|
|
Learning
Technology publication
of IEEE Computer Society’s |
|
|
Volume 11 Issue 3 |
ISSN 1438-0625 |
July 2009 |
Elementary Level Botanical Item
Generation
Programming Integrated in K-8
Traditional School Curricula
Learning Robotics using LEGO
Mindstorms
General Guidelines for Enhancing
Online Collaborative Science Studies
PLEF: A Conceptual Framework for
Mashup Personal Learning Environments.
Mobile Long Life Learner Pervasive
Assistance System
National Learning Object
Repositories An Architectural Rethink..
List of International Conferences on
Learning Technologies
From the editors…
Welcome to the July
2009 issue of Learning Technology Newsletter.
Science education is
considered as a challenging part of most national curricula, and is becoming
increasingly important in the knowledge society and knowledge-based economy.
This issue addresses science education from a number of different perspectives.
The first article,
by Hsue-Yie Wang, Ben Chang and Charng-Tzer Harn, describes PICNIC, a
parent-child coupled, inquiry-based learning camp, where each parent-child
couple uses a mobile data logger and a city-wide weather database to facilitate
climatology learning.
Subsequently, Rita
Kuo and Maiga Chang introduce a system that automatically generates multiple
choice questions to evaluate students’ cognitive abilities. The system has been
used in an elementary school for teaching a lesson about “Knowing the Plants”.
The next article,
by G. Barbara Demo, discusses current initiatives in
Tri Kurniawan
Wijaya and Gunawan discuss the use of LEGO Mindstorms for learning robotics,
while Enid J. Irwin proposes a set of guidelines for enhancing online
collaborative science studies.
The last four
articles belong to the regular article section. Mohamed Amine Chatti, Matthias
Jarke and Marcus Specht propose PLEF, a conceptual framework for mashup
personalised learning environments which can be used for science education.
Jalel Akaichi
proposes a pervasive assistance system for mobile learners able to localize, to
match learners’ free time with scheduled courses, and to make reservation of
learning resources while being in motion.
Mike Whitty, Ijaz.
A. Qureshi, Maimoona Saleem and Mehwish Shafiq discuss a case study where
e-learning is used for educating people in a developing region.
In the last paper,
Bob Strunz and Gareth Waller present the Irish National Digital Learning Object Repository, a
collaborative project which involves all six
Finally, the issue
includes a list of conferences which are related to learning technology. This
is a first attempt to elaborate the newsletter, so as to include as much useful
information as possible for people working in learning technology.
We hope that this
issue helps in keeping you informed about the current research and developments
in science learning!
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://lttf.ieee.org/learn_tech/authors.html.
|
Charalampos
Karagiannidis Sabine Graf Athabasca
University, Canada |
Using Mobile Data Logger and City-Wide Weather Database to Facilitate Parent-Child coupled Climatology Learning
Abstract:
This study shows a science learning
activity design that couples one child one parent to form a team to carry out
an inquiry-based learning activity on climate. In the two days camp, every
couple uses tablet PC equipped data logger to collect weather data and compare
and/or contrast with the database of a city-wide wireless weather sensor
network. A trial event took place and provided positive feedback.
Keywords: Inquiry-based learning, mobile technology,
wireless sensor network, parent-child coupled learning
Introduction
Higher order thinking skills (HOTS), such as
inquiring, exploring, and problem solving, are regarded more and more important
for students. The ability to questioning, hypothesizing, designing and carrying
out investigations, and making conclusions based on evidence foster students’
HOTS that they need to face the challenges in the 21st century [1]. Among the pedagogies, inquiry activities provide a valuable
context for learners to acquire, clarify, and apply an understanding of science
concepts, which help learners develop cognitive abilities and science content.
Edelson et al. [2] noted that there
are many challenges to successfully implement inquiry-based learning for
children, including that they have difficulties to conduct systematic
scientific investigations, gather data, analyze data, interpret findings, and
communicate results. This study designed an inquiry activity
in a technology-rich setting to help children and parents learn climatology. Parents
were included because parental involvement in child education generally
benefits children's learning [3]. Additionally,
parents can learn the importance of affectionate contact with their children,
especially at times when the child may be fearful or anxious [4]. This may ease
the difficulties when children face the challenges in the inquiry-based
learning activities.
Parent-Child
Coupled Inquiry-based Learning Camp (PICNIC)
The purpose of the inquiry framework was to make
the inquiry process explicit for students from backgrounds where science
inquiry may not be encouraged, or for those with limited experience of school
science [5]. The parent-child coupled inquiry-based
learning camp (PICNIC) was introduced to facilitate students carrying
out a complete process of inquiry-based learning with their parents company. In
PICNIC, every parent-child couple uses mobile devices in the outdoor climate
investigation to collect weather data. They can further use the collected data
to compare and/or contrast with the data which is automatically sensed and
recorded by a city-wide wireless weather sensor network.
The PICNIC is an extracurricular event in two full
days. It comprises with four parts. Figure 1 shows the course details and the
technologies used in PICNIC.
Technologies in
PICNIC
Computing and
networking technologies offer dramatic, new opportunities to support
inquiry-based learning [2]. Mobile and wireless
sensor network technologies played an important role in PICNIC. They are not only
the working platform for the couples to gather data, analyze,
Figure 1: Course
and technologies in PICNIC
and making the
inquiry report, but also the mediator between the child and the parent to make
them focusing on the inquiry project itself. During the field investigation,
every couple uses their table PC and running Google Maps. They can mark the
investigation locations, retrieve distance and elevation of each location in
Google Maps, and upload the measured data into it.
The availability of large-scale data collection
mechanisms has led to an explosion of data available to support the scientific
investigation of climate [6]. The city-wide wireless weather sensor network was
comprised with sixty wireless weather stations located in sixty schools in
Conclusion
Inquiry-based learning is essentially a
question-driven, open-ended process and students must have personal experiences
with scientific inquiry to understand this fundamental aspect of science [8]. For the learners who are used to the “traditional”
learning ways, they may not feel comfortable with it. The PICNIC couples one child one parent to form a team to carry out an
inquiry activity with the support of mobile and wireless sensor network
technologies. There were thirty couples attended in the trial event in 2007.
Positive feedbacks were received both from the children and the parents. A
formal event will take place in the near future to make further evaluation.
