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Learning Technology publication
of IEEE Computer Society's |
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Volume 11
Issue 1 & 2 |
ISSN
1438-0625 |
January-April
2009 |
Just-in-time mobile learning model
based on context awareness information
Mobile learning with Open Learning Environments at Shanghai Jiao Tong
University, China
Around an Inspiring Virtual Learning
World in Eighty Days.
A Mobile Quiz Platform to Challenge Players’ Knowledge on Mobile Devices
Mobile Widgets for Teacher Awareness in Learning Games
Towards Web-based Remote and Mobile Q&A System – WeQaS
Enhancement of Mobile Learning Using Wireless Sensor Network
Global Optimisation and Mobile Learning
Exploring Students’ Perceptions
toward Using Interactive Response System
Call for Papers: Inaugural issue of
the Journal of Applied Research in Workplace E-learning
Welcome to the January-April 2009 issue of Learning
Technology.
Mobile learning is used in many different contexts and
areas. This issue discusses current research about new and emerging mobile
learning technologies, and especially its usage in extreme situations. The
issue introduces papers dealing with frameworks for mobile learning, practical
learning technology solutions, and summaries of research about particular
topics.
The first article, by Romero and Wareham, discusses
the usage of mobile devices for just-in-time learning such as in emergency
situations. Romero and Warham propose a model that incorporates context
information and can be used as mirroring, meta-cognitive or guidance tool.
Subsequently, Borau, Ullrich, and Kroop introduce a
project which helps to teach large numbers of adult learners in China. The
proposed framework aims at facilitating teachers and learners to access and
combine different tools into a personalized mobile learning environment.
The next three papers deal with mobile game-based
learning. Kickmeier-Rust introduces the research project 80Days, which aims at
developing psycho-pedagogical and technological foundations for successful
digital educational games. Mobility is considered in the game on one hand
through the virtual mobility of the players, who need to investigate different
places on earth in the game, and on the other hand due to its technological
basis. Wong, Wang, Tam, Cheung, Lui, and Fok developed a mobile quiz-game
system which asks students questions on their mobile devices. Their paper describes
the design and possible uses of the quiz system in mobile learning and shares their
experiences in system development. Marty and Carron also introduce a mobile
learning game, namely the Pedagogical Dungeon, and focus in their article
mainly on issues such as immersion, mobility, and supporting teachers to
monitor students’ progress while playing the educational game.
Subsequently, Ren, Liu, and Ren propose a web-based
remote and mobile question and answer system, which aims at improving time
efficiency for students when asking questions to teachers as well as allows the
efficient management of these communication notes.
In the next article, Chang, Wang, and Lin discuss the
usage of wireless sensor networks for improving the usability, flexibility and
variability of mobile learning. They propose a framework and describe two
practical examples applying this framework, one in a classroom and the other
one in a city-wide environment.
Chiong and Weise discuss the application of global
optimisation techniques in mobile learning. They provide insights about how
global optimisation techniques can be used to improve mobile learning and point
out some of the relevant works in this area.
The last article in this issue belongs to the regular
article section and deals with interactive response systems. Liu presents a
study about students’ perception when using interactive response systems within
the class.
Furthermore, we would like to draw your attention to
the Call for Papers of the Journal of Applied Research in Workplace E-learning,
which can be found at the end of this issue.
We hope that this issue helps in keeping you informed
about the current research and developments of learning technologies,
especially in the area of mobile learning, and can stimulate further discussions,
research, and developments in this area.
We also would like to take the opportunity to invite
you to contribute your own work in progress, project reports, case studies, and
events 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.
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Sabine Graf Athabasca University, Canada
Charalampos Karagiannidis University of Thessaly, Greece |
Just-in-time mobile learning model based on context awareness information
Abstract: In urgent situations, the value of mobile learning is not only ubiquitous, perpetual availability,
but just-in-time learning based on context aware information and guidance. Our proposed
contribution is a model based on mobile-aware services that adapt to the
learning environment, embracing contextual information, mirroring levels,
guidance, and metacognitive support adaptable to learner self-regulation in
specific crisis situations.
Keywords: Just-In-Time Mobile Learning, Ubiquitous learning,
Context Awareness, Flexible Learning Environment
Just-in-time learning in extreme situations
Learning with mobile devices or mobile learning (m-learning) expands
e-learning capabilities to a much wider range of teaching and learning
contexts, including extreme situations beyond the realm of normal desktop
applications. In crisis situations, Just-In-Time Learning can help users access
knowledge and learning in less time, in a manner adaptable to both their requirements
and the learning context.
In traditional learning contexts, we normally face learning tasks where
temporal constraints are less significant; or at least, we do not confront an
extreme sense of learning urgency. However, given that learning is a major form
of adaptation to the environment (Piaget, 1936), we can consider extreme
situations where fast learning is essential: poisoning, first aid or even,
unexpected baby delivery. In cases when we are alone and do not know how to
proceed, we typically ask for external expertise (emergency numbers) allowing
us to learn and act via verbal interaction and guidance. Considering the
multimedia and web-access capabilities of most mobile devices, enriched
interaction can be employed to reduce learning cycles and more easily contend
with crisis situations successfully.
Mobile-aware developments form an emergent paradigm, which has recently
been applied to mobile learning (Lonsdale et al., 2003; Chen, Chang & Wang,
2008). In this extreme context, the main concern of the users is not learning
in the sense of a permanent change in behaviour (Domjan & Burkhard, 1986),
but how to effectively solve a problem for which he/she needs new knowledge.
Independent of the basic problem, the result of his/her experience will likely
convey learning in a relatively permanent manner, given the advantages of
experiential learning (Dewey, 1938). Providing new knowledge in this informal
learning situation within a mobile-aware Flexible Learning Environment could
allow the user to structure learning outcomes and capitalize them in the
learners’ ePortfolio (
Context-aware mobile learning model for just-in-time learning
Mobile learning has been approached as an e-learning modality with
“complete independence of both location and time” (Holzinger et al., 2005),
where more personalized learning contents could be provided, individually
enhancing ubiquity capabilities. In extreme situations the main added value of
mobile learning is the possibility to collect awareness data, display it,
analyse it, and guide the user considering the Context Awareness (CA) and
Activity Awareness (AA) data analysis to propose just-in-time learning
solutions. To take into account this contextual information, we need Flexible
Learning Environments (FLE) allowing personalized learning solutions, adapted
both to the mobile device, the learner and the context.
Figure 1:
Just-in-time mobile learning model
As can be seen in Figure
In these contexts, the mobile device could act as a mirroring,
metacognitive or guidance tool, according to Soller et al. (2004)
categorisation of computer’s role in the learning regulation process. Firstly,
as a mirroring or awareness tool, the mobile device could display CA and AA,
allowing the learner to self-evaluate his/her current learning needs. Secondly,
in a metacognitive mode, the mobile device could analyze CA and AA information
and display the results of the analysis in order to help the learner to decide
how to design his/her personal solution considering the analysis. Thirdly, if
the mobile device not only analyses, but also integrates an artificial agent
with expertise rules based on the Activity Model, that could provides guidance
on the just-in-time learning solution configuration. As such, the increased
multimedia abilities of most mobile devices are leveraged both as communication
and computational devices. Not only does it permits richer information
gathering and analysis as a registration and diagnostic device, but also as a
communication media to an external expert, and a media to convey new knowledge
to the user.
Concluding remarks
Learning needs time; however, in extreme situations time is scarce. In
critical scenarios, context just-in-time mobile learning could provide a
ubiquitous and flexible learning solution adapted to the context. The increased
media richness of most mobile devices can be leveraged as computational and
communication services embracing contextual information, mirroring levels,
guidance, and metacognitive support adaptable to learner self-regulation in
specific crisis situations.
References
Chen, G. D., Chang,
C. K., Wang, C. Y. (2008). Ubiquitous learning website: Scaffold learners by
mobile devices with information-aware techniques. Computers & Education,
50, 77-90.
