnflows into Workflow", chapter from "E-Learning Networked
Environments and Architectures, A Knowledge Processing Perspective", Eds
Pierre Samuel, Springer, collection "E-Learning Networked Environments and
Architectures, 2007
[4] L.
Vignollet, C. Martel, D. Burgos,
“Comparing Educational Modelling Languages on the “Planet Game” Case Study”,
Journal of Interactive Media in Education.
http://www-jime.open.ac.uk/2008/2008-ceml.html
Laurence Vignollet
Université de Savoie, France
laurence.vignollet@univ-savoie.fr
François Charoy
LORIA/INRIA/CNRS
Université de Lorraine
charoy@loria.fr
Miguel Bote
GSIC – EMIC
University of Valladolid, Spain
migbot@tel.uva.es
Juan Ignacio Asensio
Pérez
GSIC – EMIC
University of Valladolid, Spain
juaase@yllera.tel.uva.es
The
standardization efforts of the Institute
of Electrical and
Electronics Engineers (IEEE)1-3, the IMS Global Learning Consortium4-6,
and others have shaped the way we create, manage, and deliver training. The
Sharable Content Object Reference Model (SCORM) leverages these standardization
efforts7. Our team has been investigating the development and
delivery of SCORM-conformant adaptive training.
In general,
for student-sensitive adaptation to occur, four requirements8,9 must
be satisfied:
·
There
must be information about the student's state with regard to mastery or other
characteristics.
·
There must be information about the content available
in the domain.
·
There must be information about the instructional
environment.
·
There must be appropriate algorithms to select the
most appropriate content for the student.
It has been
noted that SCORM is limited in regard to the first requirement10.
Specifically, the SCORM definition does not contain a sufficiently rich
definition of learner attributes. Further, learner-specific information cannot
be shared between training environments, whether they are SCORM-conformant or
not. This severely limits the ability to develop student-sensitive courseware,
as there is no general and portable understanding of "who" the
student is.
To address
this limitation, we have developed a Unified Learner Model (ULM) service and
have developed interfaces to make this service available to both adaptive and
non-adaptive sharable content objects (SCOs).
The ULM stores “raw” mastery
evidence associated with a managed learning objective (LO) for a particular
learner rather than a mastery state value11. The mastery evidence
items that the ULM
stores are referred to as “endorsements” and each endorsement has associated
metadata termed “attributes.”
Endorsements
have both required and optional attributes. Optional attributes are established
by a client application using a name-value scheme. Storing attributed LO
mastery evidence rather than mastery state allows ULM processing to be told what evidence to consider when a mastery determination is to
be made, and to treat the evidence obtained from different sources differently.
The ability of the ULM
to make LO mastery determinations in real-time, based upon deliberately
attributed evidence gathered from a compendium of sources, provides fuel to
power an adaptive training system’s decision-making engine.
Our team
has been exploring architectures that would allow SCORM-conformant environments
to use the ULM
service. Consider the simplified diagram of a standard SCORM-conformant
learning environment shown in Figure 1. When a learning management system (LMS)
launches a SCO, a communications channel is established between the SCO and the
LMS. The SCO initiates all communication with the LMS by making calls to the
SCORM API using the APIWrapper.js file. Both the client and server sides of the
interface present aspects of the SCO-LMS API adapter. The SCORM API wrapper
code is intended to provide a standardized interface for the SCO and isolate it
from the specific implementation of the SCO-LMS adapter. Each LMS is free to
implement the adapter differently, but all must support the same API
functionality to maintain SCORM conformance.
Figure 1 - Basic SCORM-conformant Training Environment
We explored
a number of alternatives to providing access to a ULM service within this architecture and
determined that the most efficient means is to “wrap the API Wrapper.” This
approach extends the SCORM API wrapper software to provide ULM-specific
operations as a side effect of the standard calls (see Figure 2). For example,
consider the process of storing data in the ULM. To accomplish this, the augmented
wrapper would monitor SCORM "SetValue()" calls in order to compile
the information necessary to instigate the related ULM posting operation. Thus, when specific
"SetValue()" requests are made (e.g.,
to the “cmi.interactions.n.result” data element), the enhanced wrapper functionality
would make a ULM PostEndorsements request via a separate interface to the ULM. This strategy makes
the ULM
operations completely transparent to the SCO logic and isolates changes in the
APIWrapper software. Extending the LMS’ API wrapper functionality is reasonable
as long as the standard SCORM communication interfaces for interacting with the
LMS are preserved.
|
Figure
2 - Wrapping the API Wrapper
|
Through our
partnership with Raytheon Technical Services Company (RTSC), we implemented a partial
integration of our ULM with a Training
Management System (TMS) based on Saba’s
Learning Suite 5.4. Specifically, we created public APIs that provided access
to the required range of ULM
functionality in a way that could be employed by multiple programming
languages. Using the TMS, we were able to launch an adaptive SCO, allow both
standard and adaptive SCOs to contribute to a common learner model, and allow
learner model data contributed by a standard SCO to affect the behavior of an
adaptive SCO.