References
[1] National Research Council, Inquiry
and the National Science Education Standards: A Guide for Teaching and Learning,
[2] D. C. Edelson, D. N. Gordin and R. D. Pea, Addressing the Challenges
of Inquiry-Based Learning through Technology and Curriculum Design, Journal of the Learning Sciences, vol.
8, no. 3, Jul. 1999, pp. 391-450.
[3] K. Hoover-Dempsey and H. Sandler, Why Do Parents Become Involved in Their
Children's Education? Review of
Educational Research, vol. 67, no. 1, Spring 1997, pp. 3-42.
[4] UNESCO-IBE., Parents and Learning,
[5] P. Cuevas, O. Lee and R. Deaktor, Improving Science Inquiry with
Elementary Students of Diverse Backgrounds, Journal
of Research in Science Teaching, vol. 42, no. 3, Mar. 2005, pp. 337-357.
[6] NASA., Understanding Our
Changing Planet: Earth Science
[7] 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 8th International
Conference on Computer Supported Collaborative Learning, June 2009, pp.
365-369.
[8] National Research Council. National
Science Education Standards,
|
Hsue-Yie Wang Graduate Institute of Network Learning
Technology, Ben Chang Department of E-Learning Design and
Management, Charng-Tzer Harn Department of Industrial Education, |
Elementary Level Botanical Item Generation
Cognitive Ability
Items
Bloom
and his colleagues (1956) defined three domains for classifying teaching
objectives: cognitive, affective, and psychomotor. They use cognitive domain to
measure human mental skills (e.g. memorization). Many educators use Bloom’s
Taxonomy to evaluate students’ cognitive levels of the knowledge. Anderson and Krathwohl
(2001) revised the original Bloom’s Taxonomy to a two-dimension matrix which
covers knowledge process and cognitive processes of human beings.
Our
previous system generates true/false items automatically (Chen et al., 2008).
The generated items can be used by teachers to evaluate students’ two basic
cognitive abilities: list and describe. The system uses generative grammar and
transformation rules proposed by Chomsky in 1957 to generate correct and
incorrect statements for constructing the true/false items. This paper
describes the automatic item generator which extends the idea to construct
multiple choice items to evaluate students’ four cognitive abilities: list,
describe, summarize, and classify.
System
Architecture
As
Figure 1 shows, the automatic item generator needs three steps to construct
multiple choice items for the students, and is also an adaptive test system:
1.
Teachers
can create different knowledge topics for their different courses and/or lessons
with Knowledge Map Editor as Figure 2 shows. They can add, insert, delete, and
modify concepts stored in the knowledge maps for each topic anytime before
their students take the exams.
2.
After
the teachers create the knowledge maps, the students can take the exams with
the Item Selection module. The Item Selection module requests the Item
Generation module to construct items according to the concepts retrieved from
the knowledge map and stores the items in the Answer Sheet database. Students’ answers are also stored in the
Answer Sheet database. As Figure 3 shows, the item generator delivers items one
by one after the student clicks on the “ready to take the exam” button. The stem
of the multiple
Figure 1:
System Architecture of the Automatic Item Generator
Figure 2:
Knowledge Map Editor
Figure 3:
The multiple choice item constructed
by the Automatic Item Generator
choice item in Figure 3 asks students to
answer what the arrangement of leaves the Duranta has. The correct answer is
option 3, and the other two options are the distractors and incorrect answers.
The students can check the answers they think are correct and click on the “confirm”
button to send their answers back.
3.
When
the students complete the exams, the Cognitive Evaluation module presents the
students the evaluation results about their cognitive abilities toward to each
concept.
Experiment and
Evaluation
Nineteen
fifth grade students (around 11 years old) from the northern part of
According
to the questionnaire feedback, 73.68% of students agree or strongly agree that
the Automatic Item Generator is easy to use. Only 15.79% of students indicate
that they encountered difficulty in using the item generator. A really encouraging
feedback for us is that 78.95% of students think the items generated by the
system are helpful. The teachers also suggested to us to make the item
generator insert relevant pictures besides the items in order to reduce the
difficulty of the items.
Conclusion
This
research extends our previous true/false item generator to build an automatic
multiple choice item generator. The new item generator not only constructs
multiple choice items, but also constructs the items which can be used by the
teacher to evaluate more students’ cognitive abilities: to summarize and to classify.
Teachers
can use the Knowledge Map Editor to build their own knowledge bases for
different knowledge topics and/or courses. The students can take the adaptive
exams which cover both of true/false and multiple choice items. When the
students complete the exams, the item generator delivers the diagnosis reports
to the students.
The
item generator also records the students’ actions during the exam and we will
ask experts and teachers to evaluate the system accordingly. Our ongoing tasks
include: (1) analyzing the relations between students’ computer attitudes and
academic performances; (2) finding the teachers’ perceptions in relation to the
difficulty of the generated items; and, (3) comparing the students’ cognitive
abilities as thought of by their teachers and as found by the generator.
Reference
Anderson, L. W., & Krathwohl, D. R.
(Eds.). (2001). A taxonomy for learning,
teaching and assessing: A revision of Bloom's Taxonomy of educational
objectives: Complete edition,
Bloom, B.S. (Ed.), Engelhart, M.D., Furst,
E.J., Hill, W.H., & Krathwohl, D.R. (1956). Taxonomy of educational objectives: The classification of educational
goals. Handbook 1: Cognitive domain.
Chomsky, N., (1957). Syntactic Structure,
Chen, S.-B., Kuo, R., Chang, M., Liu, T.-C.,
& Heh, J.-S. (2008) Developing True/False Test Sheet Generating System with
Diagnosing Basic Cognitive Ability. Proceedings
of the World Conference on Educational Multimedia, Hypermedia and
Telecommunications (ED-MEDIA 2008), Vienna, Austria, June 30-July 4, 2008, 5740-5748
Rita
Kuo
Department of Digital Design
Maiga
Chang
School of Computing and Information Systems
Programming Integrated in K-8 Traditional School Curricula
During
the 2008/2009 school year several new ICT projects have been initiated in
Italian primary and junior high schools aiming at improving pupils achievements
particularly in scientific subjects. The explicit
aim of some proposals is to develop computing competencies such as problem
solving and, in general, logical skills, thus introducing in schools a
conception of computing different from the one in most current projects,
normally limited to the use of software
applications. Actually, already in school-year 2001-2002, F. Honsell and C.