Butler, P. (2006).
A Review of the Literature on Portfolios and Electronic Portfolios. New Zealand: Creative Commons Attribution,
Non Commercial Share Alike 2.5.
Dewey, J. (1938).
Experience & education.
Domjan, M. and
Burkhard, B. (1986) The principles of learning and behavior. 2nd edition.
Pacific Grove, CA: Brooks/Cole.
Holzinger, A.,
Nischelwitzer, A. & Meisenberger, M. (2005) Lifelong-Learning Support by
M-learning: Example Scenarios. Association of Computing Machinery ACM eLearn
Magazine, 5, 12, Online available. (ISSN 1535-394X)
Lonsdale, P, Baber,
C, Sharples, M and
Piaget, J. (1936)
La naissance de l'intelligence chez l'enfant. Neuchatel, Delachaux et Niestlé.
Soller,
A. Martinez, A. Jermann, P. and Muehlenbrock, M. (2005) From
Mirroring to Guiding: A Review of State of the Art Technology for Supporting
Collaborative Learning. International Journal of Artificial Intelligence in
Education, 15:261-290, 2005.
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ESADE ESADE |
Mobile learning with Open
Learning Environments at Shanghai Jiao Tong University, China
The recently started project ROLE (Responsive Open
Learning Environments) aims at delivering and testing prototypes of highly
responsive technology-enhanced learning environments, offering breakthrough
levels of effectiveness, flexibility, user-control and mass-individualisation
[1]. The ROLE consortium consists of 16 internationally renowned research
groups and companies and is funded by the European Commission. ROLE actively
seeks input by third parties and has created a discussion group at LinkedIn to
facilitate contributions [2].
ROLE researches adaptivity and personalization in
terms of content and navigation and the entire learning environment and its
functionalities. This approach permits individualization of the components,
tools, and functionalities of a learning environment, and their adjustment or
replacement by existing web-based software tools. Learning environment elements
can be combined to mashup components and functionalities, which can be adapted
by individual learners or groups to meet their own needs and to enhance the
effectiveness of their learning. This can help them to establish a livelier and
personally more meaningful learning experience. The validity of ROLE's research
will be assessed in several real-life testbeds.
The largest of the testbeds will be implemented by
Shanghai Jiao Tong University (SJTU). In a developing country such as China,
one foremost goal is to enable access to education to the largest number of
citizens possible. In the recent years, the Chinese government significantly
invested in tertiary education with the effect that the number of graduates at
all levels of higher education in China has approximately quadrupled over 6
years [3]. One of the main research questions driving research at the
e-learning lab at SJTU is how to use technology-supported learning to manage
such large numbers of students.
Solutions that will be developed in ROLE have the
potential to significantly improve teaching and learning under these
circumstances. There, especially mobile access is crucial, less because of
curiosity-driven research interests due to the novelty of mobile devices, but
out of societal necessity. In developing countries, the penetration rate of
mobile phones surpasses that of home computers significantly. Recent figures by
the China Internet Network Information Center show this trend quite clearly
[4]. The July 2008 survey reports 84.7 million computers connected to the
Internet (including desktop and laptop computers) compared to 592 million
mobile phone numbers (growing at a rate of 18%). Mobile access to the Internet
is explored by an increasing number of users. Of the 253 million Internet users
in China, about a third (84.7 million) surf the Web with their mobile phones,
22.65 million more than in the first half of 2008. The proportion of desktop
Internet users is actually dropping compared to the proportion of mobile
netizens. This trend is visible elsewhere, too. According to the International
Telecommunication Union [5], in 2007 the fixed broadband penetration rate in
Africa was 0.2%, compared to 27% mobile penetration rate. This clearly shows
that the development of learning systems usable by mobile devices is relevant
world-wide. The SJTU testbed will thus enable the ROLE consortium to learn
about the challenges of mobile Personal Learning Environments (PLE).
More specifically, the ROLE framework and tools will
be assessed at the online college of SJTU (Online-SJTU). A great majority of
the students in this online college are adult learners who study for their
bachelor degree. Most of them work full-time and study in the evenings and on
the weekends. Due to their busy schedule, they are often not able to attend
classes in person. Thus, all classes offered in this college are also broadcast
live via the Web. Students can tune in to the live classes or the recordings
from their desktop or laptop computer, but also from the mobile phone.
In China, teacher-centered teaching is still prevalent
[6]. In contrast, ROLE will allow students to be more active and to take more
control about their own learning processes. How this could look like we
illustrate in the following Scenario:
Teacher Li is a novice teacher, and still
inexperienced with ICT. He wants to increase active language production of his
students in a "English News" class. When preparing his class, Li
browses through the different "collaborative problem solving"
patterns stored in the ROLE framework. The "joint text production"
pattern catches his attention and he decides to use it for his students to produce
news articles. He adds the pattern to the course PLE. The pattern then adds the
required tools and a guide for the teachers and students that explains them how
to best use the tools in this kind of activity. Here, the tools include a
mind-mapping tool to derive jointly the structure of the article, a
collaborative text editing tool to write it, a Flickr integration to share
photos to illustrate it, and a forum for general feedback and reflection about
this activity. Later that week in the class room, Li makes the PLE page
accessible to his students and the collaborative work starts. The students are
now able to interact with their peers, whether present in the classroom, at
home or on a business trip. For instance, during the day, student can use their
mobile device to upload pictures that illustrate the news story.
Of course this scenario is just one small example of
many. However it serves to illustrate central features from a user side:
teacher, but also students will be able to access the tools they want to use
and to combine the tools to form their Personal Learning Environment.
References
[1] EU-Project
Responsive Open Learning Environments (ROLE):
http://www.role-project.eu
[2] ROLE Community at LinkedIn: http://www.linkedin.com/groups?gid=1590487
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Kerstin Borau & Carsten Ullrich Dept. of Computer Science and Engineering Shanghai Jiao Tong University Haoran Building, 6/F, 1954 Hua Shan Road 200030 Shanghai, China eMail: ullrich_c@sjtu.edu.cn Sylvana Kroop Dept. of Technology & Knowledge Centre for Social Innovation Linke Wienzeile 246 1150 Vienna, Austria eMail: kroop@zsi.at |
Around an Inspiring Virtual Learning World in Eighty Days
Computer games have become a very successful and
important part of today’s entertainment landscape. With increasing time people
spend on computer games, the idea of utilizing the motivational and didactic
potential of those games for educational purposes is getting more and more
popular and fascinating. The European research project 80Days[1]
is inspired by Jules Verne’s novel “Around the world in eighty days”. The
project started in April 2008 and aims at developing psycho-pedagogical and
technological foundations for successful digital educational games – successful
in terms of educational effectiveness as well as financial turnovers.
In the focus of psycho-pedagogical research efforts is
a scientifically sound framework for a non-invasive assessment of knowledge and
learning progress embedded in a game and a subsequent comprehensive adaptation
to the learner on micro and macro levels. The micro level refers to subtle
educational interventions such as feedback or hinting within specific learning
situations. The macro level, on the other hand, refers to an educationally
appropriate sequencing and pacing of learning situations tailored to the
individual learner.
In the first period of the project, research made
significant progress by elaborating a joint formal model of cognitive
assessment of learning progress (on the basis of Competence-based Knowledge
Space Theory) on a probabilistic and non-invasive level, the provision of
suitable support and interventions, and open interactive adaptive storytelling
(cf. Kickmeier-Rust, Hockemeyer, Albert, & Augustin, 2008). From a
technical point of view, in the first project period an accurate analysis of
learning and game design requirements has been carried out and the results have
constituted the starting point for the study on system architectures and
software modules that could have best fulfilled the requirements. Research in
the area of open, interactive storytelling achieved a technical realization of
the developed formal model in form of a story engine, which implements the psycho-pedagogical
model and which drives and adapts the game (Kickmeier-Rust, Göbel, &
Albert, 2008). Overall, psycho-pedagogical and technical efforts lead to a
compelling demonstrator game teaching geography. Significantly, this
demonstrator also represents the first steps towards achieving a multi-adaptive
system that not only adapts discrete elements of the game towards educational
purposes, but also adapts the story to accommodate wider educational
objectives.
