132
are applied in the system. Learner agents (LA) are software agents whose
functions are: (1) to represent and model a human learner; and (2) perform
tasks on behalf of human learners [14]. Resource Agents (RA) are the core
agents in the system. RA receives the LA'S request and process the request by it
self or collaborate with other agents. The request and response message in the
system are defined as KQML messages (see Figure 8).
Figure 8 The request and response KQML perforrnatives
When an LA get user's request, it queries the profile database and creates a
request KQML message. The message is packed as a SOAP message and
transport to a RA in the environment. The RA moves to one learning resource
database and queries it, then moves to the other, etc. The process will not be
terminated until the target resource is f h d out or no such resource in any
resource database. Then the RA will create a response message to make LA get
the result.
The software language to construct mobile agent system should be object
oriented, platform independent, with communication capability, and
implemented with code security [151. Aglet provided by IBM is a nice solution
for agent development because it is developed with Java which makes it can
run on any platform. It can be chose to implement a prototype system like the
application system introduced above.
6 Conclusion and Future Work
The authors of this paper put forward an agent assisted learning resource
service framework based on SOAP. KQML is applied in the framework as an
agent communication language, which makes it easy to interoperate between
two resource agents. SOAP is applied in the framework as a communication
protocol to load message and transport resource content, which provides a
communication approach over HTTPEMTP. XML is applied in the framework
as a binding specification, which makes the protocols be bind in consistent
format and parsed in a uniform avenue.
In the future work, we will focus on improving the performance of the
framework. Some methods, such as XML data compressing and package
133
predigesting can be considered to get the goal. In addition, we will try to
optimize the structure of the framework so that it can be implemented easy, and
we will also implement a practical application system based on the framework.
Acknowledgement
This work is supported by Ministry of Education (MOE), P.R.C. We
acknowledge the staff of E-Learning Working Group (ELWG) in our research
center (http://itec.hust.edu.cn),and we also thank for the support of MOE. We
thank Mr. Peng Qingtao for his provocative discussions about the application
of the framework and his perfect development work in the system
implementation.
References
[11World Wide Web Consortium, Simple ObjectAccess Protocol (SOAP)
Version 1.2 Part 0: Primer, W3C RecommendationJune 24,2003.
[2] Sperberg-McQueen, Eve Maler, Extensible Markup Language (XML) 1.O
(Second Edition), W3C Recommendation 6,2000.
[3] Yannis Labrou, Tim Finin, A Proposal for a new KQML Specification,TR
CS-97-03, February 3, 1997.
[4] Jaideep Roy and Anupama Ramanujan, XML Schema Language: Taking
XML to the Next Level, IT Professional, March-April 2001.
[5]JonT.S. Quah, Winnie C.H. Leow, Y.M. Chen, Mobile Agent Assisted
E-Learning, the First International Conference on information Technology &
Applications(ICITA 2002), 2002.
[6] Sabin-CorneliuBuraga, Developing Agent-Oriented E-Learning Systems,
proceedings of the 14thInternational Conference on Control Systems and
Computer Science, 2003.
[7] Sun Microsystem, http://www.huihoo.com/one-and-net /app7/12.1.htm#08,
2004.
[8] Paul OConnell, Rachel McCrindle, Using SOAPto Clean up Configuration
Management,the 25th Annual International Computer Software and
Applications Conference (COMPSAC’Ol), 2001.
[9] Sabin-CorneliuBuraga, DevelopingAgent-Oriented E-Learning Systems,
Proceedings of The 14th Internation- a1 Conference on Control SystemsAnd
Computer Science, 2003.
[lo] Yannis Labrou, Tim Finin, A Proposal for a new KQML Specication(TR
CS-97-03), February 3, 1997.
134
[111Zhongnan Shen, Yuanchun Shi, Guangyou Xu, A Learning Resource
Management System Based on LOM Specification,Proceedings of the 7th
International Conference on Computer Supported Cooperative Work in Design
(CSCWD 2002), Rio de Janeiro, Brazil, September 25-27,2002.
[121Learning Technology StandardsCommittee of the IEEE Computer Society,
IEEE Standard for Learning Object Metadata. 13 June 2002.
[131IMS Global Learning Consortium,Inc. IMS Content Packaging
Information Model Version 1.1.2Final Specification,8 August 2001.
[141Teresita Limoanco, Raymund Sison, Use of LearnerAgents as Student
Modeling System and Learning Companion,Proceedings of the International
Conference on Computers in Education (ICCE’02).
[151James E. (May 1996)White Mobile Agents; URL: http://www.webtechni
ques.com/archives/l996/ OS/white/.
TEACHING STROKE ORDER OF CHINESE CHARACTERS BY
USING MINIMAL FEEDBACK
KERRY TSANG AND HOWARD LEUNG
City University of Hong Kong, Tat Chee Avenue
Kowloon Tong, Kowloon, Hong Kong
In this paper, we propose a new automatic method to learn or correct the stroke order of
Chinese characters. The methodology is based on the ideas of grouping strokes and
applying the longest increasing subsequence method to provide a minimal feedback to the
user automatically. With minimal feedback, the least amount of information is needed to
be provided to the user to correct the stroke order mistakes. Experiments from user
studies show that the proposed minimal feedback approach requires less time and
achieves similar learning effectiveness compared with normal feedback.
1. Introduction
Traditionally, people learnt a Chinese character by reciting it stroke-by-stroke.
As time goes by, people write and use the characters many times, so they have a
strong memory - a reflex on the characters. Their memory may be refreshed by
reading printed text to recollect information about a Chinese character such as
the stroke shape, orientation, length, relative position, structure, number of
strokes, etc. However, the stroke order that requires the temporal information
cannot be recalled in this manner. A person may write a character in the wrong
stroke order either because the person forgets the correct way or because that
person makes some mistakes the first time he/she learns that character. Studies
have shown that children made stroke sequencing errors because sequencing
rules for Chinese characters can be ambiguous’. Additional exercises are
required to verify whether the user writes the Chinese character correctly and
the user is provided with some feedback if the stroke order is wrong.
Although a stroke-by-stroke animation of the character can be provided as
the feedback each time when a user writes a character in the wrong stroke order,
this feedback is the same in all situations so it does not specify where the user
makes the mistake. This kind of feedback is quite time-consuming especially if
the user does not make too many stroke order mistakes. Often parts of the user’s
memorized stroke order are correct, thus it is not efficient to re-learn the entire
order from the first stroke to the last stroke. As a result, we propose to provide
automatic minimal feedback to the user for correcting the stroke order mistakes.
With minimal feedback, the least amount of information is provided to the user
to correct all stroke order problems. This minimal feedback is achieved by
grouping consecutive strokes in the correct relative order and applying the
longest increasing subsequence method to identify the groups with the correct
and incorrect stroke order to be feedback to the user.
135
136
Some researches have been focused on determining the stroke order and
structure for offline Chinese character recognition and signature verification
application^^.^. Regarding handwriting education, we have done some prior
work on teaching people to write Chinese characters with automatic analysis
based on the shape information4.In this paper, we propose a novel minimal
feedback approach in teaching the stroke order. This paper is organized as
follows. In Section 2 we provide a description of our methodology and illustrate
the details of the algorithms. We describe our experiments and present the
results in Section 3. The conclusions and future work are provided in Section 4.
2. Minimal Feedback Methodology
After showing a template character to the user on a pen-based device, the user is
required to write the same character with the stylus. As illustrated in Figure 1,
the user input character is processed in four stages: matching, grouping, longest
increasing subsequence (LIS) and feedback. AAer these stages, the minimal
LIS -Matching -+ Grouping -+
feedback on the stroke order correctness is generated automatically and
presented to the user.
Feedback
2.1. Matching
The objective of this module is to determine whether the user writes a character
in the correct stroke order. There are several methods to determine the correct
stroke order from the user input such as applying offline techniques to extract
the radicals and using heuristic rules to determine the order of the radicals or
ordering the strokes with other structural rules’. The stroke sequence can also be
estimated by minimizing the total stroke distance using the direction as the cost3.
Since in our system, we collect the handwriting with a pen-based device so
the temporal information of the strokes is available. Moreover, the template
character is present in front of the user for learning that character. As a result, in
the matching stage, we can compare the strokes between the user input character
and the template character in order to determine whether the user input character
has the correct stroke order defined by the template character. The stroke
correspondence between the user input character and the template character
needs to be determined and it can be obtained by minimizing the total cost
between strokes with the Hungarian method5.