Mirolo promoted one of the first projects aiming at cultivating computing as a
science in schools that involved fifteen
primary schools in the Friuli Italian region [3]. Yet, only during the current
school-year 2008/2009 we had the first nation-wide initiatives in schools under
this approach. The Italian Kangaroo Association organised the First Italian
Kangarou Informatica contest for junior high schools, 5-7 May 2009. A. Lissoni with a group of researchers from the
Other researches explicitely address programming in primary
and secondary high schools. As an example, in educational robotics, pupils
write programs for moving mini robots. We have proposed activities with autonomous mini robots of different types to
children in kindergarten, primary and junior high schools. Pupils program by
pushing buttons, in pre-writing age, or using different iconic languages or a
textual Logo like language within an Integrated Development Environment (IDE)
designed and implemented for them in our Departement. An advantage of
programming autonomous mini robots is that it offers to pupils problems to be
solved (and programmed) that they understand and are interested in solving.
Beginning problems with robots are based on making them move in different
environments: avoiding obstacles or doing different actions depending on where
obstacles are positioned or depending on when a noise is made, etc. These
moving-activities are something that young people know quite well by
themselves. Teachers do not have to find problems: robots have wheels and,
consequently, pupils first of all want to write programs that make them move.
While designing, writing and verifying programs for controlling the
motion of mini-robots, schoolchildren and students both acquire programming competences in a young people oriented context
and have the chance of concretely
manipulating concepts present in their school curriculum with a
conctructivistic learning approach. Educational
robotics is a learning environment where robot programming activities
are integrated into standard subjects, rather than being a form of ICT added to
school curricula as one more, separate, subject or as a number of (software)
tools for practicing topics from standard subjects. Until nowadays, such
integration has rarely been present in the proposals for introducing computing
technologies in
schools,
though considered a most fruitful educational usage of computers already in
Papert’s researches of the 70’s.
During the last couple of years we
could work with k-8 pupils on several topics from traditional curricula. In the
following, we mention types of robots used and some curricular components
addressed in our activities, distinguished by school levels.
In kindergarten we
propose robots programmable to go forward, backward, left and right (the same
measure of movement) by pushing buttons. We have addressed basic counting
competencies and topological problems also with respect to the robot (that is
someone different from the child who decides the commands).
In primary school
we propose both already assembled robots and kits. Pupils program with iconic
or textual languages. While designing robot programs we cover measuring,
counting, comparing (longer, shorter, as-long-as paths), drawing of geometrical
shapes. Also, again while designing or correcting their programs, pupils are
naturally introduced to manipulate beginning physics concepts such as speed,
time, friction and their relationships. Activities concerning geography have
also been performed and a
step-by-step methodology has been experimented where learning the textual
Logo-like language for robot programming is coordinated with the parallel
acquisition of logical and linguistic abilities [1].
In junior secondary
school level we used several types of kits that pupils assembled in
different forms. During the 2008/2009 school-year we went from more evident
activities such as working with direct and inverse proportionality concepts
(typically addressed in this level of schools) to introducing algebraic
expressions[2]. This has been done by discussing with pupils how we can write
the length of the path covered by the robot during one execution of a program.
Our current work concerns the automatic synthesis of the algebraic expressions
resulting from the discussions we had this year in junior high schools. This
will be a support for teachers in motivating algebra that pupils often perceive
only as a syntactical exercise.
Other activities integrating robotics in standard curricula
are carried out by G. diBenedetto and R. Didoni with their Friend-Robot School-Net
[5] in Milano area and by researchers involved in the European
project “Teacher Education on Robotics-Enhanced Constructivist Pedagogical
methods” (TERECoP) [6]. Didoni’s experiences began around 2001 and nowadays
every year their School-Net organises the Robotics Festival [5].
Italian researchers from
References
[1] G. Marcianó and G.B. Demo (2007)
“Contributing to the Development of Linguistic and Logical Abilities through
Robotics”, Proc. EuroLogo 2007 Conf., August 2007, p.46.
[2] G. B. Demo, Robot
Programming Integrated in a Secondary Junior School Curriculum, Proc. Informatics
Education Europe IV Conf., Freiburg, Nov.2009.
[3] F. Honsell, C. Mirolo, Scientific
Coordinators, “SeT Project: the information cycle”, 2002, http://www5.indire.it:8080/set/informazione/informazione.htm
[4] A. Lissoni et
al., Working for a leap in the general perception of computing, Proc.
Informatics Education Europe III Conf.,
[5] Robotics
School-Net Friend-Robot, in Italian; http://www.amicorobot.net/index.html
[6] TERECoP
Project: http://www.terecop.eu/
G.
Barbara Demo
Informatica Department,
c.so
Svizzera 185 - 10149 Torino –
Learning Robotics using LEGO Mindstorms
Introduction
Many
people argue that learning robotics is a hard thing to do due to its
complexity. On the other hand, learning robotics can bring many advantages: we
can learn mathematics, physics, programming, mechanics, and science not only in
theory, but also in practical way. In this context, the LEGO Mindstorms
platform appears as a state-of-the-art and an innovative way to answer the
challenges in learning robotics in all education level, even in primary or
secondary education.
History of the Lego Mindstorms
The
story behind LEGO Mindstorms is, in reality, a fascinating narrative of how
three organizations (Resnick and Papert’s Epistemology and Learning research
group, the LEGO Corporation, and the MIT Media Laboratory) engaged in a complex
social interaction, which shaped the evolution of the technology (Mindell,
2000). Each group had its own interests and ideas of what success means. Thus,
each organization influenced the development of the Mindstorms product and its
Media Lab prototypes in different ways.
The
Epistemology and Learning group, for instance, endeavored to create and
disseminate new constructivist approaches to learning. In constructivist
approach, it is stated that knowledge
should not be simply transmitted from teacher to student, but actively
constructed by the mind of the student (Mindell, 2000). In addition,
learning is an active process in which people actively construct knowledge from
their experiences in the world. The LEGO Company also aspired to provide
constructivist approaches to learning, while aiming for their brand “to be the
strongest in the world among families with children”. Finally, the MIT Media
Lab sought to create a new and publicly visible model of academic research that
emphasizes the public impact of ideas, fosters idea transfer between academic
research groups and corporate sponsors, and encourages community outreach.
