A Web-based Composition Learning Envi-ronment and its Conformance to LTSA and - EML
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A Web-based Composition Learning Envi-
ronment and its Conformance to LTSA and
EML
CHIEKO NAKABASAMI
Toyo University
1. Introduction
Exponential improvements to the Internet during the past decade have
triggered proposals for the standardization of learning technologies.
Many proposals concerning learning technologies have been taken into
consideration in order to utilize Internet technologies. E-learning and
web-based training have evolved to play a central role in learning tech-
nologies[1][2]. In this paper, we explain the TeNiWoHa Checker 1 , a
web-based Japanese CALL system. We also discuss potential im-
provements to the checker, taking into consideration conformance to
the standard concerning learning technologies proposed by the Interna-
tional Standards Organization (ISO)[3].
The Institute of Electrical and Electronics Engineers (IEEE)[4] and
the European Committee for Standardization (CEN)[5] have actively
led the movement toward the standardization of learning technologies.
Their aim is the dissemination of learning technologies for information
sharing and reuse across a wider educational environment. In Japan,
1
It is available at http:// http://teniwoha.itakura.toyo.ac.jp:8080/k-project/kotoba/kotoba.jsp
1
three leading organizations--ISO SC36[6], hosted by the Information
Processing Society of Japan (IPSJ)[7]; the Advanced Learning Infra-
structure Consortium (ALIC)[8]; and the E-learning Consortium of
Japan (ELC)[9]--have been developing various standards, assisting in
research projects, and proposing research and development in education.
Their aim is to share educational material, learners’ profiles, and learn-
ing systems. They are developing application interfaces and data for-
mats for educational materials so that interoperability can be realized
among the learning systems.
The first section of this paper focuses on the system architecture and
the learning flow of the TeNiWoHa Checker. Next, we discuss how the
checker should conform to the international standard in order to fulfill
requirements of Japanese learners and teachers regarding a web-based
CALL system. It is difficult for the checker to help learners understand
implicit rules that apply to problems in fields such as mathematics and
science. In language learning, including beginning composition, learn-
ers tend to require face-to-face instruction from their teachers because
there are few rules in the field, except in grammar, and there are as
many error patterns as there are learners. However, from the perspec-
tive of e-learning, it is extremely important to improve the sharing of
language-learning resources, and learning systems should be designed
for possible use on the Internet.
In data formats on e-learning standardization, the focus is on meta-
data descriptions because interoperability is accelerated when the meta-
data descriptions are shared. On the TeNiWoHa Checker, sharing ad-
vice from teachers is thought to be indispensable, and it is necessary to
provide appropriate metadata descriptions regarding the content of the
advice.
In the last half of the paper, we introduce Learning Technology
Standard Architecture (LTSA)[10]. LTSA is a standard for learning
technologies proposed by the Learning Technology Standardization
Committee (LTSC)[11], a committee of the IEEE. First, the five layers
of LTSA are illustrated, and then the third layer, the System Compo-
nent Layer, is explained in detail. Learning Object Metadata
(LOM)[12], proposed by the LTSC for the metadata used in learning
systems, is used for representations of learning resources in LTSA.
With LOM, visual material for educational use is distributed over the
Internet by an Information-technology Promotion Agency (IPA) web
site[13]. LOM has been designed so that teachers and agents responsi-
ble for distributing materials can search for their resources through a
learning resource repository with catalog information provided by LOM.
LOM does not describe content with a more educational flavor, such as
the advice of teachers. To overcome this deficiency, we propose a rep-
resentation method for advice using Education Modeling Language
(EML)[14].
2
2. The TeNiWoHa Checker System
2.1 Purpose of the TeNiWoHa Checker
The TeNiWoHa Checker is Japanese composition learning material in a
client-server environment which has been funded by Toyo University
since 2001. It is web-based material which enables students to learn the
usage of Joshi, Japanese post-positional words, using the web browser.
Supposed users are non-Japanese students from overseas. Japanese
lessons for these students in universities consist of grammar, vocabu-
lary, reading, and composition. Composition learning, especially, in-
volves individual variations for each student, which makes teaching
composition to a large class difficult. Individualized teaching is suitable
for composition learning, and it requires “oracles” by human teachers.