137
An example of the stroke matching result between the user input character
(U) and the template character (T) is shown in Table 1. The entries in the 2nd
row represent the temporal stroke IDSof the template character while the entries
in the 1" row represent the corresponding matched temporal stroke IDSof the
user input character after finding the stroke correspondence. For example, stroke
0 of user input is matched with the stroke 0 of the template; stroke 5 of user
input is matched with the stroke 1 of the template, etc. This results in a numeric
sequence [0, 5, 6, 1'2, 3'41 representing the temporal stroke IDS of user input
(stroke 0 +stroke 5 +stroke 6 +stroke 1 +stroke 2 +stroke 3 +stroke 4)
which is the correct stroke order specified by template character. This result is
passed to later stages for grouping and extracting the longest increasing
subsequence before generating minimal feedback.
Table 1. Stroke matching result.between user and template characters
UIO 5 6 1 2 3 4
TI0 1 2 3 4 5 6
2.2. Grouping
Grouping is performed for the numeric sequence resulting from the matching
stage. A group is defined as a set of adjacent strokes in the numeric sequence
with stroke IDSforming increasing consecutive numbers. For example, there are
three stroke groups (0), (5, 6), (1, 2, 3'4) for the user character shown in Table
1. The time complexity of grouping is O(n)where n is the number of strokes.
There are two advantages in grouping the strokes: preservation of relative order
within group and reduction in computation complexity.
The strokes within a group have the correct relative stroke order because
the stroke IDSwithin a group form increasing consecutive numbers. People tend
to memorize relative stroke order rather than the absolute stroke order. This can
be easily verified by a simple experiment by first showing a person a known
character and asking that person which stroke corresponds to the 31d stroke. The
person often needs to trace the character in hisher mind starting from the 1"
stroke. On the other hand, if we show the person the first two strokes of a
character and ask that person to write the next (31d) stroke, then he/she can write
it immediately without much thinking. This is because the stroke order
information is stored sequentially in the relative stroke order in people's mind
rather than in the absolute stroke order with random access. This observation
justifies the grouping of strokes such that people can associate strokes in the
relative stroke order within each group as one unit.
138
Another advantage for grouping is the reduction in computation
complexity. Considering each group as one unit speeds up the processing of the
groups for extracting the longest increasing subsequence in the later stage.
Qualitative and quantitative analyses will be provided in subsequent sections
regarding this aspect. In addition, the groups are used for providing feedback to
the user to identify correct and incorrect stroke order. This reduces the amount
of information provided to the user hence minimal feedback can be achieved.
2.3. Longest Increasing Subsequence
After grouping, we determine which groups of the user character have the
correct stroke order by using the Longest Increasing Subsequence (LIS) method.
As suggested by the name, the LIS is the longest subsequence in which all
numbers are in increasing order. Several algorithms637have been proposed to
extract the longest increasing subsequence given an input sequence. When the
sequence is nearly sorted, i.e., when the elements of the numeric sequence are
almost strictly increasing, the performance of the algorithm6will be the worst
with O(n2)where n is the number of elements in the input sequence. Another
algorithm7is proposed in with time complexity of O(n log n). In our approach,
after grouping the strokes, we form a new sequence by taking the first number
of each group and use this sequence as the input for the LIS algorithm7.The
strokes in the associated groups from the resulting LIS are labeled as the strokes
with the correct stroke order and all other strokes in the remaining groups are
labeled with the wrong stroke order. For example, the groups formed from the
example shown in Table 1 are (0), (5,6), (1,2,3,4). The new sequence [0,5, 13
is formed by taking the first element from each group. The LIS is determined to
be [0, 11 corresponding to the strokes (0), (1,2,3,4) which are the strokes
determined to have the correct stroke order. The remaining strokes (5,6) are
considered as the strokes with wrong stroke order. This information is provided
to the user during the feedback stage.
2.4. Feedback
In this stage, according to the LIS and the groups, we show an animation of a
correct-ordered character group-by-group for achieving minimal feedback. By
using the animation group-by-group in this minimal feedback approach, the user
can just pay attention to the parts they made mistakes, thus there is no need to
learn the whole character stroke-by-stroke again as in the normal feedback.
139
3. Experiments and Results
We carry out some experiments to study the effectiveness of our proposed
minimal feedback approach for teaching people stroke order of Chinese
characters. There are two parts in the experimental setup. The first experiment is
designed to test how much time people need to learn the stroke order of a
character by using minimal feedback (group-by-group) and by using normal
feedback (stroke-by-stroke). The second experiment is to test whether people
will still remember how to write the characters with the correct stroke order
after one week. It is assumed that the subjects know how to write the characters
without the stroke-production errors such as stroke reversal, concatenation of
separate strokes and broken strokes.
Three template characters: 1. @/ , 2. @ and 3. i3 are used in these
experiments. These characters are selected because it is common that people
write them with the wrong stroke order. For example, for the character @/,
people usually write the part “&” first, and then two f .Actually, the strokes for
the part ‘‘W’ should be written at different instants. The correct stroke order is
shown in Figure 2 .
Figure 2. Stroke order for the character @.
3.1. Reduction in time complexityfor grouping
As indicated in Section 2.2, grouping reduces the time complexity for obtaining
the LIS. As stated in section 2.3, the time complexity €or LIS is O(n log n).
After collecting the user data for the four template characters, the number of
groups m iis recorded and the average number of groups is calculated in each
case. In addition, the average time complexity for grouping can be calculated by
taking the average over the quantity mi log mi.The results from 150 user input
characters are summarized in Table 2 in which the reduction in time complexity
for obtaining LIS with grouping is shown for each case. It can be seen in the last
column on Table 2 that the LIS with grouping can be computed 6 to 12 times
faster than the case without grouping.
140
Table 2. Reduction in time complexity for grouping.
Char. No. of Time Complexity Average no. Average Time Speed up
strokes without grouping of groups Complexitywith grouping factor
1.m 2 12.0
2.g 9 8.59 2.5 0.716 9.1
3.E 11 11.46 2 1.262 6.5
6 4.67 0.722
3.2. Experiment 1: Time taken _ _ learn the s.. oke order with minimal
feedback and normalfeedback
In order to compare the efficiency between using minimal and normal
feedback, a PDA program is developed to record the data as shown in Figure 3.
There are 18 people in the test group (with minimal feedback) and 18 people in
the control group (with normal feedback). The age of the subjects is between 20
and 40. With the program in the PDA, each subject will try to write characters
given the template characters. When a template is chosen, the program starts the
timer for this template character. Then the user writes the character in the
designated square region and presses a button to start the analysis. If there is
something wrong about the stroke order, the user will get the feedback. There
are two kinds of feedback: normal feedback with stroke-by-stroke animation
and the minimal feedback with group-by-group animation. The choice of
feedback depends on whether the subject belongs to the test group or the control
group. After having learnt the feedback, the user tries that character again. The
user repeats this process until the user can write in a correct stroke order and the
program will log the time the user spends for each template character.
Figure 3. PDA program for the experiment.
141
Figure 4 shows the correct stroke order of a template character and Figure 5
shows the user input sequence of strokes. After matching the strokes, the array
storing the matching result is [0,3,4,5,6,7,8,9,10,1,2w]h,ich is the correct stroke
order the user input should have. There are 3 groups (0),(3,4,5,6,7,8,9,10),(1,2)
and the LIS is [0,3,4,5,6,7,8,9,10S].trokes 1 and 2 are not in the LIS so they are
the strokes with wrong order. With minimal feedback shown in Figure 6,the
program shows an animation for each group, with the lstgroup being (0), 2"d
group being (3,4,5,6,7,8,9,10a)nd the last group being (1,2). The character can
be written correctly if stroke 1 and 2 are written at the end. On the other hand,
under normal feedback, all the strokes of the user input character will be shown
one-by-one according to the template order, as indicated by Figure 4.
"w.Figure 4. Correct stroke order for the character
Figure 5. Stroke order for the user input character.
Figure 6. Minimal feedback for the user input character
The average time users spent for each character is recordet- and the result is
summarized in Table 3.It can be observed that people spend less time to learn
about the stroke order of a character by using minimal feedback compared with
normal feedback.
Table 3. Comparison between normal feedback and minimal feedback
in terms of average learningtime required.