Ultimately, the Lab provided an environment for the research that led to the
Mindstorms product to grow and mature.
Learning
Robotics
Robotics is an interdisciplinary subject,
combining and integrating different areas of knowledge, such as mathematics,
physics, mechanics, electronics, control, computer programming, artificial
vision and artificial intelligence (Ricca et al., 2006; Karatrantrou and Panagiotakopoulos,
2008). Indeed, robotics is appealing for the integration of multi-disciplinary
skills and teams.
Learning robotics requires the usage of new
methodologies that apply the concepts of learning
by doing and learning by enjoying,
allowing to motivate and involve the students in the learning process (Leitao
et al., 2007). In addition, learning robotics also requires a deep
understanding about the structures (building) of the robot, sensors and
programming. The building of the robot determined how the robot should move or
work. The sensors enable the robot to acquire many different values from the
environment, e.g. light intensity, sound, and temperature. Furthermore, to
bring the robot “alive”, a good program is needed.
The
advantages of Lego Mindstorms
LEGO Mindstorms platform appears as a
simple, flexible, attractive, educational and suitable tool for learning
robotics. The main reason to sustain this argument is that it is a tool that
everybody is familiar with. The LEGO parts allows connectivity, eliminating the
need of using screws or glue, thus making the construction of mechanical models
much more clean and easy. It is also an ecological tool because although the
plastic is not easy to recycle, the parts are never made unusable, so they
never become garbage, being used over the time.
At high-level studies, the difficulty to
build quickly mechanical structures for the robot retracts the time and
motivation to learn robotics topics (Kelly, 2006). The possibility to build
quickly robots with different configurations provided by the LEGO platform
offers a good opportunity to learn this topic by doing and enjoying.
Moreover,
to support interactivity, Lego Mindstorms NXT has four kinds of sensors (see
figure 1) to interact with environment. Lego Mindstorms NXT comes with:
- Touch Sensors: It is like a bumper; it
enables the robot to detect press-and-release events. This kind of sensor
can be used to detect very near obstacles.
- Light Sensors: It is a rudimentary device that lets
the robot “see” in a very limited sense. Measuring the amount of light
that reaches the sensor’s inlet, it allows for distinction between bright
and dark, similar to an amoeba.
- Sound Sensors: It is the robot’s “ear.” It can detect
and measure sounds.
- Ultrasonic Sensors: It is eyelike shaped and might be
considered to be like the robot’s eyes, indeed enabling it to have a look
at what’s around it.
|
|
|
|
|
|
a) Ultrasonic Sensor |
b) Touch Sensor |
c) Sound Sensor |
d) light sensor |
Figure
1: Lego Mindstorms NXT sensors
The
Lego Mindstorms NXT software (see figure 2) enables us to program our NXT
robotic applications and upload the programs to the NXT via USB or Bluetooth
connectivity. The intuitive Mac and PC compatible drag and drop software,
powered by National Instruments LabVIEW, comes with building instructions and
programming guides to easily begin constructing and programming with Mindstorms
NXT.
Conclusion
The LEGO Mindstorms platform uses the basic
concepts of LEGO to build mechanical models. Due to the intrinsic features
exhibited by the LEGO Mindstorms platform, such as reusability, modularity,
flexibility, and cost-effectiveness, the introduction of that platform in some
Engineering curricula is useful, for example to improve learning in several
areas of knowledge, such as robotics, computer programming, artificial
intelligence, distributed systems and electronics.
Figure
2. Lego Mindstorms NXT software
References
1. Mindell, D. LEGO Mindstorms The Structure of an
Engineering (R)evolution. 6.933J Structure of Engineering
Revolutions 2000.
2. Ricca, B., Lulis, E., Bade, D. Lego Mindstorms and the Growth of Critical
Thinking.
3. Karatrantou, A., Panagiotakopoulos, C. Algorithm, Pseudo-Code and Lego Mindstorms
Programming. International Conference on Simulation, Modelling and
Programming for Autonomous Robots. Venice-Italy. 3-4 November 2008. pp. 70-79.
4. Leitao, P., Goncalves J., Barbosa J. Learning
5. Kelly, J. F. Lego Mindstorms NXT The Mayan Adventure.
Tri Kurniawan Wijaya
Department of Computer Science
Sekolah
Tinggi Teknik
Gunawan
Department of Electrical Engineering
Faculty of Industrial Technology
Institut
Teknologi Sepuluh Nopember
General Guidelines for Enhancing Online Collaborative Science Studies
Introduction
Although
the class the instructor teaches is in the San Jose State School of Library and
Information Science (Information Retrieval), the course deals with database
base design for article collections, creating and testing controlled
vocabularies, evaluating results, and drawing conclusions from observations. A
scientific study and report is an outcome of the class.
Since
the class is taught totally online to students scattered over a wide
geographical area, teamwork and collaboration are real issues for both students
and instructor. Students need to have a collaborative team effort to complete
the assignments and the instructor needs to create a social yet professional
atmosphere in order for learning to take place.
The
class is taught in Angel and previously in Blackboard. Although either Learning Management System
(LMS) has discussion boards that allow for asynchronous sharing, the technology
that greatly facilitates teamwork and collaboration is a program called
Elluminate since it allows students to meet as teams to discuss, share, and
modify documents in real time. Elluminate can also be used to quickly create
recordings of Powerpoint presentations that cover any questions or assignment
overviews that come up during the class. A transcript can easily be added to
comply with accessibility requirements. A wiki is also used for the midterm
essays and students often used Google docs for collaboratively working on their
analytical team reports about database and controlled vocabulary design.
Teamwork Process
At
the start of each semester the instructor uses a survey to ascertain student
skills, computer and online experience, and fears about the technology oriented
class. After five years of teaching the
course, student anxieties are in order of mention:
1. Teamwork
2. Time
3. Technology
4.
5. Workload
6. Isolation
7. Confidence
Student
comments indicate that teamwork exacerbated by the online environment was their
primary worry. The other concerns listed all related to the online environment
and only increased student anxiety as well as their unwillingness to
participate in the class.