The demonstrator game is teaching geography for a
target audience of 12 to 14 year olds and follows European curricula (Figure 1).
The game design includes premises, concepts, metaphors, structures, gameplay,
learning objectives, contents, background story, game characters, visual design
and game props. In concrete terms, an adventure game was realized within which
the learner takes the role of an Earth kid at the age of 14. The game starts
when a UFO is landing in the backyard and an alien named Feon is contacting the
player. Feon is an alien scout who has to collect information about Earth. The
player wants to have fun by flying a UFO and in the story pretends to be an
expert in the planet earth. He or she assists the alien to explore the planet
and to create a report about the Earth and its geographical features. This is
accomplished by the player by means of flying to different destinations on
Earth, exploring them, and collecting and acquiring geographical knowledge. The
goal is to send the Earth report as a sort of travelogue about Earth to Feon’s
mother ship. Finally, the player sees through the alien’s game (of preparing
the conquest of the earth) and reveals the “real” goal of the game: The player
has to save the planet and the only way to do it is to draw the right
conclusion from the traitorous Earth report. Therefore, the game play has got
two main goals: (a) to help the alien to complete the geographical Earth
report, and (b) to save the planet, which is revealed in the course of the
story, when the player realizes the true intention of the alien. This
demonstrator game illustrates an unconventional meaning of mobile learning; it
focuses on learning through virtual mobility. Of course, 80Days also considers
a more conventional approach to mobile learning. The technological basis for
the micro and macro adaptive features developed in the project is individual
and based on abstract services that communicate via TCP/IP. This technological
approach enables a broad online-based application of this technology,
independent from the game technology (Pierce, Conlan, & Wade, 2008).
Figure 1: Screenshot
of 80Days’ first demonstrator game teaching
geography for a target audience of 12 to 14 year old children.
The demonstrator game was subject of in-depth
evaluation activities. The evaluation work has been geared towards its
objectives of defining an evaluation framework and of implementing an array of
evaluative activities. In close collaboration of different disciplines, the
initial game design concepts were validated with a carefully designed questionnaire,
which has been administered at two major locations – Cologne in Germany and
Leicester in England. Results of altogether 281 responses (139 in German and
142 in English) have meticulously been analysed and documented. Furthermore,
the evaluation plans with adjustments and fine tuning with regard to certain
situational constraints such as the technical infrastructure at local schools
was implemented. The validation studies have been implemented in two and four
schools in England and Austria, respectively, resulting in about 100 datasets.
Multi-method approaches have been applied to analyse the empirical data thus
collected.
Empirical findings yielded beneficial effect of
playing the game, as evident and an overall satisfying usability and user experience.
Implications
for the future development of the game prototypes and the design of evaluative
activities have been drawn. In particular, the theoretical knowledge and
practical experience thus gained will contribute to advancing the research area
of evaluating usability and user experience in digital educational games.
References
Kickmeier-Rust, M. D., Göbel, S., & Albert, D. (2008). 80Days: Melding adaptive
educational technology and adaptive and interactive storytelling in digital
educational games. In R. Klamma, N. Sharda, B. Fernández-Manjòn, H. Kosch,
& M. Spaniol (Eds.), Proceedings of the First International
Workshop on Story-Telling and Educational Games (STEG'08) - The power of
narration and imagination in technology enhanced learning, September
18-19, 2008, Maastricht, The Netherlands.
Kickmeier-Rust, M. D., Hockemeyer, C., Albert, D., & Augustin, T.
(2008). Micro
adaptive, non-invasive assessment in educational games. In M. Eisenberg,
Kinshuk, M. Chang, & R. McGreal (Eds.), Proceedings of the second IEEE International Conference on Digital Game and Intelligent Toy
Enhanced Learning (pp. 135-138), November 17-19, 2008, Banff,
Canada.
Peirce N.,
Conlan O., & Wade V. (2008). Adaptive educational games: Providing
non-invasive personalised learning experiences. Proceedings of the second IEEE International Conference on Digital Game and Intelligent Toy
Enhanced Learning (pp. 28-35), November 17-19, 2008, Banff, Canada.
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Michael D. Kickmeier-Rust Department of Psychology University of Graz Austria |
A Mobile
Quiz Platform to Challenge Players’ Knowledge on
Abstract: Many new mobile technologies
including the 3G, WiFi or mobile TV have opened up unprecedented learning
opportunities on mobile devices. In addition, such technologies empower the
rapid growth of new fields of research like the edutainment for educational
entertainment. In a project awarded by the Hong Kong Wireless Development
Center, we developed a mobile quiz game system on 3G mobile phone networks in
China, Hong Kong or other countries to facilitate learning anytime and
anywhere. Our developed mobile quiz system is so generic that it can be readily
extended to any wireless network. In this paper, we discuss about the design
and possible uses of our quiz system in mobile learning, and also share the
relevant experience in system development with the evaluation strategies
carefully examined. In 2008, our project also received the Bronze Award of the
Hong Kong ICT Awards – Best Lifestyle. After all, our work shed light on many
interesting directions for future exploration.
Introduction
New telecommunication technologies or services, such
as the High-Speed Downlink Packet Access (HSDPA), IEEE 802.11 based products or
mobile TV, are reshaping our living. With the availability of powerful mobile
devices connected to a high-speed wireless network, many attractive mobile
learning applications [3] realizing the concept of learning anytime and
anywhere that can be particularly useful for students to continue learning at
home during the outbreaks of new pandemic such as the SARS or lately swine flu
in recent years, and actively sought the world-wide attention of educators,
students, lifelong learners or professionals in various disciplines. Among many
successful applications, the Cellphedia [1] is a Mobile Social Software
(MoSoSo) developed in the
In response to a call for applications on the China’s
3G network by the Hong Kong Wireless Development Center in 2007, we developed a
mobile quiz game platform based on the concept of game rooms with real-time
synchronization and the client-server model targeted for a mass of thousands of
players participating in any specific event of the Beijing Olympic Games 2008.
In addition, our project also received the Bronze Award of the Hong Kong ICT
Awards – Best Lifestyle in 2008. Our
mobile quiz system is so generic that it is transparent to the underlying
network architecture, and can be easily extended to the WiFi or other wireless
network. We discuss in detail about the design and possible uses of our quiz
system in mobile learning, and also share the relevant experience in system
development with the evaluation strategies carefully examined. After all, our
project shed light on many interesting directions for future exploration.
This paper is organized as follows. Section 2 details
the system architecture design of our mobile quiz system on 3G mobile phones or
other mobile devices. Section 3 considers various evaluation strategies on our
developed quiz system based on different criteria. Lastly, Section 4 summarizes
our work and sheds lights on future directions.
System Architecture and
Services
The system architecture of our revised mobile quiz
system is shown in Figure 1. Basically, our mobile quiz system includes the
following components:
- Mobile
Learning Platform Server;
- Administration
Console Portal;
- Result
Display Unit.
Figure 1: The
System Architecture of Our Mobile Quiz Platform
After registration and successful login, the Mobile
Learning Platform Server will push some relevant questions, possibly embedded
with some video clips, for the user to answer on any mobile devices including the
Sony PSP gaming device. The server will only display the correct answer for
each round only when all the answers are received from the registered mobile
phone or timeout occurred. The Administration Console is to monitor the
activities of individuals or groups of players, and the network traffic.
Besides, it provides an interface for the administrator to dynamically enter
new question sets into the question bank online. The Result Display Unit is
mainly to display the latest results/scores attained by the players, and more
importantly the statistics of choices such as correct versus wrong answers
selected by the players that should be useful for an instant analysis on the
spot.