Characters charOl@ charO2R charO3g
Average Time under Normal Feedback (sec) 48 44 25
Average Time under Minimal Feedback (sec) 43 41 20
6.8% 20%
Percent Improvement 10.4%
142
3.3. Experiment 2: Number ofpeople who remember how to write the
characters in the correct stroke order
After one week, users in both the test group and the control group are required
to write the characters again to test whether they still remember how to write
them in the correct stroke order. In Table 4, the average number of trials
required to write each character with the correct stroke order is shown. It can be
observed that the average number is very close to 1 in all cases meaning that
most people can write the characters correctly in a single trial after one week.
Using minimal feedback is just as effective as using the normal feedback.
Table 4. Comparison between normal feedback and minimal feedback
in terms of average number of trials required.
Characters char01 @I char0295 char03
Minimal feedback I .3 1.2 I
Normal feedback 1 1.1 1
4. Conclusions and Future Work
We proposed a new automatic approach for learning the stroke order for
Chinese characters with the notion of minimal feedback. This approach benefits
from the processes of grouping the strokes and extracting the longest increasing
subsequence to identify the strokes with correct and incorrect stroke order.
Experiments show that users require less time to learn the stroke order with
minimal feedback than with normal feedback. Both kinds of feedback have
similar learning effectiveness in terms of remembering the stroke order after a
period of time. It can be concluded that minimal feedback performs better than
normal feedback since it requires less time with similar learning effectiveness.
Currently our approach only focuses on the stroke order assuming no
stroke-production problems during the experiment. As future work, we will add
other functions for determining the stroke-production errors such as stroke
reversal, concatenation of separate strokes and broken strokes. Feedback related
to these cases will be created to enhance the learning capabilities of our system.
Acknowledgments
The work described in this paper was partially supported by a grant from City
University of Hong Kong (Project No. 700171 1).
143
References
1. N. Law, W.W. Ki, A.L.S. Chung, P.Y. KO and H.C. Lam. “Children’s
stroke sequence errors in writing Chinese characters”, Reading and
Writing:An InterdisciplinaryJournal 10, 267-292 (1998).
2. Z. Chen, C.-W. Lee and R.-H. Cheng. “Handwritten Chinese character
analysis and preclassification using stroke structural sequence”, IEEE Proc.
of the 13th Int. Con$ on Pattern Recognition 3, 89-93, (1996).
3. K.K. Lau, P.C. Yuen and Y.Y. Tang. “Stroke extraction and stroke
sequence estimation on signatures”, IEEE Proc. of the 16th International
Conferenceon Pattern Recognition 3, 119-122 (2002).
4. H. Leung and T. Komura. “Web-based Handwriting Education with Virtual
Animated Teacher”, Int. Con$ on Web-basedLearning, 293-300 (2004).
5. R.E. Burkard and E. Cela. “Linear Assignment Problems and Extensions”.
Handbook of Combinatorial Optimization,75-149 (1999).
6. C. Cerin, C. Dufourd and J.-F. Myoupo. “An efficient parallel solution for
the longest increasing subsequence problem”, Proc. of the Fifth
International Conferenceon Computing and Information, 220-224 (1993).
7. K. M. Chao. “Dynamic-programming Strategies for Analyzing
Biomolecular Sequences”, IMS Lecture Notes Series, Selected Topics in
Post-GenomeKnowledge Discovery 3, 1-24 (2004).
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AN ON-LINE PROGRAMMING ENVIRONMENT
WITH AUTOMATED ASSESSMENT
RONNIE C. T. CHEUNG
Department of Computing
The Hong Kong Polytechnic University
Hung Hom, Kowloon, Hong Kong.
Email: [email protected]. edu.hk
Practical sessions are important elements in programming courses. Students spend lots
of time in practical programming sessions. Object-oriented programming courses require
additional practices in working with design models. Our objective is to encourage active
participation for object-oriented programming beyond classroom environments. By
using a Web-based learning environment for object-oriented development, it is possible
to track all compilation activities associated with every student. We have shown that an
easy-to-use development environment improves teacher-student interaction, provides
analysis on students’ participation, and helps students with their compilation activities in
real-time. We have developed a Web-based learning environment that provides various
features to help students to learn Java Servlets. It also helps tutors to provide feedback
for programming assignments.
1. Introduction
In recent years, object-oriented programming has become one of the most
influential programming paradigms that are being widely used in education and
industry [3]. Many universities are introducing object-oriented programming
(such as Java servlet programming) early in their courses. In our courses, first-
year students also make use of an object-oriented development environment for
learning programming. These courses aim at developing students’ skills in
building reliable systems that can easily be extended and maintained. From both
pedagogical and computing perspectives, there are many advantages in teaching
object-oriented approaches to beginners. Firstly, it encourages well-structured
programming practices. Secondly, it allows at an early stage, the introduction of
important software development concepts, such as information hiding and
reusable component-based development. It also allows us to reduce the
problems associated with the paradigm shift for learning from a procedural
language to an object-oriented environment [2]. It has been found that many
students whose first programming language is a procedural language experience
problems in adjusting to the object-oriented paradigm. Finally, it should be
noted that object-orientation is currently the most popular programming
paradigm adopted by industry. Students should be well aware of the current
practices, and this provides a strong motivation for learning.
At the same time, Web-based learning is becoming more and more popular in
university environments. A Web-based environment allows students to access
145
146
course materials online. To ensure that students understand the concepts in
programming courses, practical exercises and assignments are important
elements that must be incorporated in the course contents.
Although there are many web sites providing practical exercises, most of them
do not provide immediate feedback to students. Without a web-based
environment for interaction and providing feedbacks, marking of assignments
are always delayed. To solve these problems, we have developed a Web-based
Learning Environment for OOP Assessment (WEBLOOP) [l]. It provides a
Web-based tool for drawing UML class diagrams, a code editor for modifying
the Java programs, an online compilation module and a marking module for
checking with student submissions.
With WEBLOOP, all environment settings (e.g. the class path) are performed on
the server side, students do not need to install the software (e.g. Java
Development Kit, Tomcat) and set up the environment for running the software
on their own computers. They only need to concentrate on learning concepts and
practical skills. WEBLOOP also provides a marking module for automating the
assessment process. Figure 1 shows a typical learning cycle for WEBLOOP.
Students submit Java Servlet programs online and the marker module provides
instant feedback by comparing the results with a database of test cases.
Students’ performance are recorded in the system automatically through
practical programming exercises that can be assessed on-line.
Learning+ ’ Attempt Problem+ Assessmentt‘
A Feedback+
~
Figure 1. The Learning Cycle with Automated Feedback
147
2. Systems architecture and functions
The objective of the project is to develop a web-based environment for learning
Java Servlet programming. It provides the followings features :
0 Support for drawing UML diagrams
0 A visual environment for learning Java Servlet programming
0 Support for online submission of programs
0 On-line program compilation and assessment
0 Automated feedback and monitoring of student activities
2.1. Systems architecture
Figure 2 shows the basic architecture of our remote working environment. To
access our software, such as remote compilation/execution server, students log
into our remote server to work on their Java source code. The compiled class
files and feedbacks are sent to the students PC/workstations at home. The
system architecture is a client-server architecture consisting of three components:
a class diagram drawing tool, a compilation server, and a web server for
maintaining the individual activities of each student.
Figure 2. Systems Architecture
148
2.2. The UML ClassDiagram Editor
The UML class diagram editor encourages students to design programs using
object-oriented concepts. It encourages students to solve programming problems
by drawing class diagrams first. In the WEBLOOP environment, no Java
programs can be created before the corresponding class box has been created.
Figure 3 shows a screen dump of the UML class diagram editor. The system
provides options for students to add a class, an abstract class or an interface to
the class diagram by clicking on the “create new class” button. The links
between classes in the class diagram include specialization and association.
Specialization provides an inheritance hierarchy for the classes whereas
association shows how two classes are related to each other. The program text
associated with each class box can be edited by clicking the correspond icon.
The editor is language sensitive and provides specific hnctionality for inserting
program codes for different versions of Java.
Figure 3. UML class diagram editor
149
2.3. Java source codegenerator and compilationserver
The Java source code generator automatically generates the basic structures for
the Java source code for the classes on the class diagram. This generator makes
use of information obtained from the methods, from the attributes of the classes,
and from the generalization and association between classes. The generator
gathers information from the class diagrams each time a user opens the source
code editor. Figure 4 shows the Java skeleton program generated by the source
code generator. The system also performs a reverse engineering process to
students programs to help students to derive class diagrams that are consistent
with the program modules.