Instructors
need to take a proactive role in building a collaborative environment for
students to work online.
The first step towards this goal is to look at what
the instructor wants to accomplish in the class and what type of teamwork meets
those goals. Most teamwork fits into one of the- three following types:
1. Solve problem è Present
consensus
2. Set policies è Work
Independently
3. Build product è Evaluate
Quite often more than one type is used; selection is
dependent on the assignment and outcomes.
The
second step is to determine what skills are needed by students to meet the
course goals. Generally these skills are:
1. Teamwork policies
2. Meeting facilitation
3. Project Management
4. Brainstorming
5. Consensus building
Having
a proactive strategy for teamwork leads to success and involves student
attitude and an established process.
Student Attitude
–
Participation
–
Collaboration
–
Team Goals (not egos)
Instructors can guide student attitude by setting
expectations for participation, collaboration, and team goals. Guidelines can
be established for assignments and grading criteria expressed in a rubric.
Students want to do well and will be more likely to follow clearly defined
requirements and examples.
Established Process
–
Planning
–
Communication
Having an established process relates to the second
step above that deals with establishing skills students need for planning and
communication. The skills needed are formed by the outcomes of assignments and
the technology available to students for communication. Using methods such as discussion boards,
Google docs, or wikis are more inclusive than emails which are often viewed as
exclusive and tend to inadvertently leave people out. Again detailed examples
and/or guidelines from the instructor are important since most students will
not have much experience. The level of detail depends on the grade level and
assignment expectations.
The
end result of these two steps of determining course goals and needed skills is:
Success versus Chaos! The results of
student work are greater than the sum of the parts.
Disastrous behavior
- Silent
- Absent
- Controlling
- Stubborn
When
team members do not comment or show up on discussion boards or at meetings,
they are exhibiting behavior that detracts from success. Everyone needs to
participate and all view points need to be discussed. This is behavior that
takes place on the job and in professional groups. Students need to learn these
skills since science especially is an exchange of ideas. Also the opposite, controlling or stubborn
behavior is just as costly because other team members will often stop
participating. Egos need to be left out and the team focus stressed. Instructor leadership is critical.
Successful team strategies
Successful
teams develop guidelines that strengthen participation, the key to success.
Some successful strategies are:
- Learn about teammates’ skills
–
Set team guidelines
- Discuss assignments
–
Set up a process
–
- Collaborate
–
Brainstorm
–
Build consensus
- Use tools wisely
Review
Teamwork is not always easy and takes practice. Teamwork
is constantly changing because each team or team task is different. Teamwork
becomes easier and confidence increases with practice.
Teamwork success is determined by
–
Attitude
–
Planning
Teamwork is an opportunity to practice leadership
and mentoring in a safe environment.
Team Responsibilities
–
Always show up.
–
Always do the job.
–
Always prepare for meetings.
Teammates Responsibilities
–
Always communicate with each other.
–
Always respect each other.
–
Always support each other.
Using
these simple steps will help ensure successful collaborative science projects
at any grade level.
The
observations and conclusions about teamwork resulted primarily from student
surveys, observations of team discussion boards, increased team participation
and enthusiasm, and improved grades.
Each class brings different challenges and new insights so teamwork is a
constantly evolving process and must remain flexible.
Enid J. Irwin
PLEF: A Conceptual Framework for Mashup Personal Learning Environments
There
is a wide agreement that the new era of education (especially science
education) is defined by rapid knowledge development. Among
others, Hase & Kenyon (2000) argue that this rapid rate of change suggests that
we should now be looking at a learning approach where it is the learner who
determines what and how learning should take place, and point out that
self-organized learning may well provide the optimal approach to learning in
the twenty-first century.
Self-organized
learning provides a base for the establishment of a model of learning that goes
beyond curriculum and organization centric models, and envisions a new learning
model characterized by the convergence of lifelong, informal, and ecological learning
within a learner-controlled space.
In
recent years, self-organized learning is increasingly supported by responsive,
open, and personal learning environments, where the learner is in control of
her own development and learning. The Personal Learning Environment (PLE)
concept translates the principles of self-organized learning into actual
practice.
From
a pedagogical point of view, a PLE-driven approach to learning supports a wide
variety of learning experiences outside the institutional boundaries. It puts
the learner at the center and gives her control over the learning experience.
From
a technical point of view, a PLE-driven approach to learning gets beyond
centralized learning management systems. A PLE suggests the freeform use of a
set of lightweight and loosely coupled tools and services that belong to and
are controlled by individual learners. Rather than being restricted to a
limited set of services within a centralized institution-controlled system, the
idea is to provide the learner with a plethora of different services and hand
over control to her to select, use, and remix the services the way she deems
fit. A PLE does not only provide personal spaces, which belong to and are
controlled by the learner, but also requires a social context by offering means
to connect with other personal spaces for effective knowledge sharing and
collaborative knowledge creation within open and emergent knowledge ecologies.
In
the following, we focus on the technical development of PLEs. A PLE is a
learner's gate to knowledge. It can be viewed as a self-defined collection of
services, tools, and devices that help learners build their Personal Knowledge
Networks (PKN), encompassing tacit knowledge nodes (i.e. people) and explicit
knowledge nodes (i.e. information). Thus, mechanisms that support learners in
building their PLEs become crucial. Mashups provide an interesting
solution to developing PLEs. In Web terminology, a mashup is a Web site that
combines content from more than one source (from multiple Web sites) into an
integrated experience. We differentiate between two types of mashups:
·
Mashups by
aggregation
simply assemble sets of information from different sources side by side within
a single interface. Mashups by aggregation do not require advanced programming
skills and are often a matter of cutting and pasting from one site to another.
Personalized start pages, which are individualized assemblages of feeds and
widgets, fall into this category.
·
Mashups by
integration
create more complex applications that integrate different application
programming interfaces (APIs) in order to combine data from different sources.
Unlike mashups by aggregation, the development of mashups by integration needs
considerable programming expertise.
Figure
1: PLEF Abstract View
The
Personal Learning Environment Framework (PLEF) provides a framework for mashup
personal learning environments. An abstract view of PLEF is depicted in Figure
1. PLEF leverages the possibility to plug learning components from multiple
sources into a learner-controlled space. This ranges from simply juxtaposing
content from different sources (e.g. feeds, widgets, media) into a single
interface (mashup by aggregation), to a more complex remixing of different APIs
into an integrated application, in order to create entirely different views or
uses of the original data (mashup by integration).