The TeNiWoHa Checker has been developed in order to overcome this
difficulty in realizing individualized learning with a human teacher by
implementing the web environment via computer systems.
2.2 The state of the art in web-based material
In developing the TeNiWoHa Checker, we have respected the fol-
lowing features as its web-based material.
(1) From anonymous senders to anonymous recipients
Today, much material records students’ learning process to as-
sess their improvement. The TeNiWoHa Checker, however,
does not store students’ records; it only records logs regarding
when someone runs the checker and what sentence has been in-
putted. Because the checker does not pay attention to who runs
it, interactions among anonymous users on the web may pro-
duce synergy effects that cannot be obtained with non-
anonymous users. For example, suppose someone facing prob-
lems at work surfs the web for solutions. He might happen to
get similar solutions from homepages of unknown persons by
submitting keywords via a search engine portal.
The TeNiWoHa Checker tries to apply such methods to com-
position learning because sentence correction patterns for each
student vary enormously and information from anonymous stu-
dents’ correction patterns are expected to give hints regarding
his sentence. In addition, the more students use the checker, the
richer the teachers’ advice becomes, which makes the students’
learning environment more effective. Though the checker does
not record a specific student’s logs, the teachers give advice to
that specific student. It is reasonable to say that the checker en-
sures a personal learning environment between a specified stu-
dent and teacher.
(2) Easy development and sharing of materials
The checker uses XML[15] for teachers’ advice. XML is a stan-
dard document format for information exchange via the web,
3and information can be shared among heterogeneous applica-
tions and platforms using XML, enabling teachers to manipulate
their advice easily. Before, teachers spent their time mastering
authoring applications for submitting advice. XML frees teach-
ers from such stress and offers an environment in which it is
easy to formulate and give advice.
2.3 Features of the TeNiWoHa Checker
The main function of the system is to correct students’ Japanese sen-
tences by focusing on Joshi usage. Sentence correction does not mean
modifying sentences by proposing better candidates of Joshi, however.
Instead, students correct their sentences by themselves according to the
advice of teachers and similar example sentences in the Japanese corpus.
Some of the features of the system are as follows.
(1) Improved portability due to XMLizing data
Concerning language resources for correction, the EDR
Japanese corpus and teachers’ advice are provided. XMLizing
these resources enables the integration of heterogeneous data
regardless of the various operating systems. The users of the
system pay no attention to the specific data format of the corpus
and are able to manipulate the data easily.
(2) Realization of an interactive on-demand learning environment
on the web
The system enables students to study ‘anywhere, anytime’ if
they have Internet access by way of a WWW browser. In the
system, JSP (Java Server Pages) is used to ensure interactivity
between the server computer and the students’ computers. In
addition, it is possible for teachers to browse the sentences in-
putted by the students regardless of time and place, and the
teachers’ advice is incorporated into the correction process im-
mediately.
2.4 Learning flow of the TeNiWoHa Checker
The learning flow of the TeNiWoHa Checker is shown in Figure 1. The
checker system is implemented with Java. In Fig. 1, the flow is ex-
pressed considering conformance to LTSA, as mentioned in Section 3.
Referring to the flow in Fig. 1, how the TeNiWoHa Checker processes
students’ sentences is explained in detail according to the user interface
for the students in Table 1. The numbers in parentheses below corre-
spond to the numbers in Fig. 1. In the TeNiWoHa Checker, the learning
cycle continues from (1) to (5).
4Learner
JSP Input sentences
Choose theme
TeNiWoHa Server for sentences
”XMLize” sentences Show examples
Generate association rules Explain their Checking inputted
Show examples semantic roles sentences
Show results after adding
teachers’ advices Select
Upload
advices sentences for
advising
EDR
Japanese corpus
Teacher
Advice XML
WEKA Submit advices
editing
(Java API)
Figure 1. Learning flow of the TeNiWoHa Checker
(1) Inputting sentences by students and natural language processing
on the TeNiWoHa Server( )(Figure 2)
Students input a sentence to be corrected and click ‘Check.’ The
server processing the sentences, called the TeNiWoHa Server,
receives them via Java Server Pages (JSP). Then the server ex-
tracts similar sentences, including the same nouns and verbs ap-
pearing in the students’ sentences, from the EDR Japanese cor-
pus[16].