P %is I multiPk
h?C ( r m m % t
public class Student extends Person
-Computer mycomputer;
String t e x t "The s t r i n g i s i n red";
Figure 4. The Java code editor
The compilation server consists of the remote compilation module and the Java
Applet and Servlet execution module. It is implemented using Java Sockets. It
responds to the incoming requests from students who want to compile the
program text associated with a class. The system also checks the dependencies
in the class diagram to compile associated classes that have been updated. It
identifies the user and saves the user's source code in the user workspace.
Compilation and execution can be initiated by clicking the corresponding class
icons. The simple edit-compile-cycle implemented through point-and-click
interface is important for encouraging active participation beyond classroom
environments. When these features are initiated, the system either displays the
results or returns appropriate error messages in the information area of the panel.
Figure 5 shows a sample dialog for online compilation and execution. The
WEBLOOP environment ensures that any classes can be compiled and tested as
150
soon as the skeleton code has been generated. The graphical interface also
reduces the need to remember long program names and Web links for execution.
This point-and-click execution cycle is more useful in a learning environment
than the following conventionalcycle for servlet development :
0 Set up Java, classpath, environmentvariables and development libraries in
local machine
0 Create each Java program using a conventional editor
0 Compile and debug Java programs using the Java Servlet Development
Kit (with complicatedcommand line details and parameters)
0 Upload the compiled classes to the appropriate directories
0 Open a Web Brower
0 Type in the URL to execute the Java Servlet classes in the Web server.
Document all classes using a systems engineering tool such as the
Rational Rose Package [4]
&age uni8tledModel.
ublic int attiibute3;
ublio void newOperation30
To compile the source code, users can click If there are errors, once the students have
Compile and then Save & Compile on Server modified the codes, messages are displayed on
in the menu bar. the students’ machines at home.
Figure 5 . Sample screens of WEBLOOP for on-line editing and compilation
2.4. The Marker Module
After the students finished editing and compiling their programs, they can
submit their programming assignment project by providing the subject code and
151
assignment-ID (as shown in figure 3). The marker module helps lectures in
testing the programming assignment submissions from students. It generates
feedback for students automatically by using a number of test cases for each
program. The detailed operation of the marking modules for providing
automatic feedback are as follows (as shown in figure 6 ) :
a The student submits programming assignments by providing the subject
code, assessment-id and user name to the system (Assessment Drop Box).
a The system compiles the program and stores the assessment file in
programming assessment space of the web server.
a The system returns the submission acknowledgementto the student.
a The system save student submission record to database.
a A Testing Module retrieves student program from the assignment web
space.
a The student program outputs are compared with a set of predefined test case
from the database.
a The Maker Module sends test case report to the tutor and the student.
a The Tutor provide the comment and final grade.
@
Compilation Result
I@ MakingReaulr
Figure 6. The Operations of the Automatic Marking and Feedback Module
2.5. Automated testing andfeedback
Before assignment submissions, the lecturer creates test cases for each
assessment. These may include the input and output variables. When the
students submit their programming assignments, the system retrieves the test
cases from the database. For example, if the test case includes three parameters :
152
inputl, input2 and input3, the Web URL for the corresponding submission
(using a doGet() method for the parameters) is :
http://158.132.10.186/cyberlab/z~{username}/servlet/QuadraticEq
uationServlet?assessment-id=123&test-case-num=2&servlet-na
me=QuadraticEquationServlet¶ 1=input1¶2=input2&par
a3=input3
By using the parameters from the Web URL for inputl, input2 and input3, the
system compares the results with the corresponding test cases. A test case report
is generated as a feedback to each student (as shown in figure 7).
TEST CASE REPORT
Servlet Name : QuadraticEquationServlet
Test Case Number: 5
I n p u t Result: 3 / 3
Output Result: 3 / 3
Figure 7. A Test Case Report
3. Conclusion
We have developed a Web-based Learning Environment for Object-oriented
Programming with automated feedback and assessment. The system provides
various features for students to learn Java Servlet programming. Students do not
need to install and set up the Java development kits on their local computers.
They can work with the system anywhere by launching the application remotely
with a browser. Students can also submit programming assignments through the
153
system. It provides automatic feedback by comparing the program output with a
set of pre-defined test cases. As part of our hture work, we shall extend the
system to provide conferencing facilities to improve communication among
students, tutors and lecturers.
Acknowledgments
This project is supported by Grant-no 4-ZO7P of the Hong Kong Polytechnic
University.
Reference
[1] Current version of WEBLOOP is available for public access at
http:Ncyber.comp.polyu.edu.hWcyberlablwebljsp
[1] Decker, R. and Hirshfield, S., Top-Down Teaching: Object-oriented
Programming in CS 1 (Brooks Cole, 1993).
[1] Kiilling, M. and Rosenberg, J., An Object-OrientedProgram
Development Environment for the First Programming Course, Proc. 27"
SIGCSE Technical Symposium on Computer Science Education, ACM,
Philadelphia,USA, March 1996,83-87.
[1] Rational Rose: The Assurance of Quality,
http://www.stylusinc.net/technology/rational~rose.shtml
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WEBITS AND QUALITY CONTROL IN MARKING OF
EXAMINATION SCRIPTS
PHILIP TSANG, REGGIE KWAN, ANDREW K LUI, HENRY LO
The Open University of Hong Kong
Abstract
An important component in web-based learning is the quality control in examination marking. This
is of paramount in the case of large web-based courses such as our CT212 Network Programming
and Design course, which had over 600 students and involved more than half of dozen script
markers. This paper details the principle of examination paper marking, the potential problems of
using a marking scheme, how our home-grown web-based conferencing tool, WEBITS, can help in
the synchronization of marking among markers, and some recommendations to improve the overall
quality of marking from the markers’ perspective.
Introduction
The tasks of a marker involve making an assessment of answers for both closed
and open-ended questions in network programming and design taking into
account a number of objective and subjective aspects of the marking scheme.
This paper introduces the performance of markers in examinations from the
perspective of markers. This paper also analyses how our home-grown web
conference tool, WEBITS, can help in the synchronization of marking among
markers.
Examinations in the OUHK
The examination process of the Open University of Hong Kong is very rigorous,
which has pleasantly surprised many of our external examiners who are
associated with traditional universities. The seven key stages of preparation for
course examination are encapsulated in the following[I]:
. Setting the examination paper
Nominating and appointing examination script markers
Involving external examiners
. Conducting examination script markers coordinationmeetings
. Examination script monitoring
.9 The standardizationand Award Meeting
Submission of course report
The focus of this paper is on the quality of examination marking, and we will
therefore concentrate on stage four of the examination process.
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156
Potential Problems of Marking Scheme
Taking the marking scheme of the examination for CT212 in April 2004 as an
example, some common pitfalls of the marking scheme were revealed during the
discussion meeting among the markers, as follows:
1. The answers in the marking scheme are not exhaustive. Very often, in
tackling the questions, there are a variety of ways to solve a particular
question. As a marker, it is important to list out all possible
combinations so that the marks are aligned with what answers are
acceptable. But still, the list may not be complete. Granting or not
after the meeting is always difficult for markers.
2. The answers in the marking scheme are not necessarily the most
appropriate. Markers also need to verify all the answers presented in the
student’s answer book that may have a creative or even brilliant approach.
The marker should not take it for granted that answers not like those in
the marking guides are always incorrect. Sometimes, it is necessary to
amend and supplementthe answers.
3. The answers in the marking scheme may not be concise enough. The
suggested answers should not be too vague to allow personal assumptions.
As markers, they need to make sure that the marking scheme is precise
and concise enough for their use so that it will not cover too many
possible answers by any kind of deduction.
4. The answers in the marking scheme are correct but may not be reasonably
expected from normal students. This problem is somewhat tricky as
there is a need to classify whether some difficult questions are within the
scope of the course. While there is a need to introduce some difficulties
in the questions for differentiating students, such a level of difficulty,
however, may not be expected by students, or even tutors. Hence,
markers need to provide feedback to the coordinating staff on whether a
particular answer may be too harsh for students.
5. The questions sometimes may not be clear enough. Students may not
know the exact requirements of the questions. Hence, wrong answers
may be seen that resulted from wrong interpretation. Markers need to
suggest some potential interpretation of questions whenever doubts are
found on the questions. The marking scheme should be adjusted
accordingly.
6 . The allocation of marks may not be optimal. The marker, based on his or
her experience and knowledge, should be able to comment on the
allocation of the marks. In this regard, we need to identify the
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objectives of the questions and assess whether the answer can meet the
core objectives. The higher the importance, the higher the marks that
should be given. The breakdown should be clear.