Prototype Implementation
& Evaluation
To demonstrate the feasibility of our proposal on
different platforms, we used the Java 2 Micro Edition (J2ME) technology to
build our mobile quiz system containing various game rooms running on a Mac
server that can be accessed through any J2ME-enabled 3G mobile phones. We spent
around 4 man-months to complete the implementation and testing of our mobile
quiz system. A project website [2] was set up to allow the downloading of a
client program (.jar) for installation on any mobile devices to access our
mobile quiz system as shown in the picture below.
Figure 2:
Students from 18 schools are using our mobile quiz platform in a local school contest
As our mobile quiz system is generally applicable to
any selected event or course, a detailed evaluation will be conducted in the
late 2009 to analyze the effectiveness of the mobile quiz system on motivating
and/or enhancing our students’ experience in relevant Engineering courses
including the Human-Computer Interaction or Distributed Computing Systems.
Conclusion
In this paper, we reported a completed project in
which we have successfully developed a 3G or WiFi based mobile quiz system to
facilitate learning/revision anytime and anywhere. Our developed mobile quiz
system is so generic that it can be readily extended to any wireless network. The
design and possible uses of our quiz system in mobile learning, and also
sharing the relevant experience in system development have been considered.
After all, our work shed light on many interesting directions such as the
integration of our mobile quiz platform with existing e-learning systems or
powerful search engines for further exploration.
References
[1] The Cellphedia development team, The
Cellphedia website, maintained by L. Garcia, Retrieved: November 12, 2007, from
http://www.cellphedia.com.
[2] The Mobile Quiz System development team,
The
[3] T.T. Goh, Kinshuk & Taiyu Lin.
“Developing an adaptive mobile learning system” In K.T. Lee & K. Mitchell
(Eds.) Proc. of the International Conference on Computers in Education 2003,
Hong Kong, December 2-5, 2003, p. 1062-1065.
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Jade Wong Department of Electrical & Electronic Engineering The University of Hong Kong, Hong Kong Tony Wang Department of Electrical & Electronic Engineering The University of Hong Kong, Hong Kong Vincent Tam Department of Electrical & Electronic Engineering The University of Hong Kong, Hong Kong S.W. Cheung Department of Electrical & Electronic Engineering The University of Hong Kong, Hong Kong K.S. Lui Department of Electrical & Electronic Engineering The University of Hong Kong, Hong Kong Wilton Fok Department of Electrical & Electronic Engineering The University of Hong Kong, Hong Kong |
Mobile Widgets for Teacher
Awareness in Learning Games
Abstract: The paper describes examples of
game-based learning environments, and focuses on certain issues which need to
be addressed in these environments, such as teacher monitoring of students and
immersion. The advent of mobile devices will enable new usages for teachers in
learning games.
Introduction
Our research work deals with the development of new
learning environments. We are particularly interested in studying the different
aspects linked to user awareness in these environments. The emergence of online
multiplayer games has led us to apply the metaphor of exploring a virtual
world, a dungeon, where each student embarks on a quest in order to collect
knowledge related to a learning activity. This association of games and
pedagogical contents must ensure a coherent world in which a learning session
can take place, i.e. a set of activities can be proposed to the users in a
logical order. It is particularly important in this approach to create acute
and intuitive awareness of the on-going activity for all the participants, and
especially for the teacher. This awareness can be context-dependent, e.g. it
can vary according to geographical information.
An example of a Learning Game: the Pedagogical Dungeon
Over the last few years, our team has developed
several learning environments [1], [2], [3], and has experimented with them
with students in our university, in real learning situations. Figure 1 shows a
screenshot of the pedagogical dungeon, a learning environment used with
students for learning in various domains.
The dungeon represents the place where the learning
session takes place. Each room of the dungeon represents a place where a given
activity can be performed. Resources are accessible in the room and a quiz has
to be answered to open new doors. The dungeon topology thus represents the
overall scenario of the learning session, i.e. the sequencing between
activities. There are as many rooms as actual activities, and the rooms are
linked together through corridors, showing the attainability of an activity
from other ones [4].
Need for observation
From this work, we have already observed that it is
essential for Computer Game-Based Education to offer the possibility of
monitoring the activity performed by the students and of obtaining information
or feedback about it. For example, being aware of the learning progression of
each student is an important goal for the teacher. S/he wishes to be warned of
unexpected situations or particular behaviour: a student is in difficulty;
there are too many interactions within a group of people; there is not enough
communication in a collaborative task. Being aware of these particular
situations helps the teacher to adapt her/his subsequent actions, that is to
say the learning session. Hopefully, in computer-based learning environments,
participants leave traces that can be used to collect clues, providing the
teacher with awareness about the on-going activity. These traces reflect
in-depth details of the activity and can reveal very accurate hints for the
teacher [4], especially for regulation.
Figure 1: A room in the pedagogical dungeon
Immersion
Traces of activity can be computed to better
understand the on-going learning activities, and the results (often presented
through indicators) provide the teacher with valuable information. The problem
is that most of the time, the teacher has a role in the game (providing help,
validating answers, changing the accessible documents). Consulting this
additional information provided through indicators results in a cognitive
overload. We have pointed out in [5] how to remain immersed in a learning game
by directly representing these indicators or hints for the teacher in the game.
Mobility
New ways of learning entail new habits and usages. One
of them is mobility. The dungeon enables several activities to proceed in
virtual or real places. In some scenarios, we can envisage the learners moving
in order to perform certain activities (e.g. a quest in a real museum, with
collaborative aspects). The teacher also needs to be aware of what is going on,
and we should gather and adapt the above-mentioned indicators in order to
present them on a mobile device, e.g. a PDA. A GPS is available in such devices
and thus provides geographical information concerning the various learners
equipped with them. We use this information in order to adapt the teacher
awareness: when approaching a particular student, some associated information
(performance of learning activities by this student, percentage of failure) is
displayed on the teacher’s device. The teacher can thus better adapt the
interaction with this student.
Conclusion
Learning Games are interesting environments in which
the teacher needs to remain aware of the progression of a learning session.
Allowing mobility in Learning Games brings a new dimension to these
environments, and can also provide additional geographical information used to
provide the teacher with better contextual awareness. We study these features
in the “Learning Games Factory” project, funded by the CEC. A set of widgets
dedicated to collaboration indicator representation for the teacher is
currently being developed, and experiments are scheduled for autumn 2009.
References
[1] JC. Marty, JM. Heraud, L. France, T. Carron,
“Matching the Performed Activity on an Educational Platform with a Recommended
Pedagogical Scenario: a Multi Source Approach”, Journal of
Interactive Learning Research, special issue on Usage
Analysis of Learning Systems: Existing Approaches and Scientific
Issues. Vol 18, n° 2, April 2007, Edited by
AACE Publications, ISBN 1093-023X, pp 267-283.
[2] L. Kepka, JM Heraud, L. France, JC. Marty, T. Carron, “Activity
Visualization and Regulation in a Virtual Classroom”, In Proc. of the 10th
IASTED International Conference on Computers and Advanced Technology in
Education (CATE 2007), Beijing, China, October 2007
[3] G.-C. Loghin, T. Carron T., JC. Marty, MF. Vaida, “Observation and
adaptation of a learning session based on a multi-agent system”, In Proc of the
IEEE International Conference on Intelligent Computer Communication and
Processing, Aug. 2008, Cluj-Napoca, Romania
[4] T. Carron , JC. Marty, JM. Heraud, “Teaching with Games Based
Learning Management Systems: Exploring and Observing a Pedagogical Dungeon”,
Journal Simulation and Gaming, special issue on eGames and Adaptive eLearning.