A
conceptual view of PLEF mashup engine is shown in Figure 2. PLEF mashup engine
supports both types of mashups i.e. mashups by aggregation and mashup by
integration. A key requirement for mashups by aggregation is that content
should be available in standardized formats that can be reused easily in other
contexts, such as Web feeds, widgets, and image/video formats. PLEF enables
learners to use copy-and-paste and drag-and-drop actions to easily juxtapose
different learning resources and services (e.g. feeds, widgets, and different
media) from multiple learning platforms and service providers within a
personalized space.
Figure
2: PLEF Mashup Engine
Unlike
mashups by aggregation, creating mashups by integration is a time consuming
task and impossible for a typical learner with no programming knowledge.
Moreover, in order to create mashups by integration, it is difficult to address
issues related to data interoperability, integration, and mediation. The
concept of semantic mashups (SMashups) (Sheth et al., 2007) addresses these
limitations by proposing the semantic annotation of Web services as a solution.
SMashups enable to automatically mix-up services, with different input and
output formats, based on a semantic description of the same.
Driven
by the SMashup concept, PLEF supports learners in selecting, managing, and
remixing different semantically annotated learning services with minimum
effort. Thereby, different Web service annotation standards such as Service
Mapping Description (SMD), SA-REST, and SA-WSDL can be used for the semantic
description of the services.
Driven
by the popularity of lightweight RESTful Web services,
References
Hase,
S. & Kenyon, C. (2000). From Andragogy to Heutagogy. ultibase Journal
[On-line]. Available: http://ultibase.rmit.edu.au/Articles/dec00/hase2.htm
Sheth,
A.P., Gomadam, K. & Lathem, J. (2007). SA-REST: Semantically Interoperable
and Easier-to-Use Services and Mashups. IEEE
Internet Computing, vol. 11, no. 6, pp. 91–94.
Zyp
K. (2009). Service Mapping Description. [On-line]. Available:
http://groups.google.com/group/json-schema/web/service-mapping-description-proposal
Mohamed Amine Chatti
Informatik 5 {Information Systems},
Matthias
Jarke
Informatik 5 {Information Systems},
Marcus
Specht
Open
University
Mobile Long Life Learner Pervasive Assistance System
Learning is the most sacred task for human
beings. An important number of persons fail to pursue their studies because of
various reasons and keep their ambitions for graduation or post graduation into
their hearts. Mobile professionals, a
subset of this kind of people, can find themselves in desperate situations when
they have ambitions and will to improve their skills but they cannot match
their work schedule with their class one. In fact, they are handicapped by
their mobility and the inflexibility of Long Life Learning Centers (3LC).
A Mobile Learner (ML), usually moves from
place to place connected by a road network, to take care of his/her permanent
and occasionally customers dispersed geographically. The ML activities may vary
in time and can allow him/her to have a free time at any moment. The ML has to
react quickly in front of happening events to catch an eventual course or exam.
To perform this objective, he/she has to find a 3LC, a class and a place in an
acceptable time, while moving in one of the roads (e.g. in his/her car or on
his/her feet). This can be performed using mobile devices well equipped to
query distant databases and get efficient answers while moving. Answers can be
ensured through a mediator, implemented thanks to wireless and mobile
network architectures (Lin and Chlamtac, 2001), able to provide efficient responses for
location dependent queries triggered by MLs.
The goal of this paper is to propose an
approach based on pervasive assistance system for MLs able to localize, to
match MLs free time with scheduled courses, and to make reservation of learning
resources while being in motion. It supposes the following assumptions: 3LCs
are distributed in various locations and grouped and managed in one centralized
structure, and MLs can follow their courses in any 3LC.
Any ML, obviously, ask the following
questions: Which are the nearest 3LCs close to my current position? Is there
some classes corresponding to my planned courses and to my level? Do those
classes’ schedules match with my free time? Is there available place in these
classes?
Our approach is performed to ensure
providing answers to above questions through a location based services
application interface implemented on the ML mobile device and based on the
following agents:
·
3LCs
Localor: Following
ML query, 3LC Locater agent determines the Continuous k Nearest Neighbors
(CkNNs) 3LCs thanks to Delaunay Triangulation based On road (DTr)
(Khayati and Akaichi, 2008). DTr
provides a valid response for continuous research of the k-Nearest Neighbors. (for
example: seek for me the 3 closest 3LCs from my current position).
·
Classes
and Level Matcher: More
than determining the point of interests, the learner desires are to distinguish
if these points enclose some classes corresponding to his/her planned courses
and to his/her level. This is achieved through the Classes and Level Matcher
agent able to match planned courses stored in ML mobile device database with
located 3LCs databases. It takes into account ML level and course level
provided by 3LCs.
·
Free
Time Matcher: This matcher looks for whether the computed courses
schedule corresponds to ML projected free time. This is achieved through a
matching performed according to free time preferences stored in ML mobile
device database with the 3LCs courses schedules.
·
Availability
Matcher: The agent determines whether there is an available
place for ML in the selected 3LC. If it is a positive answer ML decides on its
subscription into a class.
Moreover, mobile Graphical User Interfaces
(GUIs), aiming to help MLs to perform other tasks related to the use of some
virtual learning resources, are designed. MLs have only to provide minimal but sufficient information, to
acquire responses to their requests. The main GUIs are the following:
- Interface for CkNNs 3LCs Visualization:
Permits to visualize localized 3LCs on the road network map. Those are
displayed using a personalized color and labeled by their names, address
and real distances.
- Interface for CkNNs Browsing: Permits to zoom any
point of interest selected by ML. It is composed by
the road network and the points which can be distinguished by specific
colour. ML has only to click on any point of interest to browse learning
resources in order to choose one of them for a learning purpose. Zooming allows visualization of the
list of learning resources enclosed in any localized point of interest.
This is performed using a table of two columns. The first one displays
learning resources names, the second shows their descriptions. A button labeled ”Reservation”, in front
of each, permits to the ML to make the needed reservation. We note that this GUI is
also equipped by a button labelled “Compare”. When ML clicks on it, a
comparison is triggered between the identified points of interest, and the
number of the table columns is multiplied by the number of points of
interest.