7. Answers to the questions may be evolving. Although it is unlikely, there
is a need to address the timeliness of the answers to particular questions
as technologies are evolving very fast.
8. Although the same marking scheme is delivered to the markers, the
scheme may be subject to personal interpretation. In many cases,
markers may come from different backgrounds and have different
interpretations on both questions and answers. Some points may be
considered valid and relevant very differently. Hence, there is a need to
align the understanding for both questions and answers. The common
ground is critical to ensure fairness.
9. Although a marking scheme is used, it is not uncommon that students will
have different wordings to present the same or similar ideas. It is up to
the markers to judge whether the answers are equivalent to the suggested
answers, which is unavoidable in many cases. Should there be any
major deviation, the case should be reported to the course coordinator and
all practitioners should share their views so that the marking scheme can
evolve, yet remain unified; and
10. It is rather difficult for programming-type questions to have a clear
marking scheme as the programming logic can be very different.
Although some framework has been set, students may have different
levels of accuracy. We cannot expect that a completely executable
program can be written in the examination, but what kind of tolerance is
acceptable is extremely difficult to define.
Running the exam markers coordination meeting
The course coordinatorAecturer chairs the exam markers coordination meeting.
The aim of the meeting is to standardize the marking by training the
examination paper markers to become familiar with the marking scheme, which
is usually delivered to the markers two to three days before the coordination
meeting.
The scenario goes like this. Assume the examination of a course is finished and
everything went smoothly. Our Examination Office (EO) collects all the
examination scripts from various distributed examination centers. The EO then
records the number of students attending, and sorts the examination scripts into
equal batches to be collected by script markers. The EO also reserves two
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batches for the course coordinator to review. These batches are labeled Batch X
and Batch T. For Batch X, the course coordinator selects three scripts from this
batch as sample scripts. These are used as sample scripts for pilot marking
before the coordination meeting. In addition to the three sample scripts, the
course coordinator also marks about 10 other sample scripts so that he or she can
get a feel of the students’performance -and see if the marking scheme works.
In the meeting, problems the course coordinator and the script markers have
with the marking scheme are discussed and collective decisions on making
changes and fine-tuning are performed. This helps to eliminate differences in
marking standards among different markers. While in the past these meeting
were ALL conducted face-to-face, with the Web and with appropriate tools (such
as WEBITS), the meeting is no longer bound by bricks and mortar.
WEBITS and Marking Coordination Meeting
To facilitate the markers’ meeting, our home-grown interactive conferencingtool
is used. The tool is called WEBITS[%].For those readers who are familiar with
commercial products such as Intenvise, our WEBITS contains a subset (but the
most relevant) of the hnctionalities of Intenvise, but with a much lower total
cost of ownership. Specifically, it contains: Application sharing, audio
conferencing, whiteboard, chat-room and video conferencing. The WEBITS
design philosophy, as captured in the logo (See Figure l), is that it is the
interactions and motivation of all stakeholdersthat enhance the course.
~-
Interactive Tutoring System
Figure 1: WEBITS logo
In preparation for the meeting, the three sample scripts are scanned as pdf for
use in the WEBITS meeting. The pdf format can easily reduce a word file by 90
per cent, and thus reduce downloading time for the client. Figure 2 shows a
typical WEBITS login session.
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Through the application sharing facility, all markers can synchronize their view
of the Batch X scripts for discussion. For essay typelshort answer questions,
markers and the coordinator can see and discuss any problem questions via the
voice-chat tool of WEBITS. Any programming code in question can also be
handled via real-time telnet application sharing. Figure 3 shows our current
WEBITS System Architecture.
Figure 2 WEBITS Login Screen
Using the application sharing facilities, we can see how one marks a particular
question. This is then open for discussion: agree, disagree, enhancement,
revision, trash and remarks. It also has the ability to record the meeting
discussion for future auditing purposes.
What is Quality of Examination Marking?
In subjects like network programming and design in computer science and
network programmes, things are often either right or wrong. It is relatively
easy to devise assessment criteria for examinations. Even though design issues
and recommendations are subjective in nature, there is an identifiable
framework of a good answer or an unsatisfactory answer to a particular question.
Such a framework can be turned into a marking scheme of a flexible kind, which
enables the characteristics of good and less-good answersto be compared and
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Server
Central Server
Figure 3 WEBITS System Architecture [3]
contrasted. The quality of marking relies on whether such a framework is
common and consistent among all entities including the course coordinator,
tutors, students as well as external reviewers. Very often, markers face the
problem of being too rigid or too flexible for open-ended questions. To avoid
this situation, good marking of examination scripts should satisfy the following
basic principles of transparency, openness and fairness.
For transparency, the whole mentoring process should be transparent to all
parties. In this regard, the objectives of the courses and how the students are
being evaluated must be delivered and communicated well, not only to the
students but also to tutors and external moderators alike. The appeal mechanism
is also important for the students to build confidence in the entire quality system.
Such guidance on evaluation criteria must be delivered at the very beginning of
the course.
For openness, it is important to ensure that every stakeholder is provided with
the same set of information, and such information should be readily available to
all parties. As such, in our CT212 Network Programming and Design course,
there are a number of dissemination channels for tutors, students and staff [4].
For example, online discussion board and news announcementpages, online and
face-to-face tutorials and surgeries that are open to all students and relevant staff.
In particular for marking an examination, it is important to make sure that all
markers are provided with the same marking scheme. However, quality
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assessment is always subjective and is subject to personal interpretation. In
order to ensure that the same scheme is delivered to the markers, a discussion
meeting is critical for all markers to clear some personal assumptions for
alignment.
For fairness, all students must be on an equal footing so that the marking can be
accurate and consistent. The markers should not be biased by a particular
interest, and the following should be observed:
1. All examination scripts should be anonymous for the purpose of marking
(e.g. use of student number only or examinationnumber only);
2. Candidates should be assigned to a marker who has no direct relationship
(e.g. the tutor should not mark the answer scripts of hisher tutor group);
3. The assessment should adhere strictly to the agreed marking scheme;
4. The marking scheme should be commonly understood and agreed among
the markers. There should be no personal assumptions and flexibility;
5. Randomly sampled checking on marked scripts is necessary and should
be examined by an n-tier strategy.
Quality Assurance and Control Process
Having considered the potential problems of marking, an appropriate quality
assurance process needs to be in place before conducting the marking process.
Proactive and preventive measures are critical here. For example, the
discussion meeting and marking of sample scripts are an extremelyuseful means
for this purpose. Besides, quality checking is also vital to ensure accuracy,
compliance and consistency. Sample checking and second moderation may be
introduced to ensure the performance of the marking.
To ensure the quality of a marking scheme, the following draft “To do” list is
drawn up for possible improvement of marking scheme:
1. To explore an exhaustive list of answers in the marking scheme;
2. To verify and confirm the answers in the marking scheme;
3. To make the answers in the marking scheme concise and descriptive;
4. To ensure the answers in the marking scheme are reasonable;
5. To clarify unclear questions, looking for different potential interpretation
of questions;
6. To adjust the allocation of marks according to the importance of the issues
being examined;
7. To allow new answers to the questions as time changes;
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8. To align the common understanding for both questions and answers;
9. To avoid personal judgment, seeking advice from course coordinating staff
should there be any major deviation; and
10. To list the levels of acceptable tolerance.
Conclusion
To conclude, from the human perspective, all markers should observe the
principles of fair play and transparency. A suite of quality assurance and
control processes should be in place. The marking scheme should be
normative, descriptive, precise and concise so that the markers can compare
themselves against the standard answers as they might perceive then. By
weighting the key principles of assessment to reflect the goals of the course,
staff involved should align their common understanding and allow the evolution
of a marking scheme to ensure its fitness for purpose. From the technological
perspective, the Web clearly facilitates the quality assurance process by allowing
well planned meetings to be conducted, recorded and possible audited.
Acknowledgements
The authors wish to thank the tutors of the courses that we coordinated at
OUHK. The tutors have provided constant feedback and inspiration in our
teaching. We also want to record our appreciation for the critical comments of
Dr Rex Sharman, Education Technology and Publishing Unit (ETPU), OUHK.
Thanks also go to Prof. David Murphy, Director of our Distance Learning
Research Centre, for constant support not only in the WEBITS project but in
many otherjoint activities.