A practical Approach. Vol 39, n°3, pp353-378, sept 2008
[5] E. Gendron, T. Carron, JC. Marty, “Collaborative Indicators in
Learning Games : an immersive factor”, In Proc of the 2nd European Conference
on Games Based Learning, Barcelona, Spain 16-17 October 2008
|
Jean-Charles Marty Syscom Laboratory, University of Savoie, France Jean-Charles.Marty@univ-savoie.fr
Thibault Carron Syscom Laboratory, University of Savoie, France Thibault.Carron@univ-savoie.fr |
Towards Web-based Remote and
Mobile Q&A System – WeQaS
Abstract: In this article, we analyze the disadvantages in traditional face-to-face question and answer activities usually in office hours. To overcome its disadvantages, a web-based remote mobile Q&A system – WeQaS is proposed. Through a case study, we find that this sort of system can improve time efficiency and productivity, backup Q&A communication notes, invoke students’ enthusiasm, and especially, support mobile distance learning.
Keywords: Mobile Learnging, Distance Learning, Remote Q&A System, Web-based
Eduction
Introduction
Question and Answer (Q&A) is a frequent
educational activity between students and teachers. As lecture time is limited
to accommodate only few on-site questions, most students always hope to ask
questions after class in regular time. Teachers normally reserve office hours
after the lecture to answer students’ questions encountered in study. However,
on one hand, such a face-to-face Q&A is unavailable to remote students. On
the other hand, even though they can make conversations by phone, they still
feel inconvenient to exchange handwriting notes. Furthermore, a traditional
face-to-face Q&A has some disadvantages as follows:
1)
Low efficiency and productivity. Most students may ask
similar questions, but the teacher has to answer these questions many times. It
wastes office time. Thus, both efficiency and productivity are low.
2)
Lack of documentation. The Q&A details are not
documented during the office hours. Because teachers may not have enough time
to write down answers, students have to scribe answers but the scribed notes
may not catch exactly what teachers mean.
3)
Potential Loss. To avoid congestion in office,
teachers always set up a timeslot for each student. This may result in heavy
communication overhead to negotiate a time slot. Moreover, some students who
are unable to finish the conversation within assigned time slot will have to
stop suddenly and leave. It is always a frustrated experience for students and
may result in none interest for further Q&A.
To deal with the above problems in the traditional
face-to-face Q&A system, we present some ideas on designing a web-based
remote mobile Q&A note system – WeQaS, to facilitate communications between
remote students and teachers, and both of them can be mobile users.
Web-Based Remote and Mobile Q&A System
The design objective is to support on-line
document-enabled Q&A system for remote and mobile access. The Google mobile
[1] provides more recent advances in services and development tools.
The major modules of WeQaS are listed as follows:
1)
Account management. A teacher can initiate accounts
and authorize access rights to students. Or, students create their account by
providing their student ID.
2)
Login. Only authorized students and the teacher can
access the system.
3)
Appending questions. Students can append questions in
the system which are displayed anonymously or by name, depending on students’
preference. The questions can be read by all students or only by teacher.
4)
Attaching answers. The teacher can attach answers to
corresponding questions. The question and answer modules can be edited simultaneously.
5)
Classifying. The teacher can rate the importance of
the questions according to her experiences and current questioning frequency.
The highly rated questions will be highlighted or replicated to a separate
column called Frequently Questioned Answers (FQA). Several keywords are
assigned to questions and answers for classification.
6)
Note management. It provides management functions of
the notes in Q&A system, such as search, sort, highlight, hide and export.
The contents can be searched by keywords. The documented Q&A, called notes,
can be sorted by time or keywords. The teacher can highlight some notes for
emphasis or hide some notes for privacy. All notes can be exported to local
machine.
Case Study
We firstly use freeware Evernote [2] to do a case
study. Although our proposed system WeQaS has many distinctions with it,
feedback from students can gain some experiences and guide further design.
Using Evernote, students can post the questions in
notes and the teacher can manage the notes, e.g., categorization, sort, etc.
The teacher can append the answer behind the question. The important notes can
be moved to a separate folder. More specifically, two major types of notes are
provided in the system: one is text; the other is ink, which is similar to a
handwriting scratch file. The attribution can be assigned to a given note, such
as title, author, date, and tag (category).
Note that Evernote is not a tailored design for remote
and mobile Q&A with respect to some shortcomings. It cannot hide notes.
That is, all notes can be read by all authorized users so authorized user’s
privacy is not protected. The access control policy is rough. All authorized
users can modify the notes or attach answers. Whereas, our design surmounts
such weakness and together supplements some further improvements.
Comparisons
To the best of our knowledge, no web-based educational
system exists for facilitating Q&A. Someone may argue that why not use
other existing web-based educational tools to avoid cost to develop a new
system. We thus give comparisons between WeQaS and some well known tools to
make it clear.
Blackboard [3]: Blackboard is a comprehensive remote
education aid system. However, it has no module that is specific for
facilitating Q&A between students and teachers.
Chatroom: The chatroom always rolls in real time. It
is not easy to give answers in the chatroom because questions may be
sequentially mixed in a batch.
Mailing list (e.g., Google group) [4]: It may generate
a bulk of emails regarding the questions and answers that certain students are
not at all interested in.
Forum: It is not easy to regulate posting behavior of
students in forum. In fact, students should have mere right to post questions,
not answers.
References
[1] Google
Mobile, http://www.google.com/mobile/
[2] Evernote
System, http://www.evernote.com/about/what_is_en
[3] Blackbroad,
www.blackboard.com/
[4] Google
Group, http://groups.google.com/
|
Wei Ren School of Computer Science China University of Geosciences Wuhan, P.R.China Tenghong Liu School of Security Management Zhongnan University of Economics and Law Wuhan, P.R.China Info. and
Comm. Tech. Dept. Univ. of
Agder (UIA) Norway |
Enhancement of Mobile Learning
Using Wireless Sensor Network
Abstract: Wireless sensor network (WSN)
technology has figured out that our living environment can be embedded with
numerous sensors, and the sensors can be connected as a novel interaction
platform that can extend the usability, flexibility and variability of mobile
learning. In this study, a framework which supports micro- and macro-WSN
enhanced mobile learning is proposed. Based on the framework, two practical
examples, one in classroom and the other one in a city-wide environment, are
demonstrated to show the potential of using WSN in mobile learning.
Key words: Wireless sensor network enhanced
mobile learning
Introduction
Novel mobile and wireless
technology provide new possibilities for learning and have demonstrated the
potential of using handheld devices in education. Wireless sensor network
technology enables spatially distributed autonomous sensors to monitor physical
environmental conditions cooperatively [1]. The deployment of an ad-hoc and
multi-sensor WSN is very dynamic, depending on the purposes of requests. The
coverage of a WSN could be as small as a single classroom or as large as a
whole city. Combining the traditional mobile learning devices, including PDA,
Tablet PC, cellular phone, etc., with WSN, it can enhance the functions and
extend the territory of mobile learning.
Figure 1: Wireless sensor network enhanced mobile learning framework
Wireless Sensor Network Enhanced Mobile Learning Framework
In order to design wireless
sensor network enhanced mobile learning (WSNEML), a framework composed of a
wireless sensor group, a mobile device access interface, and a set of learning
components is proposed (Figure 1). The wireless sensor group is a set of
autonomous sensors organized as a network to detect and monitor the physical
environment. The data or commands can be accessed or executed on the handheld
devices via the mobile device access interface. In addition to the hardware
network architecture and handheld device, a set of learning components
including learning plan (LP), learning management (LM), pedagogy (PE), content
(CO), learning activity (LA) and portfolio (PO), are required in the framework.
The framework was applied in two extremely environments, one is a micro-WSNEML
covering a small space like a classroom and the other one is a macro-WSNEML
throughout Taipei City, as elaborated below.
Micro-WSNEML: Classroom Gesture Detection Wireless Sensor Network
In a computerized
classroom, such as a computer laboratory, each child is equipped with one
desktop for learning. The design concept of this computerized classroom is
one-computer-one-child, which was argued that it is adult-oriented, not child-oriented.