References
1.
IEEE
1484.11.2 Standard for Learning Technology – ECMAScript Application Programming
Interface for Content to Runtime Services Communication. Available at: http://www.ieee.org/
2.
IEEE
1484.12.1-2002 Learning Object Metadata Standard. Available at: http://www.ieee.org/
3.
IEEE
1484.12.3 Standard for Extensible Markup Language (XML) Schema Binding for
Learning Object Metadata. Available at: http://www.ieee.org/
4.
IMS
Simple Sequencing Behavior and Information Model v1.0 Final Specification, IMS
Global Learning Consortium, Inc. Available at: http://www.imsglobal.org/.
5.
IMS
Content Packaging Information Model, Version 1.1.4 Final Specification. IMS
Global Learning Consortium, Inc. Available at: http://www.imsglobal.org/
6.
IMS
Content Packaging Best Practice Guide, Version 1.1.4 Final Specification, IMS
Global Learning Consortium, Inc. October 2004 Available at: http://www.imsglobal.org/
7.
Sharable
Content Object Reference Model (SCORM®) 2004 4th Edition. ADL Co-Laboratory, USA. Available
at http://www.adlnet.gov/
8.
Mödritscher,
F., Barrios, V.M.G., Gütl, C, and Maurer, H. (2004). Why do Standards in
the Field of E-Learning not fully support Learner-centered Aspects of
Adaptivity? Proceedings of World Conference on Educational Multimedia,
Hypermedia and Telecommunications (EDMEDIA) 2004, Lugano, Switzerland,
pp. 2034-2039.
9.
Wang,
H-C., Li, T-Y. (2004).
Considering Model-based Adaptivity for Learning Objects. Learning Technology
newsletter, 6, 2, Pages 9-11.
10.
Blackmon,
W., Brooks, J., Roberta, E., and Rehak, D. (2004). The Overlap and Barriers
between SCORM, IMS Simple Sequencing, and Adaptive Sequencing.” Learning
Systems Architecture Lab (http://www.lsal.cmu.edu/).
11.
Murray, W.R. (1991). An endorsement-based
approach to student modeling for planner-controlled intelligent tutoring
systems, Technical Paper,
AL-TP-1991-0030, Air Force Systems Command, Brooks Air Force Base, Texas.
James E. McCarthy
Sonalysts, Inc.
mccarthy@sonalysts.com
Roberta J. Scroggins
Sonalysts, Inc.
rjnewton@sonalysts.com
The Distributed ePortfolio Model
Innovations
in web technology are influencing learning collaboration so that we are
beginning to see a move from a user-led ‘push’ model, where the user parcels up
personal data and offers it to interested parties via a presentational
ePortfolio, to a ‘pull’ model where interested parties can be given permission
to extract personal data automatically from a learner’s ePortfolio, based on a
pre-agreed policy. This trend is being supported by emerging standards in web
service data security, including such developments such as JISC’s new
Leap2A[1].
Driven by
the increased interest in use of automated processes in domains such as AP(e)L
(Accreditation of Prior (experiential) Learning), recording and accreditation
of professional competence and decoupling learning from the institution, the
institution-free, distributed ePortfolio model is becoming seen as the norm.
There are associated issues, however: the greater the degree of automation, the
higher the perceived risks and concerns about user privacy. For example, data
extracted could be leaked to third parties, similar to the kinds of abuse of
data from social networking sites that have been seen in recent years. In the
light of these risks, the EU Framework 7 project TAS³ (Trusted Architecture for
Securely Shared Services) has been developing a trust framework which enables
sharing of data while maintaining respect for user privacy [2].
Breaking down barriers with SAMSON
The
JISC-funded SAMSON (Shared Architecture for eMployer, Student and
Organisational Networking) project is a collaboration between the two
Nottingham HEIs (the University of Nottingham and Nottingham Trent University)
and is developing a service-orientated environment to support lifelong learning,
building on emerging technologies and standards used to integrate ePortfolio
data [3]. SAMSON’s ecosystem approach enables liberation of data to allow use
in more flexible and dynamic applications focused on collaboration around
processes, rather than depending on the specific characteristics of the
ePortfolio, or the system, itself. The project is working with a number of
employers of varying sizes to interface with the universities via ‘windows’ on
to university data, some of which is personal ePortfolio data from placement
students.