References
1. Course Coordinator Training Manual, OUHK.
2. Murphy, D., & Tsang, P. (2004) WEBITS Research Project Report,
OUHK.
3. Chan, J., Murphy, D., & Tsang, P. (2005)WEBIT Users Manual,
OUHK.
4. Tsang, P., Fong, J., & Tse, S. (2004) Using E-learningPlatform in Open
and Flexible Learning,New Horizon in Web-Based Learning, World
Scientific, pp.214-225.
PART FOUR Human Factors
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SOCIAL CAPITAL CREATION AND RECIPROCITY IN
ONLINE LEARNING PLATFORMS
ANDREW K. LUI
School of Science and Technology
Open Universityof Hong Kong, Hong Kong
YANNIE H. Y. CHEUNG
Department of Sociology
Chinese Universityof Hong Kong
REGGIE KWAN
School of Science and Technology
Open Universityof Hong Kong, Hong Kong
This paper investigates the creation of social capital in online courses. The advantagesof
using social capital to abstract the complex set of beneficial factors for online learning
and collaboration are exploited. The role of online learning platforms in facilitating
social capital creation is highlighted in a strategy based on trust development and
reciprocity. The strategy is realized in social interaction components that can be
integrated into any online learning platform. The paper reviewed several social
interaction componentsthat have been successfully deployed in an online course.
1. Introduction
This paper investigates the creation of social capital in online courses. It
specifically explores the system aspect of social capital creation and the role of
online learning platforms in facilitating beneficial social interaction processes.
This approach aims to share the responsibility expected of online instructors in
community cultivation [2].
The remainder of the paper covers the background of this work, which
begins with an introduction to social capital. Social capital includes other
concepts such as trust, reciprocity, and community, and these concepts will also
be briefly discussed. The paper then describes a strategy for social capital
creation in online courses, discusses the role of online learning platforms for
this purpose, and reviews several prototype components based on the strategy.
165
166
These components will serve as case studies of the strategy. The paper
finishes with a general discussion and suggestions for future work.
2. Background on Social Capital
The notion of social capital has been developed to abstract the productive
conditions and values embedded in social interaction and communities. High
social capital describes a state of social organization and social cohesion [3],
and it facilitates collective actions for mutual benefits [4]. These virtues of
communities, made possible by social capital, have been shown to correlate
positively with effective learning in colleges [ 5 ] , trust in institutions [6],and
access to information and knowledge [7][8]. Social capital offers a convenient
handle for dealing with the complexity of social interaction, human
characteristics, and conditions of community development. The notion adopts a
rational and economic approach in considering the participation and engagement
in a community. It has been shown that social capital has good descriptive
power in studying a range of social issues, including the development of online
learning communities [1][9].
2.1. Social Capital Creation
Many researchers suggest that an increase in social capital is equivalent to an
improvement of socially productive conditions [11][7][9][lo][121. The
important conditions include trust, reciprocity, membership scheme, and shared
norms, values, and rules. Trust gives the assurance that the relationship is
reciprocal -a member can confidently expect obligations to be fulfilled. This
encourages altruistic acts for the benefit of the wider community. Membership
of a community allows individuals to be identified for sanction, however, if they
are found to exploit trust and violate reciprocity. The suspension of
membership is usually a sufficiently threatening sanction if access to community
resources is tied with membership. The use of sanction can be complemented
by institutionalized norms and values. Social norms and values can promote
positive attitudes and actions among the members, and they can also provide a
yardstick as to whether a member is still committed to the community and
considered trustworthy.
Trust is generally regarded as the most important indicator of social
capital. Trust is the sense of comfort, belief, and confidence that one can rely
on a person or a social structure [131. A community with an abundance of trust
encourages reciprocity, participation, and volunteerism, which allow more
donations and other resources to be placed at the disposal of the community-at-
large. Trust itself exhibits reciprocity in that if a person trusts another then it is
167
likely that the trust is mutual. Reciprocity also occurs in cooperation and
relation building. Cooperation happens in a group if each trusts others to
reciprocate contributions. Reciprocal fulfillment of obligations is a positive
experience that breeds trust, and conversely, trust diminishes after a failure of
expectations.
The cultivation of a cooperative community can take the form of a
circular process of reciprocity and trust reinforcement. In the circle, trust
encourages cooperation, volunteerism and other forms of reciprocity, and then
these activities strengthen trust [ 6 ] . This is a process of positive reinforcement
activities, in which social capital increases. The circular process can operate in
a destructive mode, however, in that trust can diminish when reciprocity does
not happen as expected. This perspective of social capital creation can be
succinctly described as follows: encouraging the positive reinforcement process
while preventing the negative reinforcement process. This takes deliberate
planning to encourage participation in the positive reinforcement process.
Reciprocity can be considered in both specific and generalized contexts.
Specific reciprocity describes the situation where the fulfillment of obligation is
directed to the original provider or contributor of resources. In generalized
reciprocity, the original contributors are not concerned with the return of favors
from the recipients of resources. Instead they expect to receive something
desirable from the community in the future, perhaps intangible goods such as
recognition. The generalized form of reciprocity connects individuals with the
wider community and it is of more significance to social capital creation than
specific reciprocity.
2.2. Social Interaction in Online Environments
A discussion of social capital creation for online learning inevitably involves the
issue of social interactions in virtual environments. There have been
considerable discussions on the characteristics of online social interactions.
Critics often suggest that social interaction through computer mediated
communication is impersonal and even hostile [141. Conversely, many others
report the development of genuine online relationships that are fruitful and
intimate [181.
The reduced cue phenomenon is considered to be an undesirable
characteristic of computer mediated communicationthat social interaction has to
overcome. Face-to-face communication includes verbal communication and
other visual cues such as facial expression and gesture, and other cues. In
online social interaction, the communication facilities determine the permissible
modes and forms of communications, which are often restricted to just written
168
text. The reduction in cues decreases the sense or feeling of the other, which is
known as the concept of social presence. Social presence is regarded as the
basis of the feeling of relation and friendliness [18][16]. There are opposite
views claiming that text-only communication leads to high quality academic
discussion from a cognitive aspect [34], and it also supports the development of
close relations through the hyperpersonal effect [151. These cases merely
demonstrate the adaptive ability of human beings, and they do not devalue the
importance of cues in social interactions.
Social affordance [21], sociability [21], social translucence [191, and
social awareness [9] are concepts introduced to address the issue of social
presence in online environments. The minimalist visualization approach [20]
uses a computational method to present visual cues between online
participations. The Babble Cookies, for example, uses graphics to indicate the
activities of other participants - and who are still participating actively or
slipping away. The Group Awareness Widget [2 I] follows a similar approach in
which the activities of each online participant from the present to the past are
shown graphically.
3. Role of Online Learning Platforms in Social Capital Creation
In this work we investigate the role of an online learning platform in social
capital creation. Online learning platforms provide the only channel for social
interaction to happen and they can play a progressive role. Based on the trust
development model discussed in the previous section, we propose the following
three-item strategy of designing social interaction components for online
learning platforms:
1. Show Reciprocity. Trust building requires not just the occurrences of
reciprocity but also an awareness of reciprocity. Online activities of a
reciprocal nature are not visible because of the reduced cue problem.
Online learning platforms can include components to display information
about reciprocity.
2. Provides Opportunities of Reciprocity. Participation is the precondition
of reciprocity and offering a variety of activities encourages individuals
with varying needs and concerns to participate. Providing communication
facilities and hoping reciprocity will occur is not sufficient. Online learning
platforms can include a range of components for personal contribution and
sharing of resources. Some components should be concerned with
developing initial trust while others with developing deeper trust. The
components should also vary in the effort required, the ability required, and
169
the nature of interaction. The more components provided, the more online
learners can potentially participate.
3. Reward Reciprocity. Reward can reinforce a desirable activity such as
trust building and reciprocity. Online learning platforms can include
components that give status or more access rights to those practicing
reciprocity.
There are two more issues concerning the design of the components. If
an online learning platform provides information about online participation,
there will be a concern about online privacy. Online privacy is a complex issue
in that the perception of privacy can affect the social psychology of computer
mediated communication [22]. A simple way to approach this issue is to
provide an opt-out option for online learners. The opt-out option would stop the
using of an individual’s participatory infomation and at the same time stop their
access right to the social interaction components. The other issue is about using
a minimalist approach [20] to design the social interaction components. A
minimalist approach is economical in the development.