Children have their unique requirements in using information technology in
classroom. Instead of using monitor, keyboard, and mouse, an alternative way is
allowing children to input their message via their body motion, such as
gesture, which is a more nature way to use technology in classroom [2]. The
classroom gesture detection wireless sensor network is a set of ribbons
equipped with wireless utilization and a set of handheld devices [3]. The
ribbons are embedded with gesture detection chips and can communicate with the handheld
devices wirelessly. All the students in the classroom wear ribbons, and their
gesture signals were captured and sent to the handheld devices for further
process. By using the hardware and software, the classroom can be rearranged
from one-child-one-desktop to many-children only few handheld devices for
learning. For the learning components in the gesture detection classroom, the
learning plan is fluency building; the learning management is in the classroom;
the pedagogy is question posing and answering; the content is the item bank;
the learning activity is competition games; and the learning portfolio is the
student gesture motions. Figure 2 shows the architecture and the learning
components of the micro-WSNEML.
Figure 2: Classroom Gesture Detection Wireless Sensor Network
Macro-WSNEML: City-Wide Weather Science Inquiry-Based Learning Wireless
Sensor Network
Taipei weather inquiry-based learning network
(TWIN) is a city-wide macro-WSNEML that was intended to provide a distributed
wireless weather sensor network throughout Taipei City and to promote weather
science inquiry-based learning activities [4]. The TWIN was composed of sixty
school-based weather sensor nodes. The school-based weather sensor node is
comprised of a wireless weather sensor station, a data receiving console
connected to an Internet-connected computer, and a school server. The sensor
station can automatically detect temperature, humidity, barometer, UV radiation, rainfall
rate, wind
direction and wind speed every five minutes. Based on the actual weather data, the data receiving
console can then generate other weather data, such as dew point, wind chill
temperature, temperature-humidity-wind (THW) index, and heat index. The
wireless weather sensor stations are solar powered, and each is equipped with a
wireless module to enable the station working twenty-four hours a day and seven
days a week independently. Moreover, students can access real time or historical
weather data through the handheld devices. For example, when students work on a
project which is to compare weather status at different height of a mountain,
they can carry out a field survey by using probes to get real time data and
instantly retrieve the data at different location from the TWIN via tablet PC.
For the learning components on the TWIN platform, the learning plan is weather
science study; the learning management is on the TWIN platform; the pedagogy is
inquiry-based learning; the content is the archive of the TWIN, the learning
activity is weather inquiry tournaments; and the learning portfolio is the
inquiry-based learning progress logs. The TWIN has the advantages including
gathering actual and real-time data, exploring the environment not constrained
to geographic restriction, learning in effective and task oriented ways, and
owing personal digital archive. Figure 3 shows the architecture and the
learning components of the macro-WSNEML.
Figure 3: City-Wide Weather Wireless Sensor Network
Conclusion
Novel technology brings new
types of learning. Mobile learning has demonstrated the potential of using
handheld devices in learning. Sensor-based technology has shown the potential
in which our learning environment can be embedded with numerous sensors
collecting the physical information. Consequently, enhancement of mobile
learning using WSN can extend mobile learning to a more attractive environment.
This study proposed a WSNEML framework that can guide designers to implement such
an environment. Two different types of pilot studies are proposed and
demonstrated the potential of applying the WSN in mobile learning.
References
[1] I. Akyildiz,
W. Su, Y. Sankarasubramaniam and E. Cayirci, “A survey on sensor networks,” IEEE Communications Magazine, vol. 40, no. 8, Aug. 2002, pp.
102-114.
[2] B. Chang,
Y. S. Lin and T. W. Chan, “Distributed stories sharing: Wireless sensor network
supported group learning game,” in Proceedings of the 15th
International Conference on Computers in Education, 2007, pp.
265-268.
[3] Y. S. Lin
and B. Chang, “Wireless sensor network to support a multiple-student group
learning game with one PC in the classroom,” presented at ACM SIGGRAPH ASIA,
Singapore, 2008.
[4] B. Chang,
H. Y. Wang, C. S. Chen and J. K. Liang, “Distributed weather net: Wireless
sensor network supported inquiry-based learning,” in Proceedings
of the International Conference on Computer Supported Collaborative Learning,
Rhodes, Greece, 2009 (Accepted).
|
Ben Chang Department of E-Learning Design and Management, National Chiayi University, Taiwan, ROC Hsue-Yie Wang Graduate Institute of Network Learning
Technology, National Central University, Taiwan, ROC Yi-Shin Lin Graduate School of Art and Technology, Taipei National University of the Arts, Taiwan, ROC |
Global Optimisation and Mobile
Learning
Introduction
Mobile
devices, such as cellular phones and Personal Digital Assistants (PDA), have
become part and parcel of our everyday life. These mobile technologies and
their wide adoption in the society are influencing not only the way we live,
but also the way we learn, the way we work, and the way we socialise. According
to [1], there are estimated to be more than 1.5 billion mobile phones in the
world today.
The rapid
advancement of these portable technologies is also changing the way educational
institutions work. It has opened up new possibilities for extending learning
opportunities to all social-economic levels and a completely new dimension to
the progress in education and training known as mobile
learning. Through mobile learning, educational and training programs
that were once delivered only through a face-to-face setting or networked
computers can now be done almost anywhere, anytime.
Global Optimisation
Global
optimisation, on the other hand, is a branch of applied mathematics and
numerical analysis that focuses on finding the best possible solutions based on
a set of criteria expressed as mathematical functions, commonly known as
objective functions [2]. Global optimisation approaches can generally be
divided into two types: deterministic
and stochastic. The most successful example
of the deterministic type is perhaps the Branch and Bound[2] methods, but they are not so attractive anymore in
recent years due to the large and dynamic problem spaces that need to be
tackled in today’s real-world problems. A more appealing choice is therefore
the stochastic solvers, such as Genetic Algorithms, Particle Swarm
Optimisation, Ant Colony Optimisation, and so on. These methods are mostly
inspired in part by nature and natural systems. For an overview of some popular
nature-inspired methods and their practical applications, see [3].
So, what does
global optimisation have to do with mobile learning? An undeniable fact is that
all of us desire optimal outcomes. Very often we tend to find various
alternatives in order to maximise our gain by minimising the cost we need to
bear. Likewise, various aspects of the mobile learning environment need to be
optimised so that the mobile learners can take full advantage of it. Global
optimisation methods have been widely used in many e-learning activities. For
example, very recently an e-learning decision support framework based on a set
of soft computing techniques is introduced in [4] with the aim to improve
e-learning experience. This framework can discover an e-learning system’s usage
patterns and contribute to alleviating instructors’ workload. The
identification of students’ learning behaviour allows instructors to predict
the performance of their students and pinpoint weaker students for personalised
feedback. Besides that, we see the use of Genetic Algorithms for providing
intelligent assessment services in an e-learning environment [5] and for
classifying students in order to predict their final grade based on features
extracted from log data in a web-based educational system [6], the use of Ant
Colony Optimisation for the pedagogic material of an online teaching website
for high school students [7, 8] and for sequencing of e-learning activities [9],
as well as the use of Particle Swarm Optimisation for arranging a set of
learning resources in order to present them in a personalised way to the
learners [10]. Note that these examples are by no means a comprehensive list,
but a snapshot of some interesting works that applied global optimisation
methods to e-learning over the last couple of years.
Examples
of Global Optimisation in Mobile Learning
While
substantial works have been done on e-learning with global optimisation, its
applications to mobile learning are still rare. Lately, an adaptive testing
system for supporting versatile educational assessment has been presented [11].