- Interface for learning resources reservation:
When the ML click on the button, labeled ”Reservation”, a time table is
displayed showing the availability in time of the selected learning
resource. This allows ML to decide whether to reserve or cancel the whole
process and to go back for other points of interest.
Most of the services presented above are
interactive. Obviously, this interactivity has to be decreased due to the
professionals’ mobility related to their work nature. This can be ensured by
defining alerts according to ML preferences such as those specifying free
times, programmed locations at programmed times, etc. The mediator may extract
preferences information to compute matching performed by the above agents in
automatic way, and alert MLs in an adequate time. Those have only to visualize
such messages and to decide, whether or not, they are tolerable to their needs.
References
Khayati, M., Akaichi, J. (2008) ‘Incremental Approach
for Continuous k-Nearest Neighbors Queries on Road’, International Journal of
Intelligent Information and Database Systems (IJIIDS), Volume 2, No. 2, pp.
204-221.
Lin, Y., Chlamtac, I. (2001) ‘Wireless and
Jalel
Akaichi
ISG-University
of
41, Rue de
Le Bardo 2000
Tunisia
Distance Learning the Wave of the Future: A Case
Study of Bringing World Class Education to the Isolated Rural Poor of Pakistan
Abstract: Technology is around
everything we do. Integrating technology
into various aspects of university instruction has rapidly become an essential
component of effective teaching and learning. E-learning can be obliging in using it as an appropriate way to leverage
quality of education as it breaks the obstacles in terms of geography, time,
quality and competent teachers. The deployment of such an infrastructure
in a developing region such as N.W.F.P will also enable a better understanding
of the digital divide both within
Keywords: Information Communication Technologies (ICT), E-Learning
Introduction
The
influence of the Internet over the past two decades is unquestionable in the
ability to provide profound opportunities for both the education and business
communities around the globe. As technology evolves, we have been observing
segregation in the growth of performance between 1st world and 3rd
world countries. The e-learning portal constitutes a significant example of the
use of Information and Communication Technology (ICT) to deliver higher
education in both developed and developing countries. The
Sarhad University of Science and Information Technology (SUIT) has been playing
its part by maturing a collaborative research initiative with USA, under the
umbrella of a research project – objective of this is to expand the scope of
providing quality education through the use of the technology. Utilization
of the E-learning tools involves the local communities in the academic process
and would help to minimize the radicalism in the local communities of the NWFP.
Theoretical Framework
Over
the past decade many universities have invested heavily in information
technology in the belief that their investment would pay off and would enhance
learning and enrich the student experience. Both the education community and
the broader public community have long held great expectations for the role of
technology in teaching, learning, and instruction (Morrison, 1999). But where are we vis-à-vis instructor using
technology to enhance teaching? Research has revealed that increased use of appropriate technology in
instruction results in increased student learning (e.g., Grabe and Grabe, 1998;
Dwyer, Ringstad, & Sandholtz, 1991). Technology supports
collaboration and communication and the development of attitudes and skills. It
provides authoring support and allows instructors to monitor student activity.
Negroponte, Resnick, and Cassell (1997) argue that
digital technologies can enable students to become more active and independent
learners. The Internet will allow new ‘‘knowledge-building communities’’ in
which children and adults from around the globe can collaborate and learn from
each other. In
the student-centered classrooms of today, with the aid of the technology,
students are able to collaborate, to use critical thinking, and to find alternatives
to solutions of problems (Jaber, 1997).
Technology is nothing but applied science. Utilizing scientific ways for
learning about science and technology is not a new concept in western world. As
Mayer (2003) stated “it’s the method of
instruction that promotes learning not the medium of instruction”.
Technology as a tool for interaction
Distance education has a long history in contexts
where dispersed populations present challenges to traditional classroom-based
educational systems. To address this issue, modern information communication
technologies (ICT)-based forms of distance education are replacing
correspondence course and broadcast radio models that have been used in the
past (Davis and Niederhauser, 2005). E-learning can be obliging in using it as
an appropriate way to leverage quality of education as it breaks the obstacles
in terms of geography, time, quality and competent teachers. The employment of such an infrastructure in
a developing region such as N.W.F.P will also facilitate a better understanding
of the digital divide both within
To
implement e-learning methodology in full and positive way simply mean to
significantly change the method of teaching and learning, that is “concealed”
major target of the project and way to improve quality of education. That is why implementation of
e-learning is multifaceted and multilayered project that consists of selection
of political, social, organizational and technical measures that have to
synergize and effect in new, improved university education process.
Conclusion
We expect that educating the local communities through E-Learning tools would bring prosperity in the life of NWFP residents and put them on the path of sustainable progress. It will provide an opportunity to contribute to the development of new technologies and would contribute positively to the Pakistani society and economy. And most importantly it will add value in the NWFP communities – educating the local communities to make them better global citizens.
References
Davis, N. &. Niederhauser, S. Dale (2005), “Socio-Cultural Analysis of
Two Cases of Distance Learning in Secondary Education”. Centre for
Technology in Learning and Teaching,
Dwyer,
D.; Ringstaff, C.; & Sandholtz, J. (1991), “Changes in teachers’ beliefs
and practices in technology-rich classrooms,” Educational Leadership,
48(8), 45-52.
Grabe,
M. & Grabe, C. (1998), “Integrating technology for meaningful learning”,
Jaber,
W., (1997), “A survey of factors which
influence teachers’ use of computer-based technology”. Dissertation
Virginia Polytechnic Institute and
Mayer,
R.E. (2003), “Elements of a Science of
E-learning”. Educational Computing Research, 29(3), 297-313.
Morrison,
J. L (1999), “The Role of Technology in Education Today and
Tomorrow: An Interview with Kenneth Green”, Part II, On the Horizon,
1999, 7(1), 2-5.
Negroponte,
N, Resnick, M., & Cassell, J. (1997), “Creating
a learning revolution”. Retrieved on 25 July 2009 Available: http://education.unesco.org/unesco/educprog/
lwf/doc/portfolio/opinion8.htm.
Mike
Whitty
Adjunct
Professor of Management,
Ijaz. A.