Assuming a
compliance to open standards, use of the Leap2A ePortfolio standard and a
‘thin’ pull model enables information to be aggregated whatever the system. For
example, under the auspices of SAMSON, the University of Nottingham’s
Centre for International ePortfolio Development has been collaborating with
Pebble Learning (producers of the PebblePad ePortfolio [4]) on the JISC-funded
PIOP3 project [5]. Pebble Learning have developed an OAuth [6] method for
seamless Leap2A data retrieval from a learner’s PebblePad ePortfolio into the
SAMSON interface as viewable by the employer. The same SAMSON interface also
picks up data from the Mahara [7] ePortfolio via web services, thereby
providing an employer with a consistent view of employees’ learning data from
across different institutions and systems. In addition, Nottingham Trent
University are working
with Desire2Learn[8] to map their ePortfolio structures to Leap2A and perform
import/export of data. The University
of Derby is also working
with Pebble Learning on a separate project trialling use of Leap2A to export
data from their eAPEL system into a PebblePad ePortfolio; they envisage that it
may be possible to incorporate this into the SAMSON ecosystem at a later stage.
Building Up Trust with TAS³
The work in
SAMSON is rapidly opening up the use of data in the learning process for
sharing and use in wider collaborative processes. Management of data in this
way depends on the implementation of the TAS³ framework to create a trust
infrastructure within which the user’s personal data can be shared. This trust
framework is held together by common polices, and by monitoring of policy
decision and enforcement calls. In this model the data is tracked across the
entire framework; users are notified each time a service provider receives or
requests access to their data.
Selection
of which service providers in the network can access their data is driven by
users. Service selection is performed using the user’s selected trust policies;
these are then matched against service provider trust rankings managed by the
TAS³ infrastructure and generated from user feedback. Once access has been
granted, users also decide on the policies that secure what actions can be
performed on their data. These ‘sticky policies’ remain attached to the data as
it moves throughout the system, and the use of trust rankings allows users to
share experiences of service providers in the eLearning domain.
The
policies mandate the trust criteria that a service provider must fulfil in
order to be able to access the data, and subsequently what functions certain
types of service provider can perform on it. This functionality is restricted
according to service provider role and the specific element of data within the
data object. Monitoring of personal data use is made possible via a user’s
Dashboard, the information on which changes as service providers access and
make use of the user’s personal data.
The model
TAS³ presents to SAMSON is that of a learner-centric system where flexibility
of collaborative learning process can be achieved based on shared experience.
SAMSON is in turn applying this work, together with activity in the
standardisation domain, into work placement schemes in the UK’s East Midlands
region.
Conclusion
We see the
future use of ePortfolios being to act as data stores within wider distributed
applications. To enable this, a security framework has to be in place that
allows users to set and enforce policies to protect the personal information in
their ePortfolios. The implementation of TAS³ in Nottingham
is leading the way in illustrating how this can be achieved to empower users to
have control over how their personal data is used. The combination of the work
in TAS³ with cutting edge implementations of collaborative leaning in SAMSON
will present insights into the future demands of internet based collaborative
learning tools.
References
[1] Leap2A
homepage: http://wiki.cetis.ac.uk/LEAP2A_specification
[2] TAS³
homepage: www.tas3.eu
[3] SAMSON
homepage: http://www.jisc.ac.uk/whatwedo/programmes/
institutionalinnovation/workforcedev/samson.aspx
[4] PebblePad:
http://www.pebblepad.co.uk/
[5] PIOP_3
homepage: http://wiki.cetis.ac.uk/PIOP_3
[6] OAuth:
http://oauth.net/
[7] Mahara:
http://mahara.org/
[8] Desire2Learn:
http://www.desire2learn.com/
Tom Kirkham
University of Nottingham, UK
Thomas.Kirkham@nottingham.ac.uk
Kirstie Coolin
University of Nottingham, UK
Kirstie.Coolin@nottingham.ac.uk
Sandra Winfield
University of Nottingham, UK
Sandra.Winfield@nottingham.ac.uk
Stuart Wood
University of Nottingham, UK
Stuart.Wood@nottingham.ac.uk
Angela Smallwood
University
of Nottingham, UK
Angela.Smallwood@nottingham.ac.uk
Introduction
The introduction
of communication and information technology has revolutionized the way
journalism is conducted. Today one can claim that the majority of the work in a
journalism organization has at least one technology parameter. The internet has
become a vital part in relaying news to people. Every journalism organization
in now days ought to have a website on the WWW. The speed and the unlimited
space it offers has made the WWW one of the main channels for publishing news.