In this work, the authors integrate computer based test with mobile learning
for both formative assessment and self-assessment. Students are assessed
through a process that uses item response theory, a well-founded psychometric
theory. The problem with the use of item response theory is that a large item
bank is indispensable to a test, yet when the system has a large item bank, the
test item selection becomes a very tedious job. To solve the problem, Particle
Swarm Optimisation method is used to speed up the searching and selection
process. Furthermore, for controlling the test item exposure, an item exposure
mechanism is combined with Particle Swarm Optimisation to prevent the same test
item from appearing twice. When a test item was responded or an adaptive test
was finished by a student, this system applies maximum likelihood estimation as
an underlying psychometric theory to estimate the student’s ability and give
immediate feedback by showing the results to the student.
Apart from
Particle Swarm Optimisation, an improved Genetic Algorithm with association
rules has been proposed in [12] to analyse the vast amount of learners’ profile
data in a web-based mobile-learning system. The authors show that interesting
relationships can be found with this method within minimal execution time. If
fully developed, it is able to create an efficient mobile-learning system that
understands its learners.
Concluding Remarks
Although
brief, these works demonstrate the potential of global optimisation in mobile
learning. Genetic Algorithms have been applied extensively in mobile robots
with huge success (see [13, 14]). Similarly, swarm intelligence and other
global optimisation methods have contributed greatly to the field of
telecommunications and distributed systems (see [15, 16]). It is therefore just
a matter of time before these methods are adopted extensively in mobile
learning.
References
[1] Attewell,
J. (2005). Mobile Technologies and Learning: A Technology
Update and m-Learning Project Summary. Technology Enhanced Learning
Research Centre, Learning and Skills Development Agency. London: Learning and
Skills Development Agency.
[2] Weise,
T. (2009). Global Optimization Algorithms - Theory and
Application. Online e-book under GNU Free Documentation License,
available at http://www.it-weise.de/projects/book.pdf
[3] Chiong,
R., Neri, F., & McKay, R. I. (2009). Nature that Breeds Solutions. In R.
Chiong (Ed.), Nature-Inspired Informatics for Intelligent
Applications and Knowledge Discovery: Implications in Business, Science and
Engineering (Chapter 1). Hershey, PA: Information Science Reference.
[4] Castro,
F., Nebot, À, & Mugica, F. (2008). A Soft Computing Decision Support
Framework to Improve the e-Learning Experience. Proceedings
of the 2008 Spring Simulation Multiconference, Modeling & Simulation in
Education (pp. 781-788). San Diego, CA: The Society for Computer
Simulation, International.
[5] Alexakos,
C. E., Giotopoulos, K. C., Thermogianni, E. J., Beligiannis, G. N., &
Likothanassis, S. D. (2006). Integrating E-learning Environments with
Computational Intelligence Assessment Agents. Proceedings
of World Academy of Science, Engineering and Technology, 13, 233-238.
[6] Minaei-Bidgoli,
B., & Punch, W. F. (2003). Using Genetic Algorithms for Data Mining
Optimization in an Educational Web-based System. Lecture
Notes in Computer Science, 2724,
2252-2263.
[7] Semet, Y., Lutton, E., & Collet, P.
(2003). Ant Colony Optimisation for
e-Learning: Observing the Emergence of Pedagogical Suggestions. Proceedings of the IEEE Swarm Intelligence Symposium (pp.
46-52). Piscataway, NJ: IEEE Press.
[8] Semet, Y., Yamont, Y., Biojout, R., Luton,
E., & Collet, P. (2003). Artificial
Ant Colonies and e-Learning: An Optimisation of Pedagogical Paths. Proceedings of the 10th International Conference on Human-Computer
Interaction (pp. 1031-1035). Mahwah, NJ: Lawrence Erlbaum
Associates.
[9] Gutiérrez,
S., Valigiani, G., Collet, P., & Kloos, C. D. (2008). Adaptation of the ACO
Heuristic for Sequencing Learning Activities. Proceedings
of the European Conference on Technology Enhanced Learning
(http://ceur-ws.org/Vol-280/p15.pdf), Crete, Greece.
[10] de Marcos, L., Martínez, J. J., Gutierrez, J.
A. (2008). Swarm Intelligence in
e-Learning: A Learning Object Sequencing Agent based on Competencies. Proceedings of the 10th Annual Conference on Genetic and Evolutionary
Computation (pp. 17-24). New York, NY: ACM Press.
[11] Huang,
Y. M., Lin, Y. T., & Cheng, S. C. (2009). An Adaptive Testing System for
Supporting Versatile Educational Assessment. Computers
& Education, 52, 53-67.
[12] Zheng,
S. J., Xiong, S. J., Huang, Y., & Wu, S. X. (2008). Using Methods of
Association Rules Mining Optimization in Web-Based Mobile-Learning System. Proceedings of the International Symposium on Electronic Commerce and
Security (pp. 967-970). Washington, DC: IEEE Computer Society.
[13] Floreano,
D., & Mondada, F. (1996). Evolution of Homing Navigation in a Real Mobile
Robot. IEEE Transactions on Systems, Man, and Cybernetics,
Part B: Cybernetics, 26(3), 396-407.
[14] Kubota,
N., Morioka, T., Kojima, F., & Fukuda, T. (2001). Learning of Mobile Robots
using Perception-based Genetic Algorithm. Measurement, 29(3), 237-248.
[15] Nesmachnow,
S., Cancela, H., & Alba, E. (2009). Nature-Inspired Informatics for
Telecommunication Network Design. In R. Chiong (Ed.), Nature-Inspired
Informatics for Intelligent Applications and Knowledge Discovery: Implications
in Business, Science and Engineering (Chapter 14). Hershey, PA:
Information Science Reference.
[16] Weise,
T., & Chiong, R. (2009). Evolutionary Approaches and their Applications to
Distributed Systems. In R. Chiong (Ed.), Intelligent Systems for
Automated Learning and Adaptation: Emerging Trends and Applications
(Chapter 6). Hershey, PA: Information Science Reference.
|
Raymond Chiong Swinburne University of Technology Australia Thomas Weise University of Kassel Germany |
|
|
Exploring Students’ Perceptions toward Using Interactive Response System
Abstract: This article reports a one-semester project using the NXTudy Interactive Response System (IRS) in a classroom. The Technology Acceptance model was extended to formulate students’ perceptions, attitudes and actionable feedback in terms of using the proposed IRS. A survey was conducted and the results confirmed that “perceived usefulness” was the most important factor in the model. Teachers should explain the importance of using technology before the class starts and constantly repeat the benefits to enhance students’ understandings, so that students feel the usefulness of the technology, and further boost the intention to use, satisfaction and the willingness to recommend others to use the technology.
Keywords: TAM, IRS, perceptions, usefulness,
satisfaction, suggestion
Introduction
Intel Teaching Program (Intel, 2007) had trained over
3300 primary and secondary school teachers the skills of applying information
technology into their teaching, and planned to expand the program to reach 13
million teachers in more than 40 countries – and their one billion students by 2011.
Technology can be a powerful tool to help students develop and strengthen their
skills in succeeding in the global economy.
Some studies have explored the technological effects
on students’ learning, such as podcasting, Wiki, open source software,
web-based systems. However, those studies focused on “out-of-classroom” systems
which enable learner autonomy to study by their own outside the classroom. Little research has
investigated students’ perceptions toward applying “in-classroom” technology,
such as Interactive Response System (IRS). The urgent call for this research comes
from the proliferation of IRS introduced to the campus, such as NXTudy. IRS is
able to assist the teaching strategy to help students achieve better learning
performance. Therefore, the purpose of this study is to build a model to
evaluate students’ perceptions of using IRS and propose suggestions for
teachers to support their teaching strategy.
Teaching with IRS
NXTudy is an IRS which is composed of two parts: a remote
controller and a server. The remote controller is controlled by students and
the main function is to answer the questions given by teachers. The server
includes a PC and IRS system whose function is to present the teaching material
on the screen and receive students’ signals. A sensor receives the signals from
the remote controller and transfers the data to the server. The structure of
NXTudy is shown in Figure 1.