(2) Showing the results from the corpus( )(Figure 3)
The TeNiWoHa Server derives Joshi-noun or Joshi-verb pairs
appearing frequently in the sentences using Association
Rules[17] with WEKA[18], Java API. The TeNiWoHa Server
shows the web browser the results of association rules that are
the 10 most frequent pairs of Joshi-noun or Joshi-verbs.
(3) Browsing of students’ input by teachers( )(Figure 4)
Teachers look at the students’ inputted sentences and decide for
which sentence they will give advice.
(4) Submitting advice( )(Figure 5)
Teachers give advice regarding each sentence. They input a
comment, the correct Joshi and its semantic role, and example
sentences including the Joshi. The advice is manipulated in
XML format. In addition, the teachers are able to modify their
previously submitted advice via the web browser.
(5) Browsing teachers’ advice by students ( )(Figure 6)
Students who inputted sentences earlier browse the results again
and have a chance to get even richer correction results.
5Figure 2 Main interface of the TeNiWoHa Checker
Figure 3 Results from the EDR corpus
6Figure 4 List of students’ inputs2
Figure 5 Teachers’ advice
2
It is available at http:// http://teniwoha.itakura.toyo.ac.jp:8080/k-project/kotoba/historyEML.jsp
7Figure 6 Revised advice from the TeNiWoHa Checker
2.5 Advice description in the TeNiWoHa Checker
Teachers’ advice should play a very important role so that the TeNi-
WoHa Checker can become a popular CALL resource among Japanese
learners and teachers via the web. Suitable metadata representation
should be required for the description of teachers’ advice. In addition,
the TeNiWoHa Checker should conform to LTSA, a major e-learning
standardized architecture for realizing the sharing of material such as
advice. At present, the only reward the teachers receive for their effort
in representing XML is a personal annotation. The tag names in the
representation correspond to the field names in the form for submitted
advice by the teachers shown in (4) in Section 2.4. Improvement of the
teachers’ advice focuses on the conformance to the standardization of
learning technologies3.
3. Learning Technology Systems Architecture (LTSA)
LTSA is a standard for system architecture concerning learning tech-
nology discussed by the P1484.1 Architecture and Reference Model
Working Group of the Learning Technology Standards Committee
(LTSC), an IEEE committee. The current version of the LTSA draft [10]
is Version 9, proposed on 30 Nov. 2001.
LTSA proposes a model for implementing learning systems on the
computer and required information among learning objects in the model.
The LTSA system components have five layers. Each layer moves
down from abstraction to implementation. Figure 7 excerpts the five
3
It is available at http:// http://teniwoha.itakura.toyo.ac.jp:8080/k-project/kotoba/adviceEML.xml
8layers in LTSA from the working draft of LTSC. In Fig. 7, only Layer 3,
the LTSA system component, is indispensable for LTSA. Layer 3 is
described in Fig. 8. As shown in Fig. 8, the LTSA system components
consist of the following kinds of objects. A detailed explanation of each
object is omitted for the sake of space.
• Processes: learner entity, evaluation, coach, and delivery
• Stores: learner records, and learning resources
• Flows: learning preferences, behavior, assessment information,
performance, preference information, query, catalog info, loca-
tor, learning content, multimedia, and interaction context
Figure 7 The LTSA abstraction-implementation layers
Figure 8 LTSA system components
The teachers’ advice on the TeNiWoHa Checker is positioned as
shown in Fig. 9 if the advice is considered a learning resource, or learn-
ing metadata in a standardized e-learning system. In Fig. 9, teachers’
advice is used by the request of the TeNiWoHa Server. The TeNiWoHa
Checker can be used among more learners and teachers of Japanese if
the teachers’ advice, an important factor in the checker, conforms to the
standardized system architecture.