In the following minor sections we will discuss several components for
online learning environments in the context of social capital creation. Most of
the components are not new but they are reviewed from the new perspective of
social capital. Specifically, the elements to be reviewed include the nature of
the component, the social capital creation capability in the light of the three-item
strategy above, the effort or ability required of the user, and the involvement
required for implementation.
3.1. Prototype I : Presence Monitor
The Presence Monitor indicates the virtual location of participants currently
online and their identity (Figure 1). This component supports the visualization
of reciprocity in participation. Current online participants are aware of each
other and the nature of their activities through this component. One can
determine the identity of the active participants who share the same commitment
to participate regularly and to make progress in the course. Together with other
participatory information, one can also determine who the lurkers are. The
identification of responsible participants allows preferential offering of more
help.
The use of this component requires virtually no effort from online
participants if it is placed on the top level of an online learning environment.
The implementation requires the server-side to keep track of the virtual
whereabouts of online participants and the client-side to refresh the information
through standard HTTP refresh or a JavaScript script.
170
Figure 1. A Presence Monitor with boxes showing various virtual locations such as the offce for
download and submit assignments, or the study center where online learning materials are kept. The
identity of the online participants is shown when the mouse pointer moves over a location box.
3.2. Prototype 2: Opinion Polls
The Opinion Polls component allows online students to express their opinions
on an issue (Figure 2). The poll results are displayed only after a vote is cast.
This component provides an opportunity to share personal opinions reciprocally.
Opinion polls can provide rich information about the opinion, the status, and the
need of an online community.
The use of this component requires a little effort from online participants.
It demands minimal effort if an opinion poll is placed on the front page in an
online learning environment. Participation is a simple matter of reading and
selecting a choice. The implementationrequires a web application development
with functions consisting of poll authoring, poll display, data store, and result
display.
Ican confidently write programs with Isnd Ican confdeentlywrile proaramsWiIh ifand while
while structures. strudures.
Strongly Agree
Figure 2. The Opinion Polls Component offers choices of opinion to a question. An online student
must cast a vote first before the poll results are displayed.
3.3. Prototype 3: Interaction Table
The Interaction Table shows the interaction frequencies with each other online
student (Figure 3). This component can highlight information about reciprocity
present in asynchronous discussion. It shows the number of messages written as
a reply to each peer, and also the number of messages written as a reply from
each peer. It makes clear who have chosen to reciprocate and who have been
getting help without making a contribution. This component provides the
171
information flow that allows the acknowledgement of individual contributions
and contributors.
The use of this component requires virtually no effort from online
participants. The implementation involves the extraction of information from
discussion forum systems and formattingthe information.
Asynchronous Discussion Interaction
Figure 3. The Interaction Table displays the amount of messages exchanged with every other online
participant. The Reply column shows the number of reply messages to the peers and the Received
column shows the number of messages received from the peers.
3.4. Prototype 4: Buddies List
The Buddies List shows the participatory and interaction information of selected
peers who are considered close friends (buddies) (Figure 4). This component
provides an opportunity for an initial trust to develop into deeper trust. One can
monitor the fulfillment of the obligation of being a close friend - regular
participation and exchange of information. The buddies list is automatically
carried from one course to another to maintain continuity of trust development.
The use of this component requires a little effort from online participants
in editing the buddies list. When a peer is added to the buddies list, a message
is automatically sent to the peer containing an invitation for reciprocal addition
of the originator as a buddy. The implementation requires a web application
development with functions consisting of buddies-list editing, data store, and
data display.
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Buddies List
Figure 4. The Buddies List component indicates the interaction status between an online student and
selected peers. The first column shows the ID or the alias of buddies. The second column of the table
shows the participatory status that shows the whereabouts of a peer if online or the previous login
time. The third column shows if a mail or a real time alert is received from a peer. Only buddies can
exchange mail and alerts. The last two columns show the exchange of discussion messages in
asynchronous discussion forums.
4. Conclusion
An investigation of the creation of social capital in online courses has been
carried out. The paper reviewed the importance of sociality to learning and the
need to cultivate social interactions in online communities. The paper then
referred to previous research that the notion of social capital is a convenient
handle in developing online communities, and proposed a strategy based on
developing trust and encouraging reciprocity. The role of online learning
platforms in social interaction was highlighted, and the paper suggested the
realization of the strategy by adding social interaction components for online
learning platforms.
The social interaction components reviewed have been experimentally
deployed in the course web site for a couple of courses (Figure 5). An
important further task is to investigate empirically how the social interaction
components affect trust development and reciprocity in online courses and, in
addition, the social health of the courses.
173
Figure 5. Several social interaction components are shown on the front page of a course web site.
Some components such as the Asynchronous Discussion Interaction Table are deployed in other
pages.
Acknowledgment
The authors are gratehl to Dr. Rex Sharman of OUHK for his useful comments
about this paper.
References
1. Schwier, R.A., (2002). Shaping the Metaphor of Community in Online
Learning Environments, the International Symposium on Educational
Conferencing. The Banff Centre, Banff, Alberta.
2. Palloff, R., & Pratt, K. (1999). Building Learning Communities in
Cyberspace, Josey-Bass Publishers, San Francisco.
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ARE TEACHERS IN HONG KONG READY FOR E-LEARNING?
SO, KOON KEUNG TEDDY
The Universityof Hong Kong
[email protected]
Abstract
There is a common understanding that the twenty-first century is a more globalized and
knowledge-based era. In response to this rapid change, Hong Kong is trying to transform hersey
into an informationsociety. A lot of education reforms were implemented to our schools in the past
f a 0 years. Based on the well established hardware infrastructureand the lesson learntfrom thefirst
IT plan (1998 - 2003), the Education and Manpower Bureau released its second Information
Technology strategic plan, focusing on the real change of pedagogy, the promotion of life-long
learning and e-learning, the use of wireless technology as the extension of the existing wired network,
and the new roles of parents as well as students in the life-long learning environment. This research
adopted a survey method to conduct the study of e-learning readiness of teachers in schools of Hong
Kong. Results indicate that teachers in Hong Kong are not very preparedfor using the e-learning
technologies in teaching and learning. There are differences in readiness perceived between males
and females, secondary school teachers and primary school teachers, and teachers of secondary
schools in different bandings. Based on the data found. recommendation is made to improve the
situation.
Introduction
With the support of new communication technologies, there is a common
understanding that the twenty-first century is a more globalized and
knowledge-based era, treating knowledge as a commodity. In response to this
rapid change, Hong Kong is trying to transform herself into an information
society. A lot of education reforms were implemented to our schools so as to
equip young people to take the challenge in the past few years. We had our very
first five-year Information Technology strategic plan implemented in all primary
and secondary schools from 1998 to 2003. In this five-year period all schools set
up huge computer networks, having 91 and 247 networked computers in primary
schools and secondary schools respectively. Moreover, all schools have
broadband Internet connections, ranging from 1.5 to 10 Mbps. Although huge
resources had been poured into the project of Information Technology in
Education, the change of pedagogy I paradigm shift was not obvious. The
classroom practice changed only little. Students still learn in a passive way,
without much participation and interaction with other students and teachers.
Based on the well established hardware infrastructure and the lesson learnt from
the first IT strategic plan, the Education and Manpower Bureau (EMB) released
175
176
its second Information Technology strategic plan, bearing the title “Empowering
Learning and Teaching with Information Technology” in July 2004. The focus of
the second strategic plan is a bit different from the first one. The first plan
emphasized the initial set-up of the hardware infrastructure and teacher training.
The second strategic plan focuses on the real change of pedagogy, the promotion
of life-long learning and e-learning, the use of wireless technology as the
extension of the existing wired network, and the new roles of parents as well as
students in the life-long learning environment.
According to the report prepared by both IBM and the Economist in 2003, the
overall ranking of e-leaming readiness of Hong Kong is 19* out of 60 countries
around the world (The Economist & IBM, 2003). One of the important factors
influencing the success of e-learning is teacher training. As the way to deliver
the online curriculum is new and different from the traditional one, the
instructors must be trained to make the most of updated teaching methods. “An
ineffective teacher can waste the time of 30 or 40 students. But bad teaching
online can touch thousands. ‘We can create mass damage quickly.’” (The
Economist & IBM, 2003; p. 12)
As the readiness of teachers to use the new technology is critical to the success
of implementing e-learning in schools, it is worthy to investigate if and how they
are prepared to embrace the new technologies in their teaching and learning
activities. The purpose of this research is thus to find out how ready the teachers
of secondary and primary schools are to use the new technologies, and what
factors are influencing their readiness. It is hoped that the experience gained
from this research is beneficial to other countries exploring the use of e-learning
technology in new teaching and learning activities.