Qureshi
Dean Faculty
of Management and Computer Sciences,
Maimoona
Saleem
Research
Assistant Faculty of Management Sciences,
Mehwish Shafiq
Research
Assistant Faculty of Computer Sciences,
National Learning Object Repositories An Architectural Rethink
Abstract. User requirements have caused the
Irish National Digital Learning Repository to fundamentally rethink its
approach to service provision for the Irish Higher Educational community. This
article presents an outline of the new architecture and its approach to meeting
the demands of users.
Keywords. Repository, Learning Object,
SWORD, SRU, SRW, Sitemap
Introduction
The Irish National Digital Learning Object Repository
(NDLR) (www.ndlr.ie) is a
collaborative project which involves all six
The focus of the NLDR has been to base its operations
on academic Communities of Practice (CoPs) and to use these communities of
practice as a mechanism for the dissemination of best-practice in technology
enhanced learning using reusable learning objects. The consequence of this is
that the demands made of the repository technology have been driven by the
demands of the academic communities of practice. This user-driven approach has
resulted in a new architecture for the repository which is described in this
paper.
The unique feature of the NDLR is that because
As part of the ongoing commitment to quality in the
NDLR, a comprehensive review of user-needs and perceptions was undertaken in
2008/9 and as a consequence of this a new prototype repository architecture was
designed which makes use of the latest technologies to provide a radically
different user-experience. The rationale behind this, the design goals, the key
technologies used and the conclusions from the preliminary testing of the
architecture are presented in the following sections of this article. A
diagrammatic representation of the architecture is shown in figure 1.
Rationale
The decision to design a new architecture came from a
series of user-focus groups which identified new trends in the manner in which
users wanted to interact with the repository. The most important of these being
that their activities would be better supported through a social networking
platform or learning management system (or both) with a built-in repository.
This impetus fundamentally changed the previous
concept of the NDLR architecture which had a set of social networks and a
repository technology that was parallel to these networks, not embedded within
them. This work was started about 12 months ago and has now been successfully
prototyped, what is of interest is the fact that other national organisations
in the UK are now taking a very close interest in the approach and starting to
consider moving in this direction.
Figure 1: New NDLR
Architecture
Design Goals
The design goals for the new repository were as
follows:
·
Agnostic to the database
technolog(ies) used
·
Embeddable in a wide range of social
networking and learning management platforms
·
Capable of indexing metadata in other
repositories
·
Capable of publishing its own
metadata to crawlers such as Google
·
Federated Authentication, Creative Commons Licensing
·
Low cost of ownership
Enabling
Technologies
The three key enabling technologies that combine to
deliver the new architecture are briefly described in the following sections.
The mechanism that allows deposit in the repository is based upon SWORD and the
mechanism that allows search and retrieve of objects in the repository is based
around SRU/W.
Deposit: SWORD
Simple Web-Service Offering Repository Deposit [1] is
an application profile of the Atom publishing protocol which has been developed
under the auspices of JISC in the
SWORD is designed to ‘lower the barriers to depositing
material in repositories’ [2] and is highly appropriate for an application of
this type as most of the NDLR depositors are depositing materials for
altruistic reasons and cannot be expected to expend a great deal of effort
in the deposit process.
Search and
Retrieve: SRU/SRW
Search and Retrieve by URL [3] is a standard search
and retrieve protocol which was derived from the widely adopted but outdated
Z39.50 protocol for library search and retrieval. The SRU protocol can be
implemented as a web-service, using either SOAP or REST techniques (though REST
is increasingly the preferred approach) and in this instance it is referred to
as SRW. SRU is an XML-based protocol which has Contextual Query Language, CQL
built into it to support a powerful and database-agnostic search query
interface.
Metadata
Publishing: Sitemaps
In order to allow the content of the repository to be
searchable via Google and other search engines, it is necessary to provide a
mechanism that allows these engines to ‘crawl’ the repository and extract
information from them. This is a critical task in contemporary repository
architecture as most users searching for an object will go to Google in advance
of anything else. Google have published a mechanism called “Sitemaps” [4] to
allow this to take place. The repository needs only to generate a sitemap and
put it in a place where Google can see it for its metadata content to be
indexed.
Conclusions
The prototype system has met its design goals and a
decision to proceed with the deployment of a full-scale service based on this
architecture has been taken. It is believed that this approach will offer
significant cost-savings and an enhanced service to NDLR users, contributors
and administrators.
References
[1] Allinson, J. Et Al. (2008) ‘SWORD: Simple Web-service Offering
Repository Deposit’, Ariadne (Issue 54)
January 2008, http://www.ariadne.ac.uk/issue54/allinson-et-al/
[2] Currier, S. (2009), ' SWORD: Cutting
Through the Red Tape to Populate Learning Materials Repositories’, JISC
eLearning Focus, http://www.elearning.ac.uk/features/sword
[3] Library of Congress (2009), Standards,
The SRU Protocol, http://www.loc.gov/ standards/sru/
[4] Google (2008),
The Sitemaps Protocol, http://www.sitemaps.org/
Bob
Strunz
Gareth Waller
List of International Conferences on Learning Technologies
DIGITEL 2010 The 3rd IEEE International Conference on
Digital Game and Intelligent Toy Enhanced Learning, Kaohsiung, Taiwan, 12-16 April 2010
WMUTE 2010 The 6th IEEE International
Conference on Wireless, Mobile & Ubiquitous Technologies in Education,
SITE 2010 Society for Information Technology &
Teacher Education, San Diego, CA, USA, 29 March
- 2 April 2010
ITHET 2009 9th International Conference on
Information Technology based Higher Education and Training,
ICODL 2009 5th International Conference
on Open and Distance Learning ,
CATE 2009 12th IASTED International
Conference on Computers and Advanced Technology in Education, St. Thomas, US Virgin Islands, 22-24 November 2009
CELDA 2009 IADIS International Conference Cognition
and Exploratory Learning in Digital Age,
mLearn 2009 8th World Conference on Mobile and
Contextual Learning,
E-Learn 2009 World Conference on E-Learning
in Corporate, Government, Healthcare, & Higher Education,
MTDL 2009 ACM International Workshop on Multimedia
Technologies for Distance Learning ,
FIE 2009 39th Annual Frontiers in Education
Conference,
TELearn 2009 Technology Enhanced Learning Conference
2009, Nankang,