9Learner
JSP Input sentences
Choose theme
TeNiWoHa Server for sentences
”XMLize” sentences Show examples
Generate association rules Explain their Checking inputted
Show examples semantic roles sentences
Show results after adding
teachers’ advices Select
Upload
advices sentences for
advising
EDR
Japanese corpus Advice XML
Teacher
Submit advices
WEKA
(Java API)
Figure 9 Revised learning flow of the TeNiWoHa Checker
4. Advice description with Educational Modeling Language
(EML)
4.1 Learning Object Metadata (LOM)
As mentioned earlier, the sharing of teachers’ advice is indispensable if
the TeNiWoHa Checker is to be used among learners and teachers as
web-based material. Learning Object Metadata (LOM)[12] is proposed
by LTSC; however, LOM does not meet the TeNiWoHa Checker’s
requirements because teachers’ advice has many pedagogical features
that LOM is unable to express. No detailed explanation is given here
for the sake of space. LOM is basically metadata for categorizing mate-
rials and is organized according to the following specifications:
1. General 2. Life Cycle 3. Meta-Metadata
4. Technical 5. Educational 6. Rights
7. Relations 8. Annotation 9. Classification
In Japan, as an example concerning LOM, educational visual mate-
rial information is provided in LOM format at the web site of the
Information-technology Promotion Agency (IPA). At the IPA site,
swimming techniques for junior high school physical education stu-
dents are published in LOM format [19]. The fifth category in the
above specification, educational, might be adapted for their content if
the teachers’ advice is described in LOM. On the other hand, in LOM,
values of each term for each specification are provided with some alter-
natives, making it more difficult to describe the pedagogical aspect of
teachers’ advice in the TeNiWoHa Checker. To overcome this defi-
ciency of LOM, Educational Modeling Language is applied for the
advice in the checker.
104.2 Description of advice with Educational Modeling Lan-
guage (EML)
The design of EML was based on the learning process itself, and each
learning process is called a unit of study [20][21]. Each unit of study is
assigned one scene in a stage of the learning process. In each scene,
learners and teachers play a specified role, and various kinds of objects,
such as a knowledge object or communication object, are provided in
order to function appropriately in a learning environment for the stage
settings. In EML, learning is supposed to involve roles and activities
played by individual characters in such environments. To represent
teachers’ advice in the TeNiWoHa Checker with EML, one unit of
study should be provided for the regular learning cycle of the checker,
which should be accompanied by other units for the usage of each Joshi.
A metadata scheme of EML is illustrated in Fig.10, in which the
usage of Joshi ‘KARA’ is exemplified. The hierarchy structure of XML
elements based on EML is also shown in Fig. 10. In the Appendix, a
stub of XML representation for Fig. 10 is written. The declaration sec-
tion of XML is omitted from the Appendix, and complex units of study
are described together.
Unitofofstudy
Unit study
Totallearning
Total learning
Type=“advice for KARA”
flowofofcorrecting
flow correcting
sentences
sentences
Unit of study
Unit offor
KARA study
cause
Unit of study
Unit of study KARA for cause
KARA for
KARA for
start time
start time Unit of study
Unit of study
KARA for
KARA for
start place Metadata
Metadata
start place
Roles
Activity Content
Activity
Metadata
Metadata Method
Environment
Environment
Source
Source Knowledge Play
Knowledge Play
What object
object
What Role
Reference
Completed
Completed Activity
Figure 10 EML metadata scheme concerning learning the usage of
‘KARA’
115. Feedback from the students
We tried using the system for the last 30 minutes of a Japanese lesson
for first-year non-Japanese students. After the lesson, we interviewed
the students about the system and received the following answers.
•
•
•
•
Some students had a negative opinion because of the focus on Joshi
only; on the other hand, some had a positive opinion, saying they en-
joyed learning with the system and it was easy to operate.
6. Future work
We are planning the following improvements to the TeNiWoHa
Checker.
• Extension to materials with multimedia content
Oral learning is thought to be very significant not only in Japa-
nese language learning but also in general language learning.
Though the focus of this paper is learning the usage of Joshi,
our proposal regarding metadata representation with EML can
be adapted to many language-learning systems. For instance,
or elements are used for this purpose, by
which richer multimedia content which LOM cannot treat can
be expressed with EML. We would like to apply EML specifi-
cations to multimedia CALL systems.
• Considering IMS Learning Design for the evolving version of
EML
In February 2003, IMS[22] approved the final version of Learn-
ing Design specification[23], which was based on EML. We
should improve our system by taking Learning Design into con-
sideration.
References and Related URLs
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