Literature Review
e-Learning readiness assessment helps an organization to design e-learning
strategies comprehensively and to implement its ICT goals effectively (Kaur,
2004). Learners must be “e-ready” so that a coherent achievable strategy that is
tailored to meet their needs may be implemented (infodev, 2001). In sum, this
readiness assessment provides key information to organizations to supply
solutions that can cater to the specific needs of each learning group (McConnell
International, 2000).
Before implementing e-learning programs, organizations need to expand the
usual needs assessment process by creating a high-level requirements document
that includes: 1. Objectives (macro organizational objectives and micro target
learner population objectives); 2. An e-learning readiness score; 3. A list of
177
advantages and potential obstacles to e-learning adoption; and 4. A list of
possible e-learning configurations (Chapnick, 2000). Chapnick designed a
model for measuring the e-learning readiness of an organization aiming at
answering the questions: a. Can we do this?; b. If we can do this, how are we
going to do it?; and c. What are the outcomes and how do we measure them? His
proposed model groups different factors into eight categories:
Psychological readiness. This factor considers the individual's state of
mind as it impacts the outcome of the e-learning initiative. This is
considered one of the most important factors and has the highest
possibility of sabotaging the implementationprocess.
Sociological readiness. This factor considers the interpersonal aspects
of the environment in which the program will be implemented.
Environmental readiness. This factor considers the large-scale forces
operating on the stakeholdersboth inside and outside the organization.
Human resource readiness. This factor considers the availability and
design of the human-support system.
Financial readiness, This factor considers the budget size and
allocation process.
Technological skill (aptitude) readiness. This factor considers
observable and measurable technical competencies.
Equipment readiness. This factor considers the question of the proper
equipment possession.
Content readiness. This factor considers the subject matter and goals
of the instruction.
The Ministry of Education of Singapore found that this model is especially
useful for principals and HODS who intend to start e-learning in the school
(MOE, 2004). However, one of the major drawbacks of this model is that it is
designed to measure the readiness of using e-learning in business organizations.
It does not fully fit in the school environment. With reference to Chapnick's
model, Kaur and Abas (2004) designed a model for measuring the e-learning
readiness of the Open University Malaysia. The model consists of eight
constructs: learner, management, personnel, content, technical, environmental,
cultural and financial readiness.
There are findings that show gender differences exist in computer acceptance
(Yuen & Ma, 2002; Russell & Bradley, 1997). In his research on 462 middle
and high school students, Young (2000) found that there was a significant
gender differences in computer attitudes. The male domain scale showed that
boys were more likely to have claimed computers as a male area. Russell and
Bradley (1997) found that male teachers reported significantly greater
178
confidence with computers than females did. Therefore, they recommended that
the design of teacher professional development should take into account the
gender difference, taking care of the particular needs of female teachers.
Methodology
This research adopted a survey method to conduct the study of e-learning
readiness of teachers in schools of Hong Kong. A questionnairewas sent to 200
teachers of secondary and primary schools in the period from December 2004 to
January 2005. All items were measured on a five-point Likert scale, with 5 as
strongly agree and 1 as strongly disagree. 148 were completed and returned. 13 1
of them were valid. Descriptive statistics, one-way analysis of variance
(ANOVA), and Post Hoc tests were applied to analyze the data.
Data Findings and Discussion
Results show that there are differences in readiness perceived between males
and females, secondary school teachers and primary school teachers, and
teachers of secondary schools in different bandings. The results of this study are
summarized in tables 1 , 2 and 3.
Table 1: e-learning Readiness of Teachers of Primary vs. Secondary Schools (One-way ANOVA)
It is worth noticing that in many aspects the primary school teachers have
significant different perceptions from those of secondary school teachers.
Although officially the amount of IT training in terms of time and opportunity
offered to both primary and secondary school teachers from the Education and
Manpower Bureau (EMB) is the same, primary teachers still consider
themselves know less about what e-learning is. Furthermore, they not only do
not have enough confidence on themselves in perceiving the abilities of their
students, but they also feel that primary students do not have enough IT
competenciesto use e-learning technologies.
179
Moreover, their confidence in their principals’ understanding and support of
using e-learning in teaching and learning is not as high as their counterpart, the
secondary school teachers’. This can be originated from the comparatively
shorter history of having computers in primary schools. In Hong Kong,
secondary schools had to teach computer studies as a subject since 1982. Since
then, the teachers and students have chances to use computers. Culture and
confidence of using I operating computers were gradually built up in secondary
schools. Most of the secondary school teachers are university graduates who
most probably have experiences of using computers during their university
studies.
Not until the year 1998, the year when the first IT strategic plan in education
was launched, primary schools in Hong Kong had any computer. However, it
took another one to two years to convert normal classrooms into computer
laboratories and to complete the wiring, and set up all computer hardware. As a
result, in general, primary teachers as well as their principals had only five to six
years’ time to learn how to operate computer, to try integrating IT into their
teaching, and even less time to explore the use of e-learning. Moreover, most of
the primary school teachers are diploma graduates and they did not have much
chances of using computers in their pre-service training. This might explain the
phenomenon why primary teachers do not have much confidence in their
principals and themselves in using e-learning technologies as secondary school
teachers do.
Regarding the issue of accessibility,it is always a problem in different countries.
According to the latest statistics from EMB (2004), the average numbers of
computers installed in primary and secondary schools in Hong Kong are 97 and
247 respectively. The computer to student ratios in primary and secondary
schools are about 1:9 and 1:s respectively. Hence accessing computers is a
bigger problem among primary pupils. Although nowadays there are many
public terminals for all users, young primary pupils are considered too young to
go around by themselves. From Traditional Asian point of view, for their safety
the young kids should either stay in school or at home. As a result, their
accessibilitiesto public computer terminals are further restricted.
Gender difference is always a controversial topic. As discussed in the section of
literature review, some researches found that there is a gender difference while
some did not. This research found that there is a gender differencebetween male
and female teachers. In all three questions ‘‘I know what e-learning is”, “I am
ready for integrating e-learning in my teaching”, and “I have enough IT
competency to prepare the e-learning materials”, male teachers showed higher
180
confidence than female teachers did, although they received equal amount of IT
training from the government. The result of this study agrees with the findings
of Yuen and Ma (2002) and Russell and Bradley (1997) that there is a gender
difference between male and female teachers in perceiving their IT
competencies.
to prepare the e-learning Female 60 3.25
materiaIs
181
There are about 400 plus secondary schools in Hong Kong. They can be
categorized into three bands, according to the achievements and the performance
in the public examination of the pupils taken from primary schools. The highest
achievers will go to band 1 secondary schools, and the lowest go to band 3
schools. While sometimes it is hard to draw a line to distinguish the differences
between teachers from band 1 and band 2 secondary schools, together their
responses are significantly different from that the teachers of band 3 schools.
Significant differences can be found between the teachers from band 3 schools
and teachers from band 1, or band 2 schools, or both. Teachers from band 3
schools perceived their schools, themselves, and their students inferior to those
from band 1 and band 2 schools. At the school level, they perceived their
schools did not have a culture of sharing, which is important to the development
of a learning organization. At the classroom level they perceived both
themselves and the students were not ready for using e-learning. Another vital
factor of using e-learning is the support from the parents. Unfortunately, their
perception on the support from the parents is the lowest among the three
bandings.
Recommendation
In the light of these different perceptions from the primary and secondary school
teachers, EMB should consider providing more help / consultancy to primary
schools, principals, and teachers. Due to their short history of acquaintance with
computer, they need more technical support and in-services training so as to
build up their confidence in integrating IT in their daily teaching. It is also
recommended that the concept of using IT in education should be emphasized in
the principal training program so that principals may really take up the role of
leadership in developing the new curriculum. Moreover, it is recommended that
the design of teacher professional development should take into account the
gender difference, taking care of the particular needs of female teachers. In order
to gain support from parents in using e-learning at home, more resources should
be invested in schools for conducting parents training programs.
Conclusion
Although huge resources have been poured into IT in education planning,
schools in Hong Kong are still at the initial stage of employing e-learning in
their daily teaching and learning activities. It is necessary to conduct a needs
assessment in full scale before any e-learning program is actually being
launched as it is important to know the factors affecting teachers’ computer use
and its implications to teachers’ professional development strategies (Yuen &
Ma, 2002).
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