Journal of Distance Education Technologies, 2(1), 1-17, Jan-Mar 2004 1
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ABSTRACT
In this paper, we propose an agent-based personalized distance learning system
for delivering appropriate studying materials to learners by judging learners’
degree of understanding.The main elements of our proposed system are the agents,
which play the role of teacher. Based on the learning history they analyze the
understanding degree of learners. To evaluate the proposed distance learning
system, we carried out three experiments and a questionnaire investigation. The
evaluation results show that by making groupings of learners, the agents can
decide what kind of materials should be given to learners. Furthermore, we im-
proved the system by adding new features such as mental action of color and the
competition with other learners. The evaluation results show that an improved
system can increase learning efficiency.
Keywords: distance learning; agent-based technology; competition of learners; learner volition
stimulation
A Distance Learning System for
Delivering Appropriate Studying
Materials and
Stimulating Learner Volition
Leonard Barolli, Fukuoka Institute of Technology, Japan
Akio Koyama, Yamagata University, Japan
INTRODUCTION
During the last few years, a lot of re-
search has been going on for distance learn-
ing systems (Nakabayashi et al., 1997;
Katayama, 1999) and many large projects
such as CALAT (CALAT Project, 1998),
CALsurf (2000), WebCAI (WebCAI,
1999), The University of The Air (UOA,
1984), and WIDE University (WIDE 1997;
Ogawa 1999) have been established.
Recently, some distance learning sys-
tems, which consider a learner’s capability
and understanding have been proposed
(Matsumoto at al., 1999; Tamaki at al.,
2000). In Matsumoto et al. (1999), an
evaluation system of historical data based
on learning environment supported by edu-
cational software record is proposed, and
reappearance and analysis are carried out
for historical learning data. The analysis
from the history can be performed, but in
order to get the learner’s learning condi-
tion, the historical data are needed. Thus,
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