Data Visualization
Data
visualization can be characterized as the visual representation of data,
meaning information which has been abstracted in some schematic form, including
attributes or variables for the units of information (Wikipedia). The problem
is that there are many data visualization tools, data sources format sources,
people work with many different database and spreadsheet technologies, and the
tools to transform data sources into web-based visuals often require
programming skills that aren't available to the typical journalist. Thus in
most cases journalism organizations relay on experienced web developer to
produce data visualizations (De Groot, 2010). In order to overcome this problem
one can employ simple graphics that can be created in minutes and delivered for
free using web tools. There are ways to do basic visualizations with free tools
provided by Google and others, no programming required (De Groot, 2010).
Course objectives
The
objective of a two hour course on web design for postgraduate Journalism
students is to give them the necessary knowledge and expertise in using data
visualizations. The course was prepared by the staff of the Media Informatics
Lab in The Department of Journalism & MC.
Design rationale
The course
is based on free web tools. These tools include Goggle Spreadsheet (part of
Google Docs) and a free Content Management System (CMS), My Web Page Starter
Kit. The selection of Google Docs is based on the fact that Google spreadsheet
offers basic functions that are similar to Microsoft Excel with which most
users are familiar with. The users can also upload existing xls files and thus
work with a previously saved set of data. The free CMS was employed for some
time in the Media Informatics Lab, since it includes many features that make it
very attractive for teaching purposes. For example all data are stored in one
folder and thus one can easily collect lab exercises by simply copying the
files. Also by deleting all files from the previous folder one can reset the
CMS to its initial state, ready to be used by another student.
Learning settings
For the
purpose of this course each students is assigned a CMS. The CMS in use, is an
ASP.NET 2.0 based Content Management System. It requires installation on a
server running Microsoft Windows Server (the ASP.NET 2.0 can be installed
automatically with the optional updates). The administrator must activate the
ASP.NET and add the read permission for the ASPNET user in a specific
directory. Also students are expected to acquire Google accounts (which in many
cases already have).
Steps in the learning process
1) Students
log in and open Google Docs. After the insertion or upload of the data,
students can employ the chart function in order to generate the appropriate
chart. The chart is stored along with the data. Google Docs offers the function
of publishing the chart in any web site. It simply generates an HTML code that
can be embedded in any web page.
Figure 1 - Preparation of a Pie chart in Google Docs
Spreadsheet.
Figure 2 - Chart selection process
Figure 3 - Obtaining the necessary code to publish the
chart
2) The
students insert an HTML module in the CMS, turn on the HTML mode and paste the
code. When they turn on the view mode of the HTML module it displays the chart.
Because the chart is dynamically generated, data can be manipulated in real
time thus enabling students to publish real time data. Google Docs also offers
the possibility of publishing data tables with live data that can be updated at
anytime.
3) Students
are also encouraged to experiment with different types of charts that are
available in order to achieve the best result.
Figure 4 - Publishing a pie chart on a CMS.
The importance of live update
One of the
most important parameters of successful journalism is the speed of conveying news
to readers. This can be accomplished if one is working with tools that operate
with live data. That way, when data is updated, the visualizations are updated
as well, without having to do any additional work (for example generate a new
chart). The majority of the available data visualization packages allow users
to create an XML file from a dataset, and consequently an appropriate chart.
But that means that when the data set is changed the whole operation must be
repeated and the updated chart must be published again on the web server.
Google Spreadsheets and Gadgets is one of the best ways currently available to
let non-programmers build basic visualizations of live data (De Groot, 2010).
Conclusion
It is
obvious that Google Docs is an important tool for teaching (and also doing)
data visualization. Its features are expected to be enriched since Microsoft is
preparing to release in early September the web edition of Microsoft Office
2010 which is expected to have similar features. Finally we must also mention
that there are other Google web applications that can be embedded in dynamic
web pages, like Google maps that let users add maps of any area of the world
that give direction for a certain geographical location.
References
Len De Groot, (2010), Data Visualization:
Basics, Knight Digital Media Center
Multimedia Training.
My Webpage Starter Kit, available at http://www.codeplex.com/Wiki/View.aspx?
ProjectName=MyWebPagesStarterKit
Wikipedia (accessed June 2010) http://en.wikipedia.org/wiki/Data_visualization.
Andreas Veglis
Aristotle University of Thessaloniki,
Greece
veglis@jour.auth.gr