“Technology English” is a one-semester subject for the
undergraduates in a university in Taiwan. 248 students in total enrolled in
this subject. Students received 30 minutes training of NXTudy at the beginning
of the semester to ensure their proficiency in the operation of remote
controllers. NXTudy was used as a quiz tool followed by the regular teaching
and also used as a tool for the middle and final exam. At the end of the
semester, students were asked to fill in the questionnaire designed by the
framework described in the next section. 245 questionnaires were collected and
6 questionnaires were discarded due to their incompletion, which results in a return
rate of 98%.
Figure 1: The
structure of NXTudy
The Framework and Hypotheses
This
study extended TAM (Davis, 1989), by adding two factors: “user satisfaction” (Wixom
& Todd, 2005) and “suggestion to use” (Zeithaml et al., 1996). The former stands
for the subjects’ feelings or attitudes toward consequences or outcomes while the
latter represents the subjects’ willingness
to recommend others to use the technology. To aggregate past literature, a
framework is proposed in Figure 2.
Figure 2: The
proposed framework
The following hypotheses are investigated:
H1: Students’ PEOU affects PU.
H2: Students’ PU affects IU.
H3: Students’ PEOU affects IU.
H4: Students’ IU affects SU.
H5:Students’ IU affects SAT.
Data Analysis
The SEM (Structural Equation Model) model was constructed
by LISREL 8 .72 and is shown in Figure 3. It presents a good model fit and thus
H1, H2, H4 and H5 are supported. Only H3 is not supported. PU mediates the
effect of PEOU to affect IU and further affect SU and SAT, which implies that
the subjects’ intention is affected by the extent of usefulness and ease of
use. But the effect of PEOU needs to transit by PU, which means that how useful
the subjects perceive is the pivotal issue. Thus PU is regarded as the most
important factor in the model.
Figure 3:
Tested model
Discussion
This study makes two contributions. Firstly, this
study extended the TAM, by considering the characteristics of integrating
technology into the classrooms, and it incorporated two factors: “user
satisfaction” and “suggestion to use” to build a new model. Such integration
can help to build a conceptual bridge extended from design and implementation
decisions to system characteristics to the prediction of usage, user
satisfaction and actionable feedback (such as recommend others to use).
Furthermore, by theoretically extending the TAM, it can fully examine the role
of the IT artifact and bring more IT research streams.
Secondly, the results prove that perceived usefulness
is the most important factor, which implies that teachers should focus on this
factor for the success of using technology. Once the students’ perceptions of
usefulness are well-established, the degree of intention to use and
satisfaction would be higher, likewise they would recommend others to use the
technology and diffuse the influence of technology in teaching. Therefore apart
from repeating the benefits of the technology, ensuring the elimination of the
problems and obstacles that hinder students’ usage of the technology
appropriately can strengthen the perception of ease of use, and further enhance
the perception of usefulness. In some cases, having teaching assistants with expertise
in computer technology would be helpful, because they may help solve the
technological problems to reduce students’ frustration in operating the
technology.
References
Davis, F. D. (1989). Perceived usefulness, perceived
ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
Intel. (2007). Intel
teach program: Powering the magic of teachers. Retrieved 2009, 23
Jan, from http://download.intel.com/pressroom/kits/education/IntelTeachProgramBackgrounder.pdf
Wixom, B. H., & Todd, P. A. (2005). A
theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1),
85-102.
Zeithaml, V. A., Berry, L. L., & Parasuraman,
A. (1996). The behavioral consequences of service quality. Journal of Marketing Research, 60(2), 31-46.
|
Ying
Chieh Liu Choayang University of Technology Taiwan |
Call for Papers: Inaugural issue of the Journal of Applied Research in Workplace E-learning
Impact: Journal of Applied Research in
Workplace E-learning, a publication of the E-learning Network of Australasia (ElNet),
has been established to address the paucity of research publication avenues
with a particular emphasis on e-learning in organisational and workplace
settings. It will be a fully online journal, publishing refereed and
non-refereed contributions from both researchers and practitioners relating to
the design, implementation, evaluation and management of workplace e-learning
across a range of sectors and industries.
Submissions are invited for the special, inaugural
issue of the journal, the theme of which is "Current
issues and future directions in workplace e-learning: Mapping the research
landscape". This issue will include peer-reviewed articles that
address one or more of the following areas:
1. Summary and synthesis: Where are we now?
·
Identification and analysis of major issues, themes
and trends in the field of workplace e-learning research
·
Review of key studies and seminal pieces of literature
in this field, and how future research efforts might build upon the work
already done
2. Gap analysis: What do we
need to know more about?
·
Discussion of areas have been under-emphasised or
neglected in the field of workplace e-learning research
·
Exploration of how these areas/gaps might be addressed
3. Planning and designing: How should we move forward?
·
Setting the research agenda for workplace e-learning
·
Future directions for workplace e-learning research
and its application to practice
In addition, case studies / best practice examples and
position or commentary articles may be submitted to be either peer or editor
reviewed. Non-refereed contributions in the form of technical/application notes
(eg tools, how-tos) and book/Web site reviews are also invited.
The Editorial
Policies section of Impact's Web
site (http://journal.elnet.com.au/impact)
contains general information on the journal's focus and scope, including topics
of interest and types of articles accepted. For specific style guidelines and
advice to authors, please see the Submissions
section of the site.
Prospective authors for the inaugural issue are
strongly encouraged to submit proposals or expressions of interest to the
Editor-in-Chief well in advance of the manuscript submission deadline, in order
to allow time for feedback and discussion. This may be done via email to impactjournal@elnet.com.au,
however full manuscripts are to be submitted via the online submission system
on the journal's Web site, and not via email.
KEY DATES
Manuscript
submission deadline: 1 June 2009
Notification
of acceptance: 1 July 2009
Submission of
final articles for publication: 1 August 2009
Publication of inaugural issue (online): 1 September
2009
Impact Editorial Team
Editor-in-Chief
Mark J.W. Lee, Charles Sturt University, Australia
President, ElNet
Clint Smith, Learnworks, Australia
Manager – Publications, ElNet
Position vacant
Manager – Branding and Promotion, ElNet
Marianne Cini, Evolve Studios, Australia
Editorial Board
A.Y. Al-Zoubi, Princess Sumaya University for
Technology, Jordan
Zane L. Berge, University of Maryland, Baltimore
County, United States
Marcus S. Bowles, Institute for Working Futures,
Australia
John G. Burgoyne, Lancaster University Management
School and Henley Business School, United Kingdom
John Clayton, Waikato Institute of Technology, New
Zealand
Jay Cross, Internet Time Group, United States
Rabelani Dagada, Wits Business School and Royal
Bafokeng Administration, South Africa
Margaret Driscoll, IBM Global Solutions, United States
Wellesley R. ("Rob") Foshay, Texas
Instruments, United States
John G. Hedberg, Macquarie University, Australia
David H. Jonassen, University of Missouri, United
States
Angela Lewis, Angela Lewis Consulting, Australia
Kin Chew Lim, SIM University, Singapore
Joha Louw-Potgieter, University of Cape Town, South
Africa
Terry Marler, Otago Polytechnic, New Zealand
John G. Mitchell, John Mitchell and Associates,
Australia
Pam Moule, University of the West of England, United
Kingdom
Anna Peachey, The Open University, United Kingdom
Clark N. Quinn, Quinnovation, United States
Hanna Risku, Danube University Krems, Austria
Andrée Roy, Université de Moncton, Canada
Roderick C. Sims, Capella University, United States
J. Michael Spector, University of Georgia, United
States
Marcel van der Klink, Open University of the
Netherlands, Netherlands
Jelke van der Pal, National Aerospace Laboratory NLR,
Netherlands
Douglas R. Vogel, City University of Hong Kong, Hong
Kong
David Young, University of Derby, United Kingdom
Impact is a publication